The first mile: community experience of outbreak control during an Ebola outbreak in Luwero District, Uganda.

PubMed

de Vries, Daniel H; Rwemisisi, Jude T; Musinguzi, Laban K; Benoni, Turinawe E; Muhangi, Denis; de Groot, Marije; Kaawa-Mafigiri, David; Pool, Robert

2016-02-16

A major challenge to outbreak control lies in early detection of viral haemorrhagic fevers (VHFs) in local community contexts during the critical initial stages of an epidemic, when risk of spreading is its highest ("the first mile"). In this paper we document how a major Ebola outbreak control effort in central Uganda in 2012 was experienced from the perspective of the community. We ask to what extent the community became a resource for early detection, and identify problems encountered with community health worker and social mobilization strategies. Analysis is based on first-hand ethnographic data from the center of a small Ebola outbreak in Luwero Country, Uganda, in 2012. Three of this paper's authors were engaged in an 18 month period of fieldwork on community health resources when the outbreak occurred. In total, 13 respondents from the outbreak site were interviewed, along with 21 key informants and 61 focus group respondents from nearby Kaguugo Parish. All informants were chosen through non-probability sampling sampling. Our data illustrate the lack of credibility, from an emic perspective, of biomedical explanations which ignore local understandings. These explanations were undermined by an insensitivity to local culture, a mismatch between information circulated and the local interpretative framework, and the inability of the emergency response team to take the time needed to listen and empathize with community needs. Stigmatization of the local community--in particular its belief in amayembe spirits--fuelled historical distrust of the external health system and engendered community-level resistance to early detection. Given the available anthropological knowledge of a previous outbreak in Northern Uganda, it is surprising that so little serious effort was made this time round to take local sensibilities and culture into account. The "first mile" problem is not only a question of using local resources for early detection, but also of making use of the contextual cultural knowledge that has already been collected and is readily available. Despite remarkable technological innovations, outbreak control remains contingent upon human interaction and openness to cultural difference.

How to select a proper early warning threshold to detect infectious disease outbreaks based on the China infectious disease automated alert and response system (CIDARS).

PubMed

Wang, Ruiping; Jiang, Yonggen; Michael, Engelgau; Zhao, Genming

2017-06-12

China Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005. The CIDARS was used to strengthen infectious disease surveillance and aid in the early warning of outbreak. The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDC at all levels in China. Early warning threshold is crucial for outbreak detection in the CIDARS, but CDCs at all level are currently using thresholds recommended by the China CDC, and these recommended thresholds have recognized limitations. Our study therefore seeks to explore an operational method to select the proper early warning threshold according to the epidemic features of local infectious diseases. The data used in this study were extracted from the web-based Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS), and data for infectious disease cases were organized by calendar week (1-52) and year (2009-2015) in Excel format; Px was calculated using a percentile-based moving window (moving window [5 week*5 year], x), where x represents one of 12 centiles (0.40, 0.45, 0.50….0.95). Outbreak signals for the 12 Px were calculated using the moving percentile method (MPM) based on data from the CIDARS. When the outbreak signals generated by the 'mean + 2SD' gold standard were in line with a Px generated outbreak signal for each week during the year of 2014, this Px was then defined as the proper threshold for the infectious disease. Finally, the performance of new selected thresholds for each infectious disease was evaluated by simulated outbreak signals based on 2015 data. Six infectious diseases were selected in this study (chickenpox, mumps, hand foot and mouth diseases (HFMD), scarlet fever, influenza and rubella). Proper thresholds for chickenpox (P75), mumps (P80), influenza (P75), rubella (P45), HFMD (P75), and scarlet fever (P80) were identified. The selected proper thresholds for these 6 infectious diseases could detect almost all simulated outbreaks within a shorter time period compared to thresholds recommended by the China CDC. It is beneficial to select the proper early warning threshold to detect infectious disease aberrations based on characteristics and epidemic features of local diseases in the CIDARS.

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication

PubMed Central

Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A.; Aylward, R. Bruce; Grassly, Nicholas C.

2016-01-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities. PMID:26890053

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication.

PubMed

Blake, Isobel M; Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A; Aylward, R Bruce; Grassly, Nicholas C

2016-03-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities.

A large Legionnaires' disease outbreak in Pamplona, Spain: early detection, rapid control and no case fatality

PubMed Central

CASTILLA, J.; BARRICARTE, A.; ALDAZ, J.; GARCÍA CENOZ, M.; FERRER, T.; PELAZ, C.; PINEDA, S.; BALADRÓN, B.; MARTÍN, I.; GOÑI, B.; ARATAJO, P.; CHAMORRO, J.; LAMEIRO, F.; TORROBA, L.; DORRONSORO, I.; MARTÍNEZ-ARTOLA, V.; ESPARZA, M. J.; GASTAMINZA, M. A.; FRAILE, P.; ALDAZ, P.

2008-01-01

SUMMARY An outbreak of Legionnaire's disease was detected in Pamplona, Spain, on 1 June 2006. Patients with pneumonia were tested to detect Legionella pneumophila antigen in urine (Binax Now; Binax Inc., Scarborough, ME, USA), and all 146 confirmed cases were interviewed. The outbreak was related to district 2 (22 012 inhabitants), where 45% of the cases lived and 50% had visited; 5% lived in neighbouring districts. The highest incidence was found in the resident population of district 2 (3/1000 inhabitants), section 2 (14/1000). All 31 cooling towers of district 2 were analysed. L. pneumophila antigen (Binax Now) was detected in four towers, which were closed on 2 June. Only the strain isolated in a tower situated in section 2 of district 2 matched all five clinical isolates, as assessed by mAb and two genotyping methods, AFLP and PFGE. Eight days after closing the towers, new cases ceased appearing. Early detection and rapid coordinated medical and environmental actions permitted immediate control of the outbreak and probably contributed to the null case fatality. PMID:17662166

A large Legionnaires' disease outbreak in Pamplona, Spain: early detection, rapid control and no case fatality.

PubMed

Castilla, J; Barricarte, A; Aldaz, J; García Cenoz, M; Ferrer, T; Pelaz, C; Pineda, S; Baladrón, B; Martín, I; Goñi, B; Aratajo, P; Chamorro, J; Lameiro, F; Torroba, L; Dorronsoro, I; Martínez-Artola, V; Esparza, M J; Gastaminza, M A; Fraile, P; Aldaz, P

2008-06-01

An outbreak of Legionnaire's disease was detected in Pamplona, Spain, on 1 June 2006. Patients with pneumonia were tested to detect Legionella pneumophila antigen in urine (Binax Now; Binax Inc., Scarborough, ME, USA), and all 146 confirmed cases were interviewed. The outbreak was related to district 2 (22 012 inhabitants), where 45% of the cases lived and 50% had visited; 5% lived in neighbouring districts. The highest incidence was found in the resident population of district 2 (3/1000 inhabitants), section 2 (14/1000). All 31 cooling towers of district 2 were analysed. L. pneumophila antigen (Binax Now) was detected in four towers, which were closed on 2 June. Only the strain isolated in a tower situated in section 2 of district 2 matched all five clinical isolates, as assessed by mAb and two genotyping methods, AFLP and PFGE. Eight days after closing the towers, new cases ceased appearing. Early detection and rapid coordinated medical and environmental actions permitted immediate control of the outbreak and probably contributed to the null case fatality.

A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring.

PubMed

Takahashi, Kunihiko; Kulldorff, Martin; Tango, Toshiro; Yih, Katherine

2008-04-11

Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. Based on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic. The flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.

Social media posts and online search behaviour as early-warning system for MRSA outbreaks.

PubMed

van de Belt, Tom H; van Stockum, Pieter T; Engelen, Lucien J L P G; Lancee, Jules; Schrijver, Remco; Rodríguez-Baño, Jesús; Tacconelli, Evelina; Saris, Katja; van Gelder, Marleen M H J; Voss, Andreas

2018-01-01

Despite many preventive measures, outbreaks with multi-drug resistant micro-organisms (MDROs) still occur. Moreover, current alert systems from healthcare organizations have shortcomings due to delayed or incomplete notifications, which may amplify the spread of MDROs by introducing infected patients into a new healthcare setting and institutions. Additional sources of information about upcoming and current outbreaks, may help to prevent further spread of MDROs.The study objective was to evaluate whether methicillin-resistant Staphylococcus aureus (MRSA) outbreaks could be detected via social media posts or online search behaviour; if so, this might allow earlier detection than the official notifications by healthcare organizations. We conducted an exploratory study in which we compared information about MRSA outbreaks in the Netherlands derived from two online sources, Coosto for Social Media, and Google Trends for search behaviour, to the mandatory Dutch outbreak notification system (SO-ZI/AMR). The latter provides information on MDRO outbreaks including the date of the outbreak, micro-organism involved, the region/location, and the type of health care organization. During the research period of 15 months (455 days), 49 notifications of outbreaks were recorded in SO-ZI/AMR. For Coosto, the number of unique potential outbreaks was 37 and for Google Trends 24. The use of social media and online search behaviour missed many of the hospital outbreaks that were reported to SO-ZI/AMR, but detected additional outbreaks in long-term care facilities. Despite several limitations, using information from social media and online search behaviour allows rapid identification of potential MRSA outbreaks, especially in healthcare settings with a low notification compliance. When combined in an automated system with real-time updates, this approach might increase early discovery and subsequent implementation of preventive measures.

Spectral evidence of early-stage spruce beetle infestation in Engelmann spruce

Treesearch

Adrianna C. Foster; Jonathan A. Walter; Herman H. Shugart; Jason Sibold; Jose Negron

2017-01-01

Spruce beetle (Dendroctonus rufipennis (Kirby)) outbreaks cause widespread mortality of Engelmann spruce (Picea engelmannii (Parry ex Engelm)) within the subalpine forests of the western United States. Early detection of infestations could allow forest managers to mitigate outbreaks or anticipate a response to tree mortality and the potential effects on ecosystem...

Gastroenteritis outbreaks on cruise ships: contributing factors and thresholds for early outbreak detection

PubMed Central

Mouchtouri, Varvara A; Verykouki, Eleni; Zamfir, Dumitru; Hadjipetris, Christos; Lewis, Hannah C; Hadjichristodoulou, Christos

2017-01-01

When an increased number of acute gastroenteritis (AG) cases is detected among tourists staying at the same accommodation, outbreak management plans must be activated in a timely manner to prevent large outbreaks. Syndromic surveillance data collected between 1 January 2010 and 31 December 2013 by five seagoing cruise ships were analysed to identify attack rate thresholds for early outbreak detection. The overall incidence rate of AG was 2.81 cases per 10,000 traveller-days (95% confidence interval (CI): 0.00–17.60), while the attack rate was 19.37 cases per 10,000 travellers (95% CI: 0.00–127.69). The probability of an outbreak occurring was 11% if 4 per 1,000 passengers reported symptoms within the first 2 days of the voyage, and this increased to 23 % if 5 per 1,000 passengers reported such within the first 3 days. The risk ratio (RR) for outbreak occurrence was 2.35, 5.66 and 8.63 for 1, 2 and 3 days’ delay of symptoms reporting respectively, suggesting a dose–response relationship. Shipping companies’ policies and health authorities’ efforts may consider these thresholds for initiating outbreak response measures based on the number of cases according to day of cruise. Efforts should focus on ensuring travellers report symptoms immediately and comply with isolation measures. PMID:29162205

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

PubMed Central

Sun, Lijun; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2014-01-01

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree. PMID:24903017

[Legionella pneumophila pneumonia community epidemic outbreak in Barcelona: "The Barceloneta outbreak". Effect on the early diagnosis and treatment].

PubMed

Jericó Alba, C; Nogués Solán, X; Santos Martínez, M J; Félez Flor, M; Garcés Jarque, J M; Mariñosa Marré, M; Sanz Salvador, X

2004-02-01

Clinical and microbiological descriptive analysis of the outbreak of community legionnaire's disease recorded in the Barcelona's Barcelonesa neighborhood in November 2000. Retrospective review of the epidemiological and clinical manifestations, as well as the evolution of the cases of Legionella pneumophila pneumonia associated with the outbreak and cared of in the Hospital del Mar. The 48 patients evaluated, all of them with confirmed diagnoses, represent 89% of the cases communicated. Seventy-five percent of patients showed some underlying disease, 54% had some criterion for severity, and mortality was 4%. In 81% of cases the detection of the antigen of Legionella pneumophila in urine was the diagnostic method. The detection in urine of the Legionella pneumophila antigen makes possible the early diagnosis of legionnaire's disease, particularly in epidemic outbreaks, which that facilitates the fast establishment of the adequate treatment and contributes to the reduction in mortality even in patients of high risk.

Detection of pathogenic viruses in sewage provided early warnings of hepatitis A virus and norovirus outbreaks.

PubMed

Hellmér, Maria; Paxéus, Nicklas; Magnius, Lars; Enache, Lucica; Arnholm, Birgitta; Johansson, Annette; Bergström, Tomas; Norder, Heléne

2014-11-01

Most persons infected with enterically transmitted viruses shed large amounts of virus in feces for days or weeks, both before and after onset of symptoms. Therefore, viruses causing gastroenteritis may be detected in wastewater, even if only a few persons are infected. In this study, the presence of eight pathogenic viruses (norovirus, astrovirus, rotavirus, adenovirus, Aichi virus, parechovirus, hepatitis A virus [HAV], and hepatitis E virus) was investigated in sewage to explore whether their identification could be used as an early warning of outbreaks. Samples of the untreated sewage were collected in proportion to flow at Ryaverket, Gothenburg, Sweden. Daily samples collected during every second week between January and May 2013 were pooled and analyzed for detection of viruses by concentration through adsorption to milk proteins and PCR. The largest amount of noroviruses was detected in sewage 2 to 3 weeks before most patients were diagnosed with this infection in Gothenburg. The other viruses were detected at lower levels. HAV was detected between weeks 5 and 13, and partial sequencing of the structural VP1protein identified three different strains. Two strains were involved in an ongoing outbreak in Scandinavia and were also identified in samples from patients with acute hepatitis A in Gothenburg during spring of 2013. The third strain was unique and was not detected in any patient sample. The method used may thus be a tool to detect incipient outbreaks of these viruses and provide early warning before the causative pathogens have been recognized in health care. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Detection of Pathogenic Viruses in Sewage Provided Early Warnings of Hepatitis A Virus and Norovirus Outbreaks

PubMed Central

Hellmér, Maria; Paxéus, Nicklas; Magnius, Lars; Enache, Lucica; Arnholm, Birgitta; Johansson, Annette; Bergström, Tomas

2014-01-01

Most persons infected with enterically transmitted viruses shed large amounts of virus in feces for days or weeks, both before and after onset of symptoms. Therefore, viruses causing gastroenteritis may be detected in wastewater, even if only a few persons are infected. In this study, the presence of eight pathogenic viruses (norovirus, astrovirus, rotavirus, adenovirus, Aichi virus, parechovirus, hepatitis A virus [HAV], and hepatitis E virus) was investigated in sewage to explore whether their identification could be used as an early warning of outbreaks. Samples of the untreated sewage were collected in proportion to flow at Ryaverket, Gothenburg, Sweden. Daily samples collected during every second week between January and May 2013 were pooled and analyzed for detection of viruses by concentration through adsorption to milk proteins and PCR. The largest amount of noroviruses was detected in sewage 2 to 3 weeks before most patients were diagnosed with this infection in Gothenburg. The other viruses were detected at lower levels. HAV was detected between weeks 5 and 13, and partial sequencing of the structural VP1protein identified three different strains. Two strains were involved in an ongoing outbreak in Scandinavia and were also identified in samples from patients with acute hepatitis A in Gothenburg during spring of 2013. The third strain was unique and was not detected in any patient sample. The method used may thus be a tool to detect incipient outbreaks of these viruses and provide early warning before the causative pathogens have been recognized in health care. PMID:25172863

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System

PubMed Central

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2017-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS. PMID:28728470

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System.

PubMed

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2018-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS.

A method for detecting and characterizing outbreaks of infectious disease from clinical reports.

PubMed

Cooper, Gregory F; Villamarin, Ricardo; Rich Tsui, Fu-Chiang; Millett, Nicholas; Espino, Jeremy U; Wagner, Michael M

2015-02-01

Outbreaks of infectious disease can pose a significant threat to human health. Thus, detecting and characterizing outbreaks quickly and accurately remains an important problem. This paper describes a Bayesian framework that links clinical diagnosis of individuals in a population to epidemiological modeling of disease outbreaks in the population. Computer-based diagnosis of individuals who seek healthcare is used to guide the search for epidemiological models of population disease that explain the pattern of diagnoses well. We applied this framework to develop a system that detects influenza outbreaks from emergency department (ED) reports. The system diagnoses influenza in individuals probabilistically from evidence in ED reports that are extracted using natural language processing. These diagnoses guide the search for epidemiological models of influenza that explain the pattern of diagnoses well. Those epidemiological models with a high posterior probability determine the most likely outbreaks of specific diseases; the models are also used to characterize properties of an outbreak, such as its expected peak day and estimated size. We evaluated the method using both simulated data and data from a real influenza outbreak. The results provide support that the approach can detect and characterize outbreaks early and well enough to be valuable. We describe several extensions to the approach that appear promising. Copyright © 2014 Elsevier Inc. All rights reserved.

A Method for Detecting and Characterizing Outbreaks of Infectious Disease from Clinical Reports

PubMed Central

Cooper, Gregory F.; Villamarin, Ricardo; Tsui, Fu-Chiang (Rich); Millett, Nicholas; Espino, Jeremy U.; Wagner, Michael M.

2014-01-01

Outbreaks of infectious disease can pose a significant threat to human health. Thus, detecting and characterizing outbreaks quickly and accurately remains an important problem. This paper describes a Bayesian framework that links clinical diagnosis of individuals in a population to epidemiological modeling of disease outbreaks in the population. Computer-based diagnosis of individuals who seek healthcare is used to guide the search for epidemiological models of population disease that explain the pattern of diagnoses well. We applied this framework to develop a system that detects influenza outbreaks from emergency department (ED) reports. The system diagnoses influenza in individuals probabilistically from evidence in ED reports that are extracted using natural language processing. These diagnoses guide the search for epidemiological models of influenza that explain the pattern of diagnoses well. Those epidemiological models with a high posterior probability determine the most likely outbreaks of specific diseases; the models are also used to characterize properties of an outbreak, such as its expected peak day and estimated size. We evaluated the method using both simulated data and data from a real influenza outbreak. The results provide support that the approach can detect and characterize outbreaks early and well enough to be valuable. We describe several extensions to the approach that appear promising. PMID:25181466

The important role of early diagnosis and preventive management during a large-scale outbreak of hepatitis A in Thailand

PubMed Central

Poovorawan, Kittiyod; Chattakul, Paiboon; Chattakul, Sirirat; Thongmee, Thanunrat; Theamboonlers, Apiradee; Komolmit, Piyawat; Poovorawan, Yong

2013-01-01

Introduction Acute hepatitis A is a worldwide public health problem especially in developing countries. Recently, a large, community-wide outbreak of hepatitis A occurred in the northeast part of Thailand. Methods Demographic and clinical data as well as blood samples were collected and analyzed from patients with acute hepatitis who attended the Buengkan Provincial Hospital from June to September 2012. About 1619 patients with clinical symptoms of hepatitis A visited the hospital during the outbreak which manifested in three waves. Blood samples were collected from 205 patients. Results One hundred and seventy eight patients had hepatitis A confirmed by the presence of anti-hepatitis A virus (HAV) IgM and/or HAV-RNA. The sensitivities for anti-HAV IgM and HAV-RNA were 95.5% (170/178) and 61.8% (110/178), respectively. When HAV-RNA was combined with anti-HAV IgM test, this increased the diagnostic yield by 7.2% (8/111) in the early phase of the acute infection (less than 5 days). Investigation of the molecular structure of the detected viruses indicated that all of the infections were caused by HAV genotype IA. There were no fatalities from this outbreak. Rapid detection, health education, sanitation campaigns, and vaccination offered on a voluntary basis have steadily reduced the number of infected patients and stopped the outbreak. Conclusion Occasionally a large-scale outbreak of HAV genotype IA can occur. A combination of HAV-RNA and anti-HAV IgM tests can increase the diagnostic yield during the early phase of the acute infection. Early diagnosis and preventive management campaigns can slow down and stop the outbreak. PMID:24392680

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings

PubMed Central

Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S. Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Background Dengue outbreaks are increasing in frequency over space and time, affecting people’s health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. Methods We report on the development of the EWARS tool, based on users’ recommendations into a convenient, user-friendly and reliable software aided by a user’s workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. Findings 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. Conclusion EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities. PMID:29727447

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings.

PubMed

Hussain-Alkhateeb, Laith; Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

ID-Viewer: a visual analytics architecture for infectious diseases surveillance and response management in Pakistan.

PubMed

Ali, M A; Ahsan, Z; Amin, M; Latif, S; Ayyaz, A; Ayyaz, M N

2016-05-01

Globally, disease surveillance systems are playing a significant role in outbreak detection and response management of Infectious Diseases (IDs). However, in developing countries like Pakistan, epidemic outbreaks are difficult to detect due to scarcity of public health data and absence of automated surveillance systems. Our research is intended to formulate an integrated service-oriented visual analytics architecture for ID surveillance, identify key constituents and set up a baseline for easy reproducibility of such systems in the future. This research focuses on development of ID-Viewer, which is a visual analytics decision support system for ID surveillance. It is a blend of intelligent approaches to make use of real-time streaming data from Emergency Departments (EDs) for early outbreak detection, health care resource allocation and epidemic response management. We have developed a robust service-oriented visual analytics architecture for ID surveillance, which provides automated mechanisms for ID data acquisition, outbreak detection and epidemic response management. Classification of chief-complaints is accomplished using dynamic classification module, which employs neural networks and fuzzy-logic to categorize syndromes. Standard routines by Center for Disease Control (CDC), i.e. c1-c3 (c1-mild, c2-medium and c3-ultra), and spatial scan statistics are employed for detection of temporal and spatio-temporal disease outbreaks respectively. Prediction of imminent disease threats is accomplished using support vector regression for early warnings and response planning. Geographical visual analytics displays are developed that allow interactive visualization of syndromic clusters, monitoring disease spread patterns, and identification of spatio-temporal risk zones. We analysed performance of surveillance framework using ID data for year 2011-2015. Dynamic syndromic classifier is able to classify chief-complaints to appropriate syndromes with high classification accuracy. Outbreak detection methods are able to detect the ID outbreaks in start of epidemic time zones. Prediction model is able to forecast dengue trend for 20 weeks ahead with nominal normalized root mean square error of 0.29. Interactive geo-spatiotemporal displays, i.e. heat-maps, and choropleth are shown in respective sections. The proposed framework will set a standard and provide necessary details for future implementation of such a system for resource-constrained regions. It will improve early outbreak detection attributable to natural and man-made biological threats, monitor spatio-temporal epidemic trends and provide assurance that an outbreak has, or has not occurred. Advanced analytics features will be beneficial in timely organization/formulation of health management policies, disease control activities and efficient health care resource allocation. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Transmission patterns of smallpox: systematic review of natural outbreaks in Europe and North America since World War II.

PubMed

Bhatnagar, Vibha; Stoto, Michael A; Morton, Sally C; Boer, Rob; Bozzette, Samuel A

2006-05-05

Because smallpox (variola major) may be used as a biological weapon, we reviewed outbreaks in post-World War II Europe and North America in order to understand smallpox transmission patterns. A systematic review was used to identify papers from the National Library of Medicine, Embase, Biosis, Cochrane Library, Defense Technical Information Center, WorldCat, and reference lists of included publications. Two authors reviewed selected papers for smallpox outbreaks. 51 relevant outbreaks were identified from 1,389 publications. The median for the effective first generation reproduction rate (initial R) was 2 (range 0-38). The majority outbreaks were small (less than 5 cases) and contained within one generation. Outbreaks with few hospitalized patients had low initial R values (median of 1) and were prolonged if not initially recognized (median of 3 generations); outbreaks with mostly hospitalized patients had higher initial R values (median 12) and were shorter (median of 3 generations). Index cases with an atypical presentation of smallpox were less likely to have been diagnosed with smallpox; outbreaks in which the index case was not correctly diagnosed were larger (median of 27.5 cases) and longer (median of 3 generations) compared to outbreaks in which the index case was correctly diagnosed (median of 3 cases and 1 generation). Patterns of spread during Smallpox outbreaks varied with circumstances, but early detection and implementation of control measures is a most important influence on the magnitude of outbreaks. The majority of outbreaks studied in Europe and North America were controlled within a few generations if detected early.

Novel Use of Flu Surveillance Data: Evaluating Potential of Sentinel Populations for Early Detection of Influenza Outbreaks.

PubMed

Daughton, Ashlynn R; Velappan, Nileena; Abeyta, Esteban; Priedhorsky, Reid; Deshpande, Alina

2016-01-01

Influenza causes significant morbidity and mortality each year, with 2-8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009-2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we compare pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. This study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results.

Sharing experiences: towards an evidence based model of dengue surveillance and outbreak response in Latin America and Asia

PubMed Central

2013-01-01

Background The increasing frequency and intensity of dengue outbreaks in endemic and non-endemic countries requires a rational, evidence based response. To this end, we aimed to collate the experiences of a number of affected countries, identify strengths and limitations in dengue surveillance, outbreak preparedness, detection and response and contribute towards the development of a model contingency plan adaptable to country needs. Methods The study was undertaken in five Latin American (Brazil, Colombia, Dominican Republic, Mexico, Peru) and five in Asian countries (Indonesia, Malaysia, Maldives, Sri Lanka, Vietnam). A mixed-methods approach was used which included document analysis, key informant interviews, focus-group discussions, secondary data analysis and consensus building by an international dengue expert meeting organised by the World Health Organization, Special Program for Research and Training in Tropical Diseases (WHO-TDR). Results Country information on dengue is based on compulsory notification and reporting (“passive surveillance”), with laboratory confirmation (in all participating Latin American countries and some Asian countries) or by using a clinical syndromic definition. Seven countries additionally had sentinel sites with active dengue reporting, some also had virological surveillance. Six had agreed a formal definition of a dengue outbreak separate to seasonal variation in case numbers. Countries collected data on a range of warning signs that may identify outbreaks early, but none had developed a systematic approach to identifying and responding to the early stages of an outbreak. Outbreak response plans varied in quality, particularly regarding the early response. The surge capacity of hospitals with recent dengue outbreaks varied; those that could mobilise additional staff, beds, laboratory support and resources coped best in comparison to those improvising a coping strategy during the outbreak. Hospital outbreak management plans were present in 9/22 participating hospitals in Latin-America and 8/20 participating hospitals in Asia. Conclusions Considerable variation between countries was observed with regard to surveillance, outbreak detection, and response. Through discussion at the expert meeting, suggestions were made for the development of a more standardised approach in the form of a model contingency plan, with agreed outbreak definitions and country-specific risk assessment schemes to initiate early response activities according to the outbreak phase. This would also allow greater cross-country sharing of ideas. PMID:23800243

Sharing experiences: towards an evidence based model of dengue surveillance and outbreak response in Latin America and Asia.

PubMed

Badurdeen, Shiraz; Valladares, David Benitez; Farrar, Jeremy; Gozzer, Ernesto; Kroeger, Axel; Kuswara, Novia; Ranzinger, Silvia Runge; Tinh, Hien Tran; Leite, Priscila; Mahendradhata, Yodi; Skewes, Ronald; Verrall, Ayesha

2013-06-24

The increasing frequency and intensity of dengue outbreaks in endemic and non-endemic countries requires a rational, evidence based response. To this end, we aimed to collate the experiences of a number of affected countries, identify strengths and limitations in dengue surveillance, outbreak preparedness, detection and response and contribute towards the development of a model contingency plan adaptable to country needs. The study was undertaken in five Latin American (Brazil, Colombia, Dominican Republic, Mexico, Peru) and five in Asian countries (Indonesia, Malaysia, Maldives, Sri Lanka, Vietnam). A mixed-methods approach was used which included document analysis, key informant interviews, focus-group discussions, secondary data analysis and consensus building by an international dengue expert meeting organised by the World Health Organization, Special Program for Research and Training in Tropical Diseases (WHO-TDR). Country information on dengue is based on compulsory notification and reporting ("passive surveillance"), with laboratory confirmation (in all participating Latin American countries and some Asian countries) or by using a clinical syndromic definition. Seven countries additionally had sentinel sites with active dengue reporting, some also had virological surveillance. Six had agreed a formal definition of a dengue outbreak separate to seasonal variation in case numbers. Countries collected data on a range of warning signs that may identify outbreaks early, but none had developed a systematic approach to identifying and responding to the early stages of an outbreak. Outbreak response plans varied in quality, particularly regarding the early response. The surge capacity of hospitals with recent dengue outbreaks varied; those that could mobilise additional staff, beds, laboratory support and resources coped best in comparison to those improvising a coping strategy during the outbreak. Hospital outbreak management plans were present in 9/22 participating hospitals in Latin-America and 8/20 participating hospitals in Asia. Considerable variation between countries was observed with regard to surveillance, outbreak detection, and response. Through discussion at the expert meeting, suggestions were made for the development of a more standardised approach in the form of a model contingency plan, with agreed outbreak definitions and country-specific risk assessment schemes to initiate early response activities according to the outbreak phase. This would also allow greater cross-country sharing of ideas.

[Outbreak of pandemic virus (H1N1) 2009 in a residence for mentally disabled persons in Balearic Island, Spain].

PubMed

Giménez Duran, Jaume; Galmés Truyols, Antònia; Nicolau Riutort, Antonio; Reina Prieto, Jorge; Gallegos Álvarez, Maria de Carmen; Pareja Bezares, Antonio; Vanrell Berga, Juana María

2010-01-01

The flu season 2009-2010 has been shorter and less severe than expected. Since January 2010, influenza surveillance systems indicated rates of very low incidence of influenza without detection of virus circulation. In this context, a hospital reported a suspected outbreak of severe respiratory disease, the aetiology proved influenza A(H1N1)v. We describe the outbreak and public health measures for their control. Descriptive study of an outbreak of pandemic influenza virus in a residency home for mentally disabled. Establishment of active surveillance. The case definition of influenza was very sensitive to detect new cases early, treated early and minimize transmission. Steps were taken to contain the influenza virus infection. Among 38 cases detected 7 had serious complications(all of them with risk factors). There were no deaths. The overall attack rate was 35.2%. The first cases were workers. The residents were ill at the peak of the outbreak, and among workers the presentation was more dispersed. None of the workers and only three of residents had been vaccinated. Workers possibly have initiated and contributed to the maintenance of transmission. We emphasize the need to comply with vaccination recommendations, not just those with risk factors, but particularly for workers in contact with those.

Surveillance for outbreaks of influenza-like illness in the institutionalized elderly.

PubMed

Rosewell, A; Chiu, C; Lindley, R; Dwyer, D E; Moffatt, C R M; Shineberg, C; Clarke, E; Booy, R; MacIntyre, C R

2010-08-01

Respiratory outbreaks are common in aged-care facilities (ACFs), are both underreported and frequently identified late, and are often associated with considerable burden of illness and death. There is emerging evidence that active surveillance coupled with early and systematic intervention can reduce this burden. Active surveillance for influenza-like illness and rapid diagnosis of influenza were established in 16 ACFs in Sydney, Australia, prior to the winter of 2006. A point-of-care influenza test and laboratory direct immunofluorescence tests for common respiratory viruses were used for diagnosis. We achieved early identification of seven respiratory disease outbreaks, two of which were caused by influenza. For the influenza outbreaks, antiviral treatment and prophylaxis were initiated 4-6 days from symptom onset in the primary case. A simple active surveillance system for influenza was successfully implemented and resulted in early detection of influenza and other respiratory disease outbreaks. This enabled earlier implementation of prevention and control measures and increased the potential effectiveness of anti-influenza chemoprophylaxis.

Most Common Foodborne Pathogens and Mycotoxins on Fresh Produce: A Review of Recent Outbreaks.

PubMed

Yeni, F; Yavaş, S; Alpas, H; Soyer, Y

2016-07-03

Every year millions of people are affected and thousands of them die due to infections and intoxication as a result of foodborne outbreaks, which also cause billions of dollars' worth of damage, public health problems, and agricultural product loss. A considerable portion of these outbreaks is related to fresh produce and caused by foodborne pathogens on fresh produce and mycotoxins. Escherichia coli O104:H4 outbreak, occurred in Germany in 2011, has attracted a great attention on foodborne outbreaks caused by contaminated fresh produce, and especially the vulnerability and gaps in the early warning and notification networks in the surveillance systems in all around the world. In the frame of this paper, we reviewed the most common foodborne pathogens on fresh produce, traceback investigations of the outbreaks caused by these pathogens, and lastly international early warning and notification systems, including PulseNet International and Rapid Alert System for Food and Feed, aiming to detect foodborne outbreaks.

Case study of the use of pulsed field gel electrophoresis in the detection of a food-borne outbreak.

PubMed

De Lappe, Niall; Cormican, Martin

2015-01-01

In early July 2008, a cluster of six Salmonella Agona was identified in the Republic of Ireland. A dispersed, common source outbreak was suspected. Later in July a further case was identified and the Health Protection Agency in the UK indicated that they had 32 cases of S. Agona since Feb 2008. This chapter discusses how pulsed field gel electrophoresis was used to help confirm an outbreak and to trace the source of the outbreak.

Early detection of foot-and-mouth disease virus from infected cattle using a dry filter air sampling system

USDA-ARS?s Scientific Manuscript database

Foot-and-mouth disease (FMD) is a highly contagious livestock disease of high economic impact. Early detection of FMD virus (FMDV) is fundamental for rapid outbreak control. Air sampling collection has been demonstrated as a useful technique for detection of FMDV RNA in infected animals, related to ...

Emergence of new norovirus variants on spring cruise ships and prediction of winter epidemics.

PubMed

Verhoef, Linda; Depoortere, Evelyn; Boxman, Ingeborg; Duizer, Erwin; van Duynhoven, Yvonne; Harris, John; Johnsen, Christina; Kroneman, Annelies; Le Guyader, Soizick; Lim, Wilina; Maunula, Leena; Meldal, Hege; Ratcliff, Rod; Reuter, Gábor; Schreier, Eckart; Siebenga, Joukje; Vainio, Kirsti; Varela, Carmen; Vennema, Harry; Koopmans, Marion

2008-02-01

In June 2006, reported outbreaks of norovirus on cruise ships suddenly increased; 43 outbreaks occurred on 13 vessels. All outbreaks investigated manifested person-to-person transmission. Detection of a point source was impossible because of limited investigation of initial outbreaks and data sharing. The most probable explanation for these outbreaks is increased norovirus activity in the community, which coincided with the emergence of 2 new GGII.4 variant strains in Europe and the Pacific. As in 2002, a new GGII.4 variant detected in the spring and summer corresponded with high norovirus activity in the subsequent winter. Because outbreaks on cruise ships are likely to occur when new variants circulate, an active reporting system could function as an early warning system. Internationally accepted guidelines are needed for reporting, investigating, and controlling norovirus illness on cruise ships in Europe.

Emergence of New Norovirus Variants on Spring Cruise Ships and Prediction of Winter Epidemics

PubMed Central

Depoortere, Evelyn; Boxman, Ingeborg; Duizer, Erwin; van Duynhoven, Yvonne; Harris, John; Johnsen, Christina; Kroneman, Annelies; Le Guyader, Soizick; Lim, Wilina; Maunula, Leena; Meldal, Hege; Ratcliff, Rod; Reuter, Gábor; Schreier, Eckart; Siebenga, Joukje; Vainio, Kirsti; Varela, Carmen; Vennema, Harry; Koopmans, Marion

2008-01-01

In June 2006, reported outbreaks of norovirus on cruise ships suddenly increased; 43 outbreaks occurred on 13 vessels. All outbreaks investigated manifested person-to-person transmission. Detection of a point source was impossible because of limited investigation of initial outbreaks and data sharing. The most probable explanation for these outbreaks is increased norovirus activity in the community, which coincided with the emergence of 2 new GGII.4 variant strains in Europe and the Pacific. As in 2002, a new GGII.4 variant detected in the spring and summer corresponded with high norovirus activity in the subsequent winter. Because outbreaks on cruise ships are likely to occur when new variants circulate, an active reporting system could function as an early warning system. Internationally accepted guidelines are needed for reporting, investigating, and controlling norovirus illness on cruise ships in Europe. PMID:18258116

A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks.

PubMed

Yang, Eunjoo; Park, Hyun Woo; Choi, Yeon Hwa; Kim, Jusim; Munkhdalai, Lkhagvadorj; Musa, Ibrahim; Ryu, Keun Ho

2018-05-11

Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt⁻Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.

Predicting potential and actual distribution of sudden oak death in Oregon: prioritizing landscape contexts for early detection and eradication of disease outbreaks

Treesearch

Tomas Vaclavik; Alan Kanaskie; Everett M. Hansen; Janet L. Ohmann; Ross K. Meentemeyer

2010-01-01

An isolated outbreak of the emerging forest disease sudden oak death was discovered in Oregon forests in 2001. Despite considerable control efforts, disease continues to spread from the introduction site due to slow and incomplete detection and eradication. Annual field surveys and laboratory tests between 2001 and 2009 confirmed a total of 802 infested locations. Here...

Detecting and Responding to a Dengue Outbreak: Evaluation of Existing Strategies in Country Outbreak Response Planning

PubMed Central

Kroeger, Axel; Runge-Ranzinger, Silvia; O'Dempsey, Tim

2013-01-01

Background. Dengue outbreaks are occurring with increasing frequency and intensity. Evidence-based epidemic preparedness and effective response are now a matter of urgency. Therefore, we have analysed national and municipal dengue outbreak response plans. Methods. Thirteen country plans from Asia, Latin America and Australia, and one international plan were obtained from the World Health Organization. The information was transferred to a data analysis matrix where information was extracted according to predefined and emerging themes and analysed for scope, inconsistencies, omissions, and usefulness. Findings. Outbreak response planning currently has a considerable number of flaws. Outbreak governance was weak with a lack of clarity of stakeholder roles. Late timing of responses due to poor surveillance, a lack of combining routine data with additional alerts, and lack of triggers for initiating the response weakened the functionality of plans. Frequently an outbreak was not defined, and early response mechanisms based on alert signals were neglected. There was a distinct lack of consideration of contextual influences which can affect how an outbreak detection and response is managed. Conclusion. A model contingency plan for dengue outbreak prediction, detection, and response may help national disease control authorities to develop their own more detailed and functional context specific plans. PMID:24222774

Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks

DOE PAGES

Daughton, Ashlynn R.; Velappan, Nileena; Abeyta, Esteban; ...

2016-07-08

Influenza causes significant morbidity and mortality each year, with 2–8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009–2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we comparemore » pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. In conclusion, this study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results.« less

Novel use of flu surveillance data: Evaluating potential of sentinel populations for early detection of influenza outbreaks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daughton, Ashlynn R.; Velappan, Nileena; Abeyta, Esteban

Influenza causes significant morbidity and mortality each year, with 2–8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009–2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we comparemore » pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. In conclusion, this study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results.« less

Novel Use of Flu Surveillance Data: Evaluating Potential of Sentinel Populations for Early Detection of Influenza Outbreaks

PubMed Central

Velappan, Nileena; Abeyta, Esteban; Priedhorsky, Reid; Deshpande, Alina

2016-01-01

Influenza causes significant morbidity and mortality each year, with 2–8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009–2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we compare pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. This study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results. PMID:27391232

Value of syndromic surveillance within the Armed Forces for early warning during a dengue fever outbreak in French Guiana in 2006

PubMed Central

Meynard, Jean-Baptiste; Chaudet, Hervé; Texier, Gaetan; Ardillon, Vanessa; Ravachol, Françoise; Deparis, Xavier; Jefferson, Henry; Dussart, Philippe; Morvan, Jacques; Boutin, Jean-Paul

2008-01-01

Background A dengue fever outbreak occured in French Guiana in 2006. The objectives were to study the value of a syndromic surveillance system set up within the armed forces, compared to the traditional clinical surveillance system during this outbreak, to highlight issues involved in comparing military and civilian surveillance systems and to discuss the interest of syndromic surveillance for public health response. Methods Military syndromic surveillance allows the surveillance of suspected dengue fever cases among the 3,000 armed forces personnel. Within the same population, clinical surveillance uses several definition criteria for dengue fever cases, depending on the epidemiological situation. Civilian laboratory surveillance allows the surveillance of biologically confirmed cases, within the 200,000 inhabitants. Results It was shown that syndromic surveillance detected the dengue fever outbreak several weeks before clinical surveillance, allowing quick and effective enhancement of vector control within the armed forces. Syndromic surveillance was also found to have detected the outbreak before civilian laboratory surveillance. Conclusion Military syndromic surveillance allowed an early warning for this outbreak to be issued, enabling a quicker public health response by the armed forces. Civilian surveillance system has since introduced syndromic surveillance as part of its surveillance strategy. This should enable quicker public health responses in the future. PMID:18597694

The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health.

PubMed

Mykhalovskiy, Eric; Weir, Lorna

2006-01-01

The recent SARS epidemic has renewed widespread concerns about the global transmission of infectious diseases. In this commentary, we explore novel approaches to global infectious disease surveillance through a focus on an important Canadian contribution to the area--the Global Public Health Intelligence Network (GPHIN). GPHIN is a cutting-edge initiative that draws on the capacity of the Internet and newly available 24/7 global news coverage of health events to create a unique form of early warning outbreak detection. This commentary outlines the operation and development of GPHIN and compares it to ProMED-mail, another Internet-based approach to global health surveillance. We argue that GPHIN has created an important shift in the relationship of public health and news information. By exiting the pyramid of official reporting, GPHIN has created a new monitoring technique that has disrupted national boundaries of outbreak notification, while creating new possibilities for global outbreak response. By incorporating news within the emerging apparatus of global infectious disease surveillance, GPHIN has effectively responded to the global media's challenge to official country reporting of outbreak and enhanced the effectiveness and credibility of international public health.

A susceptible-infected model of early detection of respiratory infection outbreaks on a background of influenza

PubMed Central

Mohtashemi, Mojdeh; Szolovits, Peter; Dunyak, James; Mandl, Kenneth D.

2013-01-01

The threat of biological warfare and the emergence of new infectious agents spreading at a global scale have highlighted the need for major enhancements to the public health infrastructure. Early detection of epidemics of infectious diseases requires both real-time data and real-time interpretation of data. Despite moderate advancements in data acquisition, the state of the practice for real-time analysis of data remains inadequate. We present a nonlinear mathematical framework for modeling the transient dynamics of influenza, applied to historical data sets of patients with influenza-like illness. We estimate the vital time-varying epidemiological parameters of infections from historical data, representing normal epidemiological trends. We then introduce simulated outbreaks of different shapes and magnitudes into the historical data, and estimate the parameters representing the infection rates of anomalous deviations from normal trends. Finally, a dynamic threshold-based detection algorithm is devised to assess the timeliness and sensitivity of detecting the irregularities in the data, under a fixed low false-positive rate. We find that the detection algorithm can identify such designated abnormalities in the data with high sensitivity with specificity held at 97%, but more importantly, early during an outbreak. The proposed methodology can be applied to a broad range of influenza-like infectious diseases, whether naturally occurring or a result of bioterrorism, and thus can be an integral component of a real-time surveillance system. PMID:16556450

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Meiye; Davis, Ryan Wesley; Hatch, Anson

In the early stages of infection, patients develop non-specific or no symptoms at all. While waiting for identification of the infectious agent, precious window of opportunity for early intervention is lost. The standard diagnostics require affinity reagents and sufficient pathogen titers to reach the limit of detection. In the event of a disease outbreak, triaging the at-risk population rapidly and reliably for quarantine and countermeasure is more important than the identification of the pathogen by name. To expand Sandia's portfolio of Biological threat management capabilities, we will utilize Raman spectrometry to analyze immune subsets in whole blood to rapidly distinguishmore » infected from non-infected, and bacterial from viral infection, for the purpose of triage during an emergency outbreak. The goal of this one year LDRD is to determine whether Raman spectroscopy can provide label-free detection of early disease signatures, and define a miniaturized Raman detection system meeting requirements for low- resource settings.« less

Early warning signal for dengue outbreaks and identification of high risk areas for dengue fever in Colombia using climate and non-climate datasets.

PubMed

Lee, Jung-Seok; Carabali, Mabel; Lim, Jacqueline K; Herrera, Victor M; Park, Il-Yeon; Villar, Luis; Farlow, Andrew

2017-07-10

Dengue has been prevalent in Colombia with high risk of outbreaks in various locations. While the prediction of dengue epidemics will bring significant benefits to the society, accurate forecasts have been a challenge. Given competing health demands in Colombia, it is critical to consider the effective use of the limited healthcare resources by identifying high risk areas for dengue fever. The Climate Risk Factor (CRF) index was constructed based upon temperature, precipitation, and humidity. Considering the conditions necessary for vector survival and transmission behavior, elevation and population density were taken into account. An Early Warning Signal (EWS) model was developed by estimating the elasticity of the climate risk factor function to detect dengue epidemics. The climate risk factor index was further estimated at the smaller geographical unit (5 km by 5 km resolution) to identify populations at high risk. From January 2007 to December 2015, the Early Warning Signal model successfully detected 75% of the total number of outbreaks 1 ~ 5 months ahead of time, 12.5% in the same month, and missed 12.5% of all outbreaks. The climate risk factors showed that populations at high risk are concentrated in the Western part of Colombia where more suitable climate conditions for vector mosquitoes and the high population level were observed compared to the East. This study concludes that it is possible to detect dengue outbreaks ahead of time and identify populations at high risk for various disease prevention activities based upon observed climate and non-climate information. The study outcomes can be used to minimize potential societal losses by prioritizing limited healthcare services and resources, as well as by conducting vector control activities prior to experiencing epidemics.

Emergence of Pseudomonas aeruginosa with KPC-type carbapenemase in a teaching hospital: an 8-year study.

PubMed

García Ramírez, Dolores; Nicola, Federico; Zarate, Soledad; Relloso, Silvia; Smayevsky, Jorgelina; Arduino, Sonia

2013-10-01

An outbreak of Klebsiella pneumoniae carbapenamase (KPC)-producing K. pneumoniae occurred at our institution. Multiresistant Pseudomonas aeruginosa could have acquired this transmissible resistance mechanism, going unnoticed because its phenotypic detection in this species is difficult. We compared P. aeruginosa isolates obtained before and after the KPC-producing K. pneumoniae outbreak. No bla(KPC) genes were detected in the isolates obtained before the outbreak, whereas 33/76 (43%) of the isolates obtained after the outbreak harboured the bla(KPC) gene. P. aeruginosa may thus become a reservoir of this transmissible resistance mechanism. It is very important to understand the epidemiology of these multiresistant isolates, in order to achieve early implementation of adequate control measures to contain and reduce their dissemination in the hospital environment.

Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments.

PubMed

Thomas, Mathew J; Yoon, Paula W; Collins, James M; Davidson, Arthur J; Mac Kenzie, William R

Evaluating public health surveillance systems is critical to ensuring that conditions of public health importance are appropriately monitored. Our objectives were to qualitatively evaluate 6 state and local health departments that were early adopters of syndromic surveillance in order to (1) understand the characteristics and current uses, (2) identify the most and least useful syndromes to monitor, (3) gauge the utility for early warning and outbreak detection, and (4) assess how syndromic surveillance impacted their daily decision making. We adapted evaluation guidelines from the Centers for Disease Control and Prevention and gathered input from the Centers for Disease Control and Prevention subject matter experts in public health surveillance to develop a questionnaire. We interviewed staff members from a convenience sample of 6 local and state health departments with syndromic surveillance programs that had been in operation for more than 10 years. Three of the 6 interviewees provided an example of using syndromic surveillance to identify an outbreak (ie, cluster of foodborne illness in 1 jurisdiction) or detect a surge in cases for seasonal conditions (eg, influenza in 2 jurisdictions) prior to traditional, disease-specific systems. Although all interviewees noted that syndromic surveillance has not been routinely useful or efficient for early outbreak detection or case finding in their jurisdictions, all agreed that the information can be used to improve their understanding of dynamic disease control environments and conditions (eg, situational awareness) in their communities. In the jurisdictions studied, syndromic surveillance may be useful for monitoring the spread and intensity of large outbreaks of disease, especially influenza; enhancing public health awareness of mass gatherings and natural disasters; and assessing new, otherwise unmonitored conditions when real-time alternatives are unavailable. Future studies should explore opportunities to strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records. Health departments may accelerate the development and use of syndromic surveillance systems, including the improvement of the predictive value and strengthening the early outbreak detection capability of these systems. These efforts support getting the right information to the right people at the right time, which is the overarching goal of CDC's Surveillance Strategy.

Syndromic Surveillance Using Veterinary Laboratory Data: Algorithm Combination and Customization of Alerts

PubMed Central

Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Sanchez, Javier; Revie, Crawford W.

2013-01-01

Background Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. Methods This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed. Results The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described. Conclusion The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes. PMID:24349216

Syndromic surveillance using veterinary laboratory data: algorithm combination and customization of alerts.

PubMed

Dórea, Fernanda C; McEwen, Beverly J; McNab, W Bruce; Sanchez, Javier; Revie, Crawford W

2013-01-01

Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed. The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described. The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes.

SYBR Green Real-Time PCR for the Detection of All Enterovirus-A71 Genogroups

PubMed Central

Dubot-Pérès, Audrey; Tan, Charlene Y. Q.; de Chesse, Reine; Sibounheuang, Bountoy; Vongsouvath, Manivanh; Phommasone, Koukeo; Bessaud, Maël; Gazin, Céline; Thirion, Laurence; Phetsouvanh, Rattanaphone; Newton, Paul N.; de Lamballerie, Xavier

2014-01-01

Enterovirus A71 (EV-A71) has recently become an important public health threat, especially in South-East Asia, where it has caused massive outbreaks of Hand, Foot and Mouth disease every year, resulting in significant mortality. Rapid detection of EV-A71 early in outbreaks would facilitate implementation of prevention and control measures to limit spread. Real-time RT-PCR is the technique of choice for the rapid diagnosis of EV-A71 infection and several systems have been developed to detect circulating strains. Although eight genogroups have been described globally, none of these PCR techniques detect all eight. We describe, for the first time, a SYBR Green real-time RT-PCR system validated to detect all 8 EV-A71 genogroups. This tool could permit the early detection and shift in genogroup circulation and the standardization of HFMD virological diagnosis, facilitating networking of laboratories working on EV-A71 in different regions. PMID:24651608

Trigger events: enviroclimatic coupling of Ebola hemorrhagic fever outbreaks

NASA Technical Reports Server (NTRS)

Pinzon, Jorge E.; Wilson, James M.; Tucker, Compton J.; Arthur, Ray; Jahrling, Peter B.; Formenty, Pierre

2004-01-01

We use spatially continuous satellite data as a correlate of precipitation within tropical Africa and show that the majority of documented Ebola hemorrhagic fever outbreaks were closely associated with sharply drier conditions at the end of the rainy season. We propose that these trigger events may enhance transmission of Ebola virus from its cryptic reservoir to humans. These findings suggest specific directions to help understand the sylvatic cycle of the virus and may provide early warning tools to detect possible future outbreaks of this enigmatic disease.

The first canine visceral leishmaniasis outbreak in Campinas, State of São Paulo Southeastern Brazil.

PubMed

von Zuben, Andrea Paula Bruno; Angerami, Rodrigo Nogueira; Castagna, Claudio; Baldini, Marisa Bevilacqua Denardi; Donalisio, Maria Rita

2014-01-01

Early detection of American visceral leishmaniasis (AVL) outbreak in animals is crucial for controlling this disease in non-endemic areas. Epidemiological surveillance (2009-2012) was performed in Campinas, State of São Paulo, Brazil. In 2009, Leishmania chagasi was positively identified in four dogs. Entomological research and three serological studies (2010-2012) were undertaken as monitoring measures; these approaches revealed a moderate prevalence of Leishmania present in 4% of the canine population. Nyssomyia whitmani and Lutzomyia longipalpis were the predominant species identified. Detection of an AVL outbreak in dogs in an area with an evolving natural landscape containing sand flies is crucial for control programs.

Listeriosis Outbreaks and Associated Food Vehicles, United States, 1998–2008

PubMed Central

Cartwright, Emily J.; Jackson, Kelly A.; Johnson, Shacara D.; Graves, Lewis M.; Mahon, Barbara E.

2013-01-01

Listeria monocytogenes, a bacterial foodborne pathogen, can cause meningitis, bacteremia, and complications during pregnancy. This report summarizes listeriosis outbreaks reported to the Foodborne Disease Outbreak Surveillance System of the Centers for Disease Control and Prevention during 1998–2008. The study period includes the advent of PulseNet (a national molecular subtyping network for outbreak detection) in 1998 and the Listeria Initiative (enhanced surveillance for outbreak investigation) in 2004. Twenty-four confirmed listeriosis outbreaks were reported during 1998–2008, resulting in 359 illnesses, 215 hospitalizations, and 38 deaths. Outbreaks earlier in the study period were generally larger and longer. Serotype 4b caused the largest number of outbreaks and outbreak-associated cases. Ready-to-eat meats caused more early outbreaks, and novel vehicles (i.e., sprouts, taco/nacho salad) were associated with outbreaks later in the study period. These changes may reflect the effect of PulseNet and the Listeria Initiative and regulatory initiatives designed to prevent contamination in ready-to-eat meat and poultry products. PMID:23260661

What is the utility of using syndromic surveillance systems during large subnational infectious gastrointestinal disease outbreaks? An observational study using case studies from the past 5 years in England.

PubMed

Todkill, D; Elliot, A J; Morbey, R; Harris, J; Hawker, J; Edeghere, O; Smith, G E

2016-08-01

Syndromic surveillance systems in England have demonstrated utility in the early identification of seasonal gastrointestinal illness (GI) tracking its spatio-temporal distribution and enabling early public health action. There would be additional public health utility if syndromic surveillance systems could detect or track subnational infectious disease outbreaks. To investigate using syndromic surveillance for this purpose we retrospectively identified eight large GI outbreaks between 2009 and 2014 (four randomly and four purposively sampled). We then examined syndromic surveillance information prospectively collected by the Real-time Syndromic Surveillance team within Public Health England for evidence of possible outbreak-related changes. None of the outbreaks were identified contemporaneously and no alerts were made to relevant public health teams. Retrospectively, two of the outbreaks - which happened at similar times and in proximal geographical locations - demonstrated changes in the local trends of relevant syndromic indicators and exhibited a clustering of statistical alarms, but did not warrant alerting local health protection teams. Our suite of syndromic surveillance systems may be more suited to their original purposes than as means of detecting or monitoring localized, subnational GI outbreaks. This should, however, be considered in the context of this study's limitations; further prospective work is needed to fully explore the use of syndromic surveillance for this purpose. Provided geographical coverage is sufficient, syndromic surveillance systems could be able to provide reassurance of no or minor excess healthcare systems usage during localized GI incidents.

Case definition for Ebola and Marburg haemorrhagic fevers: a complex challenge for epidemiologists and clinicians.

PubMed

Pittalis, Silvia; Fusco, Francesco Maria; Lanini, Simone; Nisii, Carla; Puro, Vincenzo; Lauria, Francesco Nicola; Ippolito, Giuseppe

2009-10-01

Viral haemorrhagic fevers (VHFs) represent a challenge for public health because of their epidemic potential, and their possible use as bioterrorism agents poses particular concern. In 1999 the World Health Organization (WHO) proposed a case definition for VHFs, subsequently adopted by other international institutions with the aim of early detection of initial cases/outbreaks in western countries. We applied this case definition to reports of Ebola and Marburg virus infections to estimate its sensitivity to detect cases of the disease. We analyzed clinical descriptions of 795 reported cases of Ebola haemorrhagic fever: only 58.5% of patients met the proposed case definition. A similar figure was obtained reviewing 169 cases of Marburg diseases, of which only 64.5% were in accordance with the case definition. In conclusion, the WHO case definition for hemorrhagic fevers is too specific and has poor sensitivity both for case finding during Ebola or Marburg outbreaks, and for early detection of suspected cases in western countries. It can lead to a hazardous number of false negatives and its use should be discouraged for early detection of cases.

Cheese-related listeriosis outbreak, Portugal, March 2009 to February 2012.

PubMed

Magalhaes, R; Almeida, G; Ferreira, V; Santos, I; Silva, J; Mendes, M M; Pita, J; Mariano, G; Mancio, I; Sousa, M M; Farber, J; Pagotto, F; Teixeira, P

2015-04-30

In Portugal, listeriosis has been notifiable since April 2014, but there is no active surveillance programme for the disease. A retrospective study involving 25 national hospitals led to the detection of an outbreak that occurred between March 2009 and February 2012. The amount of time between the start of the outbreak and its detection was 16 months. Of the 30 cases of listeriosis reported, 27 were in the Lisbon and Vale do Tejo region. Two cases were maternal/neonatal infections and one resulted in fetal loss. The mean age of the non-maternal/neonatal cases was 59 years (standard deviation: 17); 13 cases were more than 65 years old. The case fatality rate was 36.7%. All cases were caused by molecular serogroup IVb isolates indistinguishable by pulsed-field gel electrophoresis and ribotype profiles. Collaborative investigations with the national health and food safety authorities identified cheese as the probable source of infection, traced to a processing plant. The magnitude of this outbreak, the first reported food-borne listeriosis outbreak in Portugal, highlights the importance of having an effective listeriosis surveillance system in place for early detection and resolution of outbreaks, as well as the need for a process for the prompt submission of Listeria monocytogenes isolates for routine laboratory typing.

Learning from Ebola Virus: How to Prevent Future Epidemics

PubMed Central

Kekulé, Alexander S.

2015-01-01

The recent Ebola virus disease (EVD) epidemic in Guinea, Liberia and Sierra Leone demonstrated that the World Health Organization (WHO) is incapable to control outbreaks of infectious diseases in less developed regions of the world. This essay analyses the causes for the failure of the international response and proposes four measures to improve resilience, early detection and response to future outbreaks of infectious diseases. PMID:26184283

Two consecutive nationwide outbreaks of Listeriosis in France, October 1999-February 2000.

PubMed

de Valk, H; Vaillant, V; Jacquet, C; Rocourt, J; Le Querrec, F; Stainer, F; Quelquejeu, N; Pierre, O; Pierre, V; Desenclos, J C; Goulet, V

2001-11-15

In France, listeriosis surveillance is based on mandatory notification of all culture-confirmed cases, with systematic typing of isolates and routine collection of the patient's food history. From October 1999 to March 2000, two outbreaks of listeriosis were detected through this enhanced surveillance system. In outbreak 1, analysis of the food histories of cases suggested brand X "rillettes," a pâté-like meat product, as the vehicle of infection, and the outbreak strain of Listeria monocytogenes was subsequently isolated from the incriminated rillettes. In outbreak 2, a case-control study showed that consumption of jellied pork tongue was strongly associated with infection with the outbreak strain (odds ratio = 75.5, 95% confidence interval: 4.7, 1,216.0). However, trace-back results did not permit incrimination of any particular manufacturer of jellied pork tongue, and the outbreak strain was not isolated from the incriminated food or from any production sites. Consumption of jellied pork tongue was discouraged on epidemiologic evidence alone. The consecutive occurrence of these two outbreaks confirms the epidemic potential of listeriosis, even in a context of decreasing incidence, and underlines the importance of timely case-reporting and systematic typing of human L. monocytogenes strains to allow early detection and separate investigation of different clusters.

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Innovative Technological Approach to Ebola Virus Disease Outbreak Response in Nigeria Using the Open Data Kit and Form Hub Technology.

PubMed

Tom-Aba, Daniel; Olaleye, Adeniyi; Olayinka, Adebola Tolulope; Nguku, Patrick; Waziri, Ndadilnasiya; Adewuyi, Peter; Adeoye, Olawunmi; Oladele, Saliu; Adeseye, Aderonke; Oguntimehin, Olukayode; Shuaib, Faisal

2015-01-01

The recent outbreak of Ebola Virus Disease (EVD) in West Africa has ravaged many lives. Effective containment of this outbreak relies on prompt and effective coordination and communication across various interventions; early detection and response being critical to successful control. The use of information and communications technology (ICT) in active surveillance has proved to be effective but its use in Ebola outbreak response has been limited. Due to the need for timeliness in reporting and communication for early discovery of new EVD cases and promptness in response; it became imperative to empower the response team members with technologies and solutions which would enable smooth and rapid data flow. The Open Data Kit and Form Hub technology were used in combination with the Dashboard technology and ArcGIS mapping for follow up of contacts, identification of cases, case investigation and management and also for strategic planning during the response. A remarkable improvement was recorded in the reporting of daily follow-up of contacts after the deployment of the integrated real time technology. The turnaround time between identification of symptomatic contacts and evacuation to the isolation facility and also for receipt of laboratory results was reduced and informed decisions could be taken by all concerned. Accountability in contact tracing was ensured by the use of a GPS enabled device. The use of innovative technologies in the response of the EVD outbreak in Nigeria contributed significantly to the prompt control of the outbreak and containment of the disease by providing a valuable platform for early warning and guiding early actions.

Innovative Technological Approach to Ebola Virus Disease Outbreak Response in Nigeria Using the Open Data Kit and Form Hub Technology

PubMed Central

Nguku, Patrick; Waziri, Ndadilnasiya; Adewuyi, Peter; Adeoye, Olawunmi; Adeseye, Aderonke; Oguntimehin, Olukayode; Shuaib, Faisal

2015-01-01

The recent outbreak of Ebola Virus Disease (EVD) in West Africa has ravaged many lives. Effective containment of this outbreak relies on prompt and effective coordination and communication across various interventions; early detection and response being critical to successful control. The use of information and communications technology (ICT) in active surveillance has proved to be effective but its use in Ebola outbreak response has been limited. Due to the need for timeliness in reporting and communication for early discovery of new EVD cases and promptness in response; it became imperative to empower the response team members with technologies and solutions which would enable smooth and rapid data flow. The Open Data Kit and Form Hub technology were used in combination with the Dashboard technology and ArcGIS mapping for follow up of contacts, identification of cases, case investigation and management and also for strategic planning during the response. A remarkable improvement was recorded in the reporting of daily follow-up of contacts after the deployment of the integrated real time technology. The turnaround time between identification of symptomatic contacts and evacuation to the isolation facility and also for receipt of laboratory results was reduced and informed decisions could be taken by all concerned. Accountability in contact tracing was ensured by the use of a GPS enabled device. The use of innovative technologies in the response of the EVD outbreak in Nigeria contributed significantly to the prompt control of the outbreak and containment of the disease by providing a valuable platform for early warning and guiding early actions. PMID:26115402

Detection of severe respiratory disease epidemic outbreaks by CUSUM-based overcrowd-severe-respiratory-disease-index model.

PubMed

Polanco, Carlos; Castañón-González, Jorge Alberto; Macías, Alejandro E; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

2013-01-01

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008-2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts.

Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

PubMed Central

Castañón-González, Jorge Alberto; Macías, Alejandro E.; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

2013-01-01

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts. PMID:24069063

Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application.

PubMed

Girond, Florian; Randrianasolo, Laurence; Randriamampionona, Lea; Rakotomanana, Fanjasoa; Randrianarivelojosia, Milijaona; Ratsitorahina, Maherisoa; Brou, Télesphore Yao; Herbreteau, Vincent; Mangeas, Morgan; Zigiumugabe, Sixte; Hedje, Judith; Rogier, Christophe; Piola, Patrice

2017-02-13

The use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems. This study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports. Roll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014. This approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments.

Evaluation of outbreak detection performance using multi-stream syndromic surveillance for influenza-like illness in rural Hubei Province, China: a temporal simulation model based on healthcare-seeking behaviors.

PubMed

Fan, Yunzhou; Wang, Ying; Jiang, Hongbo; Yang, Wenwen; Yu, Miao; Yan, Weirong; Diwan, Vinod K; Xu, Biao; Dong, Hengjin; Palm, Lars; Nie, Shaofa

2014-01-01

Syndromic surveillance promotes the early detection of diseases outbreaks. Although syndromic surveillance has increased in developing countries, performance on outbreak detection, particularly in cases of multi-stream surveillance, has scarcely been evaluated in rural areas. This study introduces a temporal simulation model based on healthcare-seeking behaviors to evaluate the performance of multi-stream syndromic surveillance for influenza-like illness. Data were obtained in six towns of rural Hubei Province, China, from April 2012 to June 2013. A Susceptible-Exposed-Infectious-Recovered model generated 27 scenarios of simulated influenza A (H1N1) outbreaks, which were converted into corresponding simulated syndromic datasets through the healthcare-behaviors model. We then superimposed converted syndromic datasets onto the baselines obtained to create the testing datasets. Outbreak performance of single-stream surveillance of clinic visit, frequency of over the counter drug purchases, school absenteeism, and multi-stream surveillance of their combinations were evaluated using receiver operating characteristic curves and activity monitoring operation curves. In the six towns examined, clinic visit surveillance and school absenteeism surveillance exhibited superior performances of outbreak detection than over the counter drug purchase frequency surveillance; the performance of multi-stream surveillance was preferable to signal-stream surveillance, particularly at low specificity (Sp <90%). The temporal simulation model based on healthcare-seeking behaviors offers an accessible method for evaluating the performance of multi-stream surveillance.

Dengue Contingency Planning: From Research to Policy and Practice.

PubMed

Runge-Ranzinger, Silvia; Kroeger, Axel; Olliaro, Piero; McCall, Philip J; Sánchez Tejeda, Gustavo; Lloyd, Linda S; Hakim, Lokman; Bowman, Leigh R; Horstick, Olaf; Coelho, Giovanini

2016-09-01

Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. This handbook facilitates contingency planning as well as the development and use of early warning and response systems for dengue fever epidemics, by identifying decision-making processes that contribute to the success or failure of dengue surveillance, as well as triggers that initiate effective responses to incipient outbreaks. Available evidence was evaluated using a step-wise process that included systematic literature reviews, policymaker and stakeholder interviews, a study to assess dengue contingency planning and outbreak management in 10 countries, and a retrospective logistic regression analysis to identify alarm signals for an outbreak warning system using datasets from five dengue endemic countries. Best practices for managing a dengue outbreak are provided for key elements of a dengue contingency plan including timely contingency planning, the importance of a detailed, context-specific dengue contingency plan that clearly distinguishes between routine and outbreak interventions, surveillance systems for outbreak preparedness, outbreak definitions, alert algorithms, managerial capacity, vector control capacity, and clinical management of large caseloads. Additionally, a computer-assisted early warning system, which enables countries to identify and respond to context-specific variables that predict forthcoming dengue outbreaks, has been developed. Most countries do not have comprehensive, detailed contingency plans for dengue outbreaks. Countries tend to rely on intensified vector control as their outbreak response, with minimal focus on integrated management of clinical care, epidemiological, laboratory and vector surveillance, and risk communication. The Technical Handbook for Surveillance, Dengue Outbreak Prediction/ Detection and Outbreak Response seeks to provide countries with evidence-based best practices to justify the declaration of an outbreak and the mobilization of the resources required to implement an effective dengue contingency plan.

Impact of virus strain characteristics on early detection of highly pathogenic avian influenza infection in commercial table-egg layer flocks and implications for outbreak control.

PubMed

Weaver, J Todd; Malladi, Sasidhar; Goldsmith, Timothy J; Hueston, Will; Hennessey, Morgan; Lee, Brendan; Voss, Shauna; Funk, Janel; Der, Christina; Bjork, Kathe E; Clouse, Timothy L; Halvorson, David A

2012-12-01

Early detection of highly pathogenic avian influenza (HPAI) infection in commercial poultry flocks is a critical component of outbreak control. Reducing the time to detect HPAI infection can reduce the risk of disease transmission to other flocks. The timeliness of different types of detection triggers could be dependent on clinical signs that are first observed in a flock, signs that might vary due to HPAI virus strain characteristics. We developed a stochastic disease transmission model to evaluate how transmission characteristics of various HPAI strains might effect the relative importance of increased mortality, drop in egg production, or daily real-time reverse transcriptase (RRT)-PCR testing, toward detecting HPAI infection in a commercial table-egg layer flock. On average, daily RRT-PCR testing resulted in the shortest time to detection (from 3.5 to 6.1 days) depending on the HPAI virus strain and was less variable over a range of transmission parameters compared with other triggers evaluated. Our results indicate that a trigger to detect a drop in egg production would be useful for HPAI virus strains with long infectious periods (6-8 days) and including an egg-drop detection trigger in emergency response plans would lead to earlier and consistent reporting in some cases. We discuss implications for outbreak control and risk of HPAI spread attributed to different HPAI strain characteristics where an increase in mortality or a drop in egg production or both would be among the first clinical signs observed in an infected flock.

Social Network Sensors for Early Detection of Contagious Outbreaks

PubMed Central

Christakis, Nicholas A.; Fowler, James H.

2010-01-01

Current methods for the detection of contagious outbreaks give contemporaneous information about the course of an epidemic at best. It is known that individuals near the center of a social network are likely to be infected sooner during the course of an outbreak, on average, than those at the periphery. Unfortunately, mapping a whole network to identify central individuals who might be monitored for infection is typically very difficult. We propose an alternative strategy that does not require ascertainment of global network structure, namely, simply monitoring the friends of randomly selected individuals. Such individuals are known to be more central. To evaluate whether such a friend group could indeed provide early detection, we studied a flu outbreak at Harvard College in late 2009. We followed 744 students who were either members of a group of randomly chosen individuals or a group of their friends. Based on clinical diagnoses, the progression of the epidemic in the friend group occurred 13.9 days (95% C.I. 9.9–16.6) in advance of the randomly chosen group (i.e., the population as a whole). The friend group also showed a significant lead time (p<0.05) on day 16 of the epidemic, a full 46 days before the peak in daily incidence in the population as a whole. This sensor method could provide significant additional time to react to epidemics in small or large populations under surveillance. The amount of lead time will depend on features of the outbreak and the network at hand. The method could in principle be generalized to other biological, psychological, informational, or behavioral contagions that spread in networks. PMID:20856792

[Syndromic surveillance in circumstances of bioterrorism threat--the essence, application abilities and superiority over a traditional epidemiological surveillance].

PubMed

Osemek, Paweł; Kocik, Janusz; Paśnik, Krzysztof

2009-12-01

This article provides a short review about trends of developing current syndromic surveillance systems. To improve methods of early detection of natural or bioterrorism-related outbreaks, it has to be established a new way of epidemiological thinking, which uses innovative real-time surveillance systems. Syndromic surveillance has been created for an early detection, to monitor the temporo-spatial spread of an outbreak, and to provide prompt data for immediate analysis and feedback to public health authorities. It supports timely decision making process for countermeasure procedures. Framework of syndromic surveillance system requires a proper electronic infrastructure to be build up. Optimal syndrome definitions and data sources for continuing specific diseases outbreak surveillance have not been determined so far. Systems of interest might enhance collaboration among clinical providers, primary care providers, emergency services, information-systems professionals and public health agencies. However economic scope of this undertakings effectively limits ability to implement it in Polish public health service right now. Besides, syndromic surveillance cannot replace traditional public health surveillance with a post-factum epidemiological investigation and laboratory analysis. It can be a useful supplement.

Characterization of influenza A(H1N1)pdm09 viruses isolated from Nepalese and Indian outbreak patients in early 2015.

PubMed

Nakamura, Kazuya; Shirakura, Masayuki; Fujisaki, Seiichiro; Kishida, Noriko; Burke, David F; Smith, Derek J; Kuwahara, Tomoko; Takashita, Emi; Takayama, Ikuyo; Nakauchi, Mina; Chadha, Mandeep; Potdar, Varsha; Bhushan, Arvind; Upadhyay, Bishnu Prasad; Shakya, Geeta; Odagiri, Takato; Kageyama, Tsutomu; Watanabe, Shinji

2017-09-01

We characterized influenza A(H1N1)pdm09 isolates from large-scale outbreaks that occurred in Nepal and India in early 2015. Although no specific viral features, which may have caused the outbreaks, were identified, an S84N substitution in hemagglutinin was frequently observed. Chronological phylogenetic analysis revealed that these Nepalese and Indian viruses possessing the S84N substitution constitute potential ancestors of the novel genetic subclade 6B.1 virus that spread globally in the following (2015/16) influenza season. Thus, active surveillance of circulating influenza viruses in the Southern Asia region, including Nepal and India, would be beneficial for detecting novel variant viruses prior to their worldwide spread. © 2017 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

An enrichment, amplification, and sequence-based typing (EAST) approach for foodborne pathogen detection and surveillance

USDA-ARS?s Scientific Manuscript database

Introduction: Detection of foodborne pathogens typically involves microbiological enrichment with subsequent isolation and identification of a pure culture. This is typically followed by strain typing, which provides information critical to outbreak and source investigations. In the early 1990’s pul...

A Participatory System for Preventing Pandemics of Animal Origins: Pilot Study of the Participatory One Health Disease Detection (PODD) System

PubMed Central

Yano, Terdsak; Phornwisetsirikun, Somphorn; Susumpow, Patipat; Visrutaratna, Surasing; Chanachai, Karoon; Phetra, Polawat; Chaisowwong, Warangkhana; Trakarnsirinont, Pairat; Hemwan, Phonpat; Kaewpinta, Boontuan; Singhapreecha, Charuk; Kreausukon, Khwanchai; Charoenpanyanet, Arisara ; Robert, Chongchit Sripun; Robert, Lamar; Rodtian, Pranee; Mahasing, Suteerat; Laiya, Ekkachai; Pattamakaew, Sakulrat; Tankitiyanon, Taweesart; Sansamur, Chalutwan

2018-01-01

Background Aiming for early disease detection and prompt outbreak control, digital technology with a participatory One Health approach was used to create a novel disease surveillance system called Participatory One Health Disease Detection (PODD). PODD is a community-owned surveillance system that collects data from volunteer reporters; identifies disease outbreak automatically; and notifies the local governments (LGs), surrounding villages, and relevant authorities. This system provides a direct and immediate benefit to the communities by empowering them to protect themselves. Objective The objective of this study was to determine the effectiveness of the PODD system for the rapid detection and control of disease outbreaks. Methods The system was piloted in 74 LGs in Chiang Mai, Thailand, with the participation of 296 volunteer reporters. The volunteers and LGs were key participants in the piloting of the PODD system. Volunteers monitored animal and human diseases, as well as environmental problems, in their communities and reported these events via the PODD mobile phone app. LGs were responsible for outbreak control and provided support to the volunteers. Outcome mapping was used to evaluate the performance of the LGs and volunteers. Results LGs were categorized into one of the 3 groups based on performance: A (good), B (fair), and C (poor), with the majority (46%,34/74) categorized into group B. Volunteers were similarly categorized into 4 performance groups (A-D), again with group A showing the best performance, with the majority categorized into groups B and C. After 16 months of implementation, 1029 abnormal events had been reported and confirmed to be true reports. The majority of abnormal reports were sick or dead animals (404/1029, 39.26%), followed by zoonoses and other human diseases (129/1029, 12.54%). Many potentially devastating animal disease outbreaks were detected and successfully controlled, including 26 chicken high mortality outbreaks, 4 cattle disease outbreaks, 3 pig disease outbreaks, and 3 fish disease outbreaks. In all cases, the communities and animal authorities cooperated to apply community contingency plans to control these outbreaks, and community volunteers continued to monitor the abnormal events for 3 weeks after each outbreak was controlled. Conclusions By design, PODD initially targeted only animal diseases that potentially could emerge into human pandemics (eg, avian influenza) and then, in response to community needs, expanded to cover human health and environmental health issues. PMID:29563079

Avian influenza virus detection and quantitation by real-time RT-PCR

USDA-ARS?s Scientific Manuscript database

Real-time RT-PCR (rRT-PCR) has been used for avian influenza virus (AIV) detection since the early 2000’s for routine surveillance, during outbreaks and for research. Some of the advantages of rRT-PCR are: high sensitivity, high specificity, rapid time-to-result, scalability, cost, and its inherentl...

European Surveillance for West Nile Virus in Mosquito Populations

PubMed Central

Engler, Olivier; Savini, Giovanni; Papa, Anna; Figuerola, Jordi; Groschup, Martin H.; Kampen, Helge; Medlock, Jolyon; Vaux, Alexander; Wilson, Anthony J.; Werner, Doreen; Jöst, Hanna; Goffredo, Maria; Capelli, Gioia; Federici, Valentina; Tonolla, Mauro; Patocchi, Nicola; Flacio, Eleonora; Portmann, Jasmine; Rossi-Pedruzzi, Anya; Mourelatos, Spiros; Ruiz, Santiago; Vázquez, Ana; Calzolari, Mattia; Bonilauri, Paolo; Dottori, Michele; Schaffner, Francis; Mathis, Alexander; Johnson, Nicholas

2013-01-01

A wide range of arthropod-borne viruses threaten both human and animal health either through their presence in Europe or through risk of introduction. Prominent among these is West Nile virus (WNV), primarily an avian virus, which has caused multiple outbreaks associated with human and equine mortality. Endemic outbreaks of West Nile fever have been reported in Italy, Greece, France, Romania, Hungary, Russia and Spain, with further spread expected. Most outbreaks in Western Europe have been due to infection with WNV Lineage 1. In Eastern Europe WNV Lineage 2 has been responsible for human and bird mortality, particularly in Greece, which has experienced extensive outbreaks over three consecutive years. Italy has experienced co-circulation with both virus lineages. The ability to manage this threat in a cost-effective way is dependent on early detection. Targeted surveillance for pathogens within mosquito populations offers the ability to detect viruses prior to their emergence in livestock, equine species or human populations. In addition, it can establish a baseline of mosquito-borne virus activity and allow monitoring of change to this over time. Early detection offers the opportunity to raise disease awareness, initiate vector control and preventative vaccination, now available for horses, and encourage personal protection against mosquito bites. This would have major benefits through financial savings and reduction in equid morbidity/mortality. However, effective surveillance that predicts virus outbreaks is challenged by a range of factors including limited resources, variation in mosquito capture rates (too few or too many), difficulties in mosquito identification, often reliant on specialist entomologists, and the sensitive, rapid detection of viruses in mosquito pools. Surveillance for WNV and other arboviruses within mosquito populations varies between European countries in the extent and focus of the surveillance. This study reviews the current status of WNV in mosquito populations across Europe and how this is informing our understanding of virus epidemiology. Key findings such as detection of virus, presence of vector species and invasive mosquito species are summarized, and some of the difficulties encountered when applying a cost-effective surveillance programme are highlighted. PMID:24157510

Early Warning and Outbreak Detection Using Social Networking Websites: The Potential of Twitter

NASA Astrophysics Data System (ADS)

de Quincey, Ed; Kostkova, Patty

Epidemic Intelligence is being used to gather information about potential diseases outbreaks from both formal and increasingly informal sources. A potential addition to these informal sources are social networking sites such as Facebook and Twitter. In this paper we describe a method for extracting messages, called "tweets" from the Twitter website and the results of a pilot study which collected over 135,000 tweets in a week during the current Swine Flu pandemic.

Chikungunya Detection during Dengue Outbreak in Sumatra, Indonesia: Clinical Manifestations and Virological Profile.

PubMed

Sasmono, R Tedjo; Perkasa, Aditya; Yohan, Benediktus; Haryanto, Sotianingsih; Yudhaputri, Frilasita A; Hayati, Rahma F; Ma'roef, Chairin Nisa; Ledermann, Jeremy P; Aye Myint, Khin Saw; Powers, Ann M

2017-11-01

Chikungunya fever (CHIK) is an acute viral infection caused by infection with chikungunya virus (CHIKV). The disease affects people in areas where certain Aedes species mosquito vectors are present, especially in tropical and subtropical countries. Indonesia has witnessed CHIK disease since the early 1970s with sporadic outbreaks occurring throughout the year. The CHIK clinical manifestation, characterized by fever, headache, and joint pain, is similar to that of dengue (DEN) disease. During a molecular study of a DEN outbreak in Jambi, Sumatra, in early 2015, DENV-negative samples were evaluated for evidence of CHIKV infection. Among 103 DENV-negative samples, eight samples were confirmed (7.8%) as positive for CHIKV by both molecular detection and virus isolation. The mean age of the CHIK patients was 21.3 ± 9.1 (range 11-35 years). The clinical manifestations of the CHIK patients were mild and mimicked DEN, with fever and headache as the main symptoms. Only three out of eight patients presented with classical joint pain. Sequencing of the envelope glycoprotein E1 gene and phylogenetic analysis identified all CHIKV isolates as belonging to the Asian genotype. Overall, our study confirms sustained endemic CHIKV transmission and the presence of multiple arboviruses circulating during a DEN outbreak in Indonesia. The co-circulation of arboviruses poses a public health threat and is likely to cause misdiagnosis and underreporting of CHIK in DEN-endemic areas such as Indonesia.

[Detection of local influenza outbreaks and role of virological diagnostics].

PubMed

Schweiger, B; Buda, S

2013-01-01

For many years, the Working Group on Influenza (AGI) has been the most important influenza surveillance system in Germany. An average sample of the population is covered by both syndromic and virological surveillance, which provides timely data regarding the onset and course of the influenza wave as well as its burden of disease. However, smaller influenza outbreaks cannot be detected by the AGI sentinel system. This is achieved by the information reported by the mandatory notification system (Protection Against Infection Act, IfSG), which serves as the second pillar of the national influenza surveillance. Approaches to recognize such outbreaks are based either on reported influenza virus detection and subsequent investigations by local health authorities or by notification of an accumulation of respiratory diseases or nosocomial infections and subsequent laboratory investigations. In this context, virological diagnostics plays an essential role. This has been true particularly for the early phase of the 2009 pandemic, but generally timely diagnostics is essential for the identification of outbreaks. Regarding potential future outbreaks, it is also important to keep an eye on animal influenza viruses that have repeatedly infected humans. This mainly concerns avian influenza viruses of the subtypes H5, H7, and H9 as well as porcine influenza viruses for which a specific PCR has been established at the National Influenza Reference Centre. An increased incidence of respiratory infections, both during and outside the season, should always encourage virological laboratory diagnostics to be performed as a prerequisite of further extensive investigations and an optimal outbreak management.

Comparing introduction to Europe of highly pathogenic avian influenza viruses A(H5N8) in 2014 and A(H5N1) in 2005.

PubMed

Adlhoch, C; Gossner, C; Koch, G; Brown, I; Bouwstra, R; Verdonck, F; Penttinen, P; Harder, T

2014-12-18

Since the beginning of November 2014, nine outbreaks of highly pathogenic avian influenza virus (HPAIV) A(H5N8) in poultry have been detected in four European countries. In this report, similarities and differences between the modes of introduction of HPAIV A(H5N1) and A(H5N8) into Europe are described. Experiences from outbreaks of A(H5N1) in Europe demonstrated that early detection to control HPAIV in poultry has proven pivotal to minimise the risk of zoonotic transmission and prevention of human cases.

[Chickenpox case estimation in acyclovir pharmacy survey and early bioterrorism detection].

PubMed

Sugawara, Tamie; Ohkusa, Yasushi; Kawanohara, Hirokazu; Taniguchi, Kiyosu; Okabe, Nobuhiko

2011-11-01

Early potential health hazards and bioterrorism threats require early detection. Smallpox cases caused by terrorist could, for example, be treated by prescribing acyclovir to those having fever and vesicle exanthema diagnosed as chicken pox. We have constructed real-time pharmacy surveillance scenarios using information technology (IT) to monitor acyclovir prescription. We collected the number of acyclovir prescriptions from 5138 pharmacies using the Application Server Provider System (ASP) to estimate the number of cases. We then compared the number of those given acyclovir under 15 years old from pharmacy surveillance and sentinel surveillance for chickenpox under the Infection Disease Control Law. The estimated number of under 15 years old prescribed acyclovir in pharmacy surveillance resembled sentinel surveillance results and showed a similar seasonal chickenpox pattern. The correlation coefficient was 0.8575. The estimated numbers of adults, older than 15 but under 65 years old, and elderly, older than 65, prescribed acyclovir showed no clear seasonal pattern. Pharmacy surveillance for acyclovir identified the baseline and can be used to detect unusual chickenpox outbreak. Bioterrorism attack could potentially be detected using smallpox virus when acyclovir prescription for adults suddenly increases without outbreaks in children or the elderly. This acyclovir prescription monitoring such as an application is, to our knowledge, the first of its kind anywhre.

Hot spots in a wired world: WHO surveillance of emerging and re-emerging infectious diseases.

PubMed

Heymann, D L; Rodier, G R

2001-12-01

The resurgence of the microbial threat, rooted in several recent trends, has increased the vulnerability of all nations to the risk of infectious diseases, whether newly emerging, well-established, or deliberately caused. Infectious disease intelligence, gleaned through sensitive surveillance, is the best defence. The epidemiological and laboratory techniques needed to detect, investigate, and contain a deliberate outbreak are the same as those used for natural outbreaks. In April 2000, WHO formalised an infrastructure (the Global Outbreak Alert and Response Network) for responding to the heightened need for early awareness of outbreaks and preparedness to respond. The Network, which unites 110 existing networks, is supported by several new mechanisms and a computer-driven tool for real time gathering of disease intelligence. The procedure for outbreak alert and response has four phases: systematic detection, outbreak verification, real time alerts, and rapid response. For response, the framework uses different strategies for combating known risks and unexpected events, and for improving both global and national preparedness. New forces at work in an electronically interconnected world are beginning to break down the traditional reluctance of countries to report outbreaks due to fear of the negative impact on trade and tourism. About 65% of the world's first news about infectious disease events now comes from informal sources, including press reports and the internet.

Molecular characterization of Hepatitis A virus causing an outbreak among Thai navy recruits.

PubMed

Theamboonlers, A; Rianthavorn, P; Jiamsiri, S; Kumthong, S; Silaporn, P; Thongmee, C; Poovorawan, Y

2009-12-01

Hepatitis A virus (HAV) infection is a communicable disease, typically transmitted by faecal-oral contamination. HAV outbreaks usually occur in endemic areas. We report an outbreak of HAV from June to July, 2008 among Thai navy recruits who had received training at the Sattahip Navy Base, Chonburi province, Thailand. Upon conclusion of the training, the recruits were deployed to serve at several navy bases across the country. Secondary cases of HAV infection were reported among military personnel from these navy bases. To elucidate origin and distribution of these outbreaks, we characterized the genome and genotype of HAV isolated from the different navy bases. Sera and stool from the subjects were tested for antiHAV IgM, antiHAV IgG and HAV RNA. Subsequently, molecular characterization of HAV was performed by nucleotide sequencing of the VP1-P2A region, BLAST/FASTA and phylogenetic analysis. HAV RNA was detected in specimens obtained from different areas. All isolated strains clustered in the same lineage and belonged to genotype 1A. They shared nearly 100% genome homology indicating a single point source of this outbreak. This study provides essential baseline data as a reference for genetic analysis of HAV strains causing future outbreaks. Early detection of HAV infection and identification of the source by using molecular characterization and prompt preventive measures will hopefully prevent further outbreaks.

Dengue Contingency Planning: From Research to Policy and Practice

PubMed Central

Runge-Ranzinger, Silvia; Kroeger, Axel; Olliaro, Piero; McCall, Philip J.; Sánchez Tejeda, Gustavo; Lloyd, Linda S.; Hakim, Lokman; Bowman, Leigh R.; Horstick, Olaf; Coelho, Giovanini

2016-01-01

Background Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. This handbook facilitates contingency planning as well as the development and use of early warning and response systems for dengue fever epidemics, by identifying decision-making processes that contribute to the success or failure of dengue surveillance, as well as triggers that initiate effective responses to incipient outbreaks. Methodology/Principal findings Available evidence was evaluated using a step-wise process that included systematic literature reviews, policymaker and stakeholder interviews, a study to assess dengue contingency planning and outbreak management in 10 countries, and a retrospective logistic regression analysis to identify alarm signals for an outbreak warning system using datasets from five dengue endemic countries. Best practices for managing a dengue outbreak are provided for key elements of a dengue contingency plan including timely contingency planning, the importance of a detailed, context-specific dengue contingency plan that clearly distinguishes between routine and outbreak interventions, surveillance systems for outbreak preparedness, outbreak definitions, alert algorithms, managerial capacity, vector control capacity, and clinical management of large caseloads. Additionally, a computer-assisted early warning system, which enables countries to identify and respond to context-specific variables that predict forthcoming dengue outbreaks, has been developed. Conclusions/Significance Most countries do not have comprehensive, detailed contingency plans for dengue outbreaks. Countries tend to rely on intensified vector control as their outbreak response, with minimal focus on integrated management of clinical care, epidemiological, laboratory and vector surveillance, and risk communication. The Technical Handbook for Surveillance, Dengue Outbreak Prediction/ Detection and Outbreak Response seeks to provide countries with evidence-based best practices to justify the declaration of an outbreak and the mobilization of the resources required to implement an effective dengue contingency plan. PMID:27653786

Development and evaluation of a real-time RT-PCR assay for the detection of Ebola virus (Zaire) during an Ebola outbreak in Guinea in 2014-2015.

PubMed

Dedkov, V G; Magassouba, N' F; Safonova, M V; Deviatkin, A A; Dolgova, A S; Pyankov, O V; Sergeev, A A; Utkin, D V; Odinokov, G N; Safronov, V A; Agafonov, A P; Maleev, V V; Shipulin, G A

2016-02-01

In early February 2014, an outbreak of the Ebola virus disease caused by Zaire ebolavirus (EBOV) occurred in Guinea; cases were also recorded in other West African countries with a combined population of approximately 25 million. A rapid, sensitive and inexpensive method for detecting EBOV is needed to effectively control such outbreak. Here, we report a real-time reverse-transcription PCR assay for Z. ebolavirus detection used by the Specialized Anti-epidemic Team of the Russian Federation during the Ebola virus disease prevention mission in the Republic of Guinea. The analytical sensitivity of the assay is 5 × 10(2) viral particles per ml, and high specificity is demonstrated using representative sampling of viral, bacterial and human nucleic acids. This assay can be applied successfully for detecting the West African strains of Z. ebolavirus as well as on strains isolated in the Democratic Republic of the Congo in 2014. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of the Legionella urinary antigen test on epidemiological trends in community outbreaks of legionellosis in Catalonia, Spain, 1990-2004.

PubMed

Alvarez, Josep; Domínguez, Angela; Sabrià, Miquel; Ruiz, Laura; Torner, Nuria; Cayla, Joan; Barrabeig, Irene; Sala, M Rosa; Godoy, Pere; Camps, Neus; Minguell, Sofia

2009-11-01

To describe the characteristics of community outbreaks of legionellosis in Catalonia, Spain from 1990 to 2004, to compare two time periods (1990-1996 and 1997-2004), and to assess the influence of outbreak characteristics on the case fatality rate (CFR). This is a descriptive analysis of the outbreaks detected by epidemiological surveillance units in Catalonia. Variables potentially related to the CFR were analyzed by logistic regression. Of the 118 outbreaks involving 690 patients (overall CFR 4.5%), the urinary antigen test (UAT) was used for first case diagnosis in 80.5%. The origin of the outbreak was identified as a cooling tower in 35.6%, as a water distribution system in a public building in 14.4%, and a water distribution system at other sites in 7.6%. Statistically significant differences were found in the CFR (12.2% vs. 3.9%; p=0.018) and detection of the first case by UAT (0.0% vs. 87.2%; p<0.001) between the two time periods investigated. Logistic regression showed an increase in the CFR according to outbreak size (adjusted odds ratio (aOR) 1.18; 95% confidence interval (CI) 1.05-1.33) that was significantly lower in the second period (aOR 0.09; 95% CI 0.04-0.20). Since the UAT was introduced, early diagnosis and treatment has helped to improve the outcomes and CFR of cases involved in outbreaks of legionellosis.

Early detection and control of an Acinetobacter baumannii multi-resistant outbreak in a hospital in Quito, Ecuador.

PubMed

Cartelle Gestal, Monica; Zurita, Jeannete; Gualpa, Gabriela; Gonzalez, Cecibel; Paz Y Mino, Ariane

2016-12-30

Acinetobacter baumannii (ABA) is an important opportunistic pathogen associated with high mortality rates in intensive care units (ICUs). An outbreak in the ICU of a secondary-level hospital in Quito, Ecuador, occurred during April and May 2015 and was successfully controlled. Enterobacterial repetitive intergenic consensus polymerase chain reaction (ERIC-PCR) and repetitive element palindromic (REP)-PCR was conducted on all isolates recovered from patients, as well as environmental samples, to confirm the presence of an outbreak. A case-control study was conducted by comparing the clinical histories of the affected patients and of control patients present in the ICU during the outbreak period who did not present a positive culture for ABA. Five patients were infected and two were colonized with the same clonal strain of ABA, which was also identified on the stethoscope and a monitor associated with an isolation room. Statistical analysis of case histories did not identify any additional risk factors, but the outbreak was initiated by one patient in the isolation room of the ICU who was infected with the outbreak strain. All patients who ocupied that room after the index case tested positive for at least one culture of ABA. The outbreak strain was found on the stethoscope, and a subclone was found on the monitor of that room. Having access to basic equipment will enable well-trained professionals to rapidly detect and initiate the control process of an outbreak, saving lives and money spent on nosocomial infection treatments.

Epidemiology and Management of the 2013-16 West African Ebola Outbreak.

PubMed

Boisen, M L; Hartnett, J N; Goba, A; Vandi, M A; Grant, D S; Schieffelin, J S; Garry, R F; Branco, L M

2016-09-29

The 2013-16 West African Ebola outbreak is the largest, most geographically dispersed, and deadliest on record, with 28,616 suspected cases and 11,310 deaths recorded to date in Guinea, Liberia, and Sierra Leone. We provide a review of the epidemiology and management of the 2013-16 Ebola outbreak in West Africa aimed at stimulating reflection on lessons learned that may improve the response to the next international health crisis caused by a pathogen that emerges in a region of the world with a severely limited health care infrastructure. Surveillance efforts employing rapid and effective point-of-care diagnostics designed for environments that lack advanced laboratory infrastructure will greatly aid in early detection and containment efforts during future outbreaks. Introduction of effective therapeutics and vaccines against Ebola into the public health system and the biodefense armamentarium is of the highest priority if future outbreaks are to be adequately managed and contained in a timely manner.

Nosocomial outbreak of Legionella pneumophila serogroup 3 pneumonia in a new bone marrow transplant unit: evaluation, treatment and control.

PubMed

Oren, I; Zuckerman, T; Avivi, I; Finkelstein, R; Yigla, M; Rowe, J M

2002-08-01

A nosocomial outbreak of pneumonia caused by Legionella pneumophila serogroup 3 occurred in four patients following hematopoietic stem cell transplantation (HSCT) in a new bone marrow transplantation (BMT) unit during a 2 week period. The causative organism was recovered from the water supply system to the same unit just before the outbreak. Nineteen other BMT patients were hospitalized in the same unit at the same time, giving a frequency of proven infection of 4/23 = 17%. Immediately after recognition of the outbreak, use of tap water was forbidden, humidifiers were disconnected, and ciprofloxacin prophylaxis was started for all patients in the unit, until decontamination of the water was achieved. No other cases were detected. In conclusion, contamination of the hospital water supply system with legionella carries a high risk for legionella pneumonia among BMT patients. Early recognition of the outbreak, immediate restrictions of water use, antibiotic prophylaxis for all non-infected patients, and water decontamination, successfully terminated the outbreak.

Widespread Usutu virus outbreak in birds in the Netherlands, 2016

PubMed Central

Rijks, JM; Kik, ML; Slaterus, R; Foppen, RPB; Stroo, A; IJzer, J; Stahl, J; Gröne, A; Koopmans, MGP; van der Jeugd, HP; Reusken, CBEM

2016-01-01

We report a widespread Usutu virus outbreak in birds in the Netherlands. Viral presence had been detected through targeted surveillance as early as April 2016 and increased mortality in common blackbirds and captive great grey owls was noticed from August 2016 onwards. Usutu virus infection was confirmed by post-mortem examination and RT-PCR. Extensive Usutu virus activity in the Netherlands in 2016 underlines the need to monitor mosquito activity and mosquito-borne infections in 2017 and beyond. PMID:27918257

Increased risk for autochthonous vector-borne infections transmitted by Aedes albopictus in continental Europe.

PubMed

Gossner, Céline M; Ducheyne, Els; Schaffner, Francis

2018-06-01

Autochthonous outbreaks of chikungunya and dengue during the past decade showed that continental Europe is vulnerable to Aedes albopictus -borne infections. Ae. albopictus has spread geographically, resulting in more people exposed to risk. Timely application of adequate mosquito suppression measures may delay, or even prevent, the vector population from crossing the potential epidemic abundance threshold should a pathogen be introduced. Health authorities should be on alert to detect early cases to prevent autochthonous outbreaks.

Mapping the risk of sudden oak death in Oregon: prioritizing locations for early detection and eradication

Treesearch

V& aacute; clavík Tom& aacute; & scaron; ; Alan Kanaskie; Ellen Goheen; Janet Ohmann; Everett Hansen; Ross Meentemeyer

2010-01-01

Phytophthora ramorum was first discovered in forests of southwestern Oregon in 2001. Despite intense eradication efforts, disease continues to spread from initially infested sites because of the late discovery of disease outbreaks and incomplete detection. Here we present two GIS predictive models of sudden oak death (SOD) establishment and spread...

Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models.

PubMed

Chan, Ta-Chien; Teng, Yung-Chu; Hwang, Jing-Shiang

2015-02-21

Emerging novel influenza outbreaks have increasingly been a threat to the public and a major concern of public health departments. Real-time data in seamless surveillance systems such as health insurance claims data for influenza-like illnesses (ILI) are ready for analysis, making it highly desirable to develop practical techniques to analyze such readymade data for outbreak detection so that the public can receive timely influenza epidemic warnings. This study proposes a simple and effective approach to analyze area-based health insurance claims data including outpatient and emergency department (ED) visits for early detection of any aberrations of ILI. The health insurance claims data during 2004-2009 from a national health insurance research database were used for developing early detection methods. The proposed approach fitted the daily new ILI visits and monitored the Pearson residuals directly for aberration detection. First, negative binomial regression was used for both outpatient and ED visits to adjust for potentially influential factors such as holidays, weekends, seasons, temporal dependence and temperature. Second, if the Pearson residuals exceeded 1.96, aberration signals were issued. The empirical validation of the model was done in 2008 and 2009. In addition, we designed a simulation study to compare the time of outbreak detection, non-detection probability and false alarm rate between the proposed method and modified CUSUM. The model successfully detected the aberrations of 2009 pandemic (H1N1) influenza virus in northern, central and southern Taiwan. The proposed approach was more sensitive in identifying aberrations in ED visits than those in outpatient visits. Simulation studies demonstrated that the proposed approach could detect the aberrations earlier, and with lower non-detection probability and mean false alarm rate in detecting aberrations compared to modified CUSUM methods. The proposed simple approach was able to filter out temporal trends, adjust for temperature, and issue warning signals for the first wave of the influenza epidemic in a timely and accurate manner.

An outbreak of East Coast fever in a herd of Sanga cattle in Lutale, Central Province of Zambia.

PubMed

Minjauw, B; Otte, M J; James, A D; de Castro, J J; Permin, A; Di Giulo, G

1998-05-01

An outbreak of East Coast fever (ECF) occurred in an experimental herd of Sanga cattle maintained under a traditional rangeland grazing system at Lutale, Central Province of Zambia. Two groups of cattle had been kept under different tick-control regimens for several years prior to the introduction of the disease and epidemiological information on the outbreak were recorded. Weekly tick control was no sufficient to achieve full protection against Theileria parva infection. Systematic body temperature monitoring seems to be a good method for early detection of infection resulting in an important reduction of the case fatality rate after treatment with anti-theilerial drugs.

Healthcare-associated outbreaks due to Mucorales and other uncommon fungi.

PubMed

Davoudi, Setareh; Graviss, Linda S; Kontoyiannis, Dimitrios P

2015-07-01

Healthcare-associated outbreaks of fungal infections, especially with uncommon and emerging fungi, have become more frequent in the past decade. Here, we reviewed the history and definition of healthcare-associated outbreaks of uncommon fungal infections and discussed the principles of investigating, containing and treatment of these outbreaks. In case of these uncommon diseases, occurrence of two or more cases in a short period is considered as an outbreak. Contaminated medical devices and hospital environment are the major sources of these outbreaks. Care must be taken to differentiate a real infection from colonization or contamination. Defining and identifying cases, describing epidemiologic feature of cases, finding and controlling the source of the outbreak, treating patients, and managing asymptomatic exposed patients are main steps for outbreak elimination. These fungal outbreaks are not only difficult to detect but also hard to treat. Early initiation of appropriate antifungal therapy is strongly associated with improved outcomes in infected patients. Choice of antifungal drugs should be made based on spectrum, pharmacodynamic and pharmacokinetic characteristics and adverse effects of available drugs. Combination antifungal therapy and surgical intervention may be also helpful in selected cases. A multidisciplinary approach and close collaboration between all key partners are necessary for successful control of fungal outbreaks. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model

PubMed Central

Spear, Robert C.; Marshall, John M.; Yang, Zhicong; Gong, Peng

2016-01-01

As the world’s fastest spreading vector-borne disease, dengue was estimated to infect more than 390 million people in 2010, a 30-fold increase in the past half century. Although considered to be a non-endemic country, mainland China had 55,114 reported dengue cases from 2005 to 2014, of which 47,056 occurred in 2014. Furthermore, 94% of the indigenous cases in this time period were reported in Guangdong Province, 83% of which were in Guangzhou City. In order to determine the possible determinants of the unprecedented outbreak in 2014, a population-based deterministic model was developed to describe dengue transmission dynamics in Guangzhou. Regional sensitivity analysis (RSA) was adopted to calibrate the model and entomological surveillance data was used to validate the mosquito submodel. Different scenarios were created to investigate the roles of the timing of an imported case, climate, vertical transmission from mosquitoes to their offspring, and intervention. The results suggested that an early imported case was the most important factor in determining the 2014 outbreak characteristics. Precipitation and temperature can also change the transmission dynamics. Extraordinary high precipitation in May and August, 2014 appears to have increased vector abundance. Considering the relatively small number of cases in 2013, the effect of vertical transmission was less important. The earlier and more frequent intervention in 2014 also appeared to be effective. If the intervention in 2014 was the same as that in 2013, the outbreak size may have been over an order of magnitude higher than the observed number of new cases in 2014.The early date of the first imported and locally transmitted case was largely responsible for the outbreak in 2014, but it was influenced by intervention, climate and vertical transmission. Early detection and response to imported cases in the spring and early summer is crucial to avoid large outbreaks in the future. PMID:26863623

Detecting Ebola with limited laboratory access in the Democratic Republic of Congo: evaluation of a clinical passive surveillance reporting system.

PubMed

Ashbaugh, Hayley R; Kuang, Brandon; Gadoth, Adva; Alfonso, Vivian H; Mukadi, Patrick; Doshi, Reena H; Hoff, Nicole A; Sinai, Cyrus; Mossoko, Mathias; Kebela, Benoit Ilunga; Muyembe, Jean-Jacques; Wemakoy, Emile Okitolonda; Rimoin, Anne W

2017-09-01

Ebola virus disease (EVD) can be clinically severe and highly fatal, making surveillance efforts for early disease detection of paramount importance. In areas with limited access to laboratory testing, the Integrated Disease Surveillance and Response (IDSR) strategy in the Democratic Republic of Congo (DRC) may be a vital tool in improving outbreak response. Using DRC IDSR data from the nation's four EVD outbreak periods from 2007-2014, we assessed trends of Viral Hemorrhagic Fever (VHF) and EVD differential diagnoses reportable through IDSR. With official case counts from active surveillance of EVD outbreaks, we assessed accuracy of reporting through the IDSR passive surveillance system. Although the active and passive surveillance represent distinct sets of data, the two were correlated, suggesting that passive surveillance based only on clinical evaluation may be a useful predictor of true cases prior to laboratory confirmation. There were 438 suspect VHF cases reported through the IDSR system and 416 EVD cases officially recorded across the outbreaks examined. Although collected prior to official active surveillance cases, case reporting through the IDSR during the 2007, 2008 and 2012 outbreaks coincided with official EVD epidemic curves. Additionally, all outbreak areas experienced increases in suspected cases for both malaria and typhoid fever during EVD outbreaks, underscoring the importance of training health care workers in recognising EVD differential diagnoses and the potential for co-morbidities. © 2017 John Wiley & Sons Ltd.

[Investigation of a measles outbreak caused by genotype D8 virus in Pinghu city of Zhejiang province, 2017].

PubMed

Yan, R; He, B; Yao, F Y; Xiang, Z L; He, H Q; Xie, S Y; Feng, Y

2018-03-10

Objective: To investigate the epidemiological characteristics of measles outbreak caused by genotype D8 virus in Pinghu city of Zhejiang province, and provide evidence for the control of the outbreak. Methods: The measles outbreak data were collected through National Measles Surveillance System. The outpatient records and admission records were checked, field investigation and outbreak response were conducted. Blood samples in acute phase and swab specimens were collected from the patients for laboratory testing, including serology test, RNA extraction and amplification, measles virus isolation and genotype identification. Software SPSS 17.0 and Excel 2016 were used for data analysis. Results: A total of 10 confirmed measles cases were reported in Pinghu city, and 8 cases were aged >40 years. Six blood samples were collected, in which 5 were measles D8 virus positive and 1 was negative in measles virus detection. There were epidemiological links among 10 cases which occurred in a factory, a hospital and a family at the same time. There was no statistical difference in symptoms among cases caused by D8 virus and H1a virus. After the emergent measles vaccination, the measles outbreak was effectively controlled. Conclusion: Untimely response due to the uneasy detection of measles cases in the early stage, nosocomial infection and weak barrier of measles immunity in adults might be the main reasons for this outbreak. Measles vaccination is effective in the prevention of measles D8 virus infection. It is necessary to strengthen measles genotype monitoring for the tracing of infection source and control of outbreaks.

Value of evidence from syndromic surveillance with cumulative evidence from multiple data streams with delayed reporting.

PubMed

Struchen, R; Vial, F; Andersson, M G

2017-04-26

Delayed reporting of health data may hamper the early detection of infectious diseases in surveillance systems. Furthermore, combining multiple data streams, e.g. aiming at improving a system's sensitivity, can be challenging. In this study, we used a Bayesian framework where the result is presented as the value of evidence, i.e. the likelihood ratio for the evidence under outbreak versus baseline conditions. Based on a historical data set of routinely collected cattle mortality events, we evaluated outbreak detection performance (sensitivity, time to detection, in-control run length) under the Bayesian approach among three scenarios: presence of delayed data reporting, but not accounting for it; presence of delayed data reporting accounted for; and absence of delayed data reporting (i.e. an ideal system). Performance on larger and smaller outbreaks was compared with a classical approach, considering syndromes separately or combined. We found that the Bayesian approach performed better than the classical approach, especially for the smaller outbreaks. Furthermore, the Bayesian approach performed similarly well in the scenario where delayed reporting was accounted for to the scenario where it was absent. We argue that the value of evidence framework may be suitable for surveillance systems with multiple syndromes and delayed reporting of data.

Increase in Multistate Foodborne Disease Outbreaks-United States, 1973-2010.

PubMed

Nguyen, Von D; Bennett, Sarah D; Mungai, Elisabeth; Gieraltowski, Laura; Hise, Kelley; Gould, L Hannah

2015-11-01

Changes in food production and distribution have increased opportunities for foods contaminated early in the supply chain to be distributed widely, increasing the possibility of multistate outbreaks. In recent decades, surveillance systems for foodborne disease have been improved, allowing officials to more effectively identify related cases and to trace and identify an outbreak's source. We reviewed multistate foodborne disease outbreaks reported to the Centers for Disease Control and Prevention's Foodborne Disease Outbreak Surveillance System during 1973-2010. We calculated the percentage of multistate foodborne disease outbreaks relative to all foodborne disease outbreaks and described characteristics of multistate outbreaks, including the etiologic agents and implicated foods. Multistate outbreaks accounted for 234 (0.8%) of 27,755 foodborne disease outbreaks, 24,003 (3%) of 700,600 outbreak-associated illnesses, 2839 (10%) of 29,756 outbreak-associated hospitalizations, and 99 (16%) of 628 outbreak-associated deaths. The median annual number of multistate outbreaks increased from 2.5 during 1973-1980 to 13.5 during 2001-2010; the number of multistate outbreak-associated illnesses, hospitalizations, and deaths also increased. Most multistate outbreaks were caused by Salmonella (47%) and Shiga toxin-producing Escherichia coli (26%). Foods most commonly implicated were beef (22%), fruits (13%), and leafy vegetables (13%). The number of identified and reported multistate foodborne disease outbreaks has increased. Improvements in detection, investigation, and reporting of foodborne disease outbreaks help explain the increasing number of reported multistate outbreaks and the increasing percentage of outbreaks that were multistate. Knowing the etiologic agents and foods responsible for multistate outbreaks can help to identify sources of food contamination so that the safety of the food supply can be improved.

A framework for responding to coral disease outbreaks that facilitates adaptive management.

PubMed

Beeden, Roger; Maynard, Jeffrey A; Marshall, Paul A; Heron, Scott F; Willis, Bette L

2012-01-01

Predicted increases in coral disease outbreaks associated with climate change have implications for coral reef ecosystems and the people and industries that depend on them. It is critical that coral reef managers understand these implications and have the ability to assess and reduce risk, detect and contain outbreaks, and monitor and minimise impacts. Here, we present a coral disease response framework that has four core components: (1) an early warning system, (2) a tiered impact assessment program, (3) scaled management actions and (4) a communication plan. The early warning system combines predictive tools that monitor the risk of outbreaks of temperature-dependent coral diseases with in situ observations provided by a network of observers who regularly report on coral health and reef state. Verified reports of an increase in disease prevalence trigger a tiered response of more detailed impact assessment, targeted research and/or management actions. The response is scaled to the risk posed by the outbreak, which is a function of the severity and spatial extent of the impacts. We review potential management actions to mitigate coral disease impacts and facilitate recovery, considering emerging strategies unique to coral disease and more established strategies to support reef resilience. We also describe approaches to communicating about coral disease outbreaks that will address common misperceptions and raise awareness of the coral disease threat. By adopting this framework, managers and researchers can establish a community of practice and can develop response plans for the management of coral disease outbreaks based on local needs. The collaborations between managers and researchers we suggest will enable adaptive management of disease impacts following evaluating the cost-effectiveness of emerging response actions and incrementally improving our understanding of outbreak causation.

A Framework for Responding to Coral Disease Outbreaks that Facilitates Adaptive Management

NASA Astrophysics Data System (ADS)

Beeden, Roger; Maynard, Jeffrey A.; Marshall, Paul A.; Heron, Scott F.; Willis, Bette L.

2012-01-01

Predicted increases in coral disease outbreaks associated with climate change have implications for coral reef ecosystems and the people and industries that depend on them. It is critical that coral reef managers understand these implications and have the ability to assess and reduce risk, detect and contain outbreaks, and monitor and minimise impacts. Here, we present a coral disease response framework that has four core components: (1) an early warning system, (2) a tiered impact assessment program, (3) scaled management actions and (4) a communication plan. The early warning system combines predictive tools that monitor the risk of outbreaks of temperature-dependent coral diseases with in situ observations provided by a network of observers who regularly report on coral health and reef state. Verified reports of an increase in disease prevalence trigger a tiered response of more detailed impact assessment, targeted research and/or management actions. The response is scaled to the risk posed by the outbreak, which is a function of the severity and spatial extent of the impacts. We review potential management actions to mitigate coral disease impacts and facilitate recovery, considering emerging strategies unique to coral disease and more established strategies to support reef resilience. We also describe approaches to communicating about coral disease outbreaks that will address common misperceptions and raise awareness of the coral disease threat. By adopting this framework, managers and researchers can establish a community of practice and can develop response plans for the management of coral disease outbreaks based on local needs. The collaborations between managers and researchers we suggest will enable adaptive management of disease impacts following evaluating the cost-effectiveness of emerging response actions and incrementally improving our understanding of outbreak causation.

Using health and demographic surveillance for the early detection of cholera outbreaks: analysis of community- and hospital-based data from Matlab, Bangladesh.

PubMed

Saulnier, Dell D; Persson, Lars-Åke; Streatfield, Peter Kim; Faruque, A S G; Rahman, Anisur

2016-01-01

Cholera outbreaks are a continuing problem in Bangladesh, and the timely detection of an outbreak is important for reducing morbidity and mortality. In Matlab, the ongoing Health and Demographic Surveillance System (HDSS) data records symptoms of diarrhea in children under the age of 5 years at the community level. Cholera surveillance in Matlab currently uses hospital-based data. The objective of this study is to determine whether increases in cholera in Matlab can be detected earlier by using HDSS diarrhea symptom data in a syndromic surveillance analysis, when compared to hospital admissions for cholera. HDSS diarrhea symptom data and hospital admissions for cholera in children under 5 years of age over a 2-year period were analyzed with the syndromic surveillance statistical program EARS (Early Aberration Reporting System). Dates when significant increases in either symptoms or cholera cases occurred were compared to one another. The analysis revealed that there were 43 days over 16 months when the cholera cases or diarrhea symptoms increased significantly. There were 8 months when both data sets detected days with significant increases. In 5 of the 8 months, increases in diarrheal symptoms occurred before increases of cholera cases. The increases in symptoms occurred between 1 and 15 days before the increases in cholera cases. The results suggest that the HDSS survey data may be able to detect an increase in cholera before an increase in hospital admissions is seen. However, there was no direct link between diarrheal symptom increases and cholera cases, and this, as well as other methodological weaknesses, should be taken into consideration.

Setting up an early warning system for epidemic-prone diseases in Darfur: a participative approach.

PubMed

Pinto, Augusto; Saeed, Mubarak; El Sakka, Hammam; Rashford, Adrienne; Colombo, Alessandro; Valenciano, Marta; Sabatinelli, Guido

2005-12-01

In April-May 2004, the World Health Organization (WHO) implemented, with local authorities, United Nations (UN) agencies and non-governmental organisations (NGOs), an early warning system (EWS) in Darfur, West Sudan, for internally displaced persons (IDPs). The number of consultations and deaths per week for 12 health events is recorded for two age groups (less than five years and five years and above). Thresholds are used to detect potential outbreaks. Ten weeks after the introduction of the system, NGOs were covering 54 camps, and 924,281 people (IDPs and the host population). Of these 54 camps, 41 (76%) were reporting regularly under the EWS. Between 22 May and 30 July, 179,795 consultations were reported: 18.7% for acute respiratory infections; 15% for malaria; 8.4% for bloody diarrhoea; and 1% for severe acute malnutrition. The EWS is useful for detecting outbreaks and monitoring the number of consultations required to trigger actions, but not for estimating mortality.

Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response.

PubMed

Jacobsen, Kathryn H; Aguirre, A Alonso; Bailey, Charles L; Baranova, Ancha V; Crooks, Andrew T; Croitoru, Arie; Delamater, Paul L; Gupta, Jhumka; Kehn-Hall, Kylene; Narayanan, Aarthi; Pierobon, Mariaelena; Rowan, Katherine E; Schwebach, J Reid; Seshaiyer, Padmanabhan; Sklarew, Dann M; Stefanidis, Anthony; Agouris, Peggy

2016-03-01

As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.

A Participatory System for Preventing Pandemics of Animal Origins: Pilot Study of the Participatory One Health Disease Detection (PODD) System.

PubMed

Yano, Terdsak; Phornwisetsirikun, Somphorn; Susumpow, Patipat; Visrutaratna, Surasing; Chanachai, Karoon; Phetra, Polawat; Chaisowwong, Warangkhana; Trakarnsirinont, Pairat; Hemwan, Phonpat; Kaewpinta, Boontuan; Singhapreecha, Charuk; Kreausukon, Khwanchai; Charoenpanyanet, Arisara; Robert, Chongchit Sripun; Robert, Lamar; Rodtian, Pranee; Mahasing, Suteerat; Laiya, Ekkachai; Pattamakaew, Sakulrat; Tankitiyanon, Taweesart; Sansamur, Chalutwan; Srikitjakarn, Lertrak

2018-03-21

Aiming for early disease detection and prompt outbreak control, digital technology with a participatory One Health approach was used to create a novel disease surveillance system called Participatory One Health Disease Detection (PODD). PODD is a community-owned surveillance system that collects data from volunteer reporters; identifies disease outbreak automatically; and notifies the local governments (LGs), surrounding villages, and relevant authorities. This system provides a direct and immediate benefit to the communities by empowering them to protect themselves. The objective of this study was to determine the effectiveness of the PODD system for the rapid detection and control of disease outbreaks. The system was piloted in 74 LGs in Chiang Mai, Thailand, with the participation of 296 volunteer reporters. The volunteers and LGs were key participants in the piloting of the PODD system. Volunteers monitored animal and human diseases, as well as environmental problems, in their communities and reported these events via the PODD mobile phone app. LGs were responsible for outbreak control and provided support to the volunteers. Outcome mapping was used to evaluate the performance of the LGs and volunteers. LGs were categorized into one of the 3 groups based on performance: A (good), B (fair), and C (poor), with the majority (46%,34/74) categorized into group B. Volunteers were similarly categorized into 4 performance groups (A-D), again with group A showing the best performance, with the majority categorized into groups B and C. After 16 months of implementation, 1029 abnormal events had been reported and confirmed to be true reports. The majority of abnormal reports were sick or dead animals (404/1029, 39.26%), followed by zoonoses and other human diseases (129/1029, 12.54%). Many potentially devastating animal disease outbreaks were detected and successfully controlled, including 26 chicken high mortality outbreaks, 4 cattle disease outbreaks, 3 pig disease outbreaks, and 3 fish disease outbreaks. In all cases, the communities and animal authorities cooperated to apply community contingency plans to control these outbreaks, and community volunteers continued to monitor the abnormal events for 3 weeks after each outbreak was controlled. By design, PODD initially targeted only animal diseases that potentially could emerge into human pandemics (eg, avian influenza) and then, in response to community needs, expanded to cover human health and environmental health issues. ©Terdsak Yano, Somphorn Phornwisetsirikun, Patipat Susumpow, Surasing Visrutaratna, Karoon Chanachai, Polawat Phetra, Warangkhana Chaisowwong, Pairat Trakarnsirinont, Phonpat Hemwan, Boontuan Kaewpinta, Charuk Singhapreecha, Khwanchai Kreausukon, Arisara  Charoenpanyanet, Chongchit Sripun Robert, Lamar Robert, Pranee Rodtian, Suteerat Mahasing, Ekkachai Laiya, Sakulrat Pattamakaew, Taweesart Tankitiyanon, Chalutwan Sansamur, Lertrak Srikitjakarn. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 21.03.2018.

Laboratory-Based Prospective Surveillance for Community Outbreaks of Shigella spp. in Argentina

PubMed Central

Viñas, María R.; Tuduri, Ezequiel; Galar, Alicia; Yih, Katherine; Pichel, Mariana; Stelling, John; Brengi, Silvina P.; Della Gaspera, Anabella; van der Ploeg, Claudia; Bruno, Susana; Rogé, Ariel; Caffer, María I.; Kulldorff, Martin; Galas, Marcelo

2013-01-01

Background To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. Methodology To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. Principal Findings In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. Conclusions/Significance The WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other networks, and scaled up to national and international levels for early detection and control of outbreaks. PMID:24349586

Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina.

PubMed

Viñas, María R; Tuduri, Ezequiel; Galar, Alicia; Yih, Katherine; Pichel, Mariana; Stelling, John; Brengi, Silvina P; Della Gaspera, Anabella; van der Ploeg, Claudia; Bruno, Susana; Rogé, Ariel; Caffer, María I; Kulldorff, Martin; Galas, Marcelo

2013-01-01

To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. The WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other networks, and scaled up to national and international levels for early detection and control of outbreaks.

The evaluation and application of multilocus variable number tandem repeat analysis (MLVA) for the molecular epidemiological study of Salmonella enterica subsp. enterica serovar Enteritidis infection.

PubMed

Liu, Yao; Shi, Xiaolu; Li, Yinghui; Chen, Qiongcheng; Jiang, Min; Li, Wanli; Qiu, Yaqun; Lin, Yiman; Jiang, Yixiang; Kan, Biao; Sun, Qun; Hu, Qinghua

2016-01-29

Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is one of the most prevalent Salmonella serotypes that cause gastroenteritis worldwide and the most prevalent serotype causing Salmonella infections in China. A rapid molecular typing method with high throughput and good epidemiological discrimination is urgently needed for detecting the outbreaks and finding the source for effective control of S. Enteritidis infections. In this study, 194 strains which included 47 from six outbreaks that were well-characterized epidemiologically were analyzed with pulse field gel electrophoresis (PFGE) and multilocus variable number tandem repeat analysis (MLVA). Seven VNTR loci published by the US Center for Disease Control and Prevention (CDC) were used to evaluate and develop MLVA scheme for S. Enteritidis molecular subtyping by comparing with PFGE, and then MLVA was applied to the suspected outbreaks detection. All S. Enteritidis isolates were analyzed with MLVA to establish a MLVA database in Shenzhen, Guangdong province, China to facilitate the detection of S. Enteritidis infection clusters. There were 33 MLVA types and 29 PFGE patterns among 147 sporadic isolates. These two measures had Simpson indices of 0.7701 and 0.8043, respectively, which did not differ significantly. Epidemiological concordance was evaluated by typing 47 isolates from six epidemiologically well-characterized outbreaks and it did not differ for PFGE and MLVA. We applied the well established MLVA method to detect two S. Enteritidis foodborne outbreaks and find their sources successfully in 2014. A MLVA database of 491 S. Enteritidis strains isolated from 2004 to 2014 was established for the surveillance of clusters in the future. MLVA typing of S. Enteritidis would be an effective tool for early warning and epidemiological surveillance of S. Enteritidis infections.

[The 2011 HUS epidemic in Germany. Challenges for disease control: what should be improved?].

PubMed

Krause, G; Frank, C; Gilsdorf, A; Mielke, M; Schaade, L; Stark, K; Burger, R

2013-01-01

From May to July 2011 [corrected] the world's largest outbreak of hemolytic uremic syndrome (HUS) occurred in northern Germany with dramatic consequences for the population, the health care system and the food industry. In the following we examine the detection of the outbreak, epidemic management and related public communication aspects based on scientific publications, media reports as well as own and new data analyses. The subsequent 17 recommendations concern issues such as participation in and implementation of existing and new surveillance systems particularly with respect to physicians, broad application of finely tuned microbiological typing, improved personnel capacity and crisis management structures within the public health service and evidence-based communication by administrations and scientific associations. Outbreaks of similar dimensions can inevitably occur again and result in costs which will far exceed investments needed for early detection and control. This societal balance should be taken into account in spite of limited resources in the public health sector.

Modelling disease outbreaks in realistic urban social networks

NASA Astrophysics Data System (ADS)

Eubank, Stephen; Guclu, Hasan; Anil Kumar, V. S.; Marathe, Madhav V.; Srinivasan, Aravind; Toroczkai, Zoltán; Wang, Nan

2004-05-01

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

The economic burden of a Salmonella Thompson outbreak caused by smoked salmon in the Netherlands, 2012-2013.

PubMed

Suijkerbuijk, Anita W M; Bouwknegt, Martijn; Mangen, Marie-Josee J; de Wit, G Ardine; van Pelt, Wilfrid; Bijkerk, Paul; Friesema, Ingrid H M

2017-04-01

In 2012, the Netherlands experienced the most extensive food-related outbreak of Salmonella ever recorded. It was caused by smoked salmon contaminated with Salmonella Thompson during processing. In total, 1149 cases of salmonellosis were laboratory confirmed and reported to RIVM. Twenty percent of cases was hospitalised and four cases were reported to be fatal. The purpose of this study was to estimate total costs of the Salmonella Thompson outbreak. Data from a case-control study were used to estimate the cost-of-illness of reported cases (i.e. healthcare costs, patient costs and production losses). Outbreak control costs were estimated based on interviews with staff from health authorities. Using the Dutch foodborne disease burden and cost-of-illness model, we estimated the number of underestimated cases and the associated cost-of-illness. The estimated number of cases, including reported and underestimated cases was 21 123. Adjusted for underestimation, the total cost-of-illness would be €6.8 million (95% CI €2.5-€16.7 million) with productivity losses being the main cost driver. Adding outbreak control costs, the total outbreak costs are estimated at €7.5 million. In the Netherlands, measures are taken to reduce salmonella concentrations in food, but detection of contamination during food processing remains difficult. As shown, Salmonella outbreaks have the potential for a relatively high disease and economic burden for society. Early warning and close cooperation between the industry, health authorities and laboratories is essential for rapid detection, control of outbreaks, and to reduce disease and economic burden. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

in silico Surveillance: evaluating outbreak detection with simulation models

PubMed Central

2013-01-01

Background Detecting outbreaks is a crucial task for public health officials, yet gaps remain in the systematic evaluation of outbreak detection protocols. The authors’ objectives were to design, implement, and test a flexible methodology for generating detailed synthetic surveillance data that provides realistic geographical and temporal clustering of cases and use to evaluate outbreak detection protocols. Methods A detailed representation of the Boston area was constructed, based on data about individuals, locations, and activity patterns. Influenza-like illness (ILI) transmission was simulated, producing 100 years of in silico ILI data. Six different surveillance systems were designed and developed using gathered cases from the simulated disease data. Performance was measured by inserting test outbreaks into the surveillance streams and analyzing the likelihood and timeliness of detection. Results Detection of outbreaks varied from 21% to 95%. Increased coverage did not linearly improve detection probability for all surveillance systems. Relaxing the decision threshold for signaling outbreaks greatly increased false-positives, improved outbreak detection slightly, and led to earlier outbreak detection. Conclusions Geographical distribution can be more important than coverage level. Detailed simulations of infectious disease transmission can be configured to represent nearly any conceivable scenario. They are a powerful tool for evaluating the performance of surveillance systems and methods used for outbreak detection. PMID:23343523

Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus.

PubMed

Faverjon, Céline; Andersson, M Gunnar; Decors, Anouk; Tapprest, Jackie; Tritz, Pierre; Sandoz, Alain; Kutasi, Orsolya; Sala, Carole; Leblond, Agnès

2016-06-01

Various methods are currently used for the early detection of West Nile virus (WNV) but their outputs are not quantitative and/or do not take into account all available information. Our study aimed to test a multivariate syndromic surveillance system to evaluate if the sensitivity and the specificity of detection of WNV could be improved. Weekly time series data on nervous syndromes in horses and mortality in both horses and wild birds were used. Baselines were fitted to the three time series and used to simulate 100 years of surveillance data. WNV outbreaks were simulated and inserted into the baselines based on historical data and expert opinion. Univariate and multivariate syndromic surveillance systems were tested to gauge how well they detected the outbreaks; detection was based on an empirical Bayesian approach. The systems' performances were compared using measures of sensitivity, specificity, and area under receiver operating characteristic curve (AUC). When data sources were considered separately (i.e., univariate systems), the best detection performance was obtained using the data set of nervous symptoms in horses compared to those of bird and horse mortality (AUCs equal to 0.80, 0.75, and 0.50, respectively). A multivariate outbreak detection system that used nervous symptoms in horses and bird mortality generated the best performance (AUC = 0.87). The proposed approach is suitable for performing multivariate syndromic surveillance of WNV outbreaks. This is particularly relevant, given that a multivariate surveillance system performed better than a univariate approach. Such a surveillance system could be especially useful in serving as an alert for the possibility of human viral infections. This approach can be also used for other diseases for which multiple sources of evidence are available.

Investigation of an Influenza A (H3N2) outbreak in evacuation centres following the Great East Japan earthquake, 2011.

PubMed

Kamigaki, Taro; Seino, Jin; Tohma, Kentaro; Nukiwa-Soma, Nao; Otani, Kanako; Oshitani, Hitoshi

2014-01-14

The Great East Japan Earthquake of magnitude 9.0 that struck on 11 March 2011 resulted in more than 18000 deaths or cases of missing persons. The large-scale tsunami that followed the earthquake devastated many coastal areas of the Tohoku region, including Miyagi Prefecture, and many residents of the tsunami-affected areas were compelled to reside in evacuation centres (ECs). In Japan, seasonal influenza epidemics usually occur between December and March. At the time of the Great East Japan Earthquake on 11 March 2011, influenza A (H3N2) was still circulating and there was a heightened concern regarding severe outbreaks due to influenza A (H3N2). After local hospital staff and public health nurses detected influenza cases among the evacuees, an outbreak investigation was conducted in five ECs that had reported at least one influenza case from 23 March to 11 April 2011. Cases were confirmed by point-of-care tests and those residues were obtained and subjected to reverse transcription PCR and/or real time RT-PCR for sub-typing of influenza. There were 105 confirmed cases detected during the study period with a mean attack rate of 5.3% (range, 0.8%-11.1%). An epidemiological tree for two ECs demonstrated same-room and familial links that accounted for 88.5% of cases. The majority of cases occurred in those aged 15-64 years, who were likely to have engaged in search and rescue activities. No deaths were reported in this outbreak. Familial link accounted for on average 40.5% of influenza cases in two ECs and rooms where two or more cases were reported accounted for on average 85% in those ECs. A combination of preventative measures, including case cohorting, personal hygiene, wearing masks, and early detection and treatment, were implemented during the outbreak period. Influenza can cause outbreaks in a disaster setting when the disaster occurs during an epidemic influenza season. The transmission route is more likely to be associated with sharing room and space and with familial links. The importance of influenza surveillance and early treatments should be emphasized in EC settings for implementing preventive control measures.

Drug sales data analysis for outbreak detection of infectious diseases: a systematic literature review.

PubMed

Pivette, Mathilde; Mueller, Judith E; Crépey, Pascal; Bar-Hen, Avner

2014-11-18

This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases. A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection). We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales. Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed.

Typhoid fever acquired in the United States, 1999–2010: epidemiology, microbiology, and use of a space–time scan statistic for outbreak detection

PubMed Central

IMANISHI, M.; NEWTON, A. E.; VIEIRA, A. R.; GONZALEZ-AVILES, G.; KENDALL SCOTT, M. E.; MANIKONDA, K.; MAXWELL, T. N.; HALPIN, J. L.; FREEMAN, M. M.; MEDALLA, F.; AYERS, T. L.; DERADO, G.; MAHON, B. E.; MINTZ, E. D.

2016-01-01

SUMMARY Although rare, typhoid fever cases acquired in the United States continue to be reported. Detection and investigation of outbreaks in these domestically acquired cases offer opportunities to identify chronic carriers. We searched surveillance and laboratory databases for domestically acquired typhoid fever cases, used a space–time scan statistic to identify clusters, and classified clusters as outbreaks or non-outbreaks. From 1999 to 2010, domestically acquired cases accounted for 18% of 3373 reported typhoid fever cases; their isolates were less often multidrug-resistant (2% vs. 15%) compared to isolates from travel-associated cases. We identified 28 outbreaks and two possible outbreaks within 45 space–time clusters of ⩾2 domestically acquired cases, including three outbreaks involving ⩾2 molecular subtypes. The approach detected seven of the ten outbreaks published in the literature or reported to CDC. Although this approach did not definitively identify any previously unrecognized outbreaks, it showed the potential to detect outbreaks of typhoid fever that may escape detection by routine analysis of surveillance data. Sixteen outbreaks had been linked to a carrier. Every case of typhoid fever acquired in a non-endemic country warrants thorough investigation. Space–time scan statistics, together with shoe-leather epidemiology and molecular subtyping, may improve outbreak detection. PMID:25427666

Typhoid fever acquired in the United States, 1999-2010: epidemiology, microbiology, and use of a space-time scan statistic for outbreak detection.

PubMed

Imanishi, M; Newton, A E; Vieira, A R; Gonzalez-Aviles, G; Kendall Scott, M E; Manikonda, K; Maxwell, T N; Halpin, J L; Freeman, M M; Medalla, F; Ayers, T L; Derado, G; Mahon, B E; Mintz, E D

2015-08-01

Although rare, typhoid fever cases acquired in the United States continue to be reported. Detection and investigation of outbreaks in these domestically acquired cases offer opportunities to identify chronic carriers. We searched surveillance and laboratory databases for domestically acquired typhoid fever cases, used a space-time scan statistic to identify clusters, and classified clusters as outbreaks or non-outbreaks. From 1999 to 2010, domestically acquired cases accounted for 18% of 3373 reported typhoid fever cases; their isolates were less often multidrug-resistant (2% vs. 15%) compared to isolates from travel-associated cases. We identified 28 outbreaks and two possible outbreaks within 45 space-time clusters of ⩾2 domestically acquired cases, including three outbreaks involving ⩾2 molecular subtypes. The approach detected seven of the ten outbreaks published in the literature or reported to CDC. Although this approach did not definitively identify any previously unrecognized outbreaks, it showed the potential to detect outbreaks of typhoid fever that may escape detection by routine analysis of surveillance data. Sixteen outbreaks had been linked to a carrier. Every case of typhoid fever acquired in a non-endemic country warrants thorough investigation. Space-time scan statistics, together with shoe-leather epidemiology and molecular subtyping, may improve outbreak detection.

Modeling the spread of polio in an IPV-vaccinated population: lessons learned from the 2013 silent outbreak in southern Israel.

PubMed

Yaari, Rami; Kaliner, Ehud; Grotto, Itamar; Katriel, Guy; Moran-Gilad, Jacob; Sofer, Danit; Mendelson, Ella; Miller, Elizabeth; Huppert, Amit; Anis, E; Kopel, E; Manor, Y; Mor, O; Shulman, L; Singer, R; Weil, M

2016-06-23

Polio eradication is an extraordinary globally coordinated health program in terms of its magnitude and reach, leading to the elimination of wild poliovirus (WPV) in most parts of the world. In 2013, a silent outbreak of WPV was detected in Israel, a country using an inactivated polio vaccine (IPV) exclusively since 2005. The outbreak was detected using environmental surveillance (ES) of sewage reservoirs. Stool surveys indicated the outbreak to be restricted mainly to children under the age of 10 in the Bedouin population of southern Israel. In order to curtail the outbreak, a nationwide vaccination campaign using oral polio vaccine (OPV) was conducted, targeting all children under 10. A transmission model, fitted to the results of the stool surveys, with additional conditions set by the ES measurements, was used to evaluate the prevalence of WPV in Bedouin children and the effectiveness of the vaccination campaign. Employing the parameter estimates of the model fitting, the model was used to investigate the effect of alternative timings, coverages and dosages of the OPV campaign on the outcome of the outbreak. The mean estimate for the mean reproductive number was 1.77 (95 % credible interval, 1.46-2.30). With seasonal variation, the reproductive number maximum range was between zero and six. The mean estimate for the mean infectious periods was 16.8 (8.6-24.9) days. The modeling indicates the OPV campaign was effective in curtailing the outbreak. The mean estimate for the attack rate in Bedouin children under 10 at the end of 2014 was 42 % (22-65 %), whereas without the campaign the mean projected attack rate was 57 % (35-74 %). The campaign also likely shortened the duration of the outbreak by a mean estimate of 309 (2-846) days. A faster initiation of the OPV campaign could have reduced the incidence of WPV even if a lower coverage was reached, at the risk of prolonging the outbreak. OPV campaigns are essential for interrupting WPV transmission, even in a developed country setting with a high coverage of IPV. In this setting, establishing ES of WPV circulation is particularly crucial for early detection and containment of an outbreak.

Lessons learned during active epidemiological surveillance of Ebola and Marburg viral hemorrhagic fever epidemics in Africa.

PubMed

Allaranga, Yokouide; Kone, Mamadou Lamine; Formenty, Pierre; Libama, Francois; Boumandouki, Paul; Woodfill, Celia J I; Sow, Idrissa; Duale, Sambe; Alemu, Wondimagegnehu; Yada, Adamou

2010-03-01

To review epidemiological surveillance approaches used during Ebola and Marburg hemorrhagic fever epidemics in Africa in the past fifteen years. Overall, 26 hemorrhagic epidemic outbreaks have been registered in 12 countries; 18 caused by the Ebola virus and eight by the Marburg virus. About 2551 cases have been reported, among which 268 were health workers (9,3%). Based on articles and epidemic management reports, this review analyses surveillance approaches, route of introduction of the virus into the population (urban and rural), the collaboration between the human health sector and the wildlife sector and factors that have affected epidemic management. Several factors affecting the epidemiological surveillance during Ebola and Marburg viruses hemorrhagic epidemics have been observed. During epidemics in rural settings, outbreak investigations have shown multiple introductions of the virus into the human population through wildlife. In contrast, during epidemics in urban settings a single introduction of the virus in the community was responsible for the epidemic. Active surveillance is key to containing outbreaks of Ebola and Marburg viruses Collaboration with those in charge of the conservation of wildlife is essential for the early detection of viral hemorrhagic fever epidemics. Hemorrhagic fever epidemics caused by Ebola and Marburg viruses are occurring more and more frequently in Sub-Saharan Africa and only an adapted epidemiological surveillance system will allow for early detection and effective response.

A review of influenza detection and prediction through social networking sites.

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

Outbreak of multidrug-resistant Escherichia coli sequence type 131 in a neonatal intensive care unit: efficient active surveillance prevented fatal outcome.

PubMed

Silwedel, C; Vogel, U; Claus, H; Glaser, K; Speer, C P; Wirbelauer, J

2016-06-01

Outbreaks of infections with multidrug-resistant bacteria in neonatal intensive care units (NICUs) pose a major threat, especially to extremely preterm infants. This study describes a 35-day outbreak of multidrug-resistant Escherichia coli (E. coli) in a tertiary-level NICU in Germany. To underline the importance of surveillance policies in the particularly vulnerable cohort of preterm infants and to describe the efficacy of outbreak control strategies. Data were collected retrospectively from medical reports. Infants and environment were tested for E. coli. The outbreak affected a total of 13 infants between 25(+1) and 35(+0) weeks of gestation with seven infants showing signs of infection. The outbreak strain was identified as E. coli sequence type 131. Environmental screening provided no evidence for an environmental source. Through colonization surveillance and immediate and adequate treatment of potentially infected preterm infants, no fatalities occurred. Outbreak control was achieved by strict contact precautions, enhanced screening and temporary relocation of the NICU. Relocation and reconstruction improved the NICU's structural layout, focusing on isolation capacities. Follow-up indicated carriage for several months in some infants. Routine surveillance allowed early detection of the outbreak. The identification of carriers of the outbreak strain was successfully used to direct antibiotic treatment in case of infection. Enhanced hygienic measures and ward relocation were instrumental in controlling the outbreak. Copyright © 2016. Published by Elsevier Ltd.

Development of a recombinase polymerase amplification assay for the detection of pathogenic Leptospira.

PubMed

Ahmed, Ahmed; van der Linden, Hans; Hartskeerl, Rudy A

2014-05-08

Detection of leptospires based on DNA amplification techniques is essential for the early diagnosis of leptospirosis when anti-Leptospira antibodies are below the detection limit of most serological tests. In middle and low income countries where leptospirosis is endemic, routine implementation of real-time PCR is financially and technically challenging due to the requirement of expensive thermocycler equipment. In this study we report the development and evaluation of a novel isothermal recombinase polymerase amplification assay (RPA) for detection of pathogenic Leptospira based on TwistAmp chemistry. RPA enabled the detection of less than two genome copies per reaction. Retrospective evaluation revealed a high diagnostic accuracy (sensitivity and specificity of 94.7% and 97.7%, respectively) compared to culturing as the reference standard. RPA presents a powerful tool for the early diagnosis of leptospirosis in humans and in animals. Furthermore, it enables the detection of the causative agent in reservoirs and environment, and as such is a valuable adjunct to current tools for surveillance and early outbreak warning.

Development of a Recombinase Polymerase Amplification Assay for the Detection of Pathogenic Leptospira

PubMed Central

Ahmed, Ahmed; van der Linden, Hans; Hartskeerl, Rudy A.

2014-01-01

Detection of leptospires based on DNA amplification techniques is essential for the early diagnosis of leptospirosis when anti-Leptospira antibodies are below the detection limit of most serological tests. In middle and low income countries where leptospirosis is endemic, routine implementation of real-time PCR is financially and technically challenging due to the requirement of expensive thermocycler equipment. In this study we report the development and evaluation of a novel isothermal recombinase polymerase amplification assay (RPA) for detection of pathogenic Leptospira based on TwistAmp chemistry. RPA enabled the detection of less than two genome copies per reaction. Retrospective evaluation revealed a high diagnostic accuracy (sensitivity and specificity of 94.7% and 97.7%, respectively) compared to culturing as the reference standard. RPA presents a powerful tool for the early diagnosis of leptospirosis in humans and in animals. Furthermore, it enables the detection of the causative agent in reservoirs and environment, and as such is a valuable adjunct to current tools for surveillance and early outbreak warning. PMID:24814943

Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study.

PubMed

Baker, Arthur W; Haridy, Salah; Salem, Joseph; Ilieş, Iulian; Ergai, Awatef O; Samareh, Aven; Andrianas, Nicholas; Benneyan, James C; Sexton, Daniel J; Anderson, Deverick J

2017-11-24

Traditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data. We performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations. Conventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7 months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data. Our findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Integrating Remote Sensing and Disease Surveillance to Forecast Malaria Epidemics

NASA Astrophysics Data System (ADS)

Wimberly, M. C.; Beyane, B.; DeVos, M.; Liu, Y.; Merkord, C. L.; Mihretie, A.

2015-12-01

Advance information about the timing and locations of malaria epidemics can facilitate the targeting of resources for prevention and emergency response. Early detection methods can detect incipient outbreaks by identifying deviations from expected seasonal patterns, whereas early warning approaches typically forecast future malaria risk based on lagged responses to meteorological factors. A critical limiting factor for implementing either of these approaches is the need for timely and consistent acquisition, processing and analysis of both environmental and epidemiological data. To address this need, we have developed EPIDEMIA - an integrated system for surveillance and forecasting of malaria epidemics. The EPIDEMIA system includes a public health interface for uploading and querying weekly surveillance reports as well as algorithms for automatically validating incoming data and updating the epidemiological surveillance database. The newly released EASTWeb 2.0 software application automatically downloads, processes, and summaries remotely-sensed environmental data from multiple earth science data archives. EASTWeb was implemented as a component of the EPIDEMIA system, which combines the environmental monitoring data and epidemiological surveillance data into a unified database that supports both early detection and early warning models. Dynamic linear models implemented with Kalman filtering were used to carry out forecasting and model updating. Preliminary forecasts have been disseminated to public health partners in the Amhara Region of Ethiopia and will be validated and refined as the EPIDEMIA system ingests new data. In addition to continued model development and testing, future work will involve updating the public health interface to provide a broader suite of outbreak alerts and data visualization tools that are useful to our public health partners. The EPIDEMIA system demonstrates a feasible approach to synthesizing the information from epidemiological surveillance systems and remotely-sensed environmental monitoring systems to improve malaria epidemic detection and forecasting.

Group A Streptococcus Toxic Shock Syndrome: An outbreak report and review of the literature.

PubMed

Al-ajmi, Jameela Alkhowaiter; Hill, Peter; O' Boyle, Carol; Garcia, Ma Leni Basco; Malkawi, Manal; George, Ancy; Saleh, Fatma; Lukose, Bency; Ali, Badriya Al; Elsheikh, Mamoun

2012-12-01

Group A Streptococcal (GAS) Toxic Shock Syndrome (TSS) is an acute, rapidly progressive, and often fatal illness. Outbreaks can occur in hospitals. However, early infection control measures may interrupt transmissions and prevent morbidity and mortality. Two cases of invasive GAS TSS were diagnosed within 48h after two uncomplicated laparoscopic surgeries that were performed in the same operating room of a women's hospital. Investigations conducted by the infection prevention and control department of the hospital identified 46 obstetrical staff members who were involved in the surgeries and/or had contact with either of the patients. All of the staff members were interviewed regarding any recent history of upper respiratory tract infections, the presence of skin lesions and vaginal or rectal symptoms. Throat, rectal, and vaginal cultures were obtained two times from all of the involved staff members. Throat colonization with GAS was detected in the cultures from one obstetrical intern who attended the 1st surgery and from one nurse who had formerly worked in the postnatal ward. These two strains were epidemiologically different from each other and from the outbreak strain. Both carriers were suspended from direct patient care and were treated with a ten-day course of oral clindamycin. The success of their decolonization status was assessed at the end of therapy and at three, six, nine and twelve months thereafter before reassigning them to routine work. Unfortunately, in spite of the extensive investigation of all involved personnel and of the environment, the mode of transmission to the second patient could not be established. However, droplet or airborne transmission could not be ruled out. Early and meticulous implementation of infection control measures was crucial and instrumental in the successful management and control of this outbreak. Furthermore, there were no subsequent GAS cases detected during the 24 months following the outbreak. Copyright © 2012 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

A HISTORICAL PERSPECTIVE OF DETECTION METHODS FOR GIARDIA CYSTS AND CRYPTOSPORIDIUM OOCYSTS IN WATER

EPA Science Inventory

In the mid-20th century Giardia was classified as a non-pathogenic commensal organism and Cryptosporidium was not recognized yet. However as early as 1946 a waterborne outbreak of giardiasis was suspected. From 1965 to 1979 it became clear that Giardia lamblia was indeed a human ...

Invasive Species Distribution Modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Treesearch

Tomáš Václavík; Ross K. Meentemeyer

2009-01-01

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges...

SARS and population health technology.

PubMed

Eysenbach, Gunther

2003-01-01

The recent global outbreak of SARS (severe acute respiratory syndrome) provides an opportunity to study the use and impact of public health informatics and population health technology to detect and fight a global epidemic. Population health technology is the umbrella term for technology applications that have a population focus and the potential to improve public health. This includes the Internet, but also other technologies such as wireless devices, mobile phones, smart appliances, or smart homes. In the context of an outbreak or bioterrorism attack, such technologies may help to gather intelligence and detect diseases early, and communicate and exchange information electronically worldwide. Some of the technologies brought forward during the SARS epidemic may have been primarily motivated by marketing efforts, or were more directed towards reassuring people that "something is being done," ie, fighting an "epidemic of fear." To understand "fear epidemiology" is important because early warning systems monitoring data from a large number of people may not be able to discriminate between a biological epidemic and an epidemic of fear. The need for critical evaluation of all of these technologies is stressed.

Characterization of the temporal and spatial distribution and reproductive ratio of vesicular stomatitis outbreaks in Mexico in 2008.

PubMed

Arroyo, Montserrat; Perez, Andres M; Rodriguez, Luis L

2011-02-01

To characterize the temporal and spatial distribution and reproductive ratio of vesicular stomatitis (VS) outbreaks reported in Mexico in 2008. Bovine herds in Mexico in which VS outbreaks were officially reported and confirmed from January 1 through December 31, 2008. The Poisson model of the space-time scan statistic was used to identify periods and geographical locations at highest risk for VS in Mexico in 2008. The herd reproductive ratio (R(h)) of the epidemic was computed by use of the doubling-time method. 1 significant space-time cluster of VS was detected in the state of Michoacan from September 4 through December 10, 2008. The temporal extent of the VS outbreaks and the value and pattern of decrease of the R(h) were different in the endemic zone of Tabasco and Chiapas, compared with findings in the region included in the space-time cluster. The large number of VS outbreaks reported in Mexico in 2008 was associated with the spread of the disease from the endemic zone in southern Mexico to areas sporadically affected by the disease. Results suggested that implementation of a surveillance system in the endemic zone of Mexico aimed at early detection of changes in the value of R(h) and space-time clustering of the disease could help predict occurrence of future VS outbreaks originating from this endemic zone. This information will help prevent VS spread into regions of Mexico and neighboring countries that are only sporadically affected by the disease.

Pan-genome multilocus sequence typing and outbreak-specific reference-based single nucleotide polymorphism analysis to resolve two concurrent Staphylococcus aureus outbreaks in neonatal services.

PubMed

Roisin, S; Gaudin, C; De Mendonça, R; Bellon, J; Van Vaerenbergh, K; De Bruyne, K; Byl, B; Pouseele, H; Denis, O; Supply, P

2016-06-01

We used a two-step whole genome sequencing analysis for resolving two concurrent outbreaks in two neonatal services in Belgium, caused by exfoliative toxin A-encoding-gene-positive (eta+) methicillin-susceptible Staphylococcus aureus with an otherwise sporadic spa-type t209 (ST-109). Outbreak A involved 19 neonates and one healthcare worker in a Brussels hospital from May 2011 to October 2013. After a first episode interrupted by decolonization procedures applied over 7 months, the outbreak resumed concomitantly with the onset of outbreak B in a hospital in Asse, comprising 11 neonates and one healthcare worker from mid-2012 to January 2013. Pan-genome multilocus sequence typing, defined on the basis of 42 core and accessory reference genomes, and single-nucleotide polymorphisms mapped on an outbreak-specific de novo assembly were used to compare 28 available outbreak isolates and 19 eta+/spa-type t209 isolates identified by routine or nationwide surveillance. Pan-genome multilocus sequence typing showed that the outbreaks were caused by independent clones not closely related to any of the surveillance isolates. Isolates from only ten cases with overlapping stays in outbreak A, including four pairs of twins, showed no or only a single nucleotide polymorphism variation, indicating limited sequential transmission. Detection of larger genomic variation, even from the start of the outbreak, pointed to sporadic seeding from a pre-existing exogenous source, which persisted throughout the whole course of outbreak A. Whole genome sequencing analysis can provide unique fine-tuned insights into transmission pathways of complex outbreaks even at their inception, which, with timely use, could valuably guide efforts for early source identification. Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Ebolavirus diagnosis made simple, comparable and faster than molecular detection methods: preparing for the future.

PubMed

James, Ameh S; Todd, Shawn; Pollak, Nina M; Marsh, Glenn A; Macdonald, Joanne

2018-04-23

The 2014/2015 Ebolavirus outbreak resulted in more than 28,000 cases and 11,323 reported deaths, as of March 2016. Domestic transmission of the Guinea strain associated with the outbreak occurred mainly in six African countries, and international transmission was reported in four countries. Outbreak management was limited by the inability to rapidly diagnose infected cases. A further fifteen countries in Africa are predicted to be at risk of Ebolavirus outbreaks in the future as a consequence of climate change and urbanization. Early detection of cases and reduction of transmission rates is critical to prevent and manage future severe outbreaks. We designed a rapid assay for detection of Ebolavirus using recombinase polymerase amplification, a rapid isothermal amplification technology that can be combined with portable lateral flow detection technology. The developed rapid assay operates in 30 min and was comparable with real-time TaqMan™ PCR. Designed, screened, selected and optimized oligonucleotides using the NP coding region from Ebola Zaire virus (Guinea strain). We determined the analytical sensitivity of our Ebola rapid molecular test by testing selected primers and probe with tenfold serial dilutions (1.34 × 10 10-  1.34 × 10 1 copies/μL) of cloned NP gene from Mayinga strain of Zaire ebolavirus in pCAGGS vector, and serially diluted cultured Ebolavirus as established by real-time TaqMan™ PCR that was performed using ABI7500 in Fast Mode. We tested extracted and reverse transcribed RNA from cultured Zaire ebolavirus strains - Mayinga, Gueckedou C05, Gueckedou C07, Makona, Kissidougou and Kiwit. We determined the analytical specificity of our assay with related viruses: Marburg, Ebola Reston and Ebola Sudan. We further tested for Dengue virus 1-4, Plasmodium falciparum and West Nile Virus (Kunjin strain). The assay had a detection limit of 134 copies per μL of plasmid containing the NP gene of Ebolavirus Mayinga, and cultured Ebolavirus and was highly specific for the Zaire ebolavirus species, including the Guinea strain responsible for the 2014/2015 outbreak. The assay did not detect related viruses like Marburg, Reston, or Sudan viruses, and other pathogens likely to be isolated from clinical samples. Our assay could be suitable for implementation in district and primary health laboratories, as only a heating block and centrifuge is required for operation. The technique could provide a pathway for rapid screening of patients and animals for improved management of outbreaks.

Editorial: Biological Engagement Programs: Reducing Threats and Strengthening Global Health Security Through Scientific Collaboration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fair, Jeanne M.

It is often said about infectious diseases that a “threat anywhere is a threat everywhere,” and the recent outbreaks of Ebola in West Africa and Zika virus in South America have proven that pathogens know no borders. Not only are they transboundary, pathogens do not discriminate who they infect. In addition to the natural increase in emerging zoonotic infectious diseases worldwide due to changing environmental conditions and globalization, the use of infectious diseases as warfare agents is a threat in today’s world. Early detection remains one of the best ways to prevent small outbreaks becoming epidemics and pandemics. We findmore » that an accurate diagnosis, detection, and reporting of diseases are important components of mitigating outbreaks, and biosurveillance remains the top tool in our toolbox. And while vaccines have been important for controlling more common infectious virus diseases, they are less feasible for less common diseases, emerging pathogens, and rapidly evolving microbes. Furthermore, due to globalization and increased travel, emigration, and migration, biosurveillance is critical throughout the world, not just in pockets of more developed regions.« less

Editorial: Biological Engagement Programs: Reducing Threats and Strengthening Global Health Security Through Scientific Collaboration

DOE PAGES

Fair, Jeanne M.

2017-07-12

It is often said about infectious diseases that a “threat anywhere is a threat everywhere,” and the recent outbreaks of Ebola in West Africa and Zika virus in South America have proven that pathogens know no borders. Not only are they transboundary, pathogens do not discriminate who they infect. In addition to the natural increase in emerging zoonotic infectious diseases worldwide due to changing environmental conditions and globalization, the use of infectious diseases as warfare agents is a threat in today’s world. Early detection remains one of the best ways to prevent small outbreaks becoming epidemics and pandemics. We findmore » that an accurate diagnosis, detection, and reporting of diseases are important components of mitigating outbreaks, and biosurveillance remains the top tool in our toolbox. And while vaccines have been important for controlling more common infectious virus diseases, they are less feasible for less common diseases, emerging pathogens, and rapidly evolving microbes. Furthermore, due to globalization and increased travel, emigration, and migration, biosurveillance is critical throughout the world, not just in pockets of more developed regions.« less

ANTHRAX IN THE MACKENZIE WOOD BISON (BISON BISON ATHABASCAE) POPULATION: 2012 ANTHRAX OUTBREAK AND HISTORICAL EXPOSURE IN NONOUTBREAK YEARS.

PubMed

New, Dallas; Elkin, Brett; Armstrong, Terry; Epp, Tasha

2017-10-01

Anthrax, caused by the spore-forming bacterium Bacillus anthracis, poses a threat to wood bison (Bison bison athabascae) conservation. We used descriptive epidemiology to characterize a large outbreak of anthrax in the Mackenzie bison population in the Northwest Territories, Canada, in 2012 and investigated historical serologic exposure of the bison to the bacterium in nonoutbreak years. Between late June and early August 2012, 451 bison carcasses were detected; mortality peaked from 13-19 July. A substantial number of calves, yearlings, and adult females died in the 2012 outbreak, unlike in two previous anthrax outbreaks in this population that killed mostly mature males. On the basis of the difference in estimates of population size prior to the outbreak (2012) and after the outbreak (2013), it is possible that not all dead bison were found during the outbreak. We assessed serologic history of exposure to B. anthracis by using samples from the Mackenzie wood bison population collected between 1986 and 2009. Overall, 87 of 278 samples were positive (31%). Seroprevalence was lower in females (18%, 10/55) than males (36%, 72/203). The highest proportion of positive submissions (90%) was from 1994, the year following the only anthrax outbreak within the historical data set. Both adult males and females had a higher likelihood of being seropositive than the younger age categories. There was a trend toward declining antibody levels between the 1993 and 2012 outbreak years.

Strategies in Ebola virus disease (EVD) diagnostics at the point of care.

PubMed

Coarsey, Chad T; Esiobu, Nwadiuto; Narayanan, Ramswamy; Pavlovic, Mirjana; Shafiee, Hadi; Asghar, Waseem

2017-11-01

Ebola virus disease (EVD) is a devastating, highly infectious illness with a high mortality rate. The disease is endemic to regions of Central and West Africa, where there is limited laboratory infrastructure and trained staff. The recent 2014 West African EVD outbreak has been unprecedented in case numbers and fatalities, and has proven that such regional outbreaks can become a potential threat to global public health, as it became the source for the subsequent transmission events in Spain and the USA. The urgent need for rapid and affordable means of detecting Ebola is crucial to control the spread of EVD and prevent devastating fatalities. Current diagnostic techniques include molecular diagnostics and other serological and antigen detection assays; which can be time-consuming, laboratory-based, often require trained personnel and specialized equipment. In this review, we discuss the various Ebola detection techniques currently in use, and highlight the potential future directions pertinent to the development and adoption of novel point-of-care diagnostic tools. Finally, a case is made for the need to develop novel microfluidic technologies and versatile rapid detection platforms for early detection of EVD.

Evaluation of a statewide foodborne illness complaint surveillance system in Minnesota, 2000 through 2006.

PubMed

Li, John; Smith, Kirk; Kaehler, Dawn; Everstine, Karen; Rounds, Josh; Hedberg, Craig

2010-11-01

Foodborne outbreaks are detected by recognition of similar illnesses among persons with a common exposure or by identification of case clusters through pathogen-specific surveillance. PulseNet USA has created a national framework for pathogen-specific surveillance, but no comparable effort has been made to improve surveillance of consumer complaints of suspected foodborne illness. The purpose of this study was to characterize the complaint surveillance system in Minnesota and to evaluate its use for detecting outbreaks. Minnesota Department of Health foodborne illness surveillance data from 2000 through 2006 were analyzed for this study. During this period, consumer complaint surveillance led to detection of 79% of confirmed foodborne outbreaks. Most norovirus infection outbreaks were detected through complaints. Complaint surveillance also directly led or contributed to detection of 25% of salmonellosis outbreaks. Eighty-one percent of complainants did not seek medical attention. The number of ill persons in a complainant's party was significantly associated with a complaint ultimately resulting in identification of a foodborne outbreak. Outbreak confirmation was related to a complainant's ability to identify a common exposure and was likely related to the process by which the Minnesota Department of Health chooses complaints to investigate. A significant difference (P < 0.001) was found in incubation periods between complaints that were outbreak associated (median, 27 h) and those that were not outbreak associated (median, 6 h). Complaint systems can be used to detect outbreaks caused by a variety of pathogens. Case detection for foodborne disease surveillance in Minnesota happens through a multitude of mechanisms. The ability to integrate these mechanisms and carry out rapid investigations leads to improved outbreak detection.

Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness, New York City.

PubMed

Mostashari, Farzad; Fine, Annie; Das, Debjani; Adams, John; Layton, Marcelle

2003-06-01

In 1998, the New York City Department of Health and the Mayor's Office of Emergency Management began monitoring the volume of ambulance dispatch calls as a surveillance tool for biologic terrorism. We adapted statistical techniques designed to measure excess influenza mortality and applied them to outbreak detection using ambulance dispatch data. Since 1999, we have been performing serial daily regressions to determine the alarm threshold for the current day. In this article, we evaluate this approach by simulating a series of 2,200 daily regressions. In the influenza detection implementation of this model, there were 71 (3.2%) alarms at the 99% level. Of these alarms, 64 (90%) occurred shortly before or during a period of peak influenza in each of six influenza seasons. In the bioterrorism detection implementation of this methodology, after accounting for current influenza activity, there were 24 (1.1%) alarms at the 99% level. Two occurred during a large snowstorm, 1 is unexplained, and 21 occurred shortly before or during a period of peak influenza activity in each of six influenza seasons. Our findings suggest that this surveillance system is sensitive to communitywide respiratory outbreaks with relatively few false alarms. More work needs to be done to evaluate the sensitivity of this approach for detecting nonrespiratory illness and more localized outbreaks.

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak.

PubMed

Song, X X; Zhao, Q; Tao, T; Zhou, C M; Diwan, V K; Xu, B

2018-05-30

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

THE CHALLENGE OF DETECTING CLASSICAL SWINE FEVER VIRUS CIRCULATION IN WILD BOAR (SUS SCROFA): SIMULATION OF SAMPLING OPTIONS.

PubMed

Sonnenburg, Jana; Schulz, Katja; Blome, Sandra; Staubach, Christoph

2016-10-01

Classical swine fever (CSF) is one of the most important viral diseases of domestic pigs ( Sus scrofa domesticus) and wild boar ( Sus scrofa ). For at least 4 decades, several European Union member states were confronted with outbreaks among wild boar and, as it had been shown that infected wild boar populations can be a major cause of primary outbreaks in domestic pigs, strict control measures for both species were implemented. To guarantee early detection and to demonstrate freedom from disease, intensive surveillance is carried out based on a hunting bag sample. In this context, virologic investigations play a major role in the early detection of new introductions and in regions immunized with a conventional vaccine. The required financial resources and personnel for reliable testing are often large, and sufficient sample sizes to detect low virus prevalences are difficult to obtain. We conducted a simulation to model the possible impact of changes in sample size and sampling intervals on the probability of CSF virus detection based on a study area of 65 German hunting grounds. A 5-yr period with 4,652 virologic investigations was considered. Results suggest that low prevalences could not be detected with a justifiable effort. The simulation of increased sample sizes per sampling interval showed only a slightly better performance but would be unrealistic in practice, especially outside the main hunting season. Further studies on other approaches such as targeted or risk-based sampling for virus detection in connection with (marker) antibody surveillance are needed.

H7N9 Highly Pathogenic Avian Influenza in the United States in 2017

USDA-ARS?s Scientific Manuscript database

In early March of 2017 an outbreak of highly pathogenic avian influenza H7N9 was reported from a broiler-breeder flock Tennessee. A second HPAI case was detected 2 weeks later. Subsequent active and passive surveillance identified several LPAI cases in Alabama, Georgia, Kentucky, and TN that was g...

Quantifying Network Dynamics and Information Flow Across Chinese Social Media During the African Ebola Outbreak.

PubMed

Feng, Shihui; Hossain, Liaquat; Crawford, John W; Bossomaier, Terry

2018-02-01

Social media provides us with a new platform on which to explore how the public responds to disasters and, of particular importance, how they respond to the emergence of infectious diseases such as Ebola. Provided it is appropriately informed, social media offers a potentially powerful means of supporting both early detection and effective containment of communicable diseases, which is essential for improving disaster medicine and public health preparedness. The 2014 West African Ebola outbreak is a particularly relevant contemporary case study on account of the large number of annual arrivals from Africa, including Chinese employees engaged in projects in Africa. Weibo (Weibo Corp, Beijing, China) is China's most popular social media platform, with more than 2 billion users and over 300 million daily posts, and offers great opportunity to monitor early detection and promotion of public health awareness. We present a proof-of-concept study of a subset of Weibo posts during the outbreak demonstrating potential and identifying priorities for improving the efficacy and accuracy of information dissemination. We quantify the evolution of the social network topology within Weibo relating to the efficacy of information sharing. We show how relatively few nodes in the network can have a dominant influence over both the quality and quantity of the information shared. These findings make an important contribution to disaster medicine and public health preparedness from theoretical and methodological perspectives for dealing with epidemics. (Disaster Med Public Health Preparedness. 2018;12:26-37).

Detection and forecasting of oyster norovirus outbreaks: recent advances and future perspectives.

PubMed

Wang, Jiao; Deng, Zhiqiang

2012-09-01

Norovirus is a highly infectious pathogen that is commonly found in oysters growing in fecally contaminated waters. Norovirus outbreaks can cause the closure of oyster harvesting waters and acute gastroenteritis in humans associated with consumption of contaminated raw oysters. Extensive efforts and progresses have been made in detection and forecasting of oyster norovirus outbreaks over the past decades. The main objective of this paper is to provide a literature review of methods and techniques for detecting and forecasting oyster norovirus outbreaks and thereby to identify the future directions for improving the detection and forecasting of norovirus outbreaks. It is found that (1) norovirus outbreaks display strong seasonality with the outbreak peak occurring commonly in December-March in the U.S. and April-May in the Europe; (2) norovirus outbreaks are affected by multiple environmental factors, including but not limited to precipitation, temperature, solar radiation, wind, and salinity; (3) various modeling approaches may be employed to forecast norovirus outbreaks, including Bayesian models, regression models, Artificial Neural Networks, and process-based models; and (4) diverse techniques are available for near real-time detection of norovirus outbreaks, including multiplex PCR, seminested PCR, real-time PCR, quantitative PCR, and satellite remote sensing. The findings are important to the management of oyster growing waters and to future investigations into norovirus outbreaks. It is recommended that a combined approach of sensor-assisted real time monitoring and modeling-based forecasting should be utilized for an efficient and effective detection and forecasting of norovirus outbreaks caused by consumption of contaminated oysters. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data

PubMed Central

Jombart, Thibaut; Cori, Anne; Didelot, Xavier; Cauchemez, Simon; Fraser, Christophe; Ferguson, Neil

2014-01-01

Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package outbreaker. It is applicable to various densely sampled epidemics, and improves previous approaches by detecting unobserved and imported cases, as well as allowing multiple introductions of the pathogen. Because of its generality, we believe this method will become a tool of choice for the analysis of densely sampled disease outbreaks, and will form a rigorous framework for subsequent methodological developments. PMID:24465202

Detection of infectious disease outbreaks in twenty-two fragile states, 2000-2010: a systematic review

PubMed Central

2011-01-01

Fragile states are home to a sixth of the world's population, and their populations are particularly vulnerable to infectious disease outbreaks. Timely surveillance and control are essential to minimise the impact of these outbreaks, but little evidence is published about the effectiveness of existing surveillance systems. We did a systematic review of the circumstances (mode) of detection of outbreaks occurring in 22 fragile states in the decade 2000-2010 (i.e. all states consistently meeting fragility criteria during the timeframe of the review), as well as time lags from onset to detection of these outbreaks, and from detection to further events in their timeline. The aim of this review was to enhance the evidence base for implementing infectious disease surveillance in these complex, resource-constrained settings, and to assess the relative importance of different routes whereby outbreak detection occurs. We identified 61 reports concerning 38 outbreaks. Twenty of these were detected by existing surveillance systems, but 10 detections occurred following formal notifications by participating health facilities rather than data analysis. A further 15 outbreaks were detected by informal notifications, including rumours. There were long delays from onset to detection (median 29 days) and from detection to further events (investigation, confirmation, declaration, control). Existing surveillance systems yielded the shortest detection delays when linked to reduced barriers to health care and frequent analysis and reporting of incidence data. Epidemic surveillance and control appear to be insufficiently timely in fragile states, and need to be strengthened. Greater reliance on formal and informal notifications is warranted. Outbreak reports should be more standardised and enable monitoring of surveillance systems' effectiveness. PMID:21861869

'Outbreak Gold Standard' selection to provide optimized threshold for infectious diseases early-alert based on China Infectious Disease Automated-alert and Response System.

PubMed

Wang, Rui-Ping; Jiang, Yong-Gen; Zhao, Gen-Ming; Guo, Xiao-Qin; Michael, Engelgau

2017-12-01

The China Infectious Disease Automated-alert and Response System (CIDARS) was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control (CDC) at all levels in China. In the CIDARS, thresholds are determined using the "Mean+2SD‟ in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the "Mean +2SD‟ method to the performance of 5 novel algorithms to select optimal "Outbreak Gold Standard (OGS)‟ and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The "Mean+2SD‟, C1, C2, moving average (MA), seasonal model (SM), and cumulative sum (CUSUM) algorithms were applied. Outbreak signals for the predicted value (Px) were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A (chickenpox and mumps), TYPE B (influenza and rubella) and TYPE C [hand foot and mouth disease (HFMD) and scarlet fever]. Optimized thresholds for chickenpox (P 55 ), mumps (P 50 ), influenza (P 40 , P 55 , and P 75 ), rubella (P 45 and P 75 ), HFMD (P 65 and P 70 ), and scarlet fever (P 75 and P 80 ) were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types.

Integrated Application of Random Forest and Artificial Neural Network Algorithms to Predict Viral Contamination in Coastal Waters

NASA Astrophysics Data System (ADS)

Shamkhali Chenar, S.; Deng, Z.

2017-12-01

Pathogenic viruses pose a significant public health threat and economic losses to shellfish industry in the coastal environment. Norovirus is a contagious virus and the leading cause of epidemic gastroenteritis following consumption of oysters harvested from sewage-contaminated waters. While it is challenging to detect noroviruses in coastal waters due to the lack of sensitive and routine diagnostic methods, machine learning techniques are allowing us to prevent or at least reduce the risks by developing effective predictive models. This study attempts to develop an algorithm between historical norovirus outbreak reports and environmental parameters including water temperature, solar radiation, water level, salinity, precipitation, and wind. For this purpose, the Random Forests statistical technique was utilized to select relevant environmental parameters and their various combinations with different time lags controlling the virus distribution in oyster harvesting areas along the Louisiana Coast. An Artificial Neural Networks (ANN) approach was then presented to predict the outbreaks using a final set of input variables. Finally, a sensitivity analysis was conducted to evaluate relative importance and contribution of the input variables to the model output. Findings demonstrated that the developed model was capable of reproducing historical oyster norovirus outbreaks along the Louisiana Coast with the overall accuracy of than 99.83%, demonstrating the efficacy of the model. Moreover, the increase in water temperature, solar radiation, water level, and salinity, and the decrease in wind and rainfall are associated with the reduction in the model-predicted risk of norovirus outbreak according to sensitivity analysis results. In conclusion, the presented machine learning approach provided reliable tools for predicting potential norovirus outbreaks and could be used for early detection of possible outbreaks and reduce the risk of norovirus to public health and the seafood industry.

Factors determining dengue outbreak in Malaysia.

PubMed

Ahmad, Rohani; Suzilah, Ismail; Wan Najdah, Wan Mohamad Ali; Topek, Omar; Mustafakamal, Ibrahim; Lee, Han Lim

2018-01-01

A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.

Three faces of node importance in network epidemiology: Exact results for small graphs

NASA Astrophysics Data System (ADS)

Holme, Petter

2017-12-01

We investigate three aspects of the importance of nodes with respect to susceptible-infectious-removed (SIR) disease dynamics: influence maximization (the expected outbreak size given a set of seed nodes), the effect of vaccination (how much deleting nodes would reduce the expected outbreak size), and sentinel surveillance (how early an outbreak could be detected with sensors at a set of nodes). We calculate the exact expressions of these quantities, as functions of the SIR parameters, for all connected graphs of three to seven nodes. We obtain the smallest graphs where the optimal node sets are not overlapping. We find that (i) node separation is more important than centrality for more than one active node, (ii) vaccination and influence maximization are the most different aspects of importance, and (iii) the three aspects are more similar when the infection rate is low.

An epidemic of East Coast fever on a dairy farm in eastern Tanzania.

PubMed

Msami, H M

2001-04-13

During the period August-September 1995, an epidemic of East Coast fever occurred at a dairy farm in Morogoro region of eastern Tanzania. Due to an intensive dipping scheme since 1970, a very unstable endemic status had been established in the animals. A breakdown in the dipping scheme caused a major disease outbreak; the dip wash was not changed for 18 months prior to the outbreak and dipping continued in a dip wash of unknown strength. There was also a delay in detecting the disease at an early stage. In total, 180 out of 432 (42%) of the cattle at the farm died--resulting in a loss of Tshs. 26,330,000 (US$ 42,879). The attack risk was nearly 77%. The outbreak points to the importance of adopting integrated strategies for the control of ticks and tick-borne diseases.

Cost of dengue outbreaks: literature review and country case studies

PubMed Central

2013-01-01

Background Dengue disease surveillance and vector surveillance are presumed to detect dengue outbreaks at an early stage and to save – through early response activities – resources, and reduce the social and economic impact of outbreaks on individuals, health systems and economies. The aim of this study is to unveil evidence on the cost of dengue outbreaks. Methods Economic evidence on dengue outbreaks was gathered by conducting a literature review and collecting information on the costs of recent dengue outbreaks in 4 countries: Peru, Dominican Republic, Vietnam, and Indonesia. The literature review distinguished between costs of dengue illness including cost of dengue outbreaks, cost of interventions and cost-effectiveness of interventions. Results Seventeen publications on cost of dengue showed a large range of costs from 0.2 Million US$ in Venezuela to 135.2 Million US$ in Brazil. However, these figures were not standardized to make them comparable. Furthermore, dengue outbreak costs are calculated differently across the publications, and cost of dengue illness is used interchangeably with cost of dengue outbreaks. Only one paper from Australia analysed the resources saved through active dengue surveillance. Costs of vector control interventions have been reported in 4 studies, indicating that the costs of such interventions are lower than those of actual outbreaks. Nine papers focussed on the cost-effectiveness of dengue vaccines or dengue vector control; they do not provide any direct information on cost of dengue outbreaks, but their modelling methodologies could guide future research on cost-effectiveness of national surveillance systems. The country case studies – conducted in very different geographic and health system settings - unveiled rough estimates for 2011 outbreak costs of: 12 million US$ in Vietnam, 6.75 million US$ in Indonesia, 4.5 million US$ in Peru and 2.8 million US$ in Dominican Republic (all in 2012 US$). The proportions of the different cost components (vector control; surveillance; information, education and communication; direct medical and indirect costs), as percentage of total costs, differed across the respective countries. Resources used for dengue disease control and treatment were country specific. Conclusions The evidence so far collected further confirms the methodological challenges in this field: 1) to define technically dengue outbreaks (what do we measure?) and 2) to measure accurately the costs in prospective field studies (how do we measure?). Currently, consensus on the technical definition of an outbreak is sought through the International Research Consortium on Dengue Risk Assessment, Management and Surveillance (IDAMS). Best practice guidelines should be further developed, also to improve the quality and comparability of cost study findings. Modelling the costs of dengue outbreaks and validating these models through field studies should guide further research. PMID:24195519

Cost of dengue outbreaks: literature review and country case studies.

PubMed

Stahl, Hans-Christian; Butenschoen, Vicki Marie; Tran, Hien Tinh; Gozzer, Ernesto; Skewes, Ronald; Mahendradhata, Yodi; Runge-Ranzinger, Silvia; Kroeger, Axel; Farlow, Andrew

2013-11-06

Dengue disease surveillance and vector surveillance are presumed to detect dengue outbreaks at an early stage and to save--through early response activities--resources, and reduce the social and economic impact of outbreaks on individuals, health systems and economies. The aim of this study is to unveil evidence on the cost of dengue outbreaks. Economic evidence on dengue outbreaks was gathered by conducting a literature review and collecting information on the costs of recent dengue outbreaks in 4 countries: Peru, Dominican Republic, Vietnam, and Indonesia. The literature review distinguished between costs of dengue illness including cost of dengue outbreaks, cost of interventions and cost-effectiveness of interventions. Seventeen publications on cost of dengue showed a large range of costs from 0.2 Million US$ in Venezuela to 135.2 Million US$ in Brazil. However, these figures were not standardized to make them comparable. Furthermore, dengue outbreak costs are calculated differently across the publications, and cost of dengue illness is used interchangeably with cost of dengue outbreaks. Only one paper from Australia analysed the resources saved through active dengue surveillance. Costs of vector control interventions have been reported in 4 studies, indicating that the costs of such interventions are lower than those of actual outbreaks. Nine papers focussed on the cost-effectiveness of dengue vaccines or dengue vector control; they do not provide any direct information on cost of dengue outbreaks, but their modelling methodologies could guide future research on cost-effectiveness of national surveillance systems.The country case studies--conducted in very different geographic and health system settings - unveiled rough estimates for 2011 outbreak costs of: 12 million US$ in Vietnam, 6.75 million US$ in Indonesia, 4.5 million US$ in Peru and 2.8 million US$ in Dominican Republic (all in 2012 US$). The proportions of the different cost components (vector control; surveillance; information, education and communication; direct medical and indirect costs), as percentage of total costs, differed across the respective countries. Resources used for dengue disease control and treatment were country specific. The evidence so far collected further confirms the methodological challenges in this field: 1) to define technically dengue outbreaks (what do we measure?) and 2) to measure accurately the costs in prospective field studies (how do we measure?). Currently, consensus on the technical definition of an outbreak is sought through the International Research Consortium on Dengue Risk Assessment, Management and Surveillance (IDAMS). Best practice guidelines should be further developed, also to improve the quality and comparability of cost study findings. Modelling the costs of dengue outbreaks and validating these models through field studies should guide further research.

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-05-12

In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

The epidemiological characteristics and genetic diversity of dengue virus during the third largest historical outbreak of dengue in Guangdong, China, in 2014.

PubMed

Sun, Jiufeng; Wu, De; Zhou, Huiqiong; Zhang, Huan; Guan, Dawei; He, Xiang; Cai, Songwu; Ke, Changwen; Lin, Jinyan

2016-01-01

The third largest historical outbreak of dengue occurred during July to December 2014, in 20 of 21 cities of Guangdong, China. The epidemiological and molecular characteristics of the introduction, expansion and phylogeny of the DENV isolates involved in this outbreak were investigated. A combination analyses of epidemiological characteristics and genetic diversity of dengue virus was performed in this study. In total, 45,236 cases and 6 fatalities were reported. Unemployed individuals, retirees and retailers were the most affected populations. A total of 6024 cases were verified to have DENV infections by nucleic acid detection, of which 5947, 74 and 3 were confirmed to have DENV-1, -2, and -3 infections, respectively. Phylogenetic analyses of DENV-1 isolates were assigned into three genotypes (I, IV, and V). Genotype V was the predominant genotype that likely originated from Singapore. The DENV-2 isolates were assigned to the Cosmopolitan and Asian I genotypes. A unique DENV-3 isolate (genotype III) shared high similarity with isolates obtained from Guangdong in 2013. A combination analyses demonstrated the multiple geographical origins of this outbreak, and highlight the importance of early detection, the case management and vector surveillance for preventing further dengue epidemics in Guangdong. Copyright © 2015 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Outbreaks-of Ebola virus disease in the West African sub-region.

PubMed

Osungbade, K O; Oni, A A

2014-06-01

Five West African countries, including Nigeria are currently experiencing the largest, most severe, most complex outbreak of Ebola virus disease in history. This paper provided a chronology of outbreaks of Ebola virus disease in the West African sub-region and provided an update on efforts at containing the present outbreak. Literature from Pubmed (MEDLINE), AJOL, Google Scholar and Cochrane database were reviewed. Outbreaks of Ebola, virus disease had frequently occurred mainly in Central and East African countries. Occasional outbreaks reported from outside of Africa were due to laboratory contamination and imported monkeys in quarantine facilities. The ongoing outbreak in West Africa is the largest and first in the sub-region; the number of suspected cases and deaths from this single current outbreak is already about three times the total of all cases and deaths from previous known outbreaks in 40 years. Prevention and control efforts are hindered not only by lack of a known vaccine and virus-specific treatment, but also by weak health systems, poor sanitation, poor personal hygiene and cultural beliefs and practices, including myths and misconceptions about Ebola virus disease--all of which are prevalent in affected countries. Constrained by this situation, the World Health Organisation departed from the global standard and recommended the use of not yet proven treatments to treat or prevent the disease in humans on ethical and evidential grounds. The large number of people affected by the present outbreak in West Africa and the high case-fatality rate calls for accelerated evaluation and development of the investigational medical interventions for life saving and curbing the epidemic. Meanwhile, existing interventions such as early detection and isolation, contact tracing and monitoring, and adherence to rigorous procedures of infection prevention and control should be intensified.

Probabilistic commodity-flow-based focusing of monitoring activities to facilitate early detection of Phytophthora ramorum outbreaks

Treesearch

Steven C. McKelvey; William D. Smith; Frank Koch

2012-01-01

This project summary describes a probabilistic model developed with funding support from the Forest Health Monitoring Program of the Forest Service, U.S. Department of Agriculture (BaseEM Project SO-R-08-01). The model has been implemented in SODBuster, a standalone software package developed using the Java software development kit from Sun Microsystems.

An assessment of public health surveillance of Zika virus infection and potentially associated outcomes in Latin America.

PubMed

Bautista, Leonelo E; Herrera, Víctor M

2018-05-24

We evaluated whether outbreaks of Zika virus (ZIKV) infection, newborn microcephaly, and Guillain-Barré syndrome (GBS) in Latin America may be detected through current surveillance systems, and how cases detected through surveillance may increase health care burden. We estimated the sensitivity and specificity of surveillance case definitions using published data. We assumed a 10% ZIKV infection risk during a non-outbreak period and hypothetical increases in risk during an outbreak period. We used sensitivity and specificity estimates to correct for non-differential misclassification, and calculated a misclassification-corrected relative risk comparing both periods. To identify the smallest hypothetical increase in risk resulting in a detectable outbreak we compared the misclassification-corrected relative risk to the relative risk corresponding to the upper limit of the endemic channel (mean + 2 SD). We also estimated the proportion of false positive cases detected during the outbreak. We followed the same approach for microcephaly and GBS, but assumed the risk of ZIKV infection doubled during the outbreak, and ZIKV infection increased the risk of both diseases. ZIKV infection outbreaks were not detectable through non-serological surveillance. Outbreaks were detectable through serologic surveillance if infection risk increased by at least 10%, but more than 50% of all cases were false positive. Outbreaks of severe microcephaly were detected if ZIKV infection increased prevalence of this condition by at least 24.0 times. When ZIKV infection did not increase the prevalence of severe microcephaly, 34.7 to 82.5% of all cases were false positive, depending on diagnostic accuracy. GBS outbreaks were detected if ZIKV infection increased the GBS risk by at least seven times. For optimal GBS diagnosis accuracy, the proportion of false positive cases ranged from 29 to 54% and from 45 to 56% depending on the incidence of GBS mimics. Current surveillance systems have a low probability of detecting outbreaks of ZIKV infection, severe microcephaly, and GBS, and could result in significant increases in health care burden, due to the detection of large numbers of false positive cases. In view of these limitations, Latin American countries should consider alternative options for surveillance.

West Nile encephalitis outbreak in Kerala, India, 2011.

PubMed

Anukumar, B; Sapkal, Gajanan N; Tandale, Babasheb V; Balasubramanian, R; Gangale, Daya

2014-09-01

An outbreak of acute encephalitis syndrome (AES) was reported in Kerala in India in May 2011. The outbreak features were unusual in terms of seasonality, geographical distribution, age group, and clinical manifestations in comparison to the epidemiological features of Japanese Encephalitis. To detect the etiology of the acute encephalitis syndrome outbreak. Investigation of outbreak was undertaken by collection of brief clinical history and epidemiological details along with the specimens for viral diagnosis. The serum/CSF samples (patients=208) received from the sentinel hospitals were subjected to IgM capture ELISA and RT-PCR specific for Japanese encephalitis (JE) virus and West Nile virus (WNV). The JE/WN IgM positive samples were further tested by serum neutralization assay for the presence of JE and WNV specific neutralizing antibody. Most of the affected patients were aged above 15 years. No spatial clustering of the disease was noticed. Cases were observed in premonsoon and early monsoon season and in JE non-endemic area of Kerala. A total of 47 patient samples were positive for in-house JE IgM capture ELISA and WNV IgM capture ELISA. Serum neutralization assay result revealed that 32 of 42 (76.19%) sera were positive for WNV neutralization antibodies. WNV was isolated from a clinical specimen. Phylogenetic analysis of WNV envelope gene revealed 99% homology with Russian Lineage 1 WNV. West Nile virus (WNV) etiology was confirmed by virus isolation and detection of virus specific antibody from clinical specimen. Phylogenetic analysis grouped the current strain in lineage I West Nile virus. Copyright © 2014 Elsevier B.V. All rights reserved.

Early detection of West Nile virus in France: quantitative assessment of syndromic surveillance system using nervous signs in horses.

PubMed

Faverjon, C; Vial, F; Andersson, M G; Lecollinet, S; Leblond, A

2017-04-01

West Nile virus (WNV) is a growing public health concern in Europe and there is a need to develop more efficient early detection systems. Nervous signs in horses are considered to be an early indicator of WNV and, using them in a syndromic surveillance system, might be relevant. In our study, we assessed whether or not data collected by the passive French surveillance system for the surveillance of equine diseases can be used routinely for the detection of WNV. We tested several pre-processing methods and detection algorithms based on regression. We evaluated system performances using simulated and authentic data and compared them to those of the surveillance system currently in place. Our results show that the current detection algorithm provided similar performances to those tested using simulated and real data. However, regression models can be easily and better adapted to surveillance objectives. The detection performances obtained were compatible with the early detection of WNV outbreaks in France (i.e. sensitivity 98%, specificity >94%, timeliness 2·5 weeks and around four false alarms per year) but further work is needed to determine the most suitable alarm threshold for WNV surveillance in France using cost-efficiency analysis.

Rapid Identification of a Cooling Tower-Associated Legionnaires' Disease Outbreak Supported by Polymerase Chain Reaction Testing of Environmental Samples, New York City, 2014-2015.

PubMed

Benowitz, Isaac; Fitzhenry, Robert; Boyd, Christopher; Dickinson, Michelle; Levy, Michael; Lin, Ying; Nazarian, Elizabeth; Ostrowsky, Belinda; Passaretti, Teresa; Rakeman, Jennifer; Saylors, Amy; Shamoonian, Elena; Smith, Terry-Ann; Balter, Sharon

2018-04-01

We investigated an outbreak of eight Legionnaires' disease cases among persons living in an urban residential community of 60,000 people. Possible environmental sources included two active cooling towers (air-conditioning units for large buildings) <1 km from patient residences, a market misting system, a community-wide water system used for heating and cooling, and potable water. To support a timely public health response, we used real-time polymerase chain reaction (PCR) to identify Legionella DNA in environmental samples within hours of specimen collection. We detected L. pneumophila serogroup 1 DNA only at a power plant cooling tower, supporting the decision to order remediation before culture results were available. An isolate from a power plant cooling tower sample was indistinguishable from a patient isolate by pulsed-field gel electrophoresis, suggesting the cooling tower was the outbreak source. PCR results were available <1 day after sample collection, and culture results were available as early as 5 days after plating. PCR is a valuable tool for identifying Legionella DNA in environmental samples in outbreak settings.

Hepatitis A outbreak in British Columbia, Canada: the roles of established surveillance, consumer loyalty cards and collaboration, February to May 2012.

PubMed

Swinkels, H M; Kuo, M; Embree, G; Andonov, A; Henry, B; Buxton, J A

2014-05-08

Non-travel-related hepatitis A is rare in Canada. We describe a hepatitis A outbreak investigation in British Columbia in February to May 2012 in which exposure history was collected from nine confirmed non-travel-related cases. Suspected foods were tested for hepatitis A virus (HAV): a frozen fruit blend was identified as a common exposure for six of the nine cases using supermarket loyalty cards. Consumption of the product was confirmed in each case. Genetic analysis confirmed HAV genotype 1B in the six exposed cases. Of the three non-exposed cases, the virus could not be genotyped for two of them; the virus from the other case was found to be genotype 1A and this case was therefore not considered part of the outbreak. HAV was detected by PCR from pomegranate seeds, a component of the identified frozen fruit blend. Historically low levels of HAV infection in British Columbia triggered early recognition of the outbreak. Loyalty card histories facilitated product identification and a trace-back investigation implicated imported pomegranate seeds.

Event-based surveillance of food- and waterborne diseases in Europe: urgent inquiries (outbreak alerts) during 2008 to 2013.

PubMed

Gossner, C M; de Jong, B; Hoebe, C J; Coulombier, D

2015-06-25

During 2008 to 2013, 215 outbreak alerts, also known as 'urgent inquiries' (UI), for food- and waterborne diseases were launched in Europe, the majority of them (135; 63%) being related to salmonellosis. For 110 (51%) UI, a potential food vehicle of infection was identified, with vegetables being the most reported category (34;31%). A total of 28% (n = 60) of the outbreaks reported had an international dimension, involving at least two countries (mean: 4; standard deviation: 2; range:2–14). Participating countries posted 2,343 messages(initial posts and replies, excluding updates), with a median of 11 messages per urgent inquiry (range:1–28). Of 60 multicountry UI, 50 involved between two and four countries. The UI allowed early detection of multicountry outbreaks, facilitated the identification of the suspected vehicles and consequently contributed to the timely implementation of control measures. The introduction of an epidemic intelligence information system platform in 2010 has strengthened the role of the Food- and Waterborne Diseases and Zoonoses network in facilitating timely exchange of information between public health authorities of the participating countries.

Rapid Detection and Characterization of Emerging Foreign Animal Disease Pathogens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaing, C.

To best safeguard human and animal health requires early detection and characterization of disease events. This must include effective surveillance for emerging infectious diseases. Both deliberate and natural outbreaks have enormous economic and public health impacts, and can present serious threats to national security. In this project, we developed novel next generation detection technologies to protect the agricultural economy and biosecurity. The first technology is a multiplexed assay to simultaneously detection 10 swine viral and bacterial pathogens. The second one is the Lawrence Livermore Microbial Detection Array (LLMDA) which can detect more than 10,000 microbial species including 4219 viruses, 5367more » bacteria, 265 fungi, 117 protozoa and 293 archaea. We analyzed a series of swine clinical samples from past disease events to demonstrate the utility of the assays for faster and cheaper detection of emerging and foreign animal disease pathogens, and their utility as s routine diagnosis and surveillance tool. A second goal of the study is to better understand mechanisms of African swine fever virus (ASFV) infection in pigs to aid the development of countermeasures and diagnostics. There is no vaccine available for ASF. ASF outbreak is on the rise on several European countries. Though ASF is not currently in the U.S., a potential outbreak in the U.S. would be detrimental to the swine industry and the US agricultural economy. We pursued a genome-wide approach to characterize the pig immune responses after ASFV infection. We used RNA sequencing and bioinformatics methods to identify genes and pathways that are affected during ASF infection. We have identified a list of most differentially expressed genes that are in the immune response pathways.« less

Limits to Forecasting Precision for Outbreaks of Directly Transmitted Diseases

PubMed Central

Drake, John M

2006-01-01

Background Early warning systems for outbreaks of infectious diseases are an important application of the ecological theory of epidemics. A key variable predicted by early warning systems is the final outbreak size. However, for directly transmitted diseases, the stochastic contact process by which outbreaks develop entails fundamental limits to the precision with which the final size can be predicted. Methods and Findings I studied how the expected final outbreak size and the coefficient of variation in the final size of outbreaks scale with control effectiveness and the rate of infectious contacts in the simple stochastic epidemic. As examples, I parameterized this model with data on observed ranges for the basic reproductive ratio (R 0) of nine directly transmitted diseases. I also present results from a new model, the simple stochastic epidemic with delayed-onset intervention, in which an initially supercritical outbreak (R 0 > 1) is brought under control after a delay. Conclusion The coefficient of variation of final outbreak size in the subcritical case (R 0 < 1) will be greater than one for any outbreak in which the removal rate is less than approximately 2.41 times the rate of infectious contacts, implying that for many transmissible diseases precise forecasts of the final outbreak size will be unattainable. In the delayed-onset model, the coefficient of variation (CV) was generally large (CV > 1) and increased with the delay between the start of the epidemic and intervention, and with the average outbreak size. These results suggest that early warning systems for infectious diseases should not focus exclusively on predicting outbreak size but should consider other characteristics of outbreaks such as the timing of disease emergence. PMID:16435887

Strategies in Ebola virus disease (EVD) diagnostics at the point of care

PubMed Central

Coarsey, Chad T.; Esiobu, Nwadiuto; Narayanan, Ramswamy; Pavlovic, Mirjana; Shafiee, Hadi; Asghar, Waseem

2017-01-01

Ebola virus disease (EVD) is a devastating, highly infectious illness with a high mortality rate. The disease is endemic to regions of Central and West Africa, where there is limited laboratory infrastructure and trained staff. The recent 2014 West African EVD outbreak has been unprecedented in case numbers and fatalities, and has proven that such regional outbreaks can become a potential threat to global public health, as it became the source for the subsequent transmission events in Spain and the USA. The urgent need for rapid and affordable means of detecting Ebola is crucial to control the spread of EVD and prevent devastating fatalities. Current diagnostic techniques include molecular diagnostics and other serological and antigen detection assays; which can be time-consuming, laboratory-based, often require trained personnel and specialized equipment. In this review, we discuss the various Ebola detection techniques currently in use, and highlight the potential future directions pertinent to the development and adoption of novel point-of-care diagnostic tools. Finally, a case is made for the need to develop novel microfluidic technologies and versatile rapid detection platforms for early detection of EVD. PMID:28440096

A novel measles outbreak control strategy in the Netherlands in 2013-2014 using a national electronic immunization register: A study of early MMR uptake and its determinants.

PubMed

Nic Lochlainn, Laura M; Woudenberg, Tom; van Lier, Alies; Zonnenberg, Irmgard; Philippi, Marvin; de Melker, Hester E; Hahné, Susan J M

2017-10-13

During a large measles outbreak in the Netherlands in 2013-2014, infants aged 6-14months living in municipalities with low (<90%) measles-mumps-rubella (MMR) coverage were individually invited for an early MMR using the national electronic immunization register, Præventis. We estimated uptake of early MMR prior to and during the 2013-2014 outbreak and assessed determinants for early MMR vaccination. We obtained vaccination records from Præventis, and defined early MMR as vaccination before 415days (13months) of age. A multi-level multivariable logistic regression model, restricted to infants with three diphtheria-pertussis-tetanus-polio (DPTP) vaccinations was used to examine the association between early MMR uptake and sex, parents' country of birth, socioeconomic status (SES; at postcode level) and voting proportions for the Reformed Political Party (SGP; at municipal level), used as a proxy for religious objections towards vaccination. In the 29 municipalities with low MMR coverage, uptake of early MMR was 0.5-2.2% prior to the outbreak. Between July 2013 and March 2014, 5,800 (57%) invited infants received an early MMR. Among infants with three DPTP, 70% received an early MMR. Only 1% of infants without prior DPTP received an early MMR. Lower early MMR uptake was associated with a higher SGP voter-ship (OR 0.89 per 5% increase, 95%CI 0.83-0.96), parents' with unknown country of birth (OR 0.66 95%CI 0.47-0.93) and compared with very high SES, high SES had significantly lower early MMR uptake (OR 0.66 95%CI 0.50-0.87). This is the first study describing use of Præventis during an outbreak and to assess determinants of early MMR uptake. More than half of invited infants obtained an early MMR. SES, parents' with unknown country of birth and religious objections towards vaccination were found to be associated with lower early MMR uptake. In future outbreaks, these determinants could be used to tailor intervention strategies. Copyright © 2017. Published by Elsevier Ltd.

A socio-psychological investigation into limitations and incentives concerning reporting a clinically suspect situation aimed at improving early detection of classical swine fever outbreaks.

PubMed

Elbers, A R W; Gorgievski-Duijvesteijn, M J; van der Velden, P G; Loeffen, W L A; Zarafshani, K

2010-04-21

The aim of this study was to identify limitations and incentives in reporting clinically suspect situations, possibly caused by classical swine fever (CSF), to veterinary authorities with the ultimate aim to facilitate early detection of CSF outbreaks. Focus group sessions were held with policy makers from the veterinary authorities, and representatives of veterinary practitioners and pig farmer unions. Personal interviews with a small group of pig farmers and practitioners were held to check limitations raised and solutions proposed during the focus group sessions. An electronic questionnaire was mailed to pig farmers and practitioners to investigate perceptions and attitudes with respect to clinically suspect situations possibly caused by CSF. After triangulating the responses of veterinary authorities, veterinary practitioners and farmers, six themes emerged across all groups: (1) lack of knowledge on the early signs of CSF; (2) guilt, shame and prejudice; (3) negative opinion on control measures; (4) dissatisfaction with post-reporting procedures; (5) lack of trust in government bodies; (6) uncertainty and lack of transparency of reporting procedures. The following solutions to facilitate early detection of CSF were put forward: (a) development of a clinical decision-support system for vets and farmers, in order to get faster diagnosis and detection of CSF; (b) possibility to submit blood samples directly to the reference laboratory to exclude CSF in a clinical situation with non-specific clinical signs, without isolation of the farm and free of charge for the individual farmer; (c) decrease social and economic consequences of reporting CSF, for example by improving the public opinion on first reports; (d) better schooling of veterinary officers to deal with emotions and insecurity of farmers in the process after reporting; (e) better communication of rules and regulations, where to report, what will happen next; (f) up-to-date website with information and visual material of the clinical signs of CSF. Copyright 2009 Elsevier B.V. All rights reserved.

[Study of tuberculosis outbreaks reported in Catalonia, 1998-2002].

PubMed

Bran, Carlos M; Caylá, Joan A; Domínguez, Angela; Camps, Neus; Godoy, Pere; Orcau, Angels; Barrabeig, Irene; Alcaide, José; Altet, Neus; Alvarez, Pep

2006-06-01

To analyze the characteristics of tuberculosis outbreaks declared under vigilance programs in Catalonia. Descriptive study of outbreaks from 1998 through 2002 for which reports were available. An outbreak was defined as 3 or more associated cases appearing within a year. For 2 health care regions, outbreaks for which there were full surveillance reports with contact tracing were compared to outbreaks identified but which had not been fully reported. Twenty-seven outbreaks were analyzed. Nineteen (70%) occurred within families. A total of 22 outbreaks were declared upon identification of the true index case and 5 upon detection of secondary cases. The mean annual incidence of outbreaks was 0.40/100,100 inhabitants. Most cases were in males 16 to 40 years of age and involved cavitary lesions and a clinically significant diagnostic delay. Twenty-seven outbreaks caused 69 secondary cases. A longer diagnostic delay was seen to correspond to a larger number of secondary cases (P=.08). In the 2 health care regions analyzed, full surveillance reports with contact tracing were issued for 2 of the 14 outbreaks detected (14.4%). Tuberculosis outbreaks are common but investigative follow-up is scarce. The size of the outbreak is related to the length of diagnostic delay. Rapid diagnosis, contact tracing, and the issuance of a public health report should be priorities in all outbreaks detected.

Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks

PubMed Central

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A.; Fowler, James H.

2014-01-01

Recent research has focused on the monitoring of global–scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global–scale networks. PMID:24718030

Using friends as sensors to detect global-scale contagious outbreaks.

PubMed

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A; Fowler, James H

2014-01-01

Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global-scale networks.

A Bayesian system to detect and characterize overlapping outbreaks.

PubMed

Aronis, John M; Millett, Nicholas E; Wagner, Michael M; Tsui, Fuchiang; Ye, Ye; Ferraro, Jeffrey P; Haug, Peter J; Gesteland, Per H; Cooper, Gregory F

2017-09-01

Outbreaks of infectious diseases such as influenza are a significant threat to human health. Because there are different strains of influenza which can cause independent outbreaks, and influenza can affect demographic groups at different rates and times, there is a need to recognize and characterize multiple outbreaks of influenza. This paper describes a Bayesian system that uses data from emergency department patient care reports to create epidemiological models of overlapping outbreaks of influenza. Clinical findings are extracted from patient care reports using natural language processing. These findings are analyzed by a case detection system to create disease likelihoods that are passed to a multiple outbreak detection system. We evaluated the system using real and simulated outbreaks. The results show that this approach can recognize and characterize overlapping outbreaks of influenza. We describe several extensions that appear promising. Copyright © 2017 Elsevier Inc. All rights reserved.

Application of syndromic surveillance on routinely collected cattle reproduction and milk production data for the early detection of outbreaks of Bluetongue and Schmallenberg viruses.

PubMed

Veldhuis, Anouk; Brouwer-Middelesch, Henriëtte; Marceau, Alexis; Madouasse, Aurélien; Van der Stede, Yves; Fourichon, Christine; Welby, Sarah; Wever, Paul; van Schaik, Gerdien

2016-02-01

This study aimed to evaluate the use of routinely collected reproductive and milk production data for the early detection of emerging vector-borne diseases in cattle in the Netherlands and the Flanders region of Belgium (i.e., the northern part of Belgium). Prospective space-time cluster analyses on residuals from a model on milk production were carried out to detect clusters of reduced milk yield. A CUSUM algorithm was used to detect temporal aberrations in model residuals of reproductive performance models on two indicators of gestation length. The Bluetongue serotype-8 (BTV-8) epidemics of 2006 and 2007 and the Schmallenberg virus (SBV) epidemic of 2011 were used as case studies to evaluate the sensitivity and timeliness of these methods. The methods investigated in this study did not result in a more timely detection of BTV-8 and SBV in the Netherlands and BTV-8 in Belgium given the surveillance systems in place when these viruses emerged. This could be due to (i) the large geographical units used in the analyses (country, region and province level), and (ii) the high level of sensitivity of the surveillance systems in place when these viruses emerged. Nevertheless, it might be worthwhile to use a syndromic surveillance system based on non-specific animal health data in real-time alongside regular surveillance, to increase the sense of urgency and to provide valuable quantitative information for decision makers in the initial phase of an emerging disease outbreak. Copyright © 2015 Elsevier B.V. All rights reserved.

Outbreak of E. coli O157:H7 associated with lettuce served at fast food chains in the Maritimes and Ontario, Canada, Dec 2012

PubMed Central

Tataryn, J; Morton, V; Cutler, J; McDonald, L; Whitfield, Y; Billard, B; Gad, RR; Hexemer, A

2014-01-01

Background Identification and control of multi-jurisdictional foodborne illness outbreaks can be complex because of their multidisciplinary nature and the number of investigative partners involved. Objective To describe the multi-jurisdictional outbreak response to an E. coli O157:H7 outbreak in Canada that highlights the importance of early notification and collaboration and the value of centralized interviewing. Methods Investigators from local, provincial and federal jurisdictions, using a national outbreak response protocol to clarify roles and responsibilities and facilitate collaboration, conducted a rapid investigation that included centralized re-interview of cases, descriptive methods, binomial probability, and traceback findings to identify the source of the outbreak. Results There were 31 laboratory confirmed cases identified in New Brunswick, Nova Scotia, and Ontario. Thirteen cases (42%) were hospitalized and one case (3%) developed hemolytic uremic syndrome; there were no deaths. Due to early notification a coordinated investigation was initiated before laboratory subtyping was available. Re-interview of cases identified 10 cases who had not initially reported exposure to the source of the outbreak. Less than one week after the Outbreak Investigation Coordinating Committee was formed, consumption of shredded lettuce from a fast food chain was identified as the likely source of the illnesses and the implicated importer/processor initiated a precautionary recall the same day. Conclusion This outbreak investigation highlights the importance of early notification, prompt re-interviewing and collaboration to rapidly identify the source of an outbreak. PMID:29769900

Effective surveillance strategies following a potential classical Swine Fever incursion in a remote wild pig population in North-Western Australia.

PubMed

Leslie, E; Cowled, B; Graeme Garner, M; Toribio, J-A L M L; Ward, M P

2014-10-01

Early disease detection and efficient methods of proving disease freedom can substantially improve the response to incursions of important transboundary animal diseases in previously free regions. We used a spatially explicit, stochastic disease spread model to simulate the spread of classical swine fever in wild pigs in a remote region of northern Australia and to assess the performance of disease surveillance strategies to detect infection at different time points and to delineate the size of the resulting outbreak. Although disease would likely be detected, simple random sampling was suboptimal. Radial and leapfrog sampling improved the effectiveness of surveillance at various stages of the simulated disease incursion. This work indicates that at earlier stages, radial sampling can reduce epidemic length and achieve faster outbreak delineation and control, but at later stages leapfrog sampling will outperform radial sampling in relation to supporting faster disease control with a less-extensive outbreak area. Due to the complexity of wildlife population dynamics and group behaviour, a targeted approach to surveillance needs to be implemented for the efficient use of resources and time. Using a more situation-based surveillance approach and accounting for disease distribution and the time period over which an epidemic has occurred is the best way to approach the selection of an appropriate surveillance strategy. © 2013 Blackwell Verlag GmbH.

Data-driven approach of CUSUM algorithm in temporal aberrant event detection using interactive web applications.

PubMed

Li, Ye; Whelan, Michael; Hobbs, Leigh; Fan, Wen Qi; Fung, Cecilia; Wong, Kenny; Marchand-Austin, Alex; Badiani, Tina; Johnson, Ian

2016-06-27

In 2014/2015, Public Health Ontario developed disease-specific, cumulative sum (CUSUM)-based statistical algorithms for detecting aberrant increases in reportable infectious disease incidence in Ontario. The objective of this study was to determine whether the prospective application of these CUSUM algorithms, based on historical patterns, have improved specificity and sensitivity compared to the currently used Early Aberration Reporting System (EARS) algorithm, developed by the US Centers for Disease Control and Prevention. A total of seven algorithms were developed for the following diseases: cyclosporiasis, giardiasis, influenza (one each for type A and type B), mumps, pertussis, invasive pneumococcal disease. Historical data were used as baseline to assess known outbreaks. Regression models were used to model seasonality and CUSUM was applied to the difference between observed and expected counts. An interactive web application was developed allowing program staff to directly interact with data and tune the parameters of CUSUM algorithms using their expertise on the epidemiology of each disease. Using these parameters, a CUSUM detection system was applied prospectively and the results were compared to the outputs generated by EARS. The outcome was the detection of outbreaks, or the start of a known seasonal increase and predicting the peak in activity. The CUSUM algorithms detected provincial outbreaks earlier than the EARS algorithm, identified the start of the influenza season in advance of traditional methods, and had fewer false positive alerts. Additionally, having staff involved in the creation of the algorithms improved their understanding of the algorithms and improved use in practice. Using interactive web-based technology to tune CUSUM improved the sensitivity and specificity of detection algorithms.

One-Health Simulation Modelling: Assessment of Control Strategies Against the Spread of Influenza between Swine and Human Populations Using NAADSM.

PubMed

Dorjee, S; Revie, C W; Poljak, Z; McNab, W B; McClure, J T; Sanchez, J

2016-04-01

Simulation models implemented using a range of parameters offer a useful approach to identifying effective disease intervention strategies. The objective of this study was to investigate the effects of key control strategies to mitigate the simultaneous spread of influenza among and between swine and human populations. We used the pandemic H1N1 2009 virus as a case study. The study population included swine herds (488 herds) and households-of-people (29,707 households) within a county in Ontario, Canada. Households were categorized as: (i) rural households with swine workers, (ii) rural households without swine workers and (iii) urban households without swine workers. Seventy-two scenarios were investigated based on a combination of the parameters of speed of detection and control strategies, such as quarantine strategy, effectiveness of movement restriction and ring vaccination strategy, all assessed at three levels of transmissibility of the virus at the swine-human interface. Results showed that the speed of detection of the infected units combined with the quarantine strategy had the largest impact on the duration and size of outbreaks. A combination of fast to moderate speed of the detection (where infected units were detected within 5-10 days since first infection) and quarantine of the detected units alone contained the outbreak within the swine population in most of the simulated outbreaks. Ring vaccination had no added beneficial effect. In conclusion, our study suggests that the early detection (and therefore effective surveillance) and effective quarantine had the largest impact in the control of the influenza spread, consistent with earlier studies. To our knowledge, no study had previously assessed the impact of the combination of different intervention strategies involving the simultaneous spread of influenza between swine and human populations. © 2014 Blackwell Verlag GmbH.

Sustained outbreak of measles in New South Wales, 2012: risks for measles elimination in Australia.

PubMed

Najjar, Zeina; Hope, Kirsty; Clark, Penelope; Nguyen, Oanh; Rosewell, Alexander; Conaty, Stephen

2014-01-01

On 7 April 2012, a recently returned traveller from Thailand to Australia was confirmed to have measles. An outbreak of measles subsequently occurred in the state of New South Wales, prompting a sustained and coordinated response by public health authorities. The last confirmed case presented on 29 November 2012. This report describes the outbreak and its characteristics. Cases were investigated following Australian protocols, including case interviews and assessment of contacts for post-exposure prophylaxis. Of the 168 cases identified, most occurred in south-western and western Sydney (92.9%, n = 156). Notable features of this outbreak were the disproportionately high number of cases in the 10-19-year-old age group (29.2%, n = 49), the overrepresentation among people of Pacific Islander descent (21.4%, n = 36) and acquisition in health-care facilities (21.4%, n = 36). There were no reported cases of encephalitis and no deaths. This was the largest outbreak of measles in Australia since 1997. Its occurrence highlights the need to maintain vigilant surveillance systems for early detection and containment of measles cases and to maintain high population immunity to measles through routine childhood immunization. Vaccination campaigns targeting susceptible groups may also be necessary to sustain Australia's measles elimination status.

Comparison of Statistical Algorithms for the Detection of Infectious Disease Outbreaks in Large Multiple Surveillance Systems

PubMed Central

Farrington, C. Paddy; Noufaily, Angela; Andrews, Nick J.; Charlett, Andre

2016-01-01

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s. Changes to the statistical algorithm at the heart of the system were proposed and the purpose of this paper is to compare two new algorithms with the original algorithm. Test data to evaluate performance are created from weekly counts of the number of cases of each of more than 2000 diseases over a twenty-year period. The time series of each disease is separated into one series giving the baseline (background) disease incidence and a second series giving disease outbreaks. One series is shifted forward by twelve months and the two are then recombined, giving a realistic series in which it is known where outbreaks have been added. The metrics used to evaluate performance include a scoring rule that appropriately balances sensitivity against specificity and is sensitive to variation in probabilities near 1. In the context of disease surveillance, a scoring rule can be adapted to reflect the size of outbreaks and this was done. Results indicate that the two new algorithms are comparable to each other and better than the algorithm they were designed to replace. PMID:27513749

A methodological framework for the evaluation of syndromic surveillance systems: a case study of England.

PubMed

Colón-González, Felipe J; Lake, Iain R; Morbey, Roger A; Elliot, Alex J; Pebody, Richard; Smith, Gillian E

2018-04-24

Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.

Rapid Diagnosis of Ebola Hemorrhagic Fever by Reverse Transcription-PCR in an Outbreak Setting and Assessment of Patient Viral Load as a Predictor of Outcome

PubMed Central

Towner, Jonathan S.; Rollin, Pierre E.; Bausch, Daniel G.; Sanchez, Anthony; Crary, Sharon M.; Vincent, Martin; Lee, William F.; Spiropoulou, Christina F.; Ksiazek, Thomas G.; Lukwiya, Mathew; Kaducu, Felix; Downing, Robert; Nichol, Stuart T.

2004-01-01

The largest outbreak on record of Ebola hemorrhagic fever (EHF) occurred in Uganda from August 2000 to January 2001. The outbreak was centered in the Gulu district of northern Uganda, with secondary transmission to other districts. After the initial diagnosis of Sudan ebolavirus by the National Institute for Virology in Johannesburg, South Africa, a temporary diagnostic laboratory was established within the Gulu district at St. Mary's Lacor Hospital. The laboratory used antigen capture and reverse transcription-PCR (RT-PCR) to diagnose Sudan ebolavirus infection in suspect patients. The RT-PCR and antigen-capture diagnostic assays proved very effective for detecting ebolavirus in patient serum, plasma, and whole blood. In samples collected very early in the course of infection, the RT-PCR assay could detect ebolavirus 24 to 48 h prior to detection by antigen capture. More than 1,000 blood samples were collected, with multiple samples obtained from many patients throughout the course of infection. Real-time quantitative RT-PCR was used to determine the viral load in multiple samples from patients with fatal and nonfatal cases, and these data were correlated with the disease outcome. RNA copy levels in patients who died averaged 2 log10 higher than those in patients who survived. Using clinical material from multiple EHF patients, we sequenced the variable region of the glycoprotein. This Sudan ebolavirus strain was not derived from either the earlier Boniface (1976) or Maleo (1979) strain, but it shares a common ancestor with both. Furthermore, both sequence and epidemiologic data are consistent with the outbreak having originated from a single introduction into the human population. PMID:15047846

Leapfrog diagnostics: Demonstration of a broad spectrum pathogen identification platform in a resource-limited setting

PubMed Central

2012-01-01

Background Resource-limited tropical countries are home to numerous infectious pathogens of both human and zoonotic origin. A capability for early detection to allow rapid outbreak containment and prevent spread to non-endemic regions is severely impaired by inadequate diagnostic laboratory capacity, the absence of a “cold chain” and the lack of highly trained personnel. Building up detection capacity in these countries by direct replication of the systems existing in developed countries is not a feasible approach and instead requires “leapfrogging” to the deployment of the newest diagnostic systems that do not have the infrastructure requirements of systems used in developed countries. Methods A laboratory for molecular diagnostics of infectious agents was established in Bo, Sierra Leone with a hybrid solar/diesel/battery system to ensure stable power supply and a satellite modem to enable efficient communication. An array of room temperature stabilization and refrigeration technologies for reliable transport and storage of reagents and biological samples were also tested to ensure sustainable laboratory supplies for diagnostic assays. Results The laboratory demonstrated its operational proficiency by conducting an investigation of a suspected avian influenza outbreak at a commercial poultry farm at Bo using broad range resequencing microarrays and real time RT-PCR. The results of the investigation excluded influenza viruses as a possible cause of the outbreak and indicated a link between the outbreak and the presence of Klebsiella pneumoniae. Conclusions This study demonstrated that by application of a carefully selected set of technologies and sufficient personnel training, it is feasible to deploy and effectively use a broad-range infectious pathogen detection technology in a severely resource-limited setting. PMID:22759725

Controlling the last known cluster of Ebola virus disease - Liberia, January-February 2015.

PubMed

Nyenswah, Tolbert; Fallah, Mosoka; Sieh, Sonpon; Kollie, Karsor; Badio, Moses; Gray, Alvin; Dilah, Priscilla; Shannon, Marnijina; Duwor, Stanley; Ihekweazu, Chikwe; Cordier-Lassalle, Thierry; Cordier-Lasalle, Thierry; Shinde, Shivam A; Hamblion, Esther; Davies-Wayne, Gloria; Ratnesh, Murugan; Dye, Christopher; Yoder, Jonathan S; McElroy, Peter; Hoots, Brooke; Christie, Athalia; Vertefeuille, John; Olsen, Sonja J; Laney, A Scott; Neal, Joyce J; Yaemsiri, Sirin; Navin, Thomas R; Coulter, Stewart; Pordell, Paran; Lo, Terrence; Kinkade, Carl; Mahoney, Frank

2015-05-15

As one of the three West African countries highly affected by the 2014-2015 Ebola virus disease (Ebola) epidemic, Liberia reported approximately 10,000 cases. The Ebola epidemic in Liberia was marked by intense urban transmission, multiple community outbreaks with source cases occurring in patients coming from the urban areas, and outbreaks in health care facilities (HCFs). This report, based on data from routine case investigations and contact tracing, describes efforts to stop the last known chain of Ebola transmission in Liberia. The index patient became ill on December 29, 2014, and the last of 21 associated cases was in a patient admitted into an Ebola treatment unit (ETU) on February 18, 2015. The chain of transmission was stopped because of early detection of new cases; identification, monitoring, and support of contacts in acceptable settings; effective triage within the health care system; and rapid isolation of symptomatic contacts. In addition, a "sector" approach, which divided Montserrado County into geographic units, facilitated the ability of response teams to rapidly respond to community needs. In the final stages of the outbreak, intensive coordination among partners and engagement of community leaders were needed to stop transmission in densely populated Montserrado County. A companion report describes the efforts to enhance infection prevention and control efforts in HCFs. After February 19, no additional clusters of Ebola cases have been detected in Liberia. On May 9, the World Health Organization declared the end of the Ebola outbreak in Liberia.

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

PubMed Central

2011-01-01

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia. PMID:21388561

Monitoring over-the-counter medication sales for early detection of disease outbreaks--New York City.

PubMed

Das, Debjani; Metzger, K; Heffernan, R; Balter, S; Weiss, D; Mostashari, F

2005-08-26

Over-the-counter (OTC) medications are frequently used during the initial phase of illness, and increases in their sales might serve as an early indicator of communitywide disease outbreaks. Since August 2002, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) has tracked OTC medication sales to enhance detection of natural and intentional infectious disease outbreaks. This report describes the surveillance system and presents results from retrospective analyses and a comparison between citywide trends in OTC medication sales and emergency department (ED) visits. Sales data transmitted daily to DOHMH are categorized into two groups: influenza-like illness (ILI), which includes cough and influenza medications, and gastrointestinal illness (GI), which includes major brand and generic antidiarrheals. Cyclical, linear regression models were used to identify significant (p<0.05) increases in the daily ratio of ILI to analgesics sales (analgesics are used as a denominator in the absence of total sales). Daily and weekly average ratios of GI to analgesic sales were analyzed. Citywide trends in OTC ILI and GI medication sales were compared with ED visits for fever/influenza and diarrhea syndromes. Citywide ILI drug sales were highest during annual influenza epidemics and elevated during spring and fall allergy seasons, similar to trends in the ED fever/influenza syndrome. ILI sales did not consistently provide earlier warning than the ED system of communitywide influenza. GI drug sales increased during the fall and peaked during early winter and after the blackout of August 2003. Unlike ED diarrheal visits, GI medication sales did not substantially increase during late winter (February-March). Citywide OTC medication sales can provide indications of communitywide illness, including annual influenza epidemics. Antidiarrheal medication sales were more sensitive to increases in GI caused by norovirus and influenza than illness caused by rotavirus. OTC medication sales can be considered as an adjunct syndromic surveillance system but might not be as sensitive as ED systems.

Automated detection of hospital outbreaks: A systematic review of methods.

PubMed

Leclère, Brice; Buckeridge, David L; Boëlle, Pierre-Yves; Astagneau, Pascal; Lepelletier, Didier

2017-01-01

Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results. We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies. Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%. Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.

Environmental swabs as a tool in norovirus outbreak investigation, including outbreaks on cruise ships.

PubMed

Boxman, Ingeborg L A; Dijkman, Remco; te Loeke, Nathalie A J M; Hägele, Geke; Tilburg, Jeroen J H C; Vennema, Harry; Koopmans, Marion

2009-01-01

In this study, we investigated whether environmental swabs can be used to demonstrate the presence of norovirus in outbreak settings. First, a procedure was set up based on viral RNA extraction using guanidium isothiocyanate buffer and binding of nucleic acids to silica. Subsequently, environmental swabs were taken at 23 Dutch restaurants and four cruise ships involved in outbreaks of gastroenteritis. Outbreaks were selected based on clinical symptoms consistent with viral gastroenteritis and time between consumption of suspected food and onset of clinical symptoms (>12 h). Norovirus RNA was demonstrated by real-time reverse transcriptase PCR in 51 of 86 (59%) clinical specimens from 12 of 14 outbreaks (86%), in 13 of 90 (14%) food specimens from 4 of 18 outbreaks (22%), and in 48 of 119 (40%) swab specimens taken from 14 of 27 outbreaks (52%). Positive swab samples agreed with positive clinical samples in seven outbreaks, showing identical sequences. Furthermore, norovirus was detected on swabs taken from kitchen and bathroom surfaces in five outbreaks in which no clinical samples were collected and two outbreaks with negative fecal samples. The detection rate was highest for outbreaks associated with catered meals and lowest for restaurant-associated outbreaks. The use of environmental swabs may be a useful tool in addition to testing of food and clinical specimens, particularlywhen viral RNA is detected on surfaces used for food preparation.

Automated biosurveillance data from England and Wales, 1991-2011.

PubMed

Enki, Doyo G; Noufaily, Angela; Garthwaite, Paul H; Andrews, Nick J; Charlett, André; Lane, Chris; Farrington, C Paddy

2013-01-01

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991-2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity.

Automated Biosurveillance Data from England and Wales, 1991–2011

PubMed Central

Enki, Doyo G.; Noufaily, Angela; Garthwaite, Paul H.; Andrews, Nick J.; Charlett, André; Lane, Chris

2013-01-01

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991–2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity. PMID:23260848

Swine Influenza A Outbreak, Fort Dix, New Jersey, 1976

PubMed Central

Top, Franklin H.; Hodder, Richard A.; Russell, Philip K.

2006-01-01

In early 1976, the novel A/New Jersey/76 (Hsw1N1) influenza virus caused severe respiratory illness in 13 soldiers with 1 death at Fort Dix, New Jersey. Since A/New Jersey was similar to the 1918–1919 pandemic virus, rapid outbreak assessment and enhanced surveillance were initiated. A/New Jersey virus was detected only from January 19 to February 9 and did not spread beyond Fort Dix. A/Victoria/75 (H3N2) spread simultaneously, also caused illness, and persisted until March. Up to 230 soldiers were infected with the A/New Jersey virus. Rapid recognition of A/New Jersey, swift outbreak assessment, and enhanced surveillance resulted from excellent collaboration between Fort Dix, New Jersey Department of Health, Walter Reed Army Institute of Research, and Center for Disease Control personnel. Despite efforts to define the events at Fort Dix, many questions remain unanswered, including the following: Where did A/New Jersey come from? Why did transmission stop? PMID:16494712

Clinical Update on Dengue, Chikungunya, and Zika: What We Know at the Time of Article Submission.

PubMed

Liu, Liang E; Dehning, Meaghan; Phipps, Ashley; Swienton, Ray E; Harris, Curtis A; Klein, Kelly R

2017-06-01

Mosquito-borne diseases pose a threat to individual health and population health on both a local and a global level. The threat is even more exaggerated during disasters, whether manmade or environmental. With the recent Zika virus outbreak, it is important to highlight other infections that can mimic the Zika virus and to better understand what can be done as public health officials and health care providers. This article reviews the recent literature on the Zika virus as well as chikungunya virus and dengue virus. The present findings give a better understanding of the similarities and differences between the 3 infections in terms of their characteristics, clinical presentation, diagnosis methodology, and treatment and what can be done for prevention. Additionally, the article highlights a special population that has received much focus in the latest outbreak, the pregnant individual. Education and training are instrumental in controlling the outbreak, and early detection can be lifesaving. (Disaster Med Public Health Preparedness. 2017;11:290-299).

Evidence of a louse-borne outbreak involving typhus in Douai, 1710-1712 during the war of Spanish succession.

PubMed

Nguyen-Hieu, Tung; Aboudharam, Gérard; Signoli, Michel; Rigeade, Catherine; Drancourt, Michel; Raoult, Didier

2010-10-27

The new field of paleomicrobiology allows past outbreaks to be identified by testing dental pulp of human remains with PCR. We identified a mass grave in Douai, France dating from the early XVIII(th) century. This city was besieged during the European war of Spanish succession. We tested dental pulp from 1192 teeth (including 40 from Douai) by quantitative PCR (qPCR) for R. prowazekii and B. quintana. We also used ultra-sensitive suicide PCR to detect R. prowazekii and genotyped positive samples. In the Douai remains, we identified one case of B. quintana infection (by qPCR) and R. prowazekii (by suicide PCR) in 6/21 individuals (29%). The R. prowazekii was genotype B, a genotype previously found in a Spanish isolate obtained in the first part of the XX(th) century. Louse-borne outbreaks were raging during the XVIII(th) century; our results support the hypothesis that typhus was imported into Europe by Spanish soldiers from America.

Evidence of a Louse-Borne Outbreak Involving Typhus in Douai, 1710-1712 during the War of Spanish Succession

PubMed Central

Nguyen-Hieu, Tung; Aboudharam, Gérard; Signoli, Michel; Rigeade, Catherine; Drancourt, Michel; Raoult, Didier

2010-01-01

Background The new field of paleomicrobiology allows past outbreaks to be identified by testing dental pulp of human remains with PCR. Methods We identified a mass grave in Douai, France dating from the early XVIIIth century. This city was besieged during the European war of Spanish succession. We tested dental pulp from 1192 teeth (including 40 from Douai) by quantitative PCR (qPCR) for R. prowazekii and B. quintana. We also used ultra-sensitive suicide PCR to detect R. prowazekii and genotyped positive samples. Results and Discussion In the Douai remains, we identified one case of B. quintana infection (by qPCR) and R. prowazekii (by suicide PCR) in 6/21 individuals (29%). The R. prowazekii was genotype B, a genotype previously found in a Spanish isolate obtained in the first part of the XXth century. Conclusion Louse-borne outbreaks were raging during the XVIIIth century; our results support the hypothesis that typhus was imported into Europe by Spanish soldiers from America. PMID:21060879

Time series modeling for syndromic surveillance.

PubMed

Reis, Ben Y; Mandl, Kenneth D

2003-01-23

Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization.

Descriptive epidemiology of a cholera outbreak in Kaduna State, Northwest Nigeria, 2014.

PubMed

Sule, Ibrahim Baffa; Yahaya, Mohammed; Aisha, Abubakar Ahmed; Zainab, Ahmed Datti; Ummulkhulthum, Bajoga; Nguku, Patrick

2017-01-01

Cholera is an acute gastrointestinal infection caused by Vibrio cholerae, which may lead to severe dehydration and death if not treated. This analysis is aimed at highlighting the magnitude, pattern and trend of cholera outbreak that occurred in Kaduna State in 2014. We obtained the 2014 cholera line-list from the Kaduna State Disease Surveillance and Notification officer (DSNO). We described the outbreaks in time, place and person using Epi-info 7 and Health Mapper. A total of 1468 case-patients and 54 deaths were recorded, giving a case fatality rate (CFR) of 3.68%. Female case-patients were 809(55.08%). The median age for case-patients was 15 years, with an age range of 0.04-90 years. Age specific case fatality rate (ASCFR) is highest among the > 60 years. Seven (30%) out of the 23 local government areas (LGAs) in Kaduna State were affected by the cholera outbreak in 2014. Igabi LGA has the highest attack rate (150.46 per 100,000 population) while Chikun LGA has the lowest attack rate (12.22 per 100,000 population). Chikun LGA records the highest CFR (17.54%). Cholera infection spread across LGAs sharing the same borders. The outbreak started from the first epidemic week of 2014 and lasted over 33 weeks. Our analysis revealed a protracted cholera outbreak that gradually increases in magnitude throughout the first half of 2014 and spread within contiguous LGAs. We recommended the strengthening of the state's diseases surveillance system towards timely detection and early response to disease outbreaks in the future.

The 2012 Madeira dengue outbreak: epidemiological determinants and future epidemic potential.

PubMed

Lourenço, José; Recker, Mario

2014-08-01

Dengue, a vector-borne viral disease of increasing global importance, is classically associated with tropical and sub-tropical regions around the world. Urbanisation, globalisation and climate trends, however, are facilitating the geographic spread of its mosquito vectors, thereby increasing the risk of the virus establishing itself in previously unaffected areas and causing large-scale epidemics. On 3 October 2012, two autochthonous dengue infections were reported within the Autonomous Region of Madeira, Portugal. During the following seven months, this first 'European' dengue outbreak caused more than 2000 local cases and 81 exported cases to mainland Europe. Here, using an ento-epidemiological mathematical framework, we estimate that the introduction of dengue to Madeira occurred around a month before the first official cases, during the period of maximum influx of airline travel, and that the naturally declining temperatures of autumn were the determining factor for the outbreak's demise in early December 2012. Using key estimates, together with local climate data, we further propose that there is little support for dengue endemicity on this island, but a high potential for future epidemic outbreaks when seeded between May and August-a period when detection of imported cases is crucial for Madeira's public health planning.

The 2012 Madeira Dengue Outbreak: Epidemiological Determinants and Future Epidemic Potential

PubMed Central

Lourenço, José; Recker, Mario

2014-01-01

Dengue, a vector-borne viral disease of increasing global importance, is classically associated with tropical and sub-tropical regions around the world. Urbanisation, globalisation and climate trends, however, are facilitating the geographic spread of its mosquito vectors, thereby increasing the risk of the virus establishing itself in previously unaffected areas and causing large-scale epidemics. On 3 October 2012, two autochthonous dengue infections were reported within the Autonomous Region of Madeira, Portugal. During the following seven months, this first ‘European’ dengue outbreak caused more than 2000 local cases and 81 exported cases to mainland Europe. Here, using an ento-epidemiological mathematical framework, we estimate that the introduction of dengue to Madeira occurred around a month before the first official cases, during the period of maximum influx of airline travel, and that the naturally declining temperatures of autumn were the determining factor for the outbreak's demise in early December 2012. Using key estimates, together with local climate data, we further propose that there is little support for dengue endemicity on this island, but a high potential for future epidemic outbreaks when seeded between May and August—a period when detection of imported cases is crucial for Madeira's public health planning. PMID:25144749

A university outbreak of gastroenteritis due to a small round-structured virus. Application of molecular diagnostics to identify the etiologic agent and patterns of transmission.

PubMed

Kilgore, P E; Belay, E D; Hamlin, D M; Noel, J S; Humphrey, C D; Gary, H E; Ando, T; Monroe, S S; Kludt, P E; Rosenthal, D S; Freeman, J; Glass, R I

1996-04-01

An epidemiologic investigation of a gastroenteritis outbreak in December 1994 indicated that salad consumption during lunch was linked with illness on 2 days (5 December: odds ratio [OR]=3.1, 95% confidence interval [CI]=2.0-5.0; 6 December: OR=3.1, 95% CI=1.9-4.9). Single stool or vomitus specimens from ill students and staff (case-patients) were examined for bacterial and viral pathogens. Small round-structured viruses (SRSVs) were detected by electron microscopy in stool specimens from 9 of 19 case-patients and in vomitus specimens from 3 of 5 case-patients. By reverse transcription-polymerase chain reaction (RT-PCR), the SRSVs were shown to be G-2/P2-B type strain. The nucleotide sequences of RT-PCR products from vomitus and stool specimens of ill students were identical to stool specimens from the ill salad chef. These findings suggest that a single SRSV strain was the etiologic agent in the outbreak that was possibly transmitted to students through consumption of contaminated salad. Epidemiologic investigation in conjunction with molecular diagnostics may enable early identification of sources of infection and improve outbreak control.

Rapid Identification of a Cooling Tower-Associated Legionnaires’ Disease Outbreak Supported by Polymerase Chain Reaction Testing of Environmental Samples, New York City, 2014–2015

PubMed Central

Benowitz, Isaac; Fitzhenry, Robert; Boyd, Christopher; Dickinson, Michelle; Levy, Michael; Lin, Ying; Nazarian, Elizabeth; Ostrowsky, Belinda; Passaretti, Teresa; Rakeman, Jennifer; Saylors, Amy; Shamoonian, Elena; Smith, Terry-Ann; Balter, Sharon

2018-01-01

We investigated an outbreak of eight Legionnaires’ disease cases among persons living in an urban residential community of 60,000 people. Possible environmental sources included two active cooling towers (air-conditioning units for large buildings) <1 km from patient residences, a market misting system, a community-wide water system used for heating and cooling, and potable water. To support a timely public health response, we used real-time polymerase chain reaction (PCR) to identify Legionella DNA in environmental samples within hours of specimen collection. We detected L. pneumophila serogroup 1 DNA only at a power plant cooling tower, supporting the decision to order remediation before culture results were available. An isolate from a power plant cooling tower sample was indistinguishable from a patient isolate by pulsed-field gel electrophoresis, suggesting the cooling tower was the outbreak source. PCR results were available <1 day after sample collection, and culture results were available as early as 5 days after plating. PCR is a valuable tool for identifying Legionella DNA in environmental samples in outbreak settings. PMID:29780175

Lack of chicken adaptation of newly emergent Eurasian H5N8 and reassortant H5N2 high pathogenicity avian influenza viruses in the U.S. is consistent with restricted poultry outbreaks in the Pacific flyway during 2014-2015.

PubMed

Bertran, Kateri; Swayne, David E; Pantin-Jackwood, Mary J; Kapczynski, Darrell R; Spackman, Erica; Suarez, David L

2016-07-01

In 2014-2015, the U.S. experienced an unprecedented outbreak of Eurasian clade 2.3.4.4 H5 highly pathogenic avian influenza (HPAI) virus, initially affecting mainly wild birds and few backyard and commercial poultry premises. To better model the outbreak, the pathogenesis and transmission dynamics of representative Eurasian H5N8 and reassortant H5N2 clade 2.3.4.4 HPAI viruses detected early in the North American outbreak were investigated in chickens. High mean chicken infectious doses and lack of seroconversion in survivors indicated the viruses were poorly chicken adapted. Pathobiological features were consistent with HPAI virus infection, although the delayed appearance of lesions, longer mean death times, and reduced replication in endothelial cells differed from features of most other Eurasian H5N1 HPAI viruses. Although these initial U.S. H5 HPAI viruses had reduced adaptation and transmissibility in chickens, multi-generational passage in poultry could generate poultry adapted viruses with higher infectivity and transmissibility. Copyright © 2016. Published by Elsevier Inc.

Outbreaks of influenza-like illness in long-term care facilities in Winnipeg, Canada.

PubMed

Mahmud, Salaheddin M; Thompson, Laura H; Nowicki, Deborah L; Plourde, Pierre J

2013-11-01

Outbreaks of influenza-like illness (ILI) are common in long-term care facilities (LTCFs) and result in significant morbidity and mortality among residents. We describe patterns of reported ILI outbreaks in LTCFs in Winnipeg, Canada, and examine LTCF and outbreak characteristics that influence the clinical outcomes of these outbreaks. We analyzed the electronic records of all ILI outbreaks reported by LTCFs in Winnipeg from 2003 to 2011. Outbreak duration, ILI attack rates among staff and residents, and residents' death rates were calculated by presumed viral etiology, staff vaccination rates, type of influenza chemoprophylaxis used, and time to notification to public health. Of a total of 154 reported outbreaks, most (N=80) were attributed to influenza, and these outbreaks tended to have higher attack and death rates among LTCF residents compared with outbreaks caused by other respiratory viruses (12) or those of unknown etiology (62). About 92% of residents and 38% of staff of the average LTCFs were vaccinated. Chemoprophylaxis was used in 57·5% of influenza outbreaks. Regardless of presumed viral etiology, outbreaks reported within 3 days of onset ended sooner and had lower attack and mortality rates among residents. Influenza-like illness outbreaks still occur among highly immunized LTCF residents, so in addition to vaccination of staff and residents, it is important to maintain competent infection control practices. Early identification and notification to public health authorities and possibly early initiation of control measures could improve clinical outcomes of ILI outbreaks. © 2012 John Wiley & Sons Ltd.

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014.

PubMed

Levin-Rector, Alison; Nivin, Beth; Yeung, Alice; Fine, Annie D; Greene, Sharon K

2015-08-01

Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda.

PubMed

Nyakarahuka, Luke; Ayebare, Samuel; Mosomtai, Gladys; Kankya, Clovice; Lutwama, Julius; Mwiine, Frank Norbert; Skjerve, Eystein

2017-09-05

Uganda has reported eight outbreaks caused by filoviruses between 2000 to 2016, more than any other country in the world. We used species distribution modeling to predict where filovirus outbreaks are likely to occur in Uganda to help in epidemic preparedness and surveillance. The MaxEnt software, a machine learning modeling approach that uses presence-only data was used to establish filovirus - environmental relationships. Presence-only data for filovirus outbreaks were collected from the field and online sources. Environmental covariates from Africlim that have been downscaled to a nominal resolution of 1km x 1km were used. The final model gave the relative probability of the presence of filoviruses in the study area obtained from an average of 100 bootstrap runs. Model evaluation was carried out using Receiver Operating Characteristic (ROC) plots. Maps were created using ArcGIS 10.3 mapping software. We showed that bats as potential reservoirs of filoviruses are distributed all over Uganda. Potential outbreak areas for Ebola and Marburg virus disease were predicted in West, Southwest and Central parts of Uganda, which corresponds to bat distribution and previous filovirus outbreaks areas. Additionally, the models predicted the Eastern Uganda region and other areas that have not reported outbreaks before to be potential outbreak hotspots. Rainfall variables were the most important in influencing model prediction compared to temperature variables. Despite the limitations in the prediction model due to lack of adequate sample records for outbreaks, especially for the Marburg cases, the models provided risk maps to the Uganda surveillance system on filovirus outbreaks. The risk maps will aid in identifying areas to focus the filovirus surveillance for early detection and responses hence curtailing a pandemic. The results from this study also confirm previous findings that suggest that filoviruses are mainly limited by the amount of rainfall received in an area.

Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda

PubMed Central

Nyakarahuka, Luke; Ayebare, Samuel; Mosomtai, Gladys; Kankya, Clovice; Lutwama, Julius; Mwiine, Frank Norbert; Skjerve, Eystein

2017-01-01

Introduction: Uganda has reported eight outbreaks caused by filoviruses between 2000 to 2016, more than any other country in the world. We used species distribution modeling to predict where filovirus outbreaks are likely to occur in Uganda to help in epidemic preparedness and surveillance. Methods: The MaxEnt software, a machine learning modeling approach that uses presence-only data was used to establish filovirus – environmental relationships. Presence-only data for filovirus outbreaks were collected from the field and online sources. Environmental covariates from Africlim that have been downscaled to a nominal resolution of 1km x 1km were used. The final model gave the relative probability of the presence of filoviruses in the study area obtained from an average of 100 bootstrap runs. Model evaluation was carried out using Receiver Operating Characteristic (ROC) plots. Maps were created using ArcGIS 10.3 mapping software. Results: We showed that bats as potential reservoirs of filoviruses are distributed all over Uganda. Potential outbreak areas for Ebola and Marburg virus disease were predicted in West, Southwest and Central parts of Uganda, which corresponds to bat distribution and previous filovirus outbreaks areas. Additionally, the models predicted the Eastern Uganda region and other areas that have not reported outbreaks before to be potential outbreak hotspots. Rainfall variables were the most important in influencing model prediction compared to temperature variables. Conclusions: Despite the limitations in the prediction model due to lack of adequate sample records for outbreaks, especially for the Marburg cases, the models provided risk maps to the Uganda surveillance system on filovirus outbreaks. The risk maps will aid in identifying areas to focus the filovirus surveillance for early detection and responses hence curtailing a pandemic. The results from this study also confirm previous findings that suggest that filoviruses are mainly limited by the amount of rainfall received in an area. PMID:29034123

Acute Chagas outbreaks: molecular and biological features of Trypanosoma cruzi isolates, and clinical aspects of acute cases in Santander, Colombia.

PubMed

Díaz, Martha Lucía; Leal, Sandra; Mantilla, Julio César; Molina-Berríos, Alfredo; López-Muñoz, Rodrigo; Solari, Aldo; Escobar, Patricia; González Rugeles, Clara Isabel

2015-11-26

Outbreaks of acute Chagas disease associated with oral transmission are easily detected nowadays with trained health personnel in areas of low endemicity, or in which the vector transmission has been interrupted. Given the biological and genetic diversity of Trypanosoma cruzi, the high morbidity, mortality, and the observed therapeutic failure, new characteristics of these outbreaks need to be addressed at different levels, both in Trypanosoma cruzi as in patient response. The aim of this work was to evaluate the patient's features involved in six outbreaks of acute Chagas disease which occurred in Santander, Colombia, and the characteristics of Trypanosoma cruzi clones isolated from these patients, to establish the potential relationship between the etiologic agent features with host behavior. The clinical, pathological and epidemiological aspects of outbreaks were analyzed. In addition, Trypanosoma cruzi clones were biologically characterized both in vitro and in vivo, and the susceptibility to the classical trypanocidal drugs nifurtimox and benznidazole was evaluated. Trypanosoma cruzi clones were genotyped by means of mini-exon intergenic spacer and cytochrome b genes sequencing. All clones were DTU I, and based on the mini-exon intergenic spacer, belong to two genotypes: G2 related with sub-urban, and G11 with rural outbreaks. Girón outbreak clones with higher susceptibility to drugs presented G2 genotype and C/T transition in Cyt b. The outbreaks affected mainly young population (±25.9 years), and the mortality rate was 10 %. The cardiac tissue showed intense inflammatory infiltrate, myocardial necrosis and abundant amastigote nests. However, although the gastrointestinal tissue was congestive, no inflammation or parasites were observed. Although all clones belong to DTU I, two intra-DTU genotypes were found with the sequencing of the mini-exon intergenic spacer, however there is no strict correlation between genetic groups, the cycles of the parasite or the clinical forms of the disease. Trypanosoma cruzi clones from Girón with higher sensitivity to nifurtimox presented a particular G2 genotype and C/T transition in Cyt b. When the diagnosis was early, the patients responded well to antichagasic treatment, which highlights the importance of diagnosis and treatment early to prevent fatal outcomes associated with these acute episodes.

Refining historical limits method to improve disease cluster detection, New York City, New York, USA.

PubMed

Levin-Rector, Alison; Wilson, Elisha L; Fine, Annie D; Greene, Sharon K

2015-02-01

Since the early 2000s, the Bureau of Communicable Disease of the New York City Department of Health and Mental Hygiene has analyzed reportable infectious disease data weekly by using the historical limits method to detect unusual clusters that could represent outbreaks. This method typically produced too many signals for each to be investigated with available resources while possibly failing to signal during true disease outbreaks. We made method refinements that improved the consistency of case inclusion criteria and accounted for data lags and trends and aberrations in historical data. During a 12-week period in 2013, we prospectively assessed these refinements using actual surveillance data. The refined method yielded 74 signals, a 45% decrease from what the original method would have produced. Fewer and less biased signals included a true citywide increase in legionellosis and a localized campylobacteriosis cluster subsequently linked to live-poultry markets. Future evaluations using simulated data could complement this descriptive assessment.

Review of syndromic surveillance: implications for waterborne disease detection

PubMed Central

Berger, Magdalena; Shiau, Rita; Weintraub, June M

2006-01-01

Syndromic surveillance is the gathering of data for public health purposes before laboratory or clinically confirmed information is available. Interest in syndromic surveillance has increased because of concerns about bioterrorism. In addition to bioterrorism detection, syndromic surveillance may be suited to detecting waterborne disease outbreaks. Theoretical benefits of syndromic surveillance include potential timeliness, increased response capacity, ability to establish baseline disease burdens, and ability to delineate the geographical reach of an outbreak. This review summarises the evidence gathered from retrospective, prospective, and simulation studies to assess the efficacy of syndromic surveillance for waterborne disease detection. There is little evidence that syndromic surveillance mitigates the effects of disease outbreaks through earlier detection and response. Syndromic surveillance should not be implemented at the expense of traditional disease surveillance, and should not be relied upon as a principal outbreak detection tool. The utility of syndromic surveillance is dependent on alarm thresholds that can be evaluated in practice. Syndromic data sources such as over the counter drug sales for detection of waterborne outbreaks should be further evaluated. PMID:16698988

Automated detection of hospital outbreaks: A systematic review of methods

PubMed Central

Buckeridge, David L.; Lepelletier, Didier

2017-01-01

Objectives Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results. Methods We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies. Results Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%. Conclusion Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results. PMID:28441422

Multiple outbreaks of Norwalk-like virus gastro-enteritis associated with a Mediterranean-style restaurant.

PubMed

Marshall, J A; Yuen, L K; Catton, M G; Gunesekere, I C; Wright, P J; Bettelheim, K A; Griffith, J M; Lightfoot, D; Hogg, G G; Gregory, J; Wilby, R; Gaston, J

2001-02-01

The role of diverse infectious agents, particularly Norwalk-like viruses (NLV), in three successive gastro-enteritis outbreaks in one setting (a restaurant) was evaluated. Methods included standard bacteriological tests, specific tests for Escherichia coli, tests for verocytotoxins, electron microscopy (EM) for viruses and reverse transcription-PCR (RT-PCR) methodology for NLV. No pathogenic bacteria were detected. Verocytotoxin genes, although detected by PCR in the first outbreak, could not be confirmed in the E. coli isolated, so they did not appear to be of significance. NLV was the main agent detected in each of the three outbreaks. DNA sequencing and phylogenetic analysis of the amplified products obtained from the RT-PCR positive specimens indicated that only one NLV strain was involved in each outbreak, but the NLV strains responsible for the three outbreaks were different from each other. PCR technology for detection of NLV proved highly sensitive, but failed to detect one specimen which was positive by EM. The restaurant associated with the outbreaks is a Mediterranean-style restaurant where food from a common platter is typically eaten with fingers. The findings indicate that NLV was introduced by guests or staff and was not due to a long-term reservoir within the setting.

Early detection of perceived risk among users of a UK travel health website compared with internet search activity and media coverage during the 2015–2016 Zika virus outbreak: an observational study

PubMed Central

Petersen, Jakob; Simons, Hilary; Patel, Dipti; Freedman, Joanne

2017-01-01

Objectives The Zika virus (ZIKV) outbreak in the Americas in 2015–2016 posed a novel global threat due to the association with congenital malformations and its rapid spread. Timely information about the spread of the disease was paramount to public health bodies issuing travel advisories. This paper looks at the online interaction with a national travel health website during the outbreak and compares this to trends in internet searches and news media output. Methods Time trends were created for weekly views of ZIKV-related pages on a UK travel health website, relative search volumes for ‘Zika’ on Google UK, ZIKV-related items aggregated by Google UK News and rank of ZIKV travel advisories among all other pages between 15 November 2015 and 20 August 2016. Results Time trends in traffic to the travel health website corresponded with Google searches, but less so with media items due to intense coverage of the Rio Olympics. Travel advisories for pregnant women were issued from 7 December 2015 and began to increase in popularity (rank) from early January 2016, weeks before a surge in interest as measured by Google searches/news items at the end of January 2016. Conclusions The study showed an amplification of perceived risk among users of a national travel health website weeks before the initial surge in public interest. This suggests a potential value for tools to detect changes in online information seeking behaviours for predicting periods of high demand where the routine capability of travel health services could be exceeded. PMID:28860226

Early detection of perceived risk among users of a UK travel health website compared with internet search activity and media coverage during the 2015-2016 Zika virus outbreak: an observational study.

PubMed

Petersen, Jakob; Simons, Hilary; Patel, Dipti; Freedman, Joanne

2017-08-31

The Zika virus (ZIKV) outbreak in the Americas in 2015-2016 posed a novel global threat due to the association with congenital malformations and its rapid spread. Timely information about the spread of the disease was paramount to public health bodies issuing travel advisories. This paper looks at the online interaction with a national travel health website during the outbreak and compares this to trends in internet searches and news media output. Time trends were created for weekly views of ZIKV-related pages on a UK travel health website, relative search volumes for 'Zika' on Google UK, ZIKV-related items aggregated by Google UK News and rank of ZIKV travel advisories among all other pages between 15 November 2015 and 20 August 2016. Time trends in traffic to the travel health website corresponded with Google searches, but less so with media items due to intense coverage of the Rio Olympics. Travel advisories for pregnant women were issued from 7 December 2015 and began to increase in popularity (rank) from early January 2016, weeks before a surge in interest as measured by Google searches/news items at the end of January 2016. The study showed an amplification of perceived risk among users of a national travel health website weeks before the initial surge in public interest. This suggests a potential value for tools to detect changes in online information seeking behaviours for predicting periods of high demand where the routine capability of travel health services could be exceeded. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013.

PubMed

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet; Nilles, Eric

2014-11-01

On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Almost 40% of the Santa Cruz Islands' population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities.

An Epidemiological Network Model for Disease Outbreak Detection

PubMed Central

Reis, Ben Y; Kohane, Isaac S; Mandl, Kenneth D

2007-01-01

Background Advanced disease-surveillance systems have been deployed worldwide to provide early detection of infectious disease outbreaks and bioterrorist attacks. New methods that improve the overall detection capabilities of these systems can have a broad practical impact. Furthermore, most current generation surveillance systems are vulnerable to dramatic and unpredictable shifts in the health-care data that they monitor. These shifts can occur during major public events, such as the Olympics, as a result of population surges and public closures. Shifts can also occur during epidemics and pandemics as a result of quarantines, the worried-well flooding emergency departments or, conversely, the public staying away from hospitals for fear of nosocomial infection. Most surveillance systems are not robust to such shifts in health-care utilization, either because they do not adjust baselines and alert-thresholds to new utilization levels, or because the utilization shifts themselves may trigger an alarm. As a result, public-health crises and major public events threaten to undermine health-surveillance systems at the very times they are needed most. Methods and Findings To address this challenge, we introduce a class of epidemiological network models that monitor the relationships among different health-care data streams instead of monitoring the data streams themselves. By extracting the extra information present in the relationships between the data streams, these models have the potential to improve the detection capabilities of a system. Furthermore, the models' relational nature has the potential to increase a system's robustness to unpredictable baseline shifts. We implemented these models and evaluated their effectiveness using historical emergency department data from five hospitals in a single metropolitan area, recorded over a period of 4.5 y by the Automated Epidemiological Geotemporal Integrated Surveillance real-time public health–surveillance system, developed by the Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology on behalf of the Massachusetts Department of Public Health. We performed experiments with semi-synthetic outbreaks of different magnitudes and simulated baseline shifts of different types and magnitudes. The results show that the network models provide better detection of localized outbreaks, and greater robustness to unpredictable shifts than a reference time-series modeling approach. Conclusions The integrated network models of epidemiological data streams and their interrelationships have the potential to improve current surveillance efforts, providing better localized outbreak detection under normal circumstances, as well as more robust performance in the face of shifts in health-care utilization during epidemics and major public events. PMID:17593895

Data modeling for detection of epidemic outbreak

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Jaenisch, Kristina L.; Conn, Michael S.; Faucheux, Jeffrey P.

2005-05-01

Data Modeling is successfully applied to outbreak detection using epidemicological time series data. With proper selection of features, same day detection was demonstrated. Predictive Data Models are derived from the features in the form of integro-differential equations or their solution. These models are used as real-time change detectors. Data Modeling enables change detection using only nominal (no-outbreak) examples for training. Modeling naturally occurring dynamics due to assignable causes such as flu season enables distinction to be made of chemical and biological (chem-bio) causes.

Sustained outbreak of measles in New South Wales, 2012: risks for measles elimination in Australia

PubMed Central

Hope, Kirsty; Clark, Penelope; Nguyen, Oanh; Rosewell, Alexander; Conaty, Stephen

2014-01-01

Objective On 7 April 2012, a recently returned traveller from Thailand to Australia was confirmed to have measles. An outbreak of measles subsequently occurred in the state of New South Wales, prompting a sustained and coordinated response by public health authorities. The last confirmed case presented on 29 November 2012. This report describes the outbreak and its characteristics. Methods Cases were investigated following Australian protocols, including case interviews and assessment of contacts for post-exposure prophylaxis. Results Of the 168 cases identified, most occurred in south-western and western Sydney (92.9%, n = 156). Notable features of this outbreak were the disproportionately high number of cases in the 10–19-year-old age group (29.2%, n = 49), the overrepresentation among people of Pacific Islander descent (21.4%, n = 36) and acquisition in health-care facilities (21.4%, n = 36). There were no reported cases of encephalitis and no deaths. Discussion: This was the largest outbreak of measles in Australia since 1997. Its occurrence highlights the need to maintain vigilant surveillance systems for early detection and containment of measles cases and to maintain high population immunity to measles through routine childhood immunization. Vaccination campaigns targeting susceptible groups may also be necessary to sustain Australia’s measles elimination status. PMID:25635228

A large outbreak of influenza A and B on a cruise ship causing widespread morbidity.

PubMed Central

Brotherton, J. M. L.; Delpech, V. C.; Gilbert, G. L.; Hatzi, S.; Paraskevopoulos, P. D.; McAnulty, J. M.

2003-01-01

In September 2000 an outbreak of influenza-like illness was reported on a cruise ship sailing between Sydney and Noumea with over 1,100 passengers and 400 crew on board. Laboratory testing of passengers and crew indicated that both influenza A and B had been circulating on the ship. The cruise coincided with the peak influenza period in Sydney. Morbidity was high with 40 passengers hospitalized, two of whom died. A questionnaire was sent to passengers 3 weeks after the cruise and 836 of 1,119 (75%) responded. A total of 310 passengers (37%) reported suffering from an influenza-like illness (defined as cough, fever, myalgia and weakness) and 528 (63%) had seen a doctor for illness related to the cruise. One-third of passengers reported receipt of influenza vaccination in 2000; however neither their rates of influenza-like illness nor hospitalization were significantly different from those in unvaccinated passengers. A case-control study also found no significant protective effect of influenza vaccination. With the increasing popularity of cruise vacations, such outbreaks are likely to affect increasing numbers of people. Whilst influenza vaccination of passengers and crew may afford some protection, uptake and effectiveness may not be sufficient to prevent outbreaks. Surveillance systems and early intervention measures, such as antiviral therapies, should be considered to detect and control such outbreaks. PMID:12729195

A large outbreak of influenza A and B on a cruise ship causing widespread morbidity.

PubMed

Brotherton, J M L; Delpech, V C; Gilbert, G L; Hatzi, S; Paraskevopoulos, P D; McAnulty, J M

2003-04-01

In September 2000 an outbreak of influenza-like illness was reported on a cruise ship sailing between Sydney and Noumea with over 1,100 passengers and 400 crew on board. Laboratory testing of passengers and crew indicated that both influenza A and B had been circulating on the ship. The cruise coincided with the peak influenza period in Sydney. Morbidity was high with 40 passengers hospitalized, two of whom died. A questionnaire was sent to passengers 3 weeks after the cruise and 836 of 1,119 (75%) responded. A total of 310 passengers (37%) reported suffering from an influenza-like illness (defined as cough, fever, myalgia and weakness) and 528 (63%) had seen a doctor for illness related to the cruise. One-third of passengers reported receipt of influenza vaccination in 2000; however neither their rates of influenza-like illness nor hospitalization were significantly different from those in unvaccinated passengers. A case-control study also found no significant protective effect of influenza vaccination. With the increasing popularity of cruise vacations, such outbreaks are likely to affect increasing numbers of people. Whilst influenza vaccination of passengers and crew may afford some protection, uptake and effectiveness may not be sufficient to prevent outbreaks. Surveillance systems and early intervention measures, such as antiviral therapies, should be considered to detect and control such outbreaks.

[The EHEC O104:H4 outbreak in Germany 2011 - lessons learned?!].

PubMed

Rissland, J; Kielstein, J T; Stark, K; Wichmann-Schauer, H; Stümpel, F; Pulz, M

2013-04-01

The EHEC O104:H4 outbreak 2011 in Germany provided numerous insights into the recognition and control of such epidemic situations. Food-borne outbreaks and their related dynamics may lead to a critical burden of disease and an eventual capacity overload of the medical care system. Possible difficulties in the microbiological diagnostics of new or significantly altered infectious agents may result in a delayed detection of the outbreak as well as the launching of interventional measures. Besides an early notification of the local public health office by the affected institutions, in which a complete electronic procedure and additional sentinel or surveillance instruments (e. g., in emergency departments of hospitals) may be of great help, an interdisciplinary cooperation of the local public health and food safety agencies is the key to an effective outbreak control. Corresponding organizations on the state and federal level should support the investigation process by microbiological diagnostics and advanced epidemiological analysis as well as examination of the food chains. Finally, successful crisis communication relies on "speaking with one voice" (not necessarily one person). Immediate, transparent, appropriate and honest information of the general public concerning the reasons, consequences and (counter-) measures of a crisis are the best means to keep the trust of the population and to counteract the otherwise inevitable speculations. © Georg Thieme Verlag KG Stuttgart · New York.

Disease Surveillance on Complex Social Networks

PubMed Central

Herrera, Jose L.; Srinivasan, Ravi; Brownstein, John S.; Galvani, Alison P.; Meyers, Lauren Ancel

2016-01-01

As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors—sampling the most connected, random, and friends of random individuals—in three complex social networks—a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals—early and accurate detection of epidemic emergence and peak, and general situational awareness—we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0). For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information. PMID:27415615

Disease Surveillance on Complex Social Networks.

PubMed

Herrera, Jose L; Srinivasan, Ravi; Brownstein, John S; Galvani, Alison P; Meyers, Lauren Ancel

2016-07-01

As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors-sampling the most connected, random, and friends of random individuals-in three complex social networks-a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals-early and accurate detection of epidemic emergence and peak, and general situational awareness-we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0). For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.

A Portable Reverse Transcription Recombinase Polymerase Amplification Assay for Rapid Detection of Foot-and-Mouth Disease Virus

PubMed Central

Abd El Wahed, Ahmed; El-Deeb, Ayman; El-Tholoth, Mohamed; Abd El Kader, Hanaa; Ahmed, Abeer; Hassan, Sayed; Hoffmann, Bernd; Haas, Bernd; Shalaby, Mohamed A.; Hufert, Frank T.; Weidmann, Manfred

2013-01-01

Foot-and-mouth disease (FMD) is a trans-boundary viral disease of livestock, which causes huge economic losses and constitutes a serious infectious threat for livestock farming worldwide. Early diagnosis of FMD helps to diminish its impact by adequate outbreak management. In this study, we describe the development of a real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay for the detection of FMD virus (FMDV). The FMDV RT-RPA design targeted the 3D gene of FMDV and a 260 nt molecular RNA standard was used for assay validation. The RT-RPA assay was fast (4–10 minutes) and the analytical sensitivity was determined at 1436 RNA molecules detected by probit regression analysis. The FMDV RT-RPA assay detected RNA prepared from all seven FMDV serotypes but did not detect classical swine fever virus or swine vesicular disease virus. The FMDV RT-RPA assay was used in the field during the recent FMD outbreak in Egypt. In clinical samples, reverse transcription polymerase chain reaction (RT-PCR) and RT-RPA showed a diagnostic sensitivity of 100% and 98%, respectively. In conclusion, FMDV RT-RPA was quicker and much easier to handle in the field than real-time RT-PCR. Thus RT-RPA could be easily implemented to perform diagnostics at quarantine stations or farms for rapid spot-of-infection detection. PMID:23977101

A portable reverse transcription recombinase polymerase amplification assay for rapid detection of foot-and-mouth disease virus.

PubMed

Abd El Wahed, Ahmed; El-Deeb, Ayman; El-Tholoth, Mohamed; Abd El Kader, Hanaa; Ahmed, Abeer; Hassan, Sayed; Hoffmann, Bernd; Haas, Bernd; Shalaby, Mohamed A; Hufert, Frank T; Weidmann, Manfred

2013-01-01

Foot-and-mouth disease (FMD) is a trans-boundary viral disease of livestock, which causes huge economic losses and constitutes a serious infectious threat for livestock farming worldwide. Early diagnosis of FMD helps to diminish its impact by adequate outbreak management. In this study, we describe the development of a real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay for the detection of FMD virus (FMDV). The FMDV RT-RPA design targeted the 3D gene of FMDV and a 260 nt molecular RNA standard was used for assay validation. The RT-RPA assay was fast (4-10 minutes) and the analytical sensitivity was determined at 1436 RNA molecules detected by probit regression analysis. The FMDV RT-RPA assay detected RNA prepared from all seven FMDV serotypes but did not detect classical swine fever virus or swine vesicular disease virus. The FMDV RT-RPA assay was used in the field during the recent FMD outbreak in Egypt. In clinical samples, reverse transcription polymerase chain reaction (RT-PCR) and RT-RPA showed a diagnostic sensitivity of 100% and 98%, respectively. In conclusion, FMDV RT-RPA was quicker and much easier to handle in the field than real-time RT-PCR. Thus RT-RPA could be easily implemented to perform diagnostics at quarantine stations or farms for rapid spot-of-infection detection.

The severe acute respiratory syndrome: impact on travel and tourism.

PubMed

Wilder-Smith, Annelies

2006-03-01

SARS and travel are intricately interlinked. Travelers belonged to those primarily affected in the early stages of the outbreak, travelers became vectors of the disease, and finally, travel and tourism themselves became the victims. The outbreak of SARS created international anxiety because of its novelty, its ease of transmission in certain settings, and the speed of its spread through jet travel, combined with extensive media coverage. The psychological impacts of SARS, coupled with travel restrictions imposed by various national and international authorities, have diminished international travel in 2003, far beyond the limitations to truly SARS hit areas. Governments and press, especially in non SARS affected areas, have been slow to strike the right balance between timely and frequent risk communication and placing risk in the proper context. Screening at airport entry points is costly, has a low yield and is not sufficient in itself. The low yield in detecting SARS is most likely due to a combination of factors, such as travel advisories which resulted in reduced travel to and from SARS affected areas, implementation of effective pre-departure screening at airports in SARS-hit countries, and a rapid decline in new cases at the time when screening was finally introduced. Rather than investing in airport screening measures to detect rare infectious diseases, investments should be used to strengthen screening and infection control capacities at points of entry into the healthcare system. If SARS reoccurs, the subsequent outbreak will be smaller and more easily contained if the lessons learnt from the recent epidemic are applied. Lessons learnt during the outbreak in relation to international travel will be discussed.

Environmental triggers of Past Ebola Outbreaks in Africa, 1981 - 2014

NASA Astrophysics Data System (ADS)

Dartevelle, S.; NguyRobertson, A. L.

2016-12-01

Ebola virus, especially its most common and lethal form, Zaire Ebolavirus, has eluded scientists nearly 50 years. What is its primary host? Why does it go dormant to suddenly to reappear full force years later? What are the driving forces behind its intriguing dynamic? It has been surmised that local environmental factors (such as droughts, seasons) might be at play behind the on-and-off Ebola outbreak outbursts. However, so far, no clear lead has been demonstrated making Ebola a constant hidden lethal menace lurking in the environment for many African communities. We have analyzed long-term time-series of three environmental variables that influence the controlling factor behind the cycle of Ebola virus outbreaks: (i) vegetation health, as determined from the Normalized Difference Vegetation Index (NDVI) collected by AVHRR and MODIS satellite sensors, and the weather variables (ii) temperature and (iii) precipitation from the Climate Forecast System ver. 2. Time series data were averaged monthly and spatially over a 100 km grid around past known outbreak locations. Seasonal effects were removed from these time series before applying statistical analyses identifying causal linkages between NDVI, temperature, precipitation and Ebola outbreaks. Likewise, possible tipping-points prior to outbreaks (i.e., early warning signals of an upcoming outbreak) were identified. Our results indicate that there is a causal dynamic link between outbreaks and the three environmental variables examined months prior to an outbreak. This was likely due to an abnormal change in the local precipitation pattern which influence NDVI values and to a lesser extent temperature. Furthermore, our results provide evidence that these factors demonstrate early warning signals of a dynamical system at a tipping-point, prior to a future outbreak. These tipping-point or early warning models may open new ways to furthermore develop forecast models of future Ebola outbreaks. [US Government — Approved for Public Release 16-560].

Recombinant Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

PubMed Central

Murphy, Sean Patrick; Burkom, Howard

2008-01-01

Objective Broadly, this research aims to improve the outbreak detection performance and, therefore, the cost effectiveness of automated syndromic surveillance systems by building novel, recombinant temporal aberration detection algorithms from components of previously developed detectors. Methods This study decomposes existing temporal aberration detection algorithms into two sequential stages and investigates the individual impact of each stage on outbreak detection performance. The data forecasting stage (Stage 1) generates predictions of time series values a certain number of time steps in the future based on historical data. The anomaly measure stage (Stage 2) compares features of this prediction to corresponding features of the actual time series to compute a statistical anomaly measure. A Monte Carlo simulation procedure is then used to examine the recombinant algorithms’ ability to detect synthetic aberrations injected into authentic syndromic time series. Results New methods obtained with procedural components of published, sometimes widely used, algorithms were compared to the known methods using authentic datasets with plausible stochastic injected signals. Performance improvements were found for some of the recombinant methods, and these improvements were consistent over a range of data types, outbreak types, and outbreak sizes. For gradual outbreaks, the WEWD MovAvg7+WEWD Z-Score recombinant algorithm performed best; for sudden outbreaks, the HW+WEWD Z-Score performed best. Conclusion This decomposition was found not only to yield valuable insight into the effects of the aberration detection algorithms but also to produce novel combinations of data forecasters and anomaly measures with enhanced detection performance. PMID:17947614

What factors might have led to the emergence of Ebola in West Africa?

PubMed

Alexander, Kathleen A; Sanderson, Claire E; Marathe, Madav; Lewis, Bryan L; Rivers, Caitlin M; Shaman, Jeffrey; Drake, John M; Lofgren, Eric; Dato, Virginia M; Eisenberg, Marisa C; Eubank, Stephen

2015-01-01

An Ebola outbreak of unprecedented scope emerged in West Africa in December 2013 and presently continues unabated in the countries of Guinea, Sierra Leone, and Liberia. Ebola is not new to Africa, and outbreaks have been confirmed as far back as 1976. The current West African Ebola outbreak is the largest ever recorded and differs dramatically from prior outbreaks in its duration, number of people affected, and geographic extent. The emergence of this deadly disease in West Africa invites many questions, foremost among these: why now, and why in West Africa? Here, we review the sociological, ecological, and environmental drivers that might have influenced the emergence of Ebola in this region of Africa and its spread throughout the region. Containment of the West African Ebola outbreak is the most pressing, immediate need. A comprehensive assessment of the drivers of Ebola emergence and sustained human-to-human transmission is also needed in order to prepare other countries for importation or emergence of this disease. Such assessment includes identification of country-level protocols and interagency policies for outbreak detection and rapid response, increased understanding of cultural and traditional risk factors within and between nations, delivery of culturally embedded public health education, and regional coordination and collaboration, particularly with governments and health ministries throughout Africa. Public health education is also urgently needed in countries outside of Africa in order to ensure that risk is properly understood and public concerns do not escalate unnecessarily. To prevent future outbreaks, coordinated, multiscale, early warning systems should be developed that make full use of these integrated assessments, partner with local communities in high-risk areas, and provide clearly defined response recommendations specific to the needs of each community.

What Factors Might Have Led to the Emergence of Ebola in West Africa?

PubMed Central

Alexander, Kathleen A.; Sanderson, Claire E.; Marathe, Madav; Lewis, Bryan L.; Rivers, Caitlin M.; Shaman, Jeffrey; Drake, John M.; Lofgren, Eric; Dato, Virginia M.; Eisenberg, Marisa C.; Eubank, Stephen

2015-01-01

An Ebola outbreak of unprecedented scope emerged in West Africa in December 2013 and presently continues unabated in the countries of Guinea, Sierra Leone, and Liberia. Ebola is not new to Africa, and outbreaks have been confirmed as far back as 1976. The current West African Ebola outbreak is the largest ever recorded and differs dramatically from prior outbreaks in its duration, number of people affected, and geographic extent. The emergence of this deadly disease in West Africa invites many questions, foremost among these: why now, and why in West Africa? Here, we review the sociological, ecological, and environmental drivers that might have influenced the emergence of Ebola in this region of Africa and its spread throughout the region. Containment of the West African Ebola outbreak is the most pressing, immediate need. A comprehensive assessment of the drivers of Ebola emergence and sustained human-to-human transmission is also needed in order to prepare other countries for importation or emergence of this disease. Such assessment includes identification of country-level protocols and interagency policies for outbreak detection and rapid response, increased understanding of cultural and traditional risk factors within and between nations, delivery of culturally embedded public health education, and regional coordination and collaboration, particularly with governments and health ministries throughout Africa. Public health education is also urgently needed in countries outside of Africa in order to ensure that risk is properly understood and public concerns do not escalate unnecessarily. To prevent future outbreaks, coordinated, multiscale, early warning systems should be developed that make full use of these integrated assessments, partner with local communities in high-risk areas, and provide clearly defined response recommendations specific to the needs of each community. PMID:26042592

Automatic detection of tweets reporting cases of influenza like illnesses in Australia

PubMed Central

2015-01-01

Early detection of disease outbreaks is critical for disease spread control and management. In this work we investigate the suitability of statistical machine learning approaches to automatically detect Twitter messages (tweets) that are likely to report cases of possible influenza like illnesses (ILI). Empirical results obtained on a large set of tweets originating from the state of Victoria, Australia, in a 3.5 month period show evidence that machine learning classifiers are effective in identifying tweets that mention possible cases of ILI (up to 0.736 F-measure, i.e. the harmonic mean of precision and recall), regardless of the specific technique implemented by the classifier investigated in the study. PMID:25870759

Protracted outbreak of S. Enteritidis PT 21c in a large Hamburg nursing home

PubMed Central

Frank, Christina; Buchholz, Udo; Maaß, Monika; Schröder, Arthur; Bracht, Karl-Hans; Domke, Paul-Gerhard; Rabsch, Wolfgang; Fell, Gerhard

2007-01-01

Background During August 2006, a protracted outbreak of Salmonella (S.) Enteritidis infections in a large Hamburg nursing home was investigated. Methods A site visit of the home was conducted and food suppliers' premises tested for Salmonella. Among nursing home residents a cohort study was carried out focusing on foods consumed in the three days before the first part of the outbreak. Instead of relying on residents' memory, data from the home's patient food ordering system was used as exposure data. S. Enteritidis isolates from patients and suspected food vehicles were phage typed and compared. Results Within a population of 822 nursing home residents, 94 case patients among residents (1 fatality) and 17 among staff members were counted 6 through 29 August. The outbreak peaked 7 through 9 August, two days after a spell of very warm summer weather. S. Enteritidis was consistently recovered from patients' stools throughout the outbreak. Among the food items served during 5 through 7 August, the cohort study pointed to afternoon cake on all three days as potential risk factors for disease. Investigation of the bakery supplying the cake yielded S. Enteritidis from cakes sampled 31 August. Comparison of the isolates by phage typing demonstrated both isolates from patients and the cake to be the exceedingly rare phage type 21c. Conclusion Cake (various types served on various days) contaminated with S. Enteritidis were the likely vehicle of the outbreak in the nursing home. While the cakes were probably contaminated with low pathogen dose throughout the outbreak period, high ambient summer temperatures and failure to keep the cake refrigerated led to high pathogen dose in cake on some days and in some of the housing units. This would explain the initial peak of cases, but also the drawn out nature of the outbreak with cases until the end of August. Suggestions are made to nursing homes, aiding in outbreak prevention. Early outbreak detection is crucial, such that counter measures can be swift and drawn-out outbreaks of nosocomial food-borne infections avoided. PMID:17854497

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation

PubMed Central

Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Revie, Crawford W.; Sanchez, Javier

2013-01-01

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt–Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel. PMID:23576782

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation.

PubMed

Dórea, Fernanda C; McEwen, Beverly J; McNab, W Bruce; Revie, Crawford W; Sanchez, Javier

2013-06-06

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.

Outbreak investigation in two groups of coach passengers with gastroenteritis returning from Germany to the Netherlands in February 2009.

PubMed

Visser, H; Verhoef, L; Schop, W; Götz, H M

2010-07-15

In February 2009, an outbreak of 38 cases of gastroenteritis occurred among the participants of two Dutch coach trips (A and B) who visited the same hotel in Germany. We initiated an outbreak investigation to determine possible risk of food-borne infection. A retrospective cohort study was performed among 87 passengers using a self-administered questionnaire. The response rate was 75 of 87 (86%). Mean age was 65 years. Cases were defined as participants of the two coach trips who had diarrhoea and/or vomiting at least once within 24 hours in the period between 7 and 14 February 2009. We distinguished early and late cases, with symptoms starting within or after 72 hours of arrival in the hotel. Overall attack-rate was 38 of 75 (51%). Microbiological investigation was performed on stool samples of two passengers from Coach A and two passengers from Coach B. Identical norovirus genotype II.4 sequences were detected in all four samples. Univariate analysis revealed a potential risk for early cases from juice consumption , which was most clearly seen for Coach B on day of arrival (juice at lunch: relative risk (RR): 3.9, 95% confidence interval (CI): 1.3-11.7; juice at dinner: RR: 5.5, 95% CI: 1.6-18.1). A dose-response relationship was found. This outbreak was probably caused by using the taps of juice served in large containers with a tap for self-service, due to environmental contamination through person-to-person transmission. Still the role of either contaminated juice or contact with contaminated juice cannot be ruled out.

Rapid molecular assays for the detection of yellow fever virus in low-resource settings.

PubMed

Escadafal, Camille; Faye, Oumar; Sall, Amadou Alpha; Faye, Ousmane; Weidmann, Manfred; Strohmeier, Oliver; von Stetten, Felix; Drexler, Josef; Eberhard, Michael; Niedrig, Matthias; Patel, Pranav

2014-03-01

Yellow fever (YF) is an acute viral hemorrhagic disease transmitted by Aedes mosquitoes. The causative agent, the yellow fever virus (YFV), is found in tropical and subtropical areas of South America and Africa. Although a vaccine is available since the 1930s, YF still causes thousands of deaths and several outbreaks have recently occurred in Africa. Therefore, rapid and reliable diagnostic methods easy to perform in low-resources settings could have a major impact on early detection of outbreaks and implementation of appropriate response strategies such as vaccination and/or vector control. The aim of this study was to develop a YFV nucleic acid detection method applicable in outbreak investigations and surveillance studies in low-resource and field settings. The method should be simple, robust, rapid and reliable. Therefore, we adopted an isothermal approach and developed a recombinase polymerase amplification (RPA) assay which can be performed with a small portable instrument and easy-to-use lyophilized reagents. The assay was developed in three different formats (real-time with or without microfluidic semi-automated system and lateral-flow assay) to evaluate their application for different purposes. Analytical specificity and sensitivity were evaluated with a wide panel of viruses and serial dilutions of YFV RNA. Mosquito pools and spiked human plasma samples were also tested for assay validation. Finally, real-time RPA in portable format was tested under field conditions in Senegal. The assay was able to detect 20 different YFV strains and demonstrated no cross-reactions with closely related viruses. The RPA assay proved to be a robust, portable method with a low detection limit (<21 genome equivalent copies per reaction) and rapid processing time (<20 min). Results from real-time RPA field testing were comparable to results obtained in the laboratory, thus confirming our method is suitable for YFV detection in low-resource settings.

Rapid Molecular Assays for the Detection of Yellow Fever Virus in Low-Resource Settings

PubMed Central

Escadafal, Camille; Faye, Oumar; Sall, Amadou Alpha; Faye, Ousmane; Weidmann, Manfred; Strohmeier, Oliver; von Stetten, Felix; Drexler, Josef; Eberhard, Michael; Niedrig, Matthias; Patel, Pranav

2014-01-01

Background Yellow fever (YF) is an acute viral hemorrhagic disease transmitted by Aedes mosquitoes. The causative agent, the yellow fever virus (YFV), is found in tropical and subtropical areas of South America and Africa. Although a vaccine is available since the 1930s, YF still causes thousands of deaths and several outbreaks have recently occurred in Africa. Therefore, rapid and reliable diagnostic methods easy to perform in low-resources settings could have a major impact on early detection of outbreaks and implementation of appropriate response strategies such as vaccination and/or vector control. Methodology The aim of this study was to develop a YFV nucleic acid detection method applicable in outbreak investigations and surveillance studies in low-resource and field settings. The method should be simple, robust, rapid and reliable. Therefore, we adopted an isothermal approach and developed a recombinase polymerase amplification (RPA) assay which can be performed with a small portable instrument and easy-to-use lyophilized reagents. The assay was developed in three different formats (real-time with or without microfluidic semi-automated system and lateral-flow assay) to evaluate their application for different purposes. Analytical specificity and sensitivity were evaluated with a wide panel of viruses and serial dilutions of YFV RNA. Mosquito pools and spiked human plasma samples were also tested for assay validation. Finally, real-time RPA in portable format was tested under field conditions in Senegal. Conclusion/Significance The assay was able to detect 20 different YFV strains and demonstrated no cross-reactions with closely related viruses. The RPA assay proved to be a robust, portable method with a low detection limit (<21 genome equivalent copies per reaction) and rapid processing time (<20 min). Results from real-time RPA field testing were comparable to results obtained in the laboratory, thus confirming our method is suitable for YFV detection in low-resource settings. PMID:24603874

First Report of ‘Candidatus Phytoplasma trifolii’-Related Strain of 16SrVI-A Phytoplasma Subgroup, Associated with Elm Yellows Disease in American Elm ( Ulmus americana L.) in Ohio, U.S.A

Treesearch

C.E. Flower; N. Hayes-Plazolles; J.M. Slavicek; C. Rosa

2018-01-01

During the investigation of the sudden and early onset of yellowing and mortality of American elm (Ulmus americana L.) trees at the USDA Forest Service Northern Research Station in Delaware, OH, a phytoplasma of the clover proliferation group (16SrVI) was detected as the putative causal agent of the disease outbreak.

Phylodynamics of Yellow Fever Virus in the Americas: new insights into the origin of the 2017 Brazilian outbreak.

PubMed

Mir, Daiana; Delatorre, Edson; Bonaldo, Myrna; Lourenço-de-Oliveira, Ricardo; Vicente, Ana Carolina; Bello, Gonzalo

2017-08-07

Yellow fever virus (YFV) strains circulating in the Americas belong to two distinct genotypes (I and II) that have diversified into several concurrent enzootic lineages. Since 1999, YFV genotype I has spread outside endemic regions and its recent (2017) reemergence in non-endemic Southeastern Brazilian states fuels one of the largest epizootic of jungle Yellow Fever registered in the country. To better understand this phenomenon, we reconstructed the phylodynamics of YFV American genotypes using sequences from nine countries sampled along 60 years, including strains from Brazilian 2017 outbreak. Our analyses reveals that YFV genotypes I and II follow roughly similar evolutionary and demographic dynamics until the early 1990s, when a dramatic change in the diversification process of the genotype I occurred associated with the emergence and dissemination of a new lineage (here called modern). Trinidad and Tobago was the most likely source of the YFV modern-lineage that spread to Brazil and Venezuela around the late 1980s, where it replaced all lineages previously circulating. The modern-lineage caused all major YFV outbreaks detected in non-endemic South American regions since 2000, including the 2017 Brazilian outbreak, and its dissemination was coupled to the accumulation of several amino acid substitutions particularly within non-structural viral proteins.

A space-time scan statistic for detecting emerging outbreaks.

PubMed

Tango, Toshiro; Takahashi, Kunihiko; Kohriyama, Kazuaki

2011-03-01

As a major analytical method for outbreak detection, Kulldorff's space-time scan statistic (2001, Journal of the Royal Statistical Society, Series A 164, 61-72) has been implemented in many syndromic surveillance systems. Since, however, it is based on circular windows in space, it has difficulty correctly detecting actual noncircular clusters. Takahashi et al. (2008, International Journal of Health Geographics 7, 14) proposed a flexible space-time scan statistic with the capability of detecting noncircular areas. It seems to us, however, that the detection of the most likely cluster defined in these space-time scan statistics is not the same as the detection of localized emerging disease outbreaks because the former compares the observed number of cases with the conditional expected number of cases. In this article, we propose a new space-time scan statistic which compares the observed number of cases with the unconditional expected number of cases, takes a time-to-time variation of Poisson mean into account, and implements an outbreak model to capture localized emerging disease outbreaks more timely and correctly. The proposed models are illustrated with data from weekly surveillance of the number of absentees in primary schools in Kitakyushu-shi, Japan, 2006. © 2010, The International Biometric Society.

Epidemic and economic impacts of delayed detection of foot-and-mouth disease: a case study of a simulated outbreak in California.

PubMed

Carpenter, Tim E; O'Brien, Joshua M; Hagerman, Amy D; McCarl, Bruce A

2011-01-01

The epidemic and economic impacts of Foot-and-mouth disease virus (FMDV) spread and control were examined by using epidemic simulation and economic (epinomic) optimization models. The simulated index herd was a ≥2,000 cow dairy located in California. Simulated disease spread was limited to California; however, economic impact was assessed throughout the United States and included international trade effects. Five index case detection delays were examined, which ranged from 7 to 22 days. The simulated median number of infected premises (IP) ranged from approximately 15 to 745, increasing as the detection delay increased from 7 to 22 days. Similarly, the median number of herds under quarantine increased from approximately 680 to 6,200, whereas animals slaughtered went from approximately 8,700 to 260,400 for detection delays of 7-22 days, respectively. The median economic impact of an FMD outbreak in California was estimated to result in national agriculture welfare losses of $2.3-$69.0 billion as detection delay increased from 7 to 22 days, respectively. If assuming a detection delay of 21 days, it was estimated that, for every additional hr of delay, the impact would be an additional approximately 2,000 animals slaughtered and an additional economic loss of $565 million. These findings underline the critical importance that the United States has an effective early detection system in place before an introduction of FMDV if it hopes to avoid dramatic losses to both livestock and the economy.

Comparisons Between Total Lightning Data, Mesocyclone Strength, and Storm Damage Associated with the Florida Tornado Outbreak of February 23, 1998

NASA Technical Reports Server (NTRS)

Hodanish, S; Sharp, D.; Williams, E.; Boldi, B.; Goodman, Steven J.; Raghavan, R.; Matlin, A.; Weber, M.

1998-01-01

During the early morning hours of February 23 1998, the worst tornado outbreak ever recorded occurred over the central Florida peninsula. At least 7 confirmed tornadoes, associated with 4 supercells, developed, with 3 of the tornadoes reaching F3 intensity. Many of the tornadoes where on the ground for tens of miles, uncommon for the state of Florida. A total of 42 people were killed, with over 250 people injured. During the outbreak, National Weather Service Melbourne, in collaboration with the National Aeronautics and Space Administration and the Massachusetts Institute of Technology was collecting data from a unique lightning observing system called Lightning Imaging Sensor Data Applications Display (LISDAD, Boldi et.al., this conference). This system marries radar data collected from the KMLB WSR-88D, cloud to ground data collected from the National Lightning Detection Network, and total lightning data collected from NASKs Lightning Detection And Ranging system. This poster will display, concurrently, total lightning data (displayed in 1 minute increments), time/height storm relative velocity products from the KMLB WSR-88D, and damage information (tornado/hail/wind) from each of the supercell thunderstorms. The primary objective of this poster presentation is to observe how total lightning activity changes as the convective storm intensifies, and how the lightning activity changes with respect to mesocyclone strength (vortex stretching) and damaging weather on the ground.

Genomics-enabled sensor platform for rapid detection of viruses related to disease outbreak.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brozik, Susan M; Manginell, Ronald P; Moorman, Matthew W

2013-09-01

Bioweapons and emerging infectious diseases pose growing threats to our national security. Both natural disease outbreak and outbreaks due to a bioterrorist attack are a challenge to detect, taking days after the outbreak to identify since most outbreaks are only recognized through reportable diseases by health departments and reports of unusual diseases by clinicians. In recent decades, arthropod-borne viruses (arboviruses) have emerged as some of the most significant threats to human health. They emerge, often unexpectedly, from cryptic transmission foci causing localized outbreaks that can rapidly spread to multiple continents due to increased human travel and trade. Currently, diagnosis ofmore » acute infections requires amplification of viral nucleic acids, which can be costly, highly specific, technically challenging and time consuming. No diagnostic devices suitable for use at the bedside or in an outbreak setting currently exist. The original goals of this project were to 1) develop two highly sensitive and specific diagnostic assays for detecting RNA from a wide range of arboviruses; one based on an electrochemical approach and the other a fluorescent based assay and 2) develop prototype microfluidic diagnostic platforms for preclinical and field testing that utilize the assays developed in goal 1. We generated and characterized suitable primers for West Nile Virus RNA detection. Both optical and electrochemical transduction technologies were developed for DNA-RNA hybridization detection and were implemented in microfluidic diagnostic sensing platforms that were developed in this project.« less

Diagnosis and genotyping of African swine fever viruses from 2015 outbreaks in Zambia.

PubMed

Thoromo, Jonas; Simulundu, Edgar; Chambaro, Herman M; Mataa, Liywalii; Lubaba, Caesar H; Pandey, Girja S; Takada, Ayato; Misinzo, Gerald; Mweene, Aaron S

2016-04-29

In early 2015, a highly fatal haemorrhagic disease of domestic pigs resembling African swine fever (ASF) occurred in North Western, Copperbelt, and Lusaka provinces of Zambia. Molecular diagnosis by polymerase chain reaction targeting specific amplification of p72 (B646L) gene of ASF virus (ASFV) was conducted. Fourteen out of 16 domestic pigs from the affected provinces were found to be positive for ASFV. Phylogenetic analyses based on part of the p72 and the complete p54 (E183L) genes revealed that all the ASFVs detected belonged to genotypes I and Id, respectively. Additionally, epidemiological data suggest that the same ASFV spread from Lusaka to other provinces possibly through uncontrolled and/or illegal pig movements. Although the origin of the ASFV that caused outbreaks in domestic pigs in Zambia could not be ascertained, it appears likely that the virus may have emerged from within the country or region, probably from a sylvatic cycle. It is recommended that surveillance of ASF, strict biosecurity, and quarantine measures be imposed in order to prevent further spread and emergence of new ASF outbreaks in Zambia.

Enabling analytical and Modeling Tools for Enhanced Disease Surveillance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dawn K. Manley

2003-04-01

Early detection, identification, and warning are essential to minimize casualties from a biological attack. For covert attacks, sick people are likely to provide the first indication of an attack. An enhanced medical surveillance system that synthesizes distributed health indicator information and rapidly analyzes the information can dramatically increase the number of lives saved. Current surveillance methods to detect both biological attacks and natural outbreaks are hindered by factors such as distributed ownership of information, incompatible data storage and analysis programs, and patient privacy concerns. Moreover, because data are not widely shared, few data mining algorithms have been tested on andmore » applied to diverse health indicator data. This project addressed both integration of multiple data sources and development and integration of analytical tools for rapid detection of disease outbreaks. As a first prototype, we developed an application to query and display distributed patient records. This application incorporated need-to-know access control and incorporated data from standard commercial databases. We developed and tested two different algorithms for outbreak recognition. The first is a pattern recognition technique that searches for space-time data clusters that may signal a disease outbreak. The second is a genetic algorithm to design and train neural networks (GANN) that we applied toward disease forecasting. We tested these algorithms against influenza, respiratory illness, and Dengue Fever data. Through this LDRD in combination with other internal funding, we delivered a distributed simulation capability to synthesize disparate information and models for earlier recognition and improved decision-making in the event of a biological attack. The architecture incorporates user feedback and control so that a user's decision inputs can impact the scenario outcome as well as integrated security and role-based access-control for communicating between distributed data and analytical tools. This work included construction of interfaces to various commercial database products and to one of the data analysis algorithms developed through this LDRD.« less

The epidemiologic surveillance of dengue-fever in French Guiana: when achievements trigger higher goals.

PubMed

Flamand, Claude; Quenel, Philippe; Ardillon, Vanessa; Carvalho, Luisiane; Bringay, Sandra; Teisseire, Maguelonne

2011-01-01

The epidemiology of dengue fever in French Guiana is marked by a combination of permanent transmission of the virus in the whole country and the occurrence of regular epidemics. Since 2006, a multi data source surveillance system was implemented to monitor dengue fever patterns, to improve early detection of outbreaks and to allow a better provision of information to health authorities, in order to guide and evaluate prevention activities and control measures. This report illustrates the validity and the performances of the system. We describe the experience gained by such a surveillance system and outline remaining challenges. Future works will consist in the use of other data sources such as environmental factors in order to improve knowledge on virus transmission mechanisms and determine how to use them for outbreaks prediction.

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013

PubMed Central

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet

2014-01-01

Abstract Problem On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. Approach A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Local setting Almost 40% of the Santa Cruz Islands’ population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. Relevant changes By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. Lesson learnt It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities. PMID:25378746

Characterization of Foodborne Outbreaks of Salmonella enterica Serovar Enteritidis with Whole-Genome Sequencing Single Nucleotide Polymorphism-Based Analysis for Surveillance and Outbreak Detection.

PubMed

Taylor, Angela J; Lappi, Victoria; Wolfgang, William J; Lapierre, Pascal; Palumbo, Michael J; Medus, Carlota; Boxrud, David

2015-10-01

Salmonella enterica serovar Enteritidis is a significant cause of gastrointestinal illness in the United States; however, current molecular subtyping methods lack resolution for this highly clonal serovar. Advances in next-generation sequencing technologies have made it possible to examine whole-genome sequencing (WGS) as a potential molecular subtyping tool for outbreak detection and source trace back. Here, we conducted a retrospective analysis of S. Enteritidis isolates from seven epidemiologically confirmed foodborne outbreaks and sporadic isolates (not epidemiologically linked) to determine the utility of WGS to identify outbreaks. A collection of 55 epidemiologically characterized clinical and environmental S. Enteritidis isolates were sequenced. Single nucleotide polymorphism (SNP)-based cluster analysis of the S. Enteritidis genomes revealed well supported clades, with less than four-SNP pairwise diversity, that were concordant with epidemiologically defined outbreaks. Sporadic isolates were an average of 42.5 SNPs distant from the outbreak clusters. Isolates collected from the same patient over several weeks differed by only two SNPs. Our findings show that WGS provided greater resolution between outbreak, sporadic, and suspect isolates than the current gold standard subtyping method, pulsed-field gel electrophoresis (PFGE). Furthermore, results could be obtained in a time frame suitable for surveillance activities, supporting the use of WGS as an outbreak detection and characterization method for S. Enteritidis. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Multiple Circulating Infections Can Mimic the Early Stages of Viral Hemorrhagic Fevers and Possible Human Exposure to Filoviruses in Sierra Leone Prior to the 2014 Outbreak

PubMed Central

Boisen, Matthew L.; Schieffelin, John S.; Goba, Augustine; Oottamasathien, Darin; Jones, Abigail B.; Shaffer, Jeffrey G.; Hastie, Kathryn M.; Hartnett, Jessica N.; Momoh, Mambu; Fullah, Mohammed; Gabiki, Michael; Safa, Sidiki; Zandonatti, Michelle; Fusco, Marnie; Bornholdt, Zach; Abelson, Dafna; Gire, Stephen K.; Andersen, Kristian G.; Tariyal, Ridhi; Stremlau, Mathew; Cross, Robert W.; Geisbert, Joan B.; Pitts, Kelly R.; Geisbert, Thomas W.; Kulakoski, Peter; Wilson, Russell B.; Henderson, Lee; Sabeti, Pardis C.; Grant, Donald S.; Garry, Robert F.; Saphire, Erica O.; Khan, Sheik Humarr

2015-01-01

Abstract Lassa fever (LF) is a severe viral hemorrhagic fever caused by Lassa virus (LASV). The LF program at the Kenema Government Hospital (KGH) in Eastern Sierra Leone currently provides diagnostic services and clinical care for more than 500 suspected LF cases per year. Nearly two-thirds of suspected LF patients presenting to the LF Ward test negative for either LASV antigen or anti-LASV immunoglobulin M (IgM), and therefore are considered to have a non-Lassa febrile illness (NLFI). The NLFI patients in this study were generally severely ill, which accounts for their high case fatality rate of 36%. The current studies were aimed at determining possible causes of severe febrile illnesses in non-LF cases presenting to the KGH, including possible involvement of filoviruses. A seroprevalence survey employing commercial enzyme-linked immunosorbent assay tests revealed significant IgM and IgG reactivity against dengue virus, chikungunya virus, West Nile virus (WNV), Leptospira, and typhus. A polymerase chain reaction–based survey using sera from subjects with acute LF, evidence of prior LASV exposure, or NLFI revealed widespread infection with Plasmodium falciparum malaria in febrile patients. WNV RNA was detected in a subset of patients, and a 419 nt amplicon specific to filoviral L segment RNA was detected at low levels in a single patient. However, 22% of the patients presenting at the KGH between 2011 and 2014 who were included in this survey registered anti-Ebola virus (EBOV) IgG or IgM, suggesting prior exposure to this agent. The 2014 Ebola virus disease (EVD) outbreak is already the deadliest and most widely dispersed outbreak of its kind on record. Serological evidence reported here for possible human exposure to filoviruses in Sierra Leone prior to the current EVD outbreak supports genetic analysis that EBOV may have been present in West Africa for some time prior to the 2014 outbreak. PMID:25531344

Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System

PubMed Central

Ruiz, Daniel; Poveda, Germán; Vélez, Iván D; Quiñones, Martha L; Rúa, Guillermo L; Velásquez, Luz E; Zuluaga, Juan S

2006-01-01

Background Malaria has recently re-emerged as a public health burden in Colombia. Although the problem seems to be climate-driven, there remain significant gaps of knowledge in the understanding of the complexity of malaria transmission, which have motivated attempts to develop a comprehensive model. Methods The mathematical tool was applied to represent Plasmodium falciparum malaria transmission in two endemic-areas. Entomological exogenous variables were estimated through field campaigns and laboratory experiments. Availability of breeding places was included towards representing fluctuations in vector densities. Diverse scenarios, sensitivity analyses and instabilities cases were considered during experimentation-validation process. Results Correlation coefficients and mean square errors between observed and modelled incidences reached 0.897–0.668 (P > 0.95) and 0.0002–0.0005, respectively. Temperature became the most relevant climatic parameter driving the final incidence. Accordingly, malaria outbreaks are possible during the favourable epochs following the onset of El Niño warm events. Sporogonic and gonotrophic cycles showed to be the entomological key-variables controlling the transmission potential of mosquitoes' population. Simulation results also showed that seasonality of vector density becomes an important factor towards understanding disease transmission. Conclusion The model constitutes a promising tool to deepen the understanding of the multiple interactions related to malaria transmission conducive to outbreaks. In the foreseeable future it could be implemented as a tool to diagnose possible dynamical patterns of malaria incidence under several scenarios, as well as a decision-making tool for the early detection and control of outbreaks. The model will be also able to be merged with forecasts of El Niño events to provide a National Malaria Early Warning System. PMID:16882349

Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System.

PubMed

Ruiz, Daniel; Poveda, Germán; Vélez, Iván D; Quiñones, Martha L; Rúa, Guillermo L; Velásquez, Luz E; Zuluaga, Juan S

2006-08-01

Malaria has recently re-emerged as a public health burden in Colombia. Although the problem seems to be climate-driven, there remain significant gaps of knowledge in the understanding of the complexity of malaria transmission, which have motivated attempts to develop a comprehensive model. The mathematical tool was applied to represent Plasmodium falciparum malaria transmission in two endemic-areas. Entomological exogenous variables were estimated through field campaigns and laboratory experiments. Availability of breeding places was included towards representing fluctuations in vector densities. Diverse scenarios, sensitivity analyses and instabilities cases were considered during experimentation-validation process. Correlation coefficients and mean square errors between observed and modelled incidences reached 0.897-0.668 (P > 0.95) and 0.0002-0.0005, respectively. Temperature became the most relevant climatic parameter driving the final incidence. Accordingly, malaria outbreaks are possible during the favourable epochs following the onset of El Niño warm events. Sporogonic and gonotrophic cycles showed to be the entomological key-variables controlling the transmission potential of mosquitoes' population. Simulation results also showed that seasonality of vector density becomes an important factor towards understanding disease transmission. The model constitutes a promising tool to deepen the understanding of the multiple interactions related to malaria transmission conducive to outbreaks. In the foreseeable future it could be implemented as a tool to diagnose possible dynamical patterns of malaria incidence under several scenarios, as well as a decision-making tool for the early detection and control of outbreaks. The model will be also able to be merged with forecasts of El Niño events to provide a National Malaria Early Warning System.

The highly virulent 2006 Norwegian EHEC O103:H25 outbreak strain is related to the 2011 German O104:H4 outbreak strain.

PubMed

L'Abée-Lund, Trine M; Jørgensen, Hannah J; O'Sullivan, Kristin; Bohlin, Jon; Ligård, Goro; Granum, Per Einar; Lindbäck, Toril

2012-01-01

In 2006, a severe foodborne EHEC outbreak occured in Norway. Seventeen cases were recorded and the HUS frequency was 60%. The causative strain, Esherichia coli O103:H25, is considered to be particularly virulent. Sequencing of the outbreak strain revealed resemblance to the 2011 German outbreak strain E. coli O104:H4, both in genome and Shiga toxin 2-encoding (Stx2) phage sequence. The nucleotide identity between the Stx2 phages from the Norwegian and German outbreak strains was 90%. During the 2006 outbreak, stx(2)-positive O103:H25 E. coli was isolated from two patients. All the other outbreak associated isolates, including all food isolates, were stx-negative, and carried a different phage replacing the Stx2 phage. This phage was of similar size to the Stx2 phage, but had a distinctive early phage region and no stx gene. The sequence of the early region of this phage was not retrieved from the bacterial host genome, and the origin of the phage is unknown. The contaminated food most likely contained a mixture of E. coli O103:H25 cells with either one of the phages.

The Highly Virulent 2006 Norwegian EHEC O103:H25 Outbreak Strain Is Related to the 2011 German O104:H4 Outbreak Strain

PubMed Central

L'Abée-Lund, Trine M.; Jørgensen, Hannah J.; O'Sullivan, Kristin; Bohlin, Jon; Ligård, Goro; Granum, Per Einar; Lindbäck, Toril

2012-01-01

In 2006, a severe foodborne EHEC outbreak occured in Norway. Seventeen cases were recorded and the HUS frequency was 60%. The causative strain, Esherichia coli O103:H25, is considered to be particularly virulent. Sequencing of the outbreak strain revealed resemblance to the 2011 German outbreak strain E. coli O104:H4, both in genome and Shiga toxin 2-encoding (Stx2) phage sequence. The nucleotide identity between the Stx2 phages from the Norwegian and German outbreak strains was 90%. During the 2006 outbreak, stx2-positive O103:H25 E. coli was isolated from two patients. All the other outbreak associated isolates, including all food isolates, were stx-negative, and carried a different phage replacing the Stx2 phage. This phage was of similar size to the Stx2 phage, but had a distinctive early phage region and no stx gene. The sequence of the early region of this phage was not retrieved from the bacterial host genome, and the origin of the phage is unknown. The contaminated food most likely contained a mixture of E. coli O103:H25 cells with either one of the phages. PMID:22403614

Salmonella Weltevreden food poisoning in a tea garden of Assam: An outbreak investigation.

PubMed

Saikia, L; Sharma, A; Nath, R; Choudhury, G; Borah, A K

2015-01-01

Salmonella enterica serovar Weltevreden has been a rare cause of acute gastroenteritis occurring worldwide. Here, we report an outbreak of food poisoning in a tea garden. To determine the aetiological agent and risk factors responsible for the outbreak and to take necessary steps for prevention of future outbreaks. Affected area was visited by a team of microbiologists for collecting stool samples/rectal swabs from affected patients. Samples were processed by culture followed by confirmation of the isolates biochemically, automated bacterial identification system, conventional serotyping and molecular typing. Water samples were also processed for detection of faecal contamination. Antimicrobial susceptibility testing was performed by Kirby-Bauer disc diffusion technique according to the Clinical Laboratory Standard Institute guidelines. The isolates were confirmed as S. enterica subspecies enterica serovar Weltevreden. They were found sensitive to ampicillin, amoxycillin-clavulanic acid, ciprofloxacin, ofloxacin, norfloxacin, cefotaxime, ceftriaxone, co-trimoxazole and doxycycline. Water samples showed high-level faecal contamination. Source of outbreak was found to be drinking water contaminated with dead livestock. House to house visit was made for early diagnosis and treatment of the cases, awareness campaigning and chlorination of drinking water. This report emphasises the geographical distribution of this organism in Assam. As S. Weltevreden is widely distributed in domestic animals, people should be made aware of immediate reporting of any unusual death among the livestock and their safe disposal which can significantly reduce the incidence of non-typhoidal salmonellosis in the country.

Molecular epidemiology of "Norwalk-like viruses" in outbreaks of gastroenteritis in the United States.

PubMed

Fankhauser, R L; Noel, J S; Monroe, S S; Ando, T; Glass, R I

1998-12-01

Fecal specimens from 90 outbreaks of nonbacterial gastroenteritis reported to 33 state health departments from January 1996 to June 1997 were examined to determine the importance of and to characterize "Norwalk-like viruses" (NLVs) in these outbreaks. NLVs were detected by reverse transcription-polymerase chain reaction in specimens from 86 (96%) of 90 outbreaks. Outbreaks were most frequent in nursing homes and hospitals (43%), followed by restaurants or events with catered meals (26%); consumption of contaminated food was the most commonly identified mode of transmission (37%). Nucleotide sequence analysis showed great diversity between strains but also provided evidence indicating the emergence of a common, predominant strain. The application of improved molecular techniques to detect NLVs demonstrates that most outbreaks of nonbacterial gastroenteritis in the United States appear to be associated with these viruses and that sequence analysis is a robust tool to help link or differentiate these outbreaks.

Investigation of travel-related cases in a multinational outbreak: example of the Shiga-toxin producing E. coli outbreak in Germany, May-June 2011.

PubMed

Devaux, I; Varela-Santos, C; Payne-Hallström, L; Takkinen, J; Bogaardt, C; Coulombier, D

2015-12-01

Early investigation of travel-related cases in an outbreak of an emerging infectious disease can provide useful information to epidemiologists to characterize the exposure, while they may differ in demographic profiles from cases reported in the country where the outbreak has occurred. During the spring 2011 E. coli outbreak in Germany, we proposed a methodological approach to collect a minimal set of demographic and clinical data that are relatively easy to obtain and available at an early stage of an outbreak investigation. Ninety-eight STEC O104 travel-related cases were reported in a survey by seven EU countries, Switzerland, Canada and the USA. We found a mean incubation period (n = 50) of 8·5 days, which confirmed previous estimations communicated by the Robert Koch Institute. No significant association was found between the duration of the incubation period and possible demographic and clinical factors, although the older the age, the shorter the incubation period that was observed. Such approach and observations are informative for further investigations of outbreaks of enterohaemorrhagic E. coli or other emerging infectious diseases.

PulseNet China, a model for future laboratory-based bacterial infectious disease surveillance in China.

PubMed

Li, Wei; Lu, Shan; Cui, Zhigang; Cui, Jinghua; Zhou, Haijian; Wang, Yiqing; Shao, Zhujun; Ye, Changyun; Kan, Biao; Xu, Jianguo

2012-12-01

Surveillance is critical for the prevention and control of infectious disease. China's real-time web-based infectious disease reporting system is a distinguished achievement. However, many aspects of the current China Infectious Disease Surveillance System do not yet meet the demand for timely outbreak detection and identification of emerging infectious disease. PulseNet, the national molecular typing network for foodborne disease surveillance was first established by the Centers for Disease Control and Prevention of the United States in 1995 and has proven valuable in the early detection of outbreaks and tracing the pathogen source. Since 2001, the China CDC laboratory for bacterial pathogen analysis has been a member of the PulseNet International family; and has been adapting the idea and methodology of PulseNet to develop a model for a future national laboratory-based surveillance system for all bacterial infectious disease.We summarized the development progress for the PulseNet China system and discussed it as a model for the future of China's national laboratory-based surveillance system.

Ambulatory Pediatric Surveillance of Hand, Foot and Mouth Disease as Signal of an Outbreak of Coxsackievirus A6 Infections, France, 2014–2015

PubMed Central

le Sage, François Vié; Pereira, Bruno; Cohen, Robert; Levy, Corinne; Archimbaud, Christine; Peigue-Lafeuille, Hélène; Bailly, Jean-Luc; Henquell, Cécile

2016-01-01

The clinical impact of enteroviruses associated with hand, foot and mouth disease (HFMD) is unknown outside Asia, and the prevalence of enterovirus A71 (EV-A71) in particular might be underestimated. To investigate the prevalence of enterovirus serotypes and the clinical presentations associated with HFMD in France, we conducted prospective ambulatory clinic–based surveillance of children during April 2014–March 2015. Throat or buccal swabs were collected from children with HFMD and tested for the enterovirus genome. Physical examinations were recorded on a standardized form. An enterovirus infection was detected in 523 (79.3%) of 659 children tested. Two epidemic waves occurred, dominated by coxsackievirus (CV) A6, which was detected in 53.9% of enterovirus-infected children. CV-A6 was more frequently related to atypical HFMD manifestations (eruptions extended to limbs and face). Early awareness and documentation of HFMD outbreaks can be achieved by syndromic surveillance of HFMD by ambulatory pediatricians and rapid enterovirus testing and genotyping. PMID:27767012

A Web-Based Multidrug-Resistant Organisms Surveillance and Outbreak Detection System with Rule-Based Classification and Clustering

PubMed Central

Tseng, Yi-Ju; Wu, Jung-Hsuan; Ping, Xiao-Ou; Lin, Hui-Chi; Chen, Ying-Yu; Shang, Rung-Ji; Chen, Ming-Yuan; Lai, Feipei

2012-01-01

Background The emergence and spread of multidrug-resistant organisms (MDROs) are causing a global crisis. Combating antimicrobial resistance requires prevention of transmission of resistant organisms and improved use of antimicrobials. Objectives To develop a Web-based information system for automatic integration, analysis, and interpretation of the antimicrobial susceptibility of all clinical isolates that incorporates rule-based classification and cluster analysis of MDROs and implements control chart analysis to facilitate outbreak detection. Methods Electronic microbiological data from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of MDROs. The numbers of organisms, patients, and incident patients in each MDRO pattern were presented graphically to describe spatial and time information in a Web-based user interface. Hierarchical clustering with 7 upper control limits (UCL) was used to detect suspicious outbreaks. The system’s performance in outbreak detection was evaluated based on vancomycin-resistant enterococcal outbreaks determined by a hospital-wide prospective active surveillance database compiled by infection control personnel. Results The optimal UCL for MDRO outbreak detection was the upper 90% confidence interval (CI) using germ criterion with clustering (area under ROC curve (AUC) 0.93, 95% CI 0.91 to 0.95), upper 85% CI using patient criterion (AUC 0.87, 95% CI 0.80 to 0.93), and one standard deviation using incident patient criterion (AUC 0.84, 95% CI 0.75 to 0.92). The performance indicators of each UCL were statistically significantly higher with clustering than those without clustering in germ criterion (P < .001), patient criterion (P = .04), and incident patient criterion (P < .001). Conclusion This system automatically identifies MDROs and accurately detects suspicious outbreaks of MDROs based on the antimicrobial susceptibility of all clinical isolates. PMID:23195868

An exploratory study of a text classification framework for Internet-based surveillance of emerging epidemics

PubMed Central

Torii, Manabu; Yin, Lanlan; Nguyen, Thang; Mazumdar, Chand T.; Liu, Hongfang; Hartley, David M.; Nelson, Noele P.

2014-01-01

Purpose Early detection of infectious disease outbreaks is crucial to protecting the public health of a society. Online news articles provide timely information on disease outbreaks worldwide. In this study, we investigated automated detection of articles relevant to disease outbreaks using machine learning classifiers. In a real-life setting, it is expensive to prepare a training data set for classifiers, which usually consists of manually labeled relevant and irrelevant articles. To mitigate this challenge, we examined the use of randomly sampled unlabeled articles as well as labeled relevant articles. Methods Naïve Bayes and Support Vector Machine (SVM) classifiers were trained on 149 relevant and 149 or more randomly sampled unlabeled articles. Diverse classifiers were trained by varying the number of sampled unlabeled articles and also the number of word features. The trained classifiers were applied to 15 thousand articles published over 15 days. Top-ranked articles from each classifier were pooled and the resulting set of 1337 articles was reviewed by an expert analyst to evaluate the classifiers. Results Daily averages of areas under ROC curves (AUCs) over the 15-day evaluation period were 0.841 and 0.836, respectively, for the naïve Bayes and SVM classifier. We referenced a database of disease outbreak reports to confirm that this evaluation data set resulted from the pooling method indeed covered incidents recorded in the database during the evaluation period. Conclusions The proposed text classification framework utilizing randomly sampled unlabeled articles can facilitate a cost-effective approach to training machine learning classifiers in a real-life Internet-based biosurveillance project. We plan to examine this framework further using larger data sets and using articles in non-English languages. PMID:21134784

Early and Real-Time Detection of Seasonal Influenza Onset

PubMed Central

Marques-Pita, Manuel

2017-01-01

Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases. PMID:28158192

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: A Multidisciplinary Approach for the Early Detection and Response to Disease Outbreaks

DTIC Science & Technology

2011-01-01

borne hantavirus diseases. In Kenya, USAMRU-K discovered hantaviruses in live rodents from Marigat and Garissa (Figure 15). These viruses are now...1Armed Forces Health Surveillance Center, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA Full list of author information is available at the end...6. AUTHOR (S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Armed Forces Health

Evaluating the utility of syndromic surveillance algorithms for screening to detect potentially clonal hospital infection outbreaks

PubMed Central

Talbot, Thomas R; Schaffner, William; Bloch, Karen C; Daniels, Titus L; Miller, Randolph A

2011-01-01

Objective The authors evaluated algorithms commonly used in syndromic surveillance for use as screening tools to detect potentially clonal outbreaks for review by infection control practitioners. Design Study phase 1 applied four aberrancy detection algorithms (CUSUM, EWMA, space-time scan statistic, and WSARE) to retrospective microbiologic culture data, producing a list of past candidate outbreak clusters. In phase 2, four infectious disease physicians categorized the phase 1 algorithm-identified clusters to ascertain algorithm performance. In phase 3, project members combined the algorithms to create a unified screening system and conducted a retrospective pilot evaluation. Measurements The study calculated recall and precision for each algorithm, and created precision-recall curves for various methods of combining the algorithms into a unified screening tool. Results Individual algorithm recall and precision ranged from 0.21 to 0.31 and from 0.053 to 0.29, respectively. Few candidate outbreak clusters were identified by more than one algorithm. The best method of combining the algorithms yielded an area under the precision-recall curve of 0.553. The phase 3 combined system detected all infection control-confirmed outbreaks during the retrospective evaluation period. Limitations Lack of phase 2 reviewers' agreement indicates that subjective expert review was an imperfect gold standard. Less conservative filtering of culture results and alternate parameter selection for each algorithm might have improved algorithm performance. Conclusion Hospital outbreak detection presents different challenges than traditional syndromic surveillance. Nevertheless, algorithms developed for syndromic surveillance have potential to form the basis of a combined system that might perform clinically useful hospital outbreak screening. PMID:21606134

Quantifying secondary pest outbreaks in cotton and their monetary cost with causal-inference statistics.

PubMed

Gross, Kevin; Rosenheim, Jay A

2011-10-01

Secondary pest outbreaks occur when the use of a pesticide to reduce densities of an unwanted target pest species triggers subsequent outbreaks of other pest species. Although secondary pest outbreaks are thought to be familiar in agriculture, their rigorous documentation is made difficult by the challenges of performing randomized experiments at suitable scales. Here, we quantify the frequency and monetary cost of secondary pest outbreaks elicited by early-season applications of broad-spectrum insecticides to control the plant bug Lygus spp. (primarily L. hesperus) in cotton grown in the San Joaquin Valley, California, USA. We do so by analyzing pest-control management practices for 969 cotton fields spanning nine years and 11 private ranches. Our analysis uses statistical methods to draw formal causal inferences from nonexperimental data that have become popular in public health and economics, but that are not yet widely known in ecology or agriculture. We find that, in fields that received an early-season broad-spectrum insecticide treatment for Lygus, 20.2% +/- 4.4% (mean +/- SE) of late-season pesticide costs were attributable to secondary pest outbreaks elicited by the early-season insecticide application for Lygus. In 2010 U.S. dollars, this equates to an additional $6.00 +/- $1.30 (mean +/- SE) per acre in management costs. To the extent that secondary pest outbreaks may be driven by eliminating pests' natural enemies, these figures place a lower bound on the monetary value of ecosystem services provided by native communities of arthropod predators and parasitoids in this agricultural system.

Description of the early stage of pandemic (H1N1) 2009 in Germany, 27 April-16 June 2009.

PubMed

2009-08-06

We report characteristics of the early stage of the pandemic (H1N1) 2009 in Germany. Until 16 June 2009, 198 confirmed cases were notified. Almost half of the cases (47%) were imported, mostly from Mexico and the United States. About two third of indigenous cases were outbreak-related (with two large school-associated outbreaks, n=74). According to our results Germany is still in the early stage of the pandemic with limited domestic transmission.

Decrease in milk yield associated with exposure to bluetongue virus serotype 8 in cattle herds.

PubMed

Nusinovici, S; Souty, C; Seegers, H; Beaudeau, F; Fourichon, C

2013-02-01

Decreased milk yield and reduced fertility are the primary consequences of infection by bluetongue virus serotype 8 (BTV-8). These effects must be quantified to fully assess the economic benefit of vaccination. This can be estimated by measuring the effect of BTV-8 exposure on milk yield and fertility for all cows belonging to an infected herd. The objectives of this study were (1) to quantify the mean effect of exposure to BTV-8 on milk yield following natural challenge for cows in herds previously naïve, (2) to determine the duration of reduced milk yield before and after the date disease was first detected in the herd to estimate the cumulative loss of milk yield during this period, and (3) to evaluate the influence of the proportion of infected neighboring herds on the reduction in milk yield following exposure to BTV-8. The effects of exposure to BTV-8 during the French outbreak of 2007 were assessed using mixed linear models, which allow adjustment for factors known to influence milk yield. Exposure to BTV-8 was associated with a sharp decrease in milk yield over a period of 6 mo (2 mo before to 4 mo after the reported date of disease detection in the herd). The cumulative loss of milk yield was more than 3% of annual production. The relatively earlier reduction in milk yield in infected herds detected later in the outbreak period suggests that detection of clinical signs was delayed in these herds. Finally, the greatest decrease in milk yield was observed in herds detected early during the outbreak period and located in areas with the highest disease incidence. This may be due to a greater within-herd incidence or to a greater amount of virus injected by midges to individual cows in these herds. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Rapid detection of foodborne botulism outbreaks facilitated by epidemiological linking of cases: implications for food defense and public health response.

PubMed

Newkirk, Ryan W; Hedberg, Craig W

2012-02-01

The main objective of this study was to develop an understanding of the descriptive epidemiology of foodborne botulism in the context of outbreak detection and food defense. This study used 1993-2008 data from the Centers for Disease Control and Prevention (CDC) Annual Summaries of Notifiable Diseases, 2003-2006 data from the Bacterial Foodborne and Diarrheal Disease National Case Surveillance Annual Reports, and 1993-2008 data from the Annual Listing of Foodborne Disease Outbreaks. Published outbreak investigation reports were identified through a PubMed search of MEDLINE citations for botulism outbreaks. Fifty-eight foodborne botulism outbreaks were reported to CDC between 1993 and 2008. Four hundred sixteen foodborne botulism cases were documented; 205 (49%) were associated with outbreaks. Familial connections and co-hospitalization of initial presenting cases were common in large outbreaks (>5 cases). In these outbreaks, the time from earliest exposure to outbreak recognition varied dramatically (range, 48-216 h). The identification of epidemiologic linkages between foodborne botulism cases is a critical part of diagnostic evaluation and outbreak detection. Investigation of an intentionally contaminated food item with a long shelf life and widespread distribution may be delayed until an astute physician suspects foodborne botulism; suspicion of foodborne botulism occurs more frequently when more than one case is hospitalized concurrently. In an effort to augment national botulism surveillance and antitoxin release systems and to improve food defense and public health preparedness efforts, medical organizations and Homeland Security officials should emphasize the education and training of medical personnel to improve foodborne botulism diagnostic capabilities to recognize single foodborne botulism cases and to look for epidemiologic linkages between suspected cases.

Finding Outbreaks Faster

PubMed Central

Smolinski, Mark S.; Olsen, Jennifer M.

2017-01-01

Rapid detection, reporting, and response to an infectious disease outbreak are critical to prevent localized health events from emerging as pandemic threats. Metrics to evaluate the timeliness of these critical activities, however, are lacking. Easily understood and comparable measures for tracking progress and encouraging investment in rapid detection, reporting, and response are sorely needed. We propose that the timeliness of outbreak detection, reporting, laboratory confirmation, response, and public communication should be considered as measures for improving global health security at the national level, allowing countries to track progress over time and inform investments in disease surveillance. PMID:28384035

Laboratory preparedness for detection and monitoring of Shiga toxin 2-producing Escherichia coli O104:H4 in Europe and response to the 2011 outbreak.

PubMed

Rosin, P; Niskanen, T; Palm, D; Struelens, M; Takkinen, J

2013-06-20

A hybrid strain of enteroaggregative and Shiga toxin 2-producing Escherichia coli (EAEC-STEC) serotype O104:H4 strain caused a large outbreak of haemolytic uraemic syndrome and bloody diarrhoea in 2011 in Europe. Two surveys were performed in the European Union (EU) and European Economic Area (EEA) countries to assess their laboratory capabilities to detect and characterise this previously uncommon STEC strain. Prior to the outbreak, 11 of the 32 countries in this survey had capacity at national reference laboratory (NRL) level for epidemic case confirmation according to the EU definition. During the outbreak, at primary diagnostic level, nine countries reported that clinical microbiology laboratories routinely used Shiga toxin detection assays suitable for diagnosis of infections with EAEC-STEC O104:H4, while 14 countries had NRL capacity to confirm epidemic cases. Six months after the outbreak, 22 countries reported NRL capacity to confirm such cases following initiatives taken by NRLs and the European Centre for Disease Prevention and Control (ECDC) Food- and Waterborne Disease and Zoonoses laboratory network. These data highlight the challenge of detection and confirmation of epidemic infections caused by atypical STEC strains and the benefits of coordinated EU laboratory networks to strengthen capabilities in response to a major outbreak.

Rapid virus detection procedure for molecular tracing of shellfish associated with disease outbreaks.

PubMed

de Roda Husman, Ana Maria; Lodder-Verschoor, Froukje; van den Berg, Harold H J L; Le Guyader, Françoise S; van Pelt, Hilde; van der Poel, Wim H M; Rutjes, Saskia A

2007-04-01

Detection of pathogenic viruses in oysters implicated in gastroenteritis outbreaks is often hampered by time-consuming, specialist virus extraction methods. Five virus RNA extraction methods were evaluated with respect to performance characteristics and sensitivity on artificially contaminated oyster digestive glands. The two most promising procedures were further evaluated on bioaccumulated and naturally contaminated oysters. The most efficient method was used to trace the source in an outbreak situation. Out of five RNA extraction protocols, PEG precipitation and the RNeasy Kit performed best with norovirus genogroup III-spiked digestive glands. Analyzing 24-h bioaccumulated oysters revealed a slightly better sensitivity with PEG precipitation, but the RNeasy Kit was less prone to concentrate inhibitors. The latter procedure demonstrated the presence of human noroviruses in naturally contaminated oysters and oysters implicated in an outbreak. In this outbreak, in four out of nine individually analyzed digestive glands, norovirus was detected. In one of the oysters and in one of the fecal samples of the clinical cases, identical norovirus strains were detected. A standard and rapid virus extraction method using the RNeasy Kit appeared to be most useful in tracing shellfish as the source in gastroenteritis outbreaks, and to be able to make effective and timely risk management decisions.

Vector-borne disease surveillance in livestock populations: A critical review of literature recommendations and implemented surveillance (BTV-8) in five European countries.

PubMed

Dórea, Fernanda C; Elbers, Armin R W; Hendrikx, Pascal; Enoe, Claes; Kirkeby, Carsten; Hoinville, Linda; Lindberg, Ann

2016-03-01

Preparedness against vector-borne threats depends on the existence of a long-term, sustainable surveillance of vector-borne disease and their relevant vectors. This work reviewed the availability of such surveillance systems in five European countries (Denmark, France, The Netherlands, Sweden and United Kingdom, part of the CoVetLab network). A qualitative assessment was then performed focusing on surveillance directed particularly to BTV-8. Information regarding surveillance activities were reviewed for the years 2008 and 2012. The results were then complemented with a critical scoping review of the literature aimed at identifying disease surveillance strategies and methods that are currently suggested as best suited to target vector-borne diseases in order to guide future development of surveillance in the countries in question. Passive surveillance was found to be efficient for early detection of diseases during the early phase of introduction into a free country. However, its value diminished once the disease has been established in a territory. Detection of emerging diseases was found to be very context and area specific, and thus active surveillance designs need to take the available epidemiological, ecological and entomological information into account. This was demonstrated by the effectiveness of the bulk milk surveillance in detecting the first case in Sweden, highlighting the need for output based standards to allow the most effective, context dependent, surveillance strategies to be used. Preparedness was of fundamental importance in determining the timeliness of detection and control in each country and that this in turn was heavily influenced by knowledge of emerging diseases in neighboring countries. Therefore it is crucial to share information on outbreaks between researchers and decision-makers and across borders continuously in order to react timely in case of an outbreak. Furthermore, timely reaction to an outbreak was heavily influenced by availability of control measures (vaccines), which is also strengthened if knowledge is shared quickly between countries. The assessment of the bluetongue surveillance in the affected countries showed that the degree of voluntary engagement varied, and that it is important to engage the public by general awareness and dissemination of results. The degree of engagement will also aid in establishing a passive surveillance system. Copyright © 2016 Elsevier B.V. All rights reserved.

Surfing with spirochaetes: an ongoing syphilis outbreak in Brighton.

PubMed

Poulton, M; Dean, G L; Williams, D I; Carter, P; Iversen, A; Fisher, M

2001-10-01

There has been a recent shift in the epidemiology of early syphilis in the developed world with sporadic outbreaks on a historic low level of background disease. Here we describe an ongoing outbreak of syphilis in Brighton. Data collected on all patients with a diagnosis of early infectious syphilis at Brighton GUM clinic. 30 cases of early syphilis were diagnosed over a 25 month period beginning in July 1999. 28 were homosexual or bisexual men, giving a rate of 134 cases per 100 000 homosexual men. The cases reported a median of three sexual contacts (range 1-50) in the preceding 6 months and 77% had concurrent regular and casual partners. 83% of contacts were casual and untraceable. Over one third (11) of these cases reported oral sex as their only risk factor for syphilis acquisition and were unaware of this transmission route. 70% were diagnosed with primary or secondary infection, the remaining 30% being asymptomatic with early latent infection. Eight of the cases were HIV positive and a further eight remain untested for HIV. At least one concurrent STI was found in 40% of cases. Regular outbreak control meetings, involving relevant healthcare professionals, were held to plan appropriate interventions. The high rate of casual and untraceable contacts in this outbreak suggest that alternative control measures are necessary, including on-site testing and further health education regarding the oral transmission of syphilis. Continued vigilance for syphilis is essential, especially in those patients who are HIV positive.

Maintenance of demographic and hematological profiles in a long-lasting dengue fever outbreak: implications for management.

PubMed

Dos Santos Carmo, Andréia Moreira; Suzuki, Rodrigo Buzinaro; Riquena, Michele Marcondes; Eterovic, André; Sperança, Márcia Aparecida

2016-09-05

Dengue fever (DF) outbreaks present regionally specific epidemiological and clinical characteristics. In certain medium-sized cities (100 000-250 000 inhabitants) of São Paulo State, Brazil, and after reaching an incidence of 150 cases/100 000 inhabitants ("epidemiological threshold"), clinical diagnosis indicated dengue virus (DENV) infection. During this period, other seasonally infectious diseases with symptoms and physical signs mimicking DF can simultaneously occur, with the consequential overcrowding of health care facilities as the principal drawbacks. Confirmation of clinical diagnosis of DF with serological tests may help in avoiding faulty diagnosis in patients, who might later undergo dengue hemorrhagic fever (DHF) and the dengue-shock syndrome (DSS). Furthermore, demographic and hematological profiles of patients are useful in detecting specific early characteristics associated to DF, DHF and DSS. From March to June, 2007, 456 patients from Marilia in northwest São Paulo State who had only been diagnosed for DF by clinical criteria, underwent serologic testing for non-structural 1 (NS1) DENV antigens. Individual results were used in comparative analysis according to demographic (gender, age) and hematological (leukocyte and platelet counts, percentage of atypical lymphocytes) profiles. Temporal patterns were evaluated by subdividing data according to time of initial attendance, using recorded variables as predictors of DENV infection in logistic regression models and ROC curves. Serologic DENV detection was positive in 70.6 % of the patients. Lower leukocyte and platelet counts were the most important factors in predicting DENV infection (respective medians DENV + = 3 715 cells/ml and DENV- = 6 760 cells/ml, and DENV + = 134 896 cells/ml and DENV- = 223 872 cells/ml). Furthermore, all demographic and hematological profiles presented a conservative temporal pattern throughout this long-lasting outbreak. As consistency throughout the epidemic facilitated defining the conservation pattern throughout the early stages, this was useful for improving management during the remaining period.

Yellow Fever Virus in Haemagogus leucocelaenus and Aedes serratus Mosquitoes, Southern Brazil, 2008

PubMed Central

Cardoso, Jáder da C.; de Almeida, Marco A.B.; dos Santos, Edmilson; da Fonseca, Daltro F.; Sallum, Maria A.M.; Noll, Carlos A.; Monteiro, Hamilton A. de O.; Cruz, Ana C.R.; Carvalho, Valéria L.; Pinto, Eliana V.; Castro, Francisco C.; Neto, Joaquim P. Nunes; Segura, Maria N.O.

2010-01-01

Yellow fever virus (YFV) was isolated from Haemagogus leucocelaenus mosquitoes during an epizootic in 2001 in the Rio Grande do Sul State in southern Brazil. In October 2008, a yellow fever outbreak was reported there, with nonhuman primate deaths and human cases. This latter outbreak led to intensification of surveillance measures for early detection of YFV and support for vaccination programs. We report entomologic surveillance in 2 municipalities that recorded nonhuman primate deaths. Mosquitoes were collected at ground level, identified, and processed for virus isolation and molecular analyses. Eight YFV strains were isolated (7 from pools of Hg. leucocelaenus mosquitoes and another from Aedes serratus mosquitoes); 6 were sequenced, and they grouped in the YFV South American genotype I. The results confirmed the role of Hg. leucocelaenus mosquitoes as the main YFV vector in southern Brazil and suggest that Ae. serratus mosquitoes may have a potential role as a secondary vector. PMID:21122222

Yellow fever virus in Haemagogus leucocelaenus and Aedes serratus mosquitoes, southern Brazil, 2008.

PubMed

Cardoso, Jader da C; de Almeida, Marco A B; dos Santos, Edmilson; da Fonseca, Daltro F; Sallum, Maria A M; Noll, Carlos A; Monteiro, Hamilton A de O; Cruz, Ana C R; Carvalho, Valeria L; Pinto, Eliana V; Castro, Francisco C; Nunes Neto, Joaquim P; Segura, Maria N O; Vasconcelos, Pedro F C

2010-12-01

Yellow fever virus (YFV) was isolated from Haemagogus leucocelaenus mosquitoes during an epizootic in 2001 in the Rio Grande do Sul State in southern Brazil. In October 2008, a yellow fever outbreak was reported there, with nonhuman primate deaths and human cases. This latter outbreak led to intensification of surveillance measures for early detection of YFV and support for vaccination programs. We report entomologic surveillance in 2 municipalities that recorded nonhuman primate deaths. Mosquitoes were collected at ground level, identified, and processed for virus isolation and molecular analyses. Eight YFV strains were isolated (7 from pools of Hg. leucocelaenus mosquitoes and another from Aedes serratus mosquitoes); 6 were sequenced, and they grouped in the YFV South American genotype I. The results confirmed the role of Hg. leucocelaenus mosquitoes as the main YFV vector in southern Brazil and suggest that Ae. serratus mosquitoes may have a potential role as a secondary vector.

10 years of surveillance of human tularaemia in France.

PubMed

Mailles, A; Vaillant, V

2014-11-13

Tularaemia has been mandatorily notifiable in France since October 2002. The surveillance aims to detect early any infection possibly due to bioterrorism and to follow up disease trends. We report the results of national surveillance from 2002 to 2012. A case is defined as a patient with clinical presentation suggestive of tularaemia and biological confirmation of infection or an epidemiological link with a biologically confirmed case. Clinical, biological and epidemiological data are collected using a standardised notification form. From 2002 to 2012, 433 cases were notified, with a median age of 49 years (range 2 to 95 years) and a male–female sex ratio of 1.8. Most frequent clinical presentations were glandular tularaemia (n=200; 46%) and ulceroglandular tularaemia (n=113; 26%). Most frequent at-risk exposures were handling hares (n=179; 41%) and outdoor leisure exposure to dust aerosols (n=217; 50%). Tick bites were reported by 82 patients (19%). Ten clusters (39 cases) were detected over the 10-year period, as well as a national outbreak during winter 2007/2008. The tularaemia surveillance system is able to detect small clusters as well as major outbreaks. Surveillance data show exposure to dust aerosols during outdoor leisure activities to be a major source of contamination in France.

Water-borne protozoa parasites: The Latin American perspective.

PubMed

Rosado-García, Félix Manuel; Guerrero-Flórez, Milena; Karanis, Gabriele; Hinojosa, María Del Carmen; Karanis, Panagiotis

2017-07-01

Health systems, sanitation and water access have certain limitations in nations of Latin America (LA): typical matters of developing countries. Water is often contaminated and therefore unhealthy for the consumers and users. Information on prevalence and detection of waterborne parasitic protozoa are limited or not available in LA. Only few reports have documented in this field during the last forty years and Brazil leads the list, including countries in South America and Mexico within Central America region and Caribbean islands. From 1979 to 2015, 16 outbreaks of waterborne-protozoa, were reported in Latin American countries. T. gondii and C. cayetanensis were the protozoa, which caused more outbreaks and Giardia spp. and Cryptosporidium spp. were the most frequently found protozoa in water samples. On the other hand, Latin America countries have not got a coherent methodology for detection of protozoa in water samples despite whole LA is highly vulnerable to extreme weather events related to waterborne-infections; although Brazil and Colombia have some implemented laws in their surveillance systems. It would be important to coordinate all surveillance systems in between all countries for early detection and measures against waterborne-protozoan and to establish effective and suitable diagnosis tools according to the country's economic strength and particular needs. Copyright © 2017 Elsevier GmbH. All rights reserved.

Molecular characterisation of measles virus strains among refugees from Central African Republic in Cameroon in 2014.

PubMed

Ndombo, P K; Ndze, V N; Mbarga, F D; Anderson, R; Acho, A; Ebua Chia, J; Njamnshi, A K; Rota, P A; Waku-Kouomou, D

2018-02-01

Measles is a highly infectious human viral disease caused by measles virus (MeV). An estimated 114 900 measles deaths occurred worldwide in 2014. There are currently eight clades (A-H) comprised 24 MeV genotypes. We sought to characterise MeVs among Central African Republic (CAR) refugees during the 2014 measles epidemic in Cameroon. Samples were collected from children <15 years with suspected measles infections in two refugee camps in the east region of Cameroon. Viral RNA was extracted directly from urine samples. RNA detection of MeV RNA was performed with real-time reverse transcription polymerase chain reaction (PCR) to amplify a 634 bp nucleotide fragment of the N gene. The sequence of the PCR product was obtained to determine the genotype. MeV RNA was detected in 25 out of 30 samples from suspected cases, and among the 25 positive samples, MeV sequences were obtained from 20. The MeV strains characterised were all genotype B3. The MeV strains from genotype B3 found in this outbreak were more similar to those circulating in Northern Cameroon in 2010-2011 than to MeV strains circulating in the CAR in 2011. Surveillance system should be improved to focus on refugees for early detection of and response to outbreaks.

Molecular analysis of an oyster-related norovirus outbreak.

PubMed

Nenonen, Nancy P; Hannoun, Charles; Olsson, Margareta B; Bergström, Tomas

2009-06-01

Contaminated raw oysters were implicated in a severe outbreak of norovirus (NoV) gastroenteritis affecting 30 restaurant guests. To define the outbreak source by using molecular methods to characterize NoV strains detected in patient and oyster samples. Molecular epidemiological studies based on nucleotide sequencing and phylogenetic analyses of patient and oyster NoV strains, and comparison to background dataset. NoV genotype (G) I.1 was detected in the one patient stool analyzed by in-house TaqMan real time RT-PCR and classical nested RT-PCR targeting NoV RNA-dependent polymerase (RdRp, 285 nt), and by nested RT-PCR targeting RdRp-capsid-poly(A)-3' (3085 nt). Patient strain showed >or=99% similarity (285 nt) with three NoV strains detected in two of five oysters examined by classical nested RT-PCR (RdRp). A third oyster tested positive for NoV GII.3. Phylogenetic analysis showed clustering of patient and oyster strains related to this outbreak with GI.1 strains from previous local outbreaks, and mussel studies. Sequence data revealed >or=99% similarity (285 nt) between NoV GI.1 strains detected in patient stool and suspect oysters, linking the contaminated oysters to the outbreak. Identification of human NoV GI and GII strains in oysters indicated contamination of human fecal origin, presumably from inappropriate storage in the harbor. Comparative long-fragment analysis of the patient strain revealed 99% similarity (3085 nt) with NoV GI.1 strains detected in previous outbreaks and environmental mussel studies from West Sweden, 87% with M87661 (Norwalk68) and 96% with L23828 (SRSV-KY-89/89/J). These results indicated considerable genomic stability of NoV GI.1 strains over time.

Laboratory and Molecular Characterization of Dengue Viruses in a 2014 Outbreak in Guangfo Region, Southern China.

PubMed

Luo, Zhao-Fan; Hu, Bo; Zhang, Feng-Yi; Lin, Xiang-Hua; Xie, Xiao-Ying; Pan, Kun-Yi; Li, Hong-Yu; Ren, Rui-Wen; Zhao, Wen-Zhong

2017-09-25

Non-specific symptoms and low viremia levels make early diagnosis of dengue virus (DENV) infection challenging. This study aimed to i) identify laboratory markers that can be used to predict a DENV-positive diagnosis and ii) perform a molecular characterization of DENVs from the 2014 Guangdong epidemic. This retrospective study analyzed 1,044 patients from the Guangdong epidemic who were clinically suspected cases of dengue. Viral RNA was detected by real-time RT-PCR, and viral-specific NS1 antigen was detected using enzyme-linked immuno sorbent assay. A molecular phylogenetic analysis was performed for the with the DENV C-prM gene junction. Patients with dengue infection had leukopenia (2.8 × 10 9 /L), thrombocytopenia (109.0 × 10 9 /L), elevated aspartate aminotransferase (56.0 IU/L) and alanine aminotransferase (43.5 IU/L), and prolonged activated partial thromboplastin time (APTT, 33.5 s) (all P ＜ 0.001) compared to patients without dengue. The positive predictive value of leukopenia and thrombocytopenia for DENV infection were 96.9% and 93.0%, respectively. Leukopenia, thrombocytopenia, elevated aminotransferases, and prolonged APTT were useful predictive markers for an early diagnosis of DENV infection. Phylogenetic analysis indicated that the DENVs from the 2014 epidemic were closely related to a 2010 New Delhi strain and a 2013 Guangzhou strain. The 2014 epidemic consisted of co-circulating DENV-1 genotypes I and V from multiple origins. Efficient dengue surveillance can facilitate rapid response to future outbreaks.

An integrated approach for fusion of environmental and human health data for disease surveillance.

PubMed

Burkom, Howard S; Ramac-Thomas, Liane; Babin, Steven; Holtry, Rekha; Mnatsakanyan, Zaruhi; Yund, Cynthia

2011-02-28

This paper describes the problem of public health monitoring for waterborne disease outbreaks using disparate evidence from health surveillance data streams and environmental sensors. We present a combined monitoring approach along with examples from a recent project at the Johns Hopkins University Applied Physics Laboratory in collaboration with the U.S. Environmental Protection Agency. The project objective was to build a module for the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) to include water quality data with health indicator data for the early detection of waterborne disease outbreaks. The basic question in the fused surveillance application is 'What is the likelihood of the public health threat of interest given recent information from available sources of evidence?' For a scientific perspective, we formulate this question in terms of the estimation of positive predictive value customary in classical epidemiology, and we present a solution framework using Bayesian Networks (BN). An overview of the BN approach presents advantages, disadvantages, and required adaptations needed for a fused surveillance capability that is scalable and robust relative to the practical data environment. In the BN project, we built a top-level health/water-quality fusion BN informed by separate waterborne-disease-related networks for the detection of water contamination and human health effects. Elements of the art of developing networks appropriate to this environment are discussed with examples. Results of applying these networks to a simulated contamination scenario are presented. Copyright © 2011 John Wiley & Sons, Ltd.

Real-time monitoring of school absenteeism to enhance disease surveillance: a pilot study of a mobile electronic reporting system.

PubMed

Lawpoolsri, Saranath; Khamsiriwatchara, Amnat; Liulark, Wongwat; Taweeseneepitch, Komchaluch; Sangvichean, Aumnuyphan; Thongprarong, Wiraporn; Kaewkungwal, Jaranit; Singhasivanon, Pratap

2014-05-12

School absenteeism is a common source of data used in syndromic surveillance, which can eventually be used for early outbreak detection. However, the absenteeism reporting system in most schools, especially in developing countries, relies on a paper-based method that limits its use for disease surveillance or outbreak detection. The objective of this study was to develop an electronic real-time reporting system on school absenteeism for syndromic surveillance. An electronic (Web-based) school absenteeism reporting system was developed to embed it within the normal routine process of absenteeism reporting. This electronic system allowed teachers to update students' attendance status via mobile tablets. The data from all classes and schools were then automatically sent to a centralized database for further analysis and presentation, and for monitoring temporal and spatial patterns of absent students. In addition, the system also had a disease investigation module, which provided a link between absenteeism data from schools and local health centers, to investigate causes of fever among sick students. The electronic school absenteeism reporting system was implemented in 7 primary schools in Bangkok, Thailand, with total participation of approximately 5000 students. During May-October 2012 (first semester), the percentage of absentees varied between 1% and 10%. The peak of school absenteeism (sick leave) was observed between July and September 2012, which coincided with the peak of dengue cases in children aged 6-12 years being reported to the disease surveillance system. The timeliness of a reporting system is a critical function in any surveillance system. Web-based application and mobile technology can potentially enhance the use of school absenteeism data for syndromic surveillance and outbreak detection. This study presents the factors that determine the implementation success of this reporting system.

Implementation of Nationwide Real-time Whole-genome Sequencing to Enhance Listeriosis Outbreak Detection and Investigation

PubMed Central

Jackson, Brendan R.; Tarr, Cheryl; Strain, Errol; Jackson, Kelly A.; Conrad, Amanda; Carleton, Heather; Katz, Lee S.; Stroika, Steven; Gould, L. Hannah; Mody, Rajal K.; Silk, Benjamin J.; Beal, Jennifer; Chen, Yi; Timme, Ruth; Doyle, Matthew; Fields, Angela; Wise, Matthew; Tillman, Glenn; Defibaugh-Chavez, Stephanie; Kucerova, Zuzana; Sabol, Ashley; Roache, Katie; Trees, Eija; Simmons, Mustafa; Wasilenko, Jamie; Kubota, Kristy; Pouseele, Hannes; Klimke, William; Besser, John; Brown, Eric; Allard, Marc; Gerner-Smidt, Peter

2016-01-01

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens. PMID:27090985

Identification of Norovirus as the Top Enteric Viruses Detected in Adult Cases with Acute Gastroenteritis

PubMed Central

Liu, Li-Juan; Liu, Wei; Liu, Yun-Xi; Xiao, Hong-Jv; Jia, Ning; Liu, Gang; Tong, Yi-Gang; Cao, Wu-Chun

2010-01-01

To elucidate the importance of the norovirus and other enteric viruses, and the difference of the genetic relatedness on norovirus between the outbreak and sporadic cases, a total of 557 stool samples, consisting of 503 sporadic cases and 54 samples of 4 outbreaks were collected and tested for norovirus and other enteric viruses in Beijing, China, July 2007–June 2008. The data showed norovirus, rotavirus, astrovirus, and sapovirus, were detected in 26.6%, 6.1%, 1.8%, and 0.5%, respectively. Norovirus was detected almost throughout the surveillance period, norovirus co-infecting with rotavirus, astrovirus, and sapovirus, respectively, were identified both in outbreak and the sporadic cases. GII.4/2006 was identified as the predominant strain circulating both in outbreak and sporadic cases. The results showed that norovirus was rather the important agent than other enteric viruses affected adults with acute gastroenteritis; no significant genetic relatedness of the dominant strains was found between the outbreak and sporadic cases. PMID:20348525

A concept for routine emergency-care data-based syndromic surveillance in Europe.

PubMed

Ziemann, A; Rosenkötter, N; Garcia-Castrillo Riesgo, L; Schrell, S; Kauhl, B; Vergeiner, G; Fischer, M; Lippert, F K; Krämer, A; Brand, H; Krafft, T

2014-11-01

We developed a syndromic surveillance (SyS) concept using emergency dispatch, ambulance and emergency-department data from different European countries. Based on an inventory of sub-national emergency data availability in 12 countries, we propose framework definitions for specific syndromes and a SyS system design. We tested the concept by retrospectively applying cumulative sum and spatio-temporal cluster analyses for the detection of local gastrointestinal outbreaks in four countries and comparing the results with notifiable disease reporting. Routine emergency data was available daily and electronically in 11 regions, following a common structure. We identified two gastrointestinal outbreaks in two countries; one was confirmed as a norovirus outbreak. We detected 1/147 notified outbreaks. Emergency-care data-based SyS can supplement local surveillance with near real-time information on gastrointestinal patients, especially in special circumstances, e.g. foreign tourists. It most likely cannot detect the majority of local gastrointestinal outbreaks with few, mild or dispersed cases.

Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis.

PubMed

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-03-29

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes . There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places.

[Study of epidemiological characteristics and viral sources of dengue fever outbreak in Guangxi Zhuang Autonomous Region, 2014].

PubMed

Chen, M M; Tan, Y; Tang, Z Z; Lin, M; Zhou, K J; He, W T; Yang, Y P; Wang, J

2016-10-10

Objective: To understand the epidemiological characteristics and viral sources of dengue fever outbreak in Guangxi Zhuang Autonomous Region (Guangxi) in 2014. Methods: A combined analysis of epidemiological characteristics and genetic characteristics were performed in this study. The time, population and area distributions of the cases were analyzed. Serum samples were collected from dengue fever cases to detect NS1 antigen by using commercial ELISA kits according to the guideline of the manufacture. RT-PCR assay was conducted to detect dengue virus in NS1 positive samples. Phylogenetic tree based on E gene sequence of dengue virus were further analyzed. Results: During September-December 2014, an outbreak of dengue fever caused by dengue virus type 1 and 2 occurred in Guangxi, a total of 854 cases were reported without death, including 712 laboratory confirmed cases and 142 clinical diagnosed cases, in which 79.63 % (680/854) occurred during 22 September-21 October 2014. All the cases had typical dengue fever symptoms. Most cases occurred in Nanning and Wuzhou, in which 83.61 % (714/854) were in age group 15-59 years; 46.60 % (398/854) were staff or people engaged in commercial service. A total 526 serum samples were tested for dengue virus serotype by RT-PCR assay. Among 414 positive samples, 345 were positive for dengue virus type 1 (DENV-1) and 69 were positive for dengue virus type 2 (DENV-2), no DENV-3 and DENV-4 were detected. The results of phylogenetic analysis of E gene sequence indicated that the sequences of 99.12 % (113/114) of DENV-1 strains in Nanning in China shared 100.00 % homology with the isolate (SG EHI D1/529Y13) from Singapore in 2013, which belonged to the genotype Ⅰ; All the DENV-2 isolates from Wuzhou shared 99.80 % homology with the isolate (D14005) from Guangdong province, which belonged to genotype Cosmopolitan. Conclusions: The outbreak was caused by DENV-1 from Singapore and DENV-2 from Guangdong province in China. It is necessary to strengthen the surveillance and early warning for imported dengue fever, conduct vector control and improve the diagnosis of suspected dengue fever cases for the effective control of dengue fever outbreak.

METHODS FOR DETECTION OF CRYPTOSPORIDIUM SP. AND GIARDIA SP.

EPA Science Inventory

There have been several waterborne outbreaks of giardiasis caused by infection with Giardia lamblia, and cryptosporidiosis, caused by infection with Cryptosporidium parvum. These outbreaks have created a need to detect these organisms in source and finished drinking water. The pr...

Cell Phones ≠ Self and Other Problems with Big Data Detection and Containment during Epidemics.

PubMed

Erikson, Susan L

2018-03-08

Evidence from Sierra Leone reveals the significant limitations of big data in disease detection and containment efforts. Early in the 2014-2016 Ebola epidemic in West Africa, media heralded HealthMap's ability to detect the outbreak from newsfeeds. Later, big data-specifically, call detail record data collected from millions of cell phones-was hyped as useful for stopping the disease by tracking contagious people. It did not work. In this article, I trace the causes of big data's containment failures. During epidemics, big data experiments can have opportunity costs: namely, forestalling urgent response. Finally, what counts as data during epidemics must include that coming from anthropological technologies because they are so useful for detection and containment. © 2018 The Authors Medical Anthropology Quarterly published by Wiley Periodicals, Inc. on behalf of American Anthropological Association.

Unsterilized Feed as the Apparent Cause of a Mouse Parvovirus Outbreak

PubMed Central

2013-01-01

In early 2009, we experienced a widespread outbreak of mouse parvoviruses 1 and 2 (MPV) at our institution, which encompasses approximately 50,000 cages located in 7 campus vivaria. MPV had not been detected for several years; however, during a single 4-mo sentinel-testing rotation comprising all racks at the institution, 72 of 927 rack sentinels tested serologically positive for MPV1, MPV2, or both. PCR of fecal samples from several index cases confirmed MPV. Each sentinel-positive rack contained between 0 and 10 infected colony cages. Positive racks appeared to be randomly distributed, although several small facilities escaped infection. We investigated how this infection may have entered the facilities, in which mice were maintained in barrier caging with sterilized feed, bedding, and equipment, and procedures were in place to prevent incoming infection and cross-contamination. The only widespread change that occurred during the 3 mo preceding the first positive test was that every cage had been treated for 12 wk with an unsterilized fenbendazole-medicated diet. At the completion of fenbendazole treatment, sterilized feed was reinstituted. Evidence of MPV infection was eliminated within 7 mo via an intensive test-and-remove policy in combination with movement controls, and we have had no further positive tests in the 3.5 y since the outbreak. Although the possibility remains that MPV infection resulted from fomites or undetected infections in incoming mice, the timing and extent of this outbreak together with the complete absence of new cases after sterilized feed was reinstituted strongly implicate unsterilized feed as the source of this MPV outbreak. PMID:23562038

Unsterilized feed as the apparent cause of a mouse parvovirus outbreak.

PubMed

Watson, Julie

2013-01-01

In early 2009, we experienced a widespread outbreak of mouse parvoviruses 1 and 2 (MPV) at our institution, which encompasses approximately 50,000 cages located in 7 campus vivaria. MPV had not been detected for several years; however, during a single 4-mo sentinel-testing rotation comprising all racks at the institution, 72 of 927 rack sentinels tested serologically positive for MPV1, MPV2, or both. PCR of fecal samples from several index cases confirmed MPV. Each sentinel-positive rack contained between 0 and 10 infected colony cages. Positive racks appeared to be randomly distributed, although several small facilities escaped infection. We investigated how this infection may have entered the facilities, in which mice were maintained in barrier caging with sterilized feed, bedding, and equipment, and procedures were in place to prevent incoming infection and cross-contamination. The only widespread change that occurred during the 3 mo preceding the first positive test was that every cage had been treated for 12 wk with an unsterilized fenbendazole-medicated diet. At the completion of fenbendazole treatment, sterilized feed was reinstituted. Evidence of MPV infection was eliminated within 7 mo via an intensive test-and-remove policy in combination with movement controls, and we have had no further positive tests in the 3.5 y since the outbreak. Although the possibility remains that MPV infection resulted from fomites or undetected infections in incoming mice, the timing and extent of this outbreak together with the complete absence of new cases after sterilized feed was reinstituted strongly implicate unsterilized feed as the source of this MPV outbreak.

Molecular Characterization of the 2016 New World Screwworm (Diptera: Calliphoridae) Outbreak in the Florida Keys.

PubMed

Dupuis, Julian R; Guerrero, Felix D; Skoda, Steven R; Phillips, Pamela L; Welch, John B; Schlater, Jack L; Azeredo-Espin, Ana Maria L; Pérez de León, Adalberto A; Geib, Scott M

2018-05-19

New World screwworm (NWS), Cochliomyia hominivorax (Coquerel 1858) (Diptera: Calliphoridae), is a myiasis-causing fly that can be a serious threat to the health of livestock, wildlife, and humans. Its progressive eradication from the southern United States, Mexico, and Central America from the 1950s to 2000s is an excellent example of successful pest management using sterile insect technique (SIT). In late 2016, autochthonous NWS were detected in the Florida Keys, representing this species' first invasion in the United States in >30 yr. Rapid use of quarantine and SIT was successful in eliminating the infestation by early 2017; however, the geographic source of this infestation remains unknown. Here, we use amplicon sequencing to generate mitochondrial and nuclear sequence data representing all confirmed cases of NWS from this infestation, and compare these sequences to preexisting data sets sampling the native distribution of NWS. We ask two questions regarding the FL Keys outbreak. First, is this infestation the result of a single invasion from one source, or multiple invasions from different sources? And second, what is the geographic origin of this invasion? We found virtually no sequence variation between specimens collected from the FL Keys outbreak, which is consistent with a single source of introduction. However, we also found very little geographic resolution in any of the data sets, which precludes identification of the source of this outbreak. Our lack of success in answering our second question speaks to the need for finer-scale genetic or genomic assessments of NWS population structure, which would facilitate source determination of potential future outbreaks.

Prevalence of small round structured virus infections in acute gastroenteritis outbreaks in Tokyo.

PubMed

Sekine, S; Okada, S; Hayashi, Y; Ando, T; Terayama, T; Yabuuchi, K; Miki, T; Ohashi, M

1989-01-01

During the three-year period from 1984 to 1987, 506 acute gastroenteritis outbreaks involving 14,383 patients were reported to the Bureau of Public Health, Tokyo Metropolitan Government. Eighty (4,324 patients) of 150 outbreaks (4,860 patients) from which etiologic agents were not identified were subjected to virological investigation. Spherical particles of 28-32 nm in diameter with capsomere-like structures on the surface were detected in patients' stool specimens. Buoyant density of the particles appeared to be 1.36 to 1.40 g/ml in CsCl. Seroconversion to the particles was observed in patients by immune electron microscopy. From these observations, we concluded that the detected particles were members of small round structured virus (SRSV), and that they were implicated in the etiologically ill-defined outbreaks encountered. Prevalence of SRSV infections in these outbreaks was examined by electron microscopy. SRSV was positive in 83.8% of the outbreaks, and 96.4% of the cases. SRSV-positive outbreaks usually occurred during winter in contrast to bacterial outbreaks which often occurred in the summer season. Of 80 outbreaks examined, 53 were associated with the ingestion of oysters, and the remaining 27 mostly with food other than oysters. Oyster-associated outbreaks usually occurred on a small scale, while unassociated ones on diverse scales ranged from family clusters to large outbreaks.

Distribution of outbreak reporting in health care institutions by day of the week.

PubMed

Amirov, Chingiz; Walton, Ryan N; Ahmed, Sarah; Binns, Malcolm A; Van Toen, Jane E; Candon, Heather L

2012-12-01

The notion that outbreaks are more likely to occur on Friday is prevalent among staff in health care institutions. However, there is little evidence to support or discredit this notion. We postulated that outbreaks were no more likely to be reported on any particular day of the week. A total of 901 institutional outbreaks in Toronto health care facilities were tabulated according to type, outbreak setting, and day of the week reported. A χ(2) goodness-of-fit test compared daily values for 7-day per week and 5-day per week periods. Post hoc partitioning was used to pinpoint specific day(s) of the week that differed significantly. Fewer outbreaks were reported on Saturdays and Sundays. Further analysis examined the distribution of outbreak reporting specifically focusing on the Monday to Friday weekday period. Among the weekdays, higher proportions of outbreaks were reported on Mondays and Fridays. Our null hypothesis was rejected. Overall, Mondays and Fridays had the highest occurrence of outbreak reporting. We suggest that this might be due to "deadline" and "catch-up" reporting related to the "weekend effect," whereby structural differences in weekend staffing affect detection of outbreaks. Such delays warrant reexamination of surveillance processes for timely outbreak detection independent of calendar cycle. Copyright © 2012 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Detection limit used for early warning in public health surveillance.

PubMed

Kobari, Tsuyoshi; Iwaki, Kazuo; Nagashima, Tomomi; Ishii, Fumiyoshi; Hayashi, Yuzuru; Yajima, Takehiko

2009-06-01

A theory of detection limit, developed in analytical chemistry, is applied to public health surveillance to detect an outbreak of national emergencies such as natural disaster and bioterrorism. In this investigation, the influenza epidemic around the Tokyo area from 2003 to 2006 is taken as a model of normal and large-scale epidemics. The detection limit of the normal epidemic is used as a threshold with a specified level of significance to identify a sign of the abnormal epidemic among the daily variation in anti-influenza drug sales at community pharmacies. While auto-correlation of data is often an obstacle to an unbiased estimator of standard deviation involved in the detection limit, the analytical theory (FUMI) can successfully treat the auto-correlation of the drug sales in the same way as the auto-correlation appearing as 1/f noise in many analytical instruments.

Fever detection from free-text clinical records for biosurveillance.

PubMed

Chapman, Wendy W; Dowling, John N; Wagner, Michael M

2004-04-01

Automatic detection of cases of febrile illness may have potential for early detection of outbreaks of infectious disease either by identification of anomalous numbers of febrile illness or in concert with other information in diagnosing specific syndromes, such as febrile respiratory syndrome. At most institutions, febrile information is contained only in free-text clinical records. We compared the sensitivity and specificity of three fever detection algorithms for detecting fever from free-text. Keyword CC and CoCo classified patients based on triage chief complaints; Keyword HP classified patients based on dictated emergency department reports. Keyword HP was the most sensitive (sensitivity 0.98, specificity 0.89), and Keyword CC was the most specific (sensitivity 0.61, specificity 1.0). Because chief complaints are available sooner than emergency department reports, we suggest a combined application that classifies patients based on their chief complaint followed by classification based on their emergency department report, once the report becomes available.

Deep sequencing of H7N8 avian influenza viruses from surveillance zone supports H7N8 high pathogenicity avian influenza was limited to a single outbreak farm in Indiana during 2016

USDA-ARS?s Scientific Manuscript database

In mid-January 2016, an outbreak of H7N8 high pathogenicity avian influenza (HPAI) virus in commercial turkeys occurred in Indiana. The outbreak was first detected by an increase in mortality followed by laboratory confirmation of H7N8 HPAI virus. Surveillance within the 10 km Control Zone detected...

Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore.

PubMed

Shi, Yuan; Liu, Xu; Kok, Suet-Yheng; Rajarethinam, Jayanthi; Liang, Shaohong; Yap, Grace; Chong, Chee-Seng; Lee, Kim-Sung; Tan, Sharon S Y; Chin, Christopher Kuan Yew; Lo, Andrew; Kong, Waiming; Ng, Lee Ching; Cook, Alex R

2016-09-01

With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore's dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak alerts and policy decision support in Singapore. Environ Health Perspect 124:1369-1375; http://dx.doi.org/10.1289/ehp.1509981.

Characterizing the reproduction number of epidemics with early subexponential growth dynamics

PubMed Central

Viboud, Cécile; Simonsen, Lone; Moghadas, Seyed M.

2016-01-01

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible–infectious–removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The generalized-growth concept also provides us a compelling argument for the unexpected extinction of certain emerging disease outbreaks during the early ascending phase. Overall, our approach promotes a more reliable and data-driven characterization of the early epidemic phase, which is important for accurate estimation of the reproduction number and prediction of disease impact. PMID:27707909

Forest defoliator outbreaks under climate change: effects on the frequency and severity of outbreaks of five pine insect pests.

PubMed

Haynes, Kyle J; Allstadt, Andrew J; Klimetzek, Dietrich

2014-06-01

To identify general patterns in the effects of climate change on the outbreak dynamics of forest-defoliating insect species, we examined a 212-year record (1800-2011) of outbreaks of five pine-defoliating species (Bupalus piniarius, Panolis flammea, Lymantria monacha, Dendrolimus pini, and Diprion pini) in Bavaria, Germany for the evidence of climate-driven changes in the severity, cyclicity, and frequency of outbreaks. We also accounted for historical changes in forestry practices and examined effects of past insecticide use to suppress outbreaks. Analysis of relationships between severity or occurrence of outbreaks and detrended measures of temperature and precipitation revealed a mixture of positive and negative relationships between temperature and outbreak activity. Two moth species (P. flammea and Dendrolimus pini) exhibited lower outbreak activity following years or decades of unusually warm temperatures, whereas a sawfly (Diprion pini), for which voltinism is influenced by temperature, displayed increased outbreak occurrence in years of high summer temperatures. We detected only one apparent effect of precipitation, which showed Dendrolimus pini outbreaks tending to follow drought. Wavelet analysis of outbreak time series suggested climate change may be associated with collapse of L. monacha and Dendrolimus pini outbreak cycles (loss of cyclicity and discontinuation of outbreaks, respectively), but high-frequency cycles for B. piniarius and P. flammea in the late 1900s. Regional outbreak severity was generally not related to past suppression efforts (area treated with insecticides). Recent shifts in forestry practices affecting tree species composition roughly coincided with high-frequency outbreak cycles in B. piniarius and P. flammea but are unlikely to explain the detected relationships between climate and outbreak severity or collapses of outbreak cycles. Our results highlight both individualistic responses of different pine-defoliating species to climate changes and some patterns that are consistent across defoliator species in this and other forest systems, including collapsing of population cycles. © 2014 John Wiley & Sons Ltd.

TESTING METHODS FOR DETECTION OF CRYPTOSPORIDIUM SPP. IN WATER SAMPLES

EPA Science Inventory

A large waterborne outbreak of cryptosporidiosis in Milwaukee, Wisconsin, U.S.A. in 1993 prompted a search for ways to prevent large-scale waterborne outbreaks of protozoan parasitoses. Methods for detecting Cryptosporidium parvum play an integral role in strategies that lead to...

Detection of multiple enteric virus strains within a foodborne outbreak of gastroenteritis: an indication of the source of contamination.

PubMed Central

Gallimore, C. I.; Pipkin, C.; Shrimpton, H.; Green, A. D.; Pickford, Y.; McCartney, C.; Sutherland, G.; Brown, D. W. G.; Gray, J. J.

2005-01-01

An outbreak of acute gastroenteritis of suspected viral aetiology occurred in April 2003 in the British Royal Fleet Auxiliary ship (RFA) Argus deployed in the Northern Arabian Gulf. There were 37 cases amongst a crew of 400 personnel. Of 13 samples examined from cases amongst the crew, six enteric viruses were detected by reverse transcriptase polymerase chain reaction (RT-PCR). Five different viruses were identified including, three norovirus genotypes, a sapovirus and a rotavirus. No multiple infections were detected. A common food source was implicated in the outbreak and epidemiological analysis showed a statistically significant association with salad as the source of the outbreak, with a relative risk of 3.41 (95% confidence interval of 1.7-6.81) of eating salad on a particular date prior to the onset of symptoms. Faecal contamination of the salad at source was the most probable explanation for the diversity of viruses detected and characterized. PMID:15724709

Massively multiplexed microbial identification using resequencing DNA microarrays for outbreak investigation

NASA Astrophysics Data System (ADS)

Leski, T. A.; Ansumana, R.; Jimmy, D. H.; Bangura, U.; Malanoski, A. P.; Lin, B.; Stenger, D. A.

2011-06-01

Multiplexed microbial diagnostic assays are a promising method for detection and identification of pathogens causing syndromes characterized by nonspecific symptoms in which traditional differential diagnosis is difficult. Also such assays can play an important role in outbreak investigations and environmental screening for intentional or accidental release of biothreat agents, which requires simultaneous testing for hundreds of potential pathogens. The resequencing pathogen microarray (RPM) is an emerging technological platform, relying on a combination of massively multiplex PCR and high-density DNA microarrays for rapid detection and high-resolution identification of hundreds of infectious agents simultaneously. The RPM diagnostic system was deployed in Sierra Leone, West Africa in collaboration with Njala University and Mercy Hospital Research Laboratory located in Bo. We used the RPM-Flu microarray designed for broad-range detection of human respiratory pathogens, to investigate a suspected outbreak of avian influenza in a number of poultry farms in which significant mortality of chickens was observed. The microarray results were additionally confirmed by influenza specific real-time PCR. The results of the study excluded the possibility that the outbreak was caused by influenza, but implicated Klebsiella pneumoniae as a possible pathogen. The outcome of this feasibility study confirms that application of broad-spectrum detection platforms for outbreak investigation in low-resource locations is possible and allows for rapid discovery of the responsible agents, even in cases when different agents are suspected. This strategy enables quick and cost effective detection of low probability events such as outbreak of a rare disease or intentional release of a biothreat agent.

Detection of dengue virus in individual Aedes aegypti mosquitoes in Delhi, India.

PubMed

Vikram, Kumar; Nagpal, B N; Pande, Veena; Srivastava, Aruna; Saxena, Rekha; Singh, Himmat; Gupta, Sanjeev K; Tuli, N R; Yadav, N K; Olivier, Telle; Richard, Paul; Valecha, Neena

2015-06-01

Delhi, the capital city of India, has so far witnessed several outbreaks of dengue fever since 1967 (last one reported in 2013). Improved virological and entomological surveillance are the only tools that can help in prevention of dengue as well as in the development of dengue control programmes. The aim of the study was to conduct a prospective field study to detect dengue virus in adult Aedes aegypti mosquitoes collected from various localities represented by different socioeconomic groups in Delhi. The study areas were selected and categorized into high, medium and low income groups on the basis of socioeconomical characteristics of the resident population, where dengue cases were reported during the past three years by MCD. Dengue viral infection was detected in the head squash of each adult mosquito by immunofluorescent assay (IFA) employing monoclonal antibodies against dengue virus (DENV). A total of 2408 females and 1206 males of Ae. aegypti were collected and tested by IFA. Out of 2408 Ae. aegypti females, 14 were found positive, with minimum infection rate (MIR) of 5.8 per 1000 mosquitoes. Among the 18 study areas, 11 localities were found positive for dengue virus infection. Low income group (LIG) areas showed highest mosquito infectivity (9.8), followed by medium income group (MIG), i.e. 6.2; while least was observed in high income group (HIG), i.e. 1.3. No vertical transmission of dengue virus could be detected in 1206 Ae. aegypti males collected. The study concludes that there was high MIR in the identified localities of low and medium income groups. Estimation of MIR in a female Aedes mosquito in the existing arsenals for dengue surveillance would be an added advantage for early warning of dengue outbreak. The presence of infected mosquitoes in identified localities of Delhi was alarming and require rigorous vector surveillance so that the severe outbreaks can be prevented.

Detecting and tracking dust outbreaks by using high temporal resolution satellite data

NASA Astrophysics Data System (ADS)

Sannazzaro, Filomena; Marchese, Francesco; Filizzola, Carolina; Tramutoli, Valerio; Pergola, Nicola; Mazzeo, Giuseppe; Paciello, Rossana

2013-04-01

A dust storm is a meteorological phenomenon generated by the action of wind, mainly in arid and semi-arid regions of the planet, particularly at subtropical latitudes. Dust outbreaks, of which frequency increases from year to year concurrently with climate change and reduction of moisture in the soil, may strongly impact on human activity as well as on environment and climate. Efficient early warning systems are then required to monitor them and to mitigate their effects. Satellite remote sensing thanks to a global coverage, to a high frequency of observation and low costs of data represents an important tool for studying and monitoring dust outbreaks. Several techniques have been then proposed to detect and monitor these phenomena from space, analyzing signal in different bands of the electromagnetic spectrum. In particular, methods based on the reverse absorption behaviour of silicate particles in comparison with ice crystals and water droplets, at 11 and 12 micron wavelengths, have been largely employed for detecting dust, although some important issues both in terms of reliability and sensitivity still remain. In this work, an optimized configuration of an innovative algorithm for dust detection, based on the largely accepted Robust Satellite Techniques (RST) multi-temporal approach, is then presented. This optimized algorithm configuration is tested here on Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, analyzing some important dust events affecting Mediterranean basin in recent years. Results of this study, assessed on the basis of independent satellite-based aerosol products, generated by using the Total Ozone Mapping Spectrometer (TOMS), the Ozone Monitoring Instrument (OMI), and the Moderate Resolution Imaging Spectroradiometer (MODIS) data, show that when the spectral resolution of SEVIRI is properly exploited dust and meteorological clouds may be better discriminated. These results encourage further experimentations of the proposed algorithm in view of a possible future implementation in operational monitoring systems.

Molecular detection of bovine coronavirus in a diarrhea outbreak in pasture-feeding Nellore steers in southern Brazil.

PubMed

Ribeiro, Juliane; Lorenzetti, Elis; Alfieri, Alice Fernandes; Alfieri, Amauri Alcindo

2016-03-01

Worldwide diarrhea outbreaks in cattle herds are more frequently detected in calves being that diarrhea outbreaks in adult cattle are not common. Winter dysentery (WD) is a bovine coronavirus (BCoV) enteric infection that is more reported in Northern hemisphere. Seasonal outbreaks of WD in adult cattle occur mainly in dairy cows. WD has not been described in beef cattle herds of tropical countries. This study describes the molecular detection of BCoV in a diarrhea outbreak in beef cattle steers (Nellore) raised on pasture in Parana, southern Brazil. During the outbreak, the farm had about 600 fattening steers. Watery and bloody diarrhea unresponsive to systemic broad-spectrum antibiotic therapy reveals a morbidity rate of approximately 15 %. The BCoV N gene was identified in 42.9 % (6/14) of the diarrheic fecal samples evaluated by semi-nested polymerase chain reaction (SN-PCR) technique. Other enteric microorganisms occasionally identified in adult cattle and evaluated in this study such as bovine groups A, B, and C rotavirus, bovine viral diarrhea virus, bovine torovirus, aichivirus B, and Eimeria sp. were not identified in the fecal samples. To the best knowledge of the authors, this is the first description of the BCoV diagnosis in fecal samples collected in a diarrhea outbreak in adult beef cattle grazing in the grass in a tropical country.

Burkholderia stabilis outbreak associated with contaminated commercially-available washing gloves, Switzerland, May 2015 to August 2016

PubMed Central

Sommerstein, Rami; Führer, Urs; Lo Priore, Elia; Casanova, Carlo; Meinel, Dominik M; Seth-Smith, Helena MB; Kronenberg, Andreas; Koch, Daniel; Senn, Laurence; Widmer, Andreas F; Egli, Adrian; Marschall, Jonas

2017-01-01

We describe an outbreak of Burkholderia stabilis associated with contaminated washing gloves, a commercially available Class I medical device. Triggered by an increase in Burkholderia cepacia complex (BCC) bacteremias and the detection of BCC in unopened packages of washing gloves, an ad hoc national outbreak committee comprising representatives of a public health organisation, a regulatory agency, and an expert association convened and commissioned an outbreak investigation. The investigation included retrospective case finding across Switzerland and whole genome sequencing (WGS) of isolates from cases and gloves. The investigation revealed that BCC were detected in clinical samples of 46 cases aged 17 to 91 years (33% females) from nine institutions between May 2015 and August 2016. Twenty-two isolates from case patients and 16 from washing gloves underwent WGS. All available outbreak isolates clustered within a span of < 19 differing alleles, while 13 unrelated clinical isolates differed by > 1,500 alleles. This BCC outbreak was rapidly identified, communicated, investigated and halted by an ad hoc collaboration of multiple stakeholders. WGS served as useful tool for confirming the source of the outbreak. This outbreak also highlights current regulatory limitations regarding Class I medical devices and the usefulness of a nationally coordinated outbreak response. PMID:29233255

There's No Place Like Home: Crown-of-Thorns Outbreaks in the Central Pacific Are Regionally Derived and Independent Events

PubMed Central

Timmers, Molly A.; Bird, Christopher E.; Skillings, Derek J.; Smouse, Peter E.; Toonen, Robert J.

2012-01-01

One of the most significant biological disturbances on a tropical coral reef is a population outbreak of the fecund, corallivorous crown-of-thorns sea star, Acanthaster planci. Although the factors that trigger an initial outbreak may vary, successive outbreaks within and across regions are assumed to spread via the planktonic larvae released from a primary outbreak. This secondary outbreak hypothesis is predominantly based on the high dispersal potential of A. planci and the assertion that outbreak populations (a rogue subset of the larger population) are genetically more similar to each other than they are to low-density non-outbreak populations. Here we use molecular techniques to evaluate the spatial scale at which A. planci outbreaks can propagate via larval dispersal in the central Pacific Ocean by inferring the location and severity of gene flow restrictions from the analysis of mtDNA control region sequence (656 specimens, 17 non-outbreak and six outbreak locations, six archipelagos, and three regions). Substantial regional, archipelagic, and subarchipelagic-scale genetic structuring of A. planci populations indicate that larvae rarely realize their dispersal potential and outbreaks in the central Pacific do not spread across the expanses of open ocean. On a finer scale, genetic partitioning was detected within two of three islands with multiple sampling sites. The finest spatial structure was detected at Pearl & Hermes Atoll, between the lagoon and forereef habitats (<10 km). Despite using a genetic marker capable of revealing subtle partitioning, we found no evidence that outbreaks were a rogue genetic subset of a greater population. Overall, outbreaks that occur at similar times across population partitions are genetically independent and likely due to nutrient inputs and similar climatic and ecological conditions that conspire to fuel plankton blooms. PMID:22363570

GHOST: global hepatitis outbreak and surveillance technology.

PubMed

Longmire, Atkinson G; Sims, Seth; Rytsareva, Inna; Campo, David S; Skums, Pavel; Dimitrova, Zoya; Ramachandran, Sumathi; Medrzycki, Magdalena; Thai, Hong; Ganova-Raeva, Lilia; Lin, Yulin; Punkova, Lili T; Sue, Amanda; Mirabito, Massimo; Wang, Silver; Tracy, Robin; Bolet, Victor; Sukalac, Thom; Lynberg, Chris; Khudyakov, Yury

2017-12-06

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

Whole Genome Sequencing versus Traditional Genotyping for Investigation of a Mycobacterium tuberculosis Outbreak: A Longitudinal Molecular Epidemiological Study

PubMed Central

Rückert, Christian; Nübel, Ulrich; Blom, Jochen; Wirth, Thierry; Jaenicke, Sebastian; Schuback, Sieglinde; Rüsch-Gerdes, Sabine; Supply, Philip; Kalinowski, Jörn; Niemann, Stefan

2013-01-01

Background Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. Methods and Findings During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. Conclusions Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context. Please see later in the article for the Editors' Summary PMID:23424287

Causes of Outbreaks Associated with Drinking Water in the United States from 1971 to 2006

PubMed Central

Craun, Gunther F.; Brunkard, Joan M.; Yoder, Jonathan S.; Roberts, Virginia A.; Carpenter, Joe; Wade, Tim; Calderon, Rebecca L.; Roberts, Jacquelin M.; Beach, Michael J.; Roy, Sharon L.

2010-01-01

Summary: Since 1971, the CDC, EPA, and Council of State and Territorial Epidemiologists (CSTE) have maintained the collaborative national Waterborne Disease and Outbreak Surveillance System (WBDOSS) to document waterborne disease outbreaks (WBDOs) reported by local, state, and territorial health departments. WBDOs were recently reclassified to better characterize water system deficiencies and risk factors; data were analyzed for trends in outbreak occurrence, etiologies, and deficiencies during 1971 to 2006. A total of 833 WBDOs, 577,991 cases of illness, and 106 deaths were reported during 1971 to 2006. Trends of public health significance include (i) a decrease in the number of reported outbreaks over time and in the annual proportion of outbreaks reported in public water systems, (ii) an increase in the annual proportion of outbreaks reported in individual water systems and in the proportion of outbreaks associated with premise plumbing deficiencies in public water systems, (iii) no change in the annual proportion of outbreaks associated with distribution system deficiencies or the use of untreated and improperly treated groundwater in public water systems, and (iv) the increasing importance of Legionella since its inclusion in WBDOSS in 2001. Data from WBDOSS have helped inform public health and regulatory responses. Additional resources for waterborne disease surveillance and outbreak detection are essential to improve our ability to monitor, detect, and prevent waterborne disease in the United States. PMID:20610821

Economic impact of a nationwide outbreak of salmonellosis: cost-benefit of early intervention.

PubMed

Roberts, J A; Sockett, P N; Gill, O N

1989-05-06

The recognition and investigation of an outbreak of food poisoning in 1982 due to chocolate contaminated with Salmonella napoli enabled the food that carried the salmonella to be identified and four fifths of the implicated consignment of chocolate to be withdrawn. The economic benefits of prompt intervention in the outbreak have been assessed. The cost of the outbreak was over 0.5 pounds m. It is estimated that five deaths were prevented by the intervention and that 185 admissions to hospital and 29,000 cases of S napoli enteritis were avoided. This successful investigation yielded a 3.5-fold rate of return to the public sector and a 23.3-fold return to society on an investment in public health surveillance. A methodology is described that can be used to estimate the benefits of early intervention in outbreaks of foodborne illness and topics for further research are suggested. It is concluded that public health authorities and industry have much to gain by collaborating in the research into the design of cost effective programmes to prevent foodborne infections.

Ebola Virus Disease: Rapid Diagnosis and Timely Case Reporting are Critical to the Early Response for Outbreak Control

PubMed Central

Stamm, Lola V.

2015-01-01

Ebola virus disease (EVD) is a life-threatening zoonosis caused by infection with the Ebola virus. Since the first reported EVD outbreak in the Democratic Republic of the Congo, several small outbreaks have been reported in central Africa with about 2,400 cases occurring between 1976 and 2013. The 2013–2015 EVD outbreak in west Africa is the first documented outbreak in this region and the largest ever with over 27,000 cases and more than 11,000 deaths. Although EVD transmission rates have recently decreased in west Africa, this crisis continues to threaten global health and security, particularly since infected travelers could spread EVD to other resource-limited areas of the world. Because vaccines and drugs are not yet licensed for EVD, outbreak control is dependent on the use of non-pharmaceutical interventions (e.g., infection control practices, isolation of EVD cases, contact tracing with follow-up and quarantine, sanitary burial, health education). However, delays in diagnosing and reporting EVD cases in less accessible rural areas continue to hamper control efforts. New advances in rapid diagnostics for identifying presumptive EVD cases and in mobile-based technologies for communicating critical health-related information should facilitate deployment of an early response to prevent the amplification of sporadic EVD cases into large-scale outbreaks. PMID:26175026

Predicting Dengue Fever Outbreaks in French Guiana Using Climate Indicators.

PubMed

Adde, Antoine; Roucou, Pascal; Mangeas, Morgan; Ardillon, Vanessa; Desenclos, Jean-Claude; Rousset, Dominique; Girod, Romain; Briolant, Sébastien; Quenel, Philippe; Flamand, Claude

2016-04-01

Dengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana. Lagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical epidemic year and to define the best indices for predicting dengue fever outbreaks during the period 1991-2013. A logistic regression was then performed to build a forecast model. We demonstrate that a model based on summer Equatorial Pacific Ocean sea surface temperatures and Azores High sea-level pressure had predictive value and was able to predict 80% of the outbreaks while incorrectly predicting only 15% of the non-epidemic years. Predictions for 2014-2015 were consistent with the observed non-epidemic conditions, and an outbreak in early 2016 was predicted. These findings indicate that outbreak resurgence can be modeled using a simple combination of climate indicators. This might be useful for anticipating public health actions to mitigate the effects of major outbreaks, particularly in areas where resources are limited and medical infrastructures are generally insufficient.

Towards cross-lingual alerting for bursty epidemic events.

PubMed

Collier, Nigel

2011-10-06

Online news reports are increasingly becoming a source for event-based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challanges as opportunities due to the patterns of reporting complex spatio-temporal events. In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup.

Technical description of RODS: a real-time public health surveillance system.

PubMed

Tsui, Fu-Chiang; Espino, Jeremy U; Dato, Virginia M; Gesteland, Per H; Hutman, Judith; Wagner, Michael M

2003-01-01

This report describes the design and implementation of the Real-time Outbreak and Disease Surveillance (RODS) system, a computer-based public health surveillance system for early detection of disease outbreaks. Hospitals send RODS data from clinical encounters over virtual private networks and leased lines using the Health Level 7 (HL7) message protocol. The data are sent in real time. RODS automatically classifies the registration chief complaint from the visit into one of seven syndrome categories using Bayesian classifiers. It stores the data in a relational database, aggregates the data for analysis using data warehousing techniques, applies univariate and multivariate statistical detection algorithms to the data, and alerts users of when the algorithms identify anomalous patterns in the syndrome counts. RODS also has a Web-based user interface that supports temporal and spatial analyses. RODS processes sales of over-the-counter health care products in a similar manner but receives such data in batch mode on a daily basis. RODS was used during the 2002 Winter Olympics and currently operates in two states-Pennsylvania and Utah. It has been and continues to be a resource for implementing, evaluating, and applying new methods of public health surveillance.

A comparison of the immune response between early exposed and 1 year post exposure to Bacillus anthracis in Indonesia

NASA Astrophysics Data System (ADS)

Redhono, D.; Kusumawardani, A.; Dirgahayu, P.

2018-03-01

Anthrax is one of the zoonotic diseases that usually affects animals and can be transmitted to humans. Immune response of the body during an infection is the presence of antibodies as an effort to defend the body and it will survive for some time in the blood. The aim study is to find out how the initial response to the formation of antibodies and how these antibodies survive after one year. This study is cohort to people exposed to anthrax and found 130 people exposed to anthrax. The most risk factor was direct contact and consumed infected animal meat, which was 34.6%. Clinical manifestations of the skin were 12.3% and all respondents showed positive IgG. While 87.7% did not show any anthrax symptoms. IgG serum examination after 1 year of exposure to anthrax obtained 3.8% still detected antibodies in the body. The relationship between IgG titers with clinical manifestations of anthrax at one year post-outbreak is highly significant p 0.028. In conclusion a significant association between the clinical manifestation with antibody serum anthrax and it still detected after one-year post outbreaks of anthrax.

Trends of major disease outbreaks in the African region, 2003-2007.

PubMed

Kebede, Senait; Duales, Sambe; Yokouide, Allarangar; Alemu, Wondimagegnehu

2010-03-01

Communicable disease outbreaks cause millions of deaths throughout Sub-Saharan Africa each year. Most of the diseases causing epidemics in the region have been nearly eradicated or brought under control in other parts of the world. In recent years, considerable effort has been directed toward public health initiatives and strategies with a potential for significant impact in the fight against infectious diseases. In 1998, the World Health Organization African Regional Office (WHO/AFRO) launched the Integrated Disease Surveillance and Response (IDSR) strategy aimed at mitigating the impact of communicable diseases, including epidemic-prone diseases, through improving surveillance, laboratory confirmation and appropriate and timely public health interventions. Over the past decade, WHO and its partners have been providing technical and financial resources to African countries to strengthen epidemic preparedness and response (EPR) activities. This review examined the major epidemics reported to WHO/AFRO from 2003 to 2007. we conduct a review of documents and reports obtained from WHO/AFRO, WHO inter-country team, and partners and held meeting and discussions with key stakeholders to elicit the experiences of local, regional and international efforts against these epidemics to evaluate the lessons learned and to stimulate discussion on the future course for enhancing EPR. The most commonly reported epidemic outbreaks in Africa include: cholera, dysentery, malaria and hemorrhagic fevers (e.g. Ebola, Rift Valley fever, Crimean-Congo fever and yellow fever). The cyclic meningococcal meningitis outbreak that affects countries along the "meningitis belt" (spanning Sub-Saharan Africa from Senegal and The Gambia to Kenya and Ethiopia) accounts for other major epidemics in the region. The reporting of disease outbreaks to WHO/AFRO has improved since the launch of the IDSR strategy in 1998. Although the epidemic trends for cholera showed a decline in case fatality rate (CFR) suggesting improvement in detection and quality of response by the health sector, the number of countries affected has increased. Major epidemic diseases continue to occur in most countries in the region. Among the major challenges to overcome are: poor coordination of EPR, weak public health infrastructure, lack of trained workers and inconsistent supply of diagnostic, treatment and prevention commodities. To successfully reduce the levels of morbidity and mortality resulting from epidemic outbreaks, urgent and long-term investments are needed to strengthen capacities for early detection and timely and effective response. Effective advocacy, collaboration and resource mobilization efforts involving local health officials, governments and the international community are critically needed to reduce the heavy burden of disease outbreaks on African populations.

Estimating challenge load due to disease outbreaks and other challenges using reproduction records of sows.

PubMed

Mathur, P K; Herrero-Medrano, J M; Alexandri, P; Knol, E F; ten Napel, J; Rashidi, H; Mulder, H A

2014-12-01

A method was developed and tested to estimate challenge load due to disease outbreaks and other challenges in sows using reproduction records. The method was based on reproduction records from a farm with known disease outbreaks. It was assumed that the reduction in weekly reproductive output within a farm is proportional to the magnitude of the challenge. As the challenge increases beyond certain threshold, it is manifested as an outbreak. The reproduction records were divided into 3 datasets. The first dataset called the Training dataset consisted of 57,135 reproduction records from 10,901 sows from 1 farm in Canada with several outbreaks of porcine reproductive and respiratory syndrome (PRRS). The known disease status of sows was regressed on the traits number born alive, number of losses as a combination of still birth and mummified piglets, and number of weaned piglets. The regression coefficients from this analysis were then used as weighting factors for derivation of an index measure called challenge load indicator. These weighting factors were derived with i) a two-step approach using residuals or year-week solutions estimated from a previous step, and ii) a single-step approach using the trait values directly. Two types of models were used for each approach: a logistic regression model and a general additive model. The estimates of challenge load indicator were then compared based on their ability to detect PRRS outbreaks in a Test dataset consisting of records from 65,826 sows from 15 farms in the Netherlands. These farms differed from the Canadian farm with respect to PRRS virus strains, severity and frequency of outbreaks. The single-step approach using a general additive model was best and detected 14 out of the 15 outbreaks. This approach was then further validated using the third dataset consisting of reproduction records of 831,855 sows in 431 farms located in different countries in Europe and America. A total of 41 out of 48 outbreaks detected using data analysis were confirmed based on diagnostic information received from the farms. Among these, 30 outbreaks were due to PRRS while 11 were due to other diseases and challenging conditions. The results suggest that proposed method could be useful for estimation of challenge load and detection of challenge phases such as disease outbreaks.

[Meningitis outbreak caused by Echovirus serotype 30 in the Valencian Community].

PubMed

Juliá, M Lirios; Colomina, Javier; Domínguez, Victoria; Orta, Nieves; Guerrero, Antonio

2009-05-01

Aseptic meningitis can be caused by several agents, and in many cases the etiology remains unknown. The aim of this study to analyze the clinical and epidemiological characteristics of a meningitis outbreak detected in Health Department 11 of the Valencian Community (Spain). The study was performed in children hospitalized between November and December 2006 with meningitis symptoms, CSF pleocytosis, and negative CSF bacteriological culture. An epidemiological survey was conducted among cases and family members. Virus detection and phylogenetic analysis were performed with molecular biology techniques. The outbreak affected at least 44 children, with a mean age (standard deviation) of 5.5 years (2.9). The average hospital stay was 3.1 days and outcome was favorable in all cases. In 24 patients the CSF specimen sufficed for viral detection by PCR; enteroviruses ultimately serotyped as echovirus 30 were detected in 12 of them (50%). This serotype has been recently found in other parts of our country. Detection of echovirus 30 in CSF and the epidemiological presentation of cases enabled determination of the etiology of the outbreak. This finding coincided in time with other outbreaks of echovirus 30 in Spain, a fact that may explain the epidemic situation in the Valencian Community during 2006. Establishment of a national surveillance network for monitoring systemic enterovirus infection would provide data on the circulation patterns and identify new emerging serotypes.

Virus excretion and antibody dynamics in goats inoculated with a field isolate of peste des petits ruminants virus.

PubMed

Liu, W; Wu, X; Wang, Z; Bao, J; Li, L; Zhao, Y; Li, J

2013-11-01

A field isolate of peste des petits ruminants virus (PPRV) from an outbreak in Tibet, China, was inoculated into goats to investigate the dynamics of virus excretion and antibody production. Further, animals received PPRV vaccine strain Nigeria 75/1. Ocular, nasal and oral samples were tested for the presence of virus antigen by one-step real-time qualitative RT-PCR (qRT-PCR); competitive ELISA (c-ELISA) was used for the measurement of specific antibodies against PPRV. Virus particles could be detected as early as day 3 post-inoculation (pi) and virus excretion lasted for up to day 26 pi. All four goats inoculated with the PPRV field isolate were seropositive as early as day 10 pi. In animals inoculated with the vaccine strain, antibody was detected at day 14 pi, and levels of neutralizing antibodies remained above the protection threshold level (1 : 8) for 8 months. Both virus particles and neutralizing antibodies were detected earlier in goats challenged with the field isolate than in those receiving the vaccine strain. © 2013 Blackwell Verlag GmbH.

Surveillance data for waterborne illness detection: an assessment following a massive waterborne outbreak of Cryptosporidium infection.

PubMed Central

Proctor, M. E.; Blair, K. A.; Davis, J. P.

1998-01-01

Following the 1993 Milwaukee cryptosporidiosis outbreak, we examined data from eight sources available during the time of the outbreak. Although there was a remarkable temporal correspondence of surveillance peaks, the most timely data involved use of systems in which personnel with existing close ties to public health programmes perceived the importance of providing information despite workload constraints associated with an outbreak. During the investigation, surveillance systems which could be easily linked with laboratory data, were flexible in adding new variables, and which demonstrated low baseline variability were most useful. Geographically fixed nursing home residents served as an ideal population with nonconfounded exposures. Use of surrogate measurements of morbidity can trigger worthwhile public health responses in advance of laboratory-confirmed diagnosis and help reduce total morbidity associated with an outbreak. This report describes the relative strengths and weaknesses of these surveillance methods for community-wide waterborne illness detection and their application in outbreak decision making. PMID:9528817

Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America

PubMed Central

Bowman, Leigh R.; Tejeda, Gustavo S.; Coelho, Giovanini E.; Sulaiman, Lokman H.; Gill, Balvinder S.; McCall, Philip J.; Olliaro, Piero L.; Ranzinger, Silvia R.; Quang, Luong C.; Ramm, Ronald S.; Kroeger, Axel; Petzold, Max G.

2016-01-01

Background Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently. Methodology/Principal Findings The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007–2013. These data were split between the years 2007–2011 (historic period) and 2012–2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1–12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1–12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4–16 weeks. Conclusions/Significance An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission. PMID:27348752

Label-Free Detection and Serotyping of Salmonellae by Surface Enhanced Raman Spectroscopy with Immunomagnetic Separation

USDA-ARS?s Scientific Manuscript database

Salmonella spp. are one of the leading causes of foodborne outbreaks in the United States and globally. Current detection and characterization techniques for Salmonella are time consuming and rapid methods could greatly benefit outbreak investigation, new case prevention and disease treatment. In th...

Plasmodium falciparum Malaria, Southern Algeria, 2007

PubMed Central

Gassen, Ibrahim; Khechache, Yacine; Lamali, Karima; Tchicha, Boualem; Brengues, Cécile; Menegon, Michela; Severini, Carlo; Fontenille, Didier; Harrat, Zoubir

2010-01-01

An outbreak of Plasmodium falciparum malaria occurred in Tinzaouatine in southern Algeria in 2007. The likely vector, Anopheles gambiae mosquitoes, had not been detected in Algeria. Genes for resistance to chloroquine were detected in the parasite. The outbreak shows the potential for an increase in malaria vectors in Algeria. PMID:20113565

Simultaneous detection and serotyping of Salmonellae by immunomagnetic separation and label-free surface enhanced Raman spectroscopy

USDA-ARS?s Scientific Manuscript database

Salmonella spp. are one of the leading causes of foodborne outbreaks in the United States and globally. Current detection and characterization techniques for Salmonellae are time consuming and costly, and rapid methods could greatly benefit outbreak investigation, new case prevention and disease tre...

Evaluation of infectivity, virulence and transmission of FDMV field strains of serotypes O and A isolated in 2010 from outbreaks in the Republic of Korea

USDA-ARS?s Scientific Manuscript database

Since the early 2000s outbreaks of foot-and-mouth disease (FMD) have been described in several previously FMD-free Asian nations, including the Republic of Korea (ROK). One outbreak with FMD virus (FDMV) serotype A and two with serotype O occurred in ROK in 2010/2011. The causative viruses belong t...

Factors influencing the spatial and temporal dynamics of engelmann spruce mortality during a spruce beetle outbreak on the Markagunt Plateau, Utah

Treesearch

R. Justin DeRose; James N. Long

2012-01-01

Host conditions are known to influence spruce beetle population levels, but whether they influence the spatial and temporal patterns of beetle-caused mortality during an outbreak is unknown. Using dendrochronological techniques, we quantified the spatiotemporal dynamics of a modern (late 1980s through the early 2000s) spruce beetle outbreak in Engelmann spruce on the...

Sensitive Detection of Norovirus Using Phage Nanoparticle Reporters in Lateral-Flow Assay

PubMed Central

Hagström, Anna E. V.; Garvey, Gavin; Paterson, Andrew S.; Dhamane, Sagar; Adhikari, Meena; Estes, Mary K.; Strych, Ulrich; Kourentzi, Katerina; Atmar, Robert L.; Willson, Richard C.

2015-01-01

Noroviruses are recognized worldwide as the principal cause of acute, non-bacterial gastroenteritis, resulting in 19-21 million cases of disease every year in the United States. Noroviruses have a very low infectious dose, a short incubation period, high resistance to traditional disinfection techniques and multiple modes of transmission, making early, point-of-care detection essential for controlling the spread of the disease. The traditional diagnostic tools, electron microscopy, RT-PCR and ELISA require sophisticated and expensive instrumentation, and are considered too laborious and slow to be useful during severe outbreaks. In this paper we describe the development of a new, rapid and sensitive lateral-flow assay using labeled phage particles for the detection of the prototypical norovirus GI.1 (Norwalk), with a limit of detection of 107 virus-like particles per mL, one hundred-fold lower than a conventional gold nanoparticle lateral-flow assay using the same antibody pair. PMID:25978622

A multi-data source surveillance system to detect a bioterrorism attack during the G8 Summit in Scotland.

PubMed

Meyer, N; McMenamin, J; Robertson, C; Donaghy, M; Allardice, G; Cooper, D

2008-07-01

In 18 weeks, Health Protection Scotland (HPS) deployed a syndromic surveillance system to early-detect natural or intentional disease outbreaks during the G8 Summit 2005 at Gleneagles, Scotland. The system integrated clinical and non-clinical datasets. Clinical datasets included Accident & Emergency (A&E) syndromes, and General Practice (GPs) codes grouped into syndromes. Non-clinical data included telephone calls to a nurse helpline, laboratory test orders, and hotel staff absenteeism. A cumulative sum-based detection algorithm and a log-linear regression model identified signals in the data. The system had a fax-based track for real-time identification of unusual presentations. Ninety-five signals were triggered by the detection algorithms and four forms were faxed to HPS. Thirteen signals were investigated. The system successfully complemented a traditional surveillance system in identifying a small cluster of gastroenteritis among the police force and triggered interventions to prevent further cases.

Detection of Bacterial Meningitis Pathogens by PCR-Mass Spectrometry in Cerebrospinal Fluid.

PubMed

Jing-Zi, Piao; Zheng-Xin, He; Wei-Jun, Chen; Yong-Qiang, Jiang

2018-06-01

Acute bacterial meningitis remains a life-threatening infectious disease with considerable morbidity and mortality. DNA-based detection methods are an urgent requisite for meningitis-causing bacterial pathogens for the prevention of outbreaks and control of infections. We proposed a novel PCR-mass spectrometry (PCR-Mass) assay for the simultaneous detection of four meningitis-causing agents, Neisseria meningitidis, Streptococcus pneumoniae, Haemophilus influenzae, and Mycobacterium tuberculosis in the present study. A total of 138 cerebrospinal fluid (CSF) samples (including 56 CSF culture positive, 44 CSF culture negative, and 38 CSF control) were enrolled and analyzed by PCR/Mass. Results were compared to real-time PCR detection. These four targeting pathogens could be discriminated without cross-reaction by the accurate detection of the corresponding extension products with different masses. The limits of detection were 102 copies/reaction for S. pneumoniae, H. influenzae, and N. meningitidis and 103 for M. tuberculosis. The evaluation of the culture-positive CSF specimens from the meningitis patients provided an overall agreement rate of 85.7% with PCR-Mass and real-time PCR. The PCR-Mass was also able to detect the targeting pathogens from culture-negative CSF specimens from meningitis patients receiving early antibiotic treatment. PCR-Mass could be used for the molecular detection of bacterial meningitis and tuberculosis, especially when early antibiotic treatment has been administered to the suspected patients.

Long-Term Dynamics of Bluetongue Virus in Wild Ruminants: Relationship with Outbreaks in Livestock in Spain, 2006-2011

PubMed Central

Lorca-Oró, Cristina; López-Olvera, Jorge Ramón; Ruiz-Fons, Francisco; Acevedo, Pelayo; García-Bocanegra, Ignacio; Oleaga, Álvaro; Gortázar, Christian; Pujols, Joan

2014-01-01

Wild and domestic ruminants are susceptible to Bluetongue virus (BTV) infection. Three BTV serotypes (BTV-4, BTV-1 and BTV-8) have been detected in Spain in the last decade. Even though control strategies have been applied to livestock, BTV circulation has been frequently detected in wild ruminant populations in Spain. The aim of the present study is to assess the role for wild ruminants in maintaining BTV after the vaccination programs in livestock in mainland Spain. A total of 931 out 1,914 (48.6%) serum samples, collected from eight different wild ruminant species between 2006 and 2011, were BTV positive by ELISA. In order to detect specific antibodies against BTV-1, BTV-4 and BTV-8, positive sera were also tested by serumneutralisation test (SNT). From the ELISA positive samples that could be tested by SNT (687 out of 931), 292 (42.5%) showed neutralising antibodies against one or two BTV serotypes. For each BTV seroptype, the number of outbreaks in livestock (11,857 outbreaks in total) was modelled with pure autoregressive models and the resulting smoothed values, representing the predicted number of BTV outbreaks in livestock at municipality level, were positively correlated with BTV persistence in wild species. The strength of this relationship significantly decreased as red deer (Cervus elaphus) population abundance increased. In addition, BTV RNA was detected by real time RT-PCR in 32 out of 311 (10.3%) spleen samples from seropositive animals. Although BT outbreaks in livestock have decreased substantially after vaccination campaigns, our results indicated that wild ruminants have been exposed to BTV in territories where outbreaks in domestic animals occurred. The detection of BTV RNA and spatial association between BT outbreaks in livestock and BTV rates in red deer are consistent with the hypothesis of virus circulation and BTV maintenance within Iberian wild ruminant populations. PMID:24940879

Measles outbreak investigation in Guji zone of Oromia Region, Ethiopia.

PubMed

Belda, Ketema; Tegegne, Ayesheshem Ademe; Mersha, Amare Mengistu; Bayenessagne, Mekonnen Getahun; Hussein, Ibrahim; Bezabeh, Belay

2017-01-01

Despite the increase of immunization coverage (administrative) of measles in the country, there are widespread outbreaks of measles. In this respect, we investigated one of the outbreaks that occurred in hard to reach kebeles of Guji Zone, Oromia region, to identify the contributing factors that lead to the protracted outbreak of measles. We used a cross-sectional study design to investigate a measles outbreak in Guji zone, Oromia region. Data entry and analysis was performed using EPI-Info version 7.1.0.6 and MS-Microsoft Excel. In three months' time a total of 1059 suspected cases and two deaths were reported from 9 woredas affected by a measles outbreak in Guji zone. The cumulative attack rate of 81/100,000 population and case fatality ratio of 0.2% was recorded. Of these, 821 (77.5%) cases were < 15 years of age, and 742 (70%) were zero doses of measles vaccine. Although, all age groups were affected under five years old were more affected 495 (48%) than any other age groups. In response to the outbreak, an outbreak response immunization was organized at the 11th week of the epidemic, when the epidemic curve started to decline. 6 months to14 years old were targeted for outbreak response immunization and the overall coverage was 97 % (range: 90-103%). Case management with vitamin A supplementation, active case search, and health education was some of the activities carried out to curb the outbreak. We conclude that low routine immunization coverage in conjunction with low access to routine immunization in hard to reach areas, low community awareness in utilization of immunization service, inadequate cold chain management and delivery of a potent vaccine in hard to reach woredas/kebeles were likely contributed to the outbreak that's triggered a broad spread epidemic affecting mostly children without any vaccination. We also figured that the case-based surveillance lacks sensitivity and timely confirmation of the outbreak, which as a result outbreak response immunization were delayed. We recommend establishing reaching every child (REC) strategy in Guji zone with particular emphasis too hard reach areas to enhance the current immunization service, and furthermore to conduct data quality self-assessment or cluster coverage survey to verify the reported high vaccination coverage in some kebeles. We also recommend conducting the second opportunity as a form of supplemental immunization activities in 2-3 year interval or consider the national second dose introduction in the routine immunization system to improve population immunity. We further recommend that there is a need to boost the sensitivity of case-based surveillance system to be able to early detect, confirm and react to future epidemics.

Detection and molecular characterization of norovirus from oysters implicated in outbreaks in the US.

PubMed

Woods, Jacquelina W; Calci, Kevin R; Marchant-Tambone, Joey G; Burkhardt, William

2016-10-01

Human noroviruses are the leading cause of non-bacterial shellfish associated gastroenteritis. Here we report on the detection and characterization of norovirus (NoV) in shellfish associated outbreaks. Requests were received from state and federal officials for technical assistance in the analysis of shellfish for NoV and male specific coliphage (MSC; an enteric virus surrogate) during the years 2009 thru 2014. In outbreaks where NoV was detected, genogroup II (GII) levels ranged from 2.4 to 82.0 RT-qPCR U/g of digestive diverticula (DD) while NoV genogroup I (GI) levels ranged from 1.5 to 29.8 RT-qPCR U/g of DD. Murine norovirus extraction efficiencies ranged between 50 and 85%. MSC levels ranged from <6 to 80 PFU/100 g. Phylogenetic analysis of the outbreak sequences revealed strains clustering with GI.8, GI.4, GII.3, GII.4, GII.7, and GII.21. There was 100% homology between the shellfish and clinical strains occurring in 2 of 8 outbreaks. Known shellfish consumption data demonstrated probable infectious particles ingested as low as 12. These investigations demonstrate effective detection, quantification, and characterization of NoV in shellfish associated with illness. Published by Elsevier Ltd.

Diagnostic Evasion of Highly-Resistant Microorganisms: A Critical Factor in Nosocomial Outbreaks.

PubMed

Zhou, Xuewei; Friedrich, Alexander W; Bathoorn, Erik

2017-01-01

Highly resistant microorganisms (HRMOs) may evade screening strategies used in routine diagnostics. Bacteria that have evolved to evade diagnostic tests may have a selective advantage in the nosocomial environment. Evasion of resistance detection can result from the following mechanisms: low-level expression of resistance genes not resulting in detectable resistance, slow growing variants, mimicry of wild-type-resistance, and resistance mechanisms that are only detected if induced by antibiotic pressure. We reviewed reports on hospital outbreaks in the Netherlands over the past 5 years. Remarkably, many outbreaks including major nation-wide outbreaks were caused by microorganisms able to evade resistance detection by diagnostic screening tests. We describe various examples of diagnostic evasion by several HRMOs and discuss this in a broad and international perspective. The epidemiology of hospital-associated bacteria may strongly be affected by diagnostic screening strategies. This may result in an increasing reservoir of resistance genes in hospital populations that is unnoticed. The resistance elements may horizontally transfer to hosts with systems for high-level expression, resulting in a clinically significant resistance problem. We advise to communicate the identification of HRMOs that evade diagnostics within national and regional networks. Such signaling networks may prevent inter-hospital outbreaks, and allow collaborative development of adapted diagnostic tests.

Time delays in the response to the Neisseria meningitidis serogroup C outbreak in Nigeria - 2017.

PubMed

Hassan, Assad; Mustapha, G U; Lawal, Bola B; Na'uzo, Aliyu M; Ismail, Raji; Womi-Eteng Oboma, Eteng; Oyebanji, Oyeronke; Agenyi, Jeremiah; Thomas, Chima; Balogun, Muhammad Shakir; Dalhat, Mahmood M; Nguku, Patrick; Ihekweazu, Chikwe

2018-01-01

Nigeria reports high rates of mortality linked with recurring meningococcal meningitis outbreaks within the African meningitis belt. Few studies have thoroughly described the response to these outbreaks to provide strong and actionable public health messages. We describe how time delays affected the response to the 2016/2017 meningococcal meningitis outbreak in Nigeria. Using data from Nigeria Centre for Disease Control (NCDC), National Primary Health Care Development Agency (NPHCDA), World Health Organisation (WHO), and situation reports of rapid response teams, we calculated attack and death rates of reported suspected meningococcal meningitis cases per week in Zamfara, Sokoto and Yobe states respectively, between epidemiological week 49 in 2016 and epidemiological week 25 in 2017. We identified when alert and epidemic thresholds were crossed and determined when the outbreak was detected and notified in each state. We examined response activities to the outbreak. There were 12,535 suspected meningococcal meningitis cases and 877 deaths (CFR: 7.0%) in the three states. It took an average time of three weeks before the outbreaks were detected and notified to NCDC. Four weeks after receiving notification, an integrated response coordinating centre was set up by NCDC and requests for vaccines were sent to International Coordinating Group (ICG) on vaccine provision. While it took ICG one week to approve the requests, it took an average of two weeks for approximately 41% of requested vaccines to arrive. On the average, it took nine weeks from the date the epidemic threshold was crossed to commencement of reactive vaccination in the three states. There were delays in detection and notification of the outbreak, in coordinating response activities, in requesting for vaccines and their arrival from ICG, and in initiating reactive vaccination. Reducing these delays in future outbreaks could help decrease the morbidity and mortality linked with meningococcal meningitis outbreaks.

[An outbreak of mumps in a high school: Estimation of vaccine effectiveness. Zaragoza 2011].

PubMed

Compés-Dea, Cecilia; Guimbao-Bescós, Joaquín; Gaspar-Escayola, José Ignacio; Lázaro-Belanche, María Ángeles; Aznar-Brieba, Amaya

2015-01-01

Mumps outbreaks continue to occur, even after the consolidation of vaccination programs. An outbreak of mumps occurred in a high school in Zaragoza during December 2011. To describe the outbreak and estimate vaccine effectiveness. unilateral or bilateral swelling of the parotid or other salivary glands for three or more days without any other apparent cause. People attending the 'Parque Goya' High School or with transmission chain origin in the High School. From two days before the onset of symptoms of the first case to five days after the last case. Samples were collected for virus confirmation (IgM, urine culture and oropharyngeal exudate), and isolates were processed for genotyping. A retrospective cohort study was performed in two high school classrooms to estimate vaccine efficacy. Public health authorities conducted active surveillance, isolation of cases, and vaccination of susceptible contacts. There were 27 cases. Twenty-one (77.8%) were vaccinated with two doses of Measles-Mumps-Rubella vaccine. Twelve (44%) were confirmed microbiologically. G1 genotype was determined in six cases. According to the cohort study, vaccine efficacy for one dose was 34% (95%CI: -44 to 70), and was 67% (95%CI: 28 to 83) for two doses. Vaccine effectiveness was lower than expected. Early detection and isolation of cases have been instrumental in preventing new cases in schools. Copyright © 2014 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

Climate, Water, and Human Health: Large Scale Hydroclimatic Controls in Forecasting Cholera Epidemics

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A. S.; Islam, S.

2009-12-01

Despite ravaging the continents through seven global pandemics in past centuries, the seasonal and interannual variability of cholera outbreaks remain a mystery. Previous studies have focused on the role of various environmental and climatic factors, but provided little or no predictive capability. Recent findings suggest a more prominent role of large scale hydroclimatic extremes - droughts and floods - and attempt to explain the seasonality and the unique dual cholera peaks in the Bengal Delta region of South Asia. We investigate the seasonal and interannual nature of cholera epidemiology in three geographically distinct locations within the region to identify the larger scale hydroclimatic controls that can set the ecological and environmental ‘stage’ for outbreaks and have significant memory on a seasonal scale. Here we show that two distinctly different, pre and post monsoon, cholera transmission mechanisms related to large scale climatic controls prevail in the region. An implication of our findings is that extreme climatic events such as prolonged droughts, record floods, and major cyclones may cause major disruption in the ecosystem and trigger large epidemics. We postulate that a quantitative understanding of the large-scale hydroclimatic controls and dominant processes with significant system memory will form the basis for forecasting such epidemic outbreaks. A multivariate regression method using these predictor variables to develop probabilistic forecasts of cholera outbreaks will be explored. Forecasts from such a system with a seasonal lead-time are likely to have measurable impact on early cholera detection and prevention efforts in endemic regions.

MALDI-TOF MS typing of a nosocomial methicillin-resistant Staphylococcus aureus outbreak in a neonatal intensive care unit.

PubMed

Steensels, Deborah; Deplano, Ariane; Denis, Olivier; Simon, Anne; Verroken, Alexia

2017-08-01

The early detection of a methicillin-resistant Staphylococcus aureus (MRSA) outbreak is decisive to control its spread and rapidly initiate adequate infection control measures. Therefore, prompt determination of epidemiologic relatedness of clinical MRSA isolates is essential. Genetic typing methods have a high discriminatory power but their availability remains restricted. In this study, we aimed to challenge matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a typing tool of a nosocomial MRSA outbreak in a neonatal intensive care unit. Over a 2-year period, 15 MRSA isolates were recovered from patients (n = 14) and health care workers (n = 1) at the neonatal intensive care unit. Five reference strains were included for comparison. Identification was performed by MALDI-TOF MS and susceptibility profiles determined by automated broth microdilution. Typing analysis by MALDI-TOF MS included mean spectrum profiles and subsequent dendrogram creation using BioNumerics software. Results were compared with spa typing and pulsed-field gel electrophoresis (PFGE). Our study showed good concordance (93%) between PFGE, spa typing, and MALDI-TOF MS for the outbreak-related MRSA strains. MALDI-TOF MS typing showed excellent typeability and discriminatory power but showed poor reproducibility. This study is one of the first to document the potential usefulness of MALDI-TOF MS with standardized data analysis as a typing tool for investigating a nosocomial MRSA outbreak. A concordance of 93% compared to reference typing techniques was observed. However, because of poor reproducibility, long-term follow-up of prospective isolated strains is not practical for routine use. Further studies are needed to confirm our observations.

Immune Memory to Sudan Virus: Comparison between Two Separate Disease Outbreaks

PubMed Central

Sobarzo, Ariel; Eskira, Yael; Herbert, Andrew S.; Kuehne, Ana I.; Stonier, Spencer W.; Ochayon, David E.; Fedida-Metula, Shlomit; Balinandi, Steven; Kislev, Yaara; Tali, Neta; Lewis, Eli C.; Lutwama, Julius Julian; Dye, John M.; Yavelsky, Victoria; Lobel, Leslie

2015-01-01

Recovery from ebolavirus infection in humans is associated with the development of both cell-mediated and humoral immune responses. According to recent studies, individuals that did not survive infection with ebolaviruses appear to have lacked a robust adaptive immune response and the expression of several early innate response markers. However, a comprehensive protective immune profile has yet to be described. Here, we examine cellular memory immune responses among survivors of two separate Ebolavirus outbreaks (EVDs) due to Sudan virus (SUDV) infection in Uganda—Gulu 2000–2001 and Kibaale 2012. Freshly collected blood samples were stimulated with inactivated SUDV, as well as with recombinant SUDV or Ebola virus (EBOV) GP (GP1–649). In addition, ELISA and plaque reduction neutralization assays were performed to determine anti-SUDV IgG titers and neutralization capacity. Cytokine expression was measured in whole blood cultures in response to SUDV and SUDV GP stimulation in both survivor pools, demonstrating recall responses that indicate immune memory. Cytokine responses between groups were similar but had distinct differences. Neutralizing, SUDV-specific IgG activity against irradiated SUDV and SUDV recombinant proteins were detected in both survivor cohorts. Furthermore, humoral and cell-mediated crossreactivity to EBOV and EBOV recombinant GP1–649 was observed in both cohorts. In conclusion, immune responses in both groups of survivors demonstrate persistent recognition of relevant antigens, albeit larger cohorts are required in order to reach greater statistical significance. The differing cytokine responses between Gulu and Kibaale outbreak survivors suggests that each outbreak may not yield identical memory responses and promotes the merits of studying the immune responses among outbreaks of the same virus. Finally, our demonstration of cross-reactive immune recognition suggests that there is potential for developing cross-protective vaccines for ebolaviruses. PMID:25569078

Immune memory to Sudan virus: comparison between two separate disease outbreaks.

PubMed

Sobarzo, Ariel; Eskira, Yael; Herbert, Andrew S; Kuehne, Ana I; Stonier, Spencer W; Ochayon, David E; Fedida-Metula, Shlomit; Balinandi, Steven; Kislev, Yaara; Tali, Neta; Lewis, Eli C; Lutwama, Julius Julian; Dye, John M; Yavelsky, Victoria; Lobel, Leslie

2015-01-06

Recovery from ebolavirus infection in humans is associated with the development of both cell-mediated and humoral immune responses. According to recent studies, individuals that did not survive infection with ebolaviruses appear to have lacked a robust adaptive immune response and the expression of several early innate response markers. However, a comprehensive protective immune profile has yet to be described. Here, we examine cellular memory immune responses among survivors of two separate Ebolavirus outbreaks (EVDs) due to Sudan virus (SUDV) infection in Uganda-Gulu 2000-2001 and Kibaale 2012. Freshly collected blood samples were stimulated with inactivated SUDV, as well as with recombinant SUDV or Ebola virus (EBOV) GP (GP1-649). In addition, ELISA and plaque reduction neutralization assays were performed to determine anti-SUDV IgG titers and neutralization capacity. Cytokine expression was measured in whole blood cultures in response to SUDV and SUDV GP stimulation in both survivor pools, demonstrating recall responses that indicate immune memory. Cytokine responses between groups were similar but had distinct differences. Neutralizing, SUDV-specific IgG activity against irradiated SUDV and SUDV recombinant proteins were detected in both survivor cohorts. Furthermore, humoral and cell-mediated crossreactivity to EBOV and EBOV recombinant GP1-649 was observed in both cohorts. In conclusion, immune responses in both groups of survivors demonstrate persistent recognition of relevant antigens, albeit larger cohorts are required in order to reach greater statistical significance. The differing cytokine responses between Gulu and Kibaale outbreak survivors suggests that each outbreak may not yield identical memory responses and promotes the merits of studying the immune responses among outbreaks of the same virus. Finally, our demonstration of cross-reactive immune recognition suggests that there is potential for developing cross-protective vaccines for ebolaviruses.

Strengthening the diagnostic capacity to detect Bio Safety Level 3 organisms in unusual respiratory viral outbreaks.

PubMed

van Asten, Liselotte; van der Lubben, Mariken; van den Wijngaard, Cees; van Pelt, Wilfrid; Verheij, Robert; Jacobi, Andre; Overduin, Pieter; Meijer, Adam; Luijt, Dirk; Claas, Eric; Hermans, Mirjam; Melchers, Willem; Rossen, John; Schuurman, Rob; Wolffs, Petra; Boucher, Charles; Bouchier, Charles; Schirm, Jurjen; Kroes, Louis; Leenders, Sander; Galama, Joep; Peeters, Marcel; van Loon, Anton; Stobberingh, Ellen; Schutten, Martin; Koopmans, Marion

2009-07-01

Experience with a highly pathogenic avian influenza outbreak in the Netherlands (2003) illustrated that the diagnostic demand for respiratory viruses at different biosafety levels (including BSL3), can increase unexpectedly and dramatically. We describe the measures taken since, aimed at strengthening national laboratory surge capacity and improving preparedness for dealing with diagnostic demand during outbreaks of (emerging) respiratory virus infections, including pandemic influenza virus. Academic and peripheral medical-microbiological laboratories collaborated to determine minimal laboratory requirements for the identification of viruses in the early stages of a pandemic or a large outbreak of avian influenza virus. Next, an enhanced collaborative national network of outbreak assistance laboratories (OAL) was set up. An inventory was made of the maximum diagnostic throughput that this network can deliver in a period of intensified demand. For an estimate of the potential magnitude of this surge demand, historical counts were calculated from hospital- and physician-based registries of patients presenting with respiratory symptoms. Number of respiratory physician-visits ranged from 140,000 to 615,000 per month and hospitalizations ranged from 3000 to 11,500 per month. The established OAL-network provides rapid diagnostic response with agreed quality requirements and a maximum throughput capacity of 1275 samples/day (38,000 per month), assuming other routine diagnostic work needs to be maintained. Thus surge demand for diagnostics for hospitalized cases (if not distinguishable from other respiratory illness) could be handled by the OAL network. Assessing etiology of community acquired acute respiratory infection however, may rapidly exceed the capacity of the network. Therefore algorithms are needed for triaging for laboratory diagnostics; currently this is not addressed in pandemic preparedness plans.

Paradigm shift: contribution of field epidemiology training in advancing the “One Health” approach to strengthen disease surveillance and outbreak investigations in Africa

PubMed Central

Monday, Busuulwa; Gitta, Sheba Nakacubo; Wasswa, Peter; Namusisi, Olivia; Bingi, Aloysius; Musenero, Monica; Mukanga, David

2011-01-01

The occurrence of major zoonotic disease outbreaks in Sub-Saharan Africa has had a significant impact on the already constrained public health systems. This has, as a result, justified the need to identify creative strategies to address threats from emerging and re-emerging infectious diseases at the human-animal-environmental interface, and implement robust multi-disease public health surveillance systems that will enhance early detection and response. Additionally, enhanced reporting and timely investigation of all suspected notifiable infectious disease threats within the health system is vital. Field epidemiology and laboratory training programs (FELTPs) have made significant contributions to public health systems for more than 10 years by producing highly skilled field epidemiologists. These epidemiologists have not only improved disease surveillance and response to outbreaks, but also improved management of health systems. Furthermore, the FETPs/FELTPs have laid an excellent foundation that brings clinicians, veterinarians, and environmental health professionals drawn from different governmental sectors, to work with a common purpose of disease control and prevention. The emergence of the One Health approach in the last decade has coincided with the present, paradigm, shift that calls for multi-sectoral and cross-sectoral collaboration towards disease surveillance, detection, reporting and timely response. The positive impact from the integration of FETP/FELTP and the One Health approach by selected programs in Africa has demonstrated the importance of multi-sectoral collaboration in addressing threats from infectious and non- infectious causes to man, animals and the environment. PMID:22359701

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013–2016

PubMed Central

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.; Rollin, Pierre E.

2016-01-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013–2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community’s insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Continued efforts during the outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research. PMID:27070842

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016

DOE PAGES

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.; ...

2016-06-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Finally, continued efforts during themore » outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.« less

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Finally, continued efforts during themore » outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.« less

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016.

PubMed

Spengler, Jessica R; Ervin, Elizabeth D; Towner, Jonathan S; Rollin, Pierre E; Nichol, Stuart T

2016-06-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Continued efforts during the outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis.

PubMed

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control.

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

PubMed Central

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. PMID:27583523

Simultaneous subtyping and pathotyping of avian influenza viruses in chickens in Taiwan using reverse transcription loop-mediated isothermal amplification and microarray

PubMed Central

WANG, Lih-Chiann; HUANG, Dean; CHEN, Hui-Wen

2016-01-01

The H6N1 avian influenza virus has circulated in Taiwan for more than 40 years. The sporadic activity of low pathogenic H5N2 virus has been noted since 2003, and highly pathogenic H5N2 avian influenza virus has been detected since 2008. Ressortant viruses between H6N1 and H5N2 viruses have become established and enzootic in chickens throughout Taiwan. Outbreaks caused by Novel highly pathogenic H5 avian influenza viruses whose HA genes were closely related to that of the H5N8 virus isolated from ducks in Korea in 2014 were isolated from outbreaks in Taiwan since early 2015. The avian influenza virus infection status is becoming much more complicated in chickens in Taiwan. This necessitates a rapid and simple approach to detect and differentiate the viruses that prevail. H6N1, H5N2 and novel H5 viruses were simultaneously subtyped and pathotyped in this study using reverse transcription loop-mediated isothermal amplification and microarray, with detection limits of 10°, 101 and 10° viral copy numbers, respectively. The microarray signals were read by the naked eye with no expensive equipment needed. The method developed in this study could greatly improve avian influenza virus surveillance efficiency. PMID:27086860

Nosocomial transmission of respiratory syncytial virus in an outpatient cancer center.

PubMed

Chu, Helen Y; Englund, Janet A; Podczervinski, Sara; Kuypers, Jane; Campbell, Angela P; Boeckh, Michael; Pergam, Steven A; Casper, Corey

2014-06-01

Respiratory syncytial virus (RSV) outbreaks in inpatient settings are associated with poor outcomes in cancer patients. The use of molecular epidemiology to document RSV transmission in the outpatient setting has not been well described. We performed a retrospective cohort study of 2 nosocomial outbreaks of RSV at the Seattle Cancer Care Alliance. Subjects included patients seen at the Seattle Cancer Care Alliance with RSV detected in 2 outbreaks in 2007-2008 and 2012 and all employees with respiratory viruses detected in the 2007-2008 outbreak. A subset of samples was sequenced using semi-nested PCR targeting the RSV attachment glycoprotein coding region. Fifty-one cases of RSV were identified in 2007-2008. Clustering of identical viral strains was detected in 10 of 15 patients (67%) with RSV sequenced from 2007 to 2008. As part of a multimodal infection control strategy implemented as a response to the outbreak, symptomatic employees had nasal washes collected. Of 254 employee samples, 91 (34%) tested positive for a respiratory virus, including 14 with RSV. In another RSV outbreak in 2012, 24 cases of RSV were identified; 9 of 10 patients (90%) had the same viral strain, and 1 (10%) had another viral strain. We document spread of clonal strains within an outpatient cancer care setting. Infection control interventions should be implemented in outpatient, as well as inpatient, settings to reduce person-to-person transmission and limit progression of RSV outbreaks. Copyright © 2014 American Society for Blood and Marrow Transplantation. All rights reserved.

Nosocomial Transmission of Respiratory Syncytial Virus in an Outpatient Cancer Center

PubMed Central

Chu, Helen Y.; Englund, Janet A.; Podczervinski, Sara; Kuypers, Jane; Campbell, Angela P.; Boeckh, Michael; Pergam, Steven A.; Casper, Crey

2014-01-01

Background Respiratory syncytial virus (RSV) outbreaks in inpatient settings are associated with poor outcomes in cancer patients. The use of molecular epidemiology to document RSV transmission in the outpatient setting has not been well described. Methods We performed a retrospective cohort study of two nosocomial outbreaks of RSV at the Seattle Cancer Care Alliance (SCCA). Subjects included patients seen at the SCCA with RSV detected in two outbreaks in 2007-2008 and 2012, and all employees with respiratory viruses detected in the 2007-2008 outbreak. A subset of samples was sequenced using semi-nested polymerase chain reaction targeting the RSV attachment glycoprotein coding region. Results Fifty-one cases of RSV were identified in 2007-2008. Clustering of identical viral strains was detected in 10 (67%) of 15 patients with RSV sequenced from 2007-2008. As part of a multimodal infection control strategy implemented as a response to the outbreak, symptomatic employees had nasal washes collected. Of 254 employee samples, 91 (34%) tested positive for a respiratory virus, including 14 with RSV. In another RSV outbreak in 2012, 24 cases of RSV were identified; nine (90%) of 10 patients had the same viral strain, and 1 (10%) had another viral strain. Conclusions We document spread of clonal strains within an outpatient cancer care setting. Infection control interventions should be implemented in outpatient, as well as inpatient, settings to reduce person-to-person transmission and limit progression of RSV outbreaks. PMID:24607551

Phylogeny of Yellow Fever Virus, Uganda, 2016.

PubMed

Hughes, Holly R; Kayiwa, John; Mossel, Eric C; Lutwama, Julius; Staples, J Erin; Lambert, Amy J

2018-08-17

In April 2016, a yellow fever outbreak was detected in Uganda. Removal of contaminating ribosomal RNA in a clinical sample improved the sensitivity of next-generation sequencing. Molecular analyses determined the Uganda yellow fever outbreak was distinct from the concurrent yellow fever outbreak in Angola, improving our understanding of yellow fever epidemiology.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network.

PubMed

Cordes, Kristina M; Cookson, Susan T; Boyd, Andrew T; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad; Husain, Farah

2017-11-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network

PubMed Central

Cordes, Kristina M.; Cookson, Susan T.; Boyd, Andrew T.; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad

2017-01-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security. PMID:29155660

A single Legionella pneumophila genotype in the freshwater system in a ship experiencing three separate outbreaks of legionellosis in 6 years.

PubMed

Ahlen, Catrine; Aas, Marianne; Krusnell, Jadwiga; Iversen, Ole-Jan

2016-01-01

Recurrent legionella outbreaks at one and the same location are common. We have identified a single Legionella pneumophila genotype associated with recurrent Legionella outbreaks over 6 years. Field emergency surveys following Legionella outbreaks were performed on a vessel in 2008, 2009 and 2013. Water samples from both the distribution and technical parts of the potable water system were analyzed with respect to L. pneumophila [Real-Time PCR, cultivation, serotyping and genotyping (PFGE)] and free-living amoebae, (FLA). Legionella pneumophila serogroup 1 was present in the ship's potable water system during every outbreak. Genotyping of the 2008 survey material showed two separate PFGE genotypes while those in 2009 and 2013 demonstrated the presence of only one of the two genotypes. FLA with intracellular L. pneumophila of the same genotype were also detected. Analyses of the freshwater system on a ship following three separate Legionella outbreaks, for L. pneumophila and FLAs, revealed a single L. pneumophila genotype and FLA (Hartmanella). It is reasonable to assume that the L. pneumophila genotype detected in the freshwater system was the causal agent in the outbreaks onboard. Persistence of an apparently low-pathogenic L. pneumophila genotype and FLA in a potable water system represent a potential risk for recurrent outbreaks.

The importance of waterborne disease outbreak surveillance in the United States.

PubMed

Craun, Gunther Franz

2012-01-01

Analyses of the causes of disease outbreaks associated with contaminated drinking water in the United States have helped inform prevention efforts at the national, state, and local levels. This article describes the changing nature of disease outbreaks in public water systems during 1971-2008 and discusses the importance of a collaborative waterborne outbreak surveillance system established in 1971. Increasing reports of outbreaks throughout the early 1980s emphasized that microbial contaminants remained a health-risk challenge for suppliers of drinking water. Outbreak investigations identified the responsible etiologic agents and deficiencies in the treatment and distribution of drinking water, especially the high risk associated with unfiltered surface water systems. Surveillance information was important in establishing an effective research program that guided government regulations and industry actions to improve drinking water quality. Recent surveillance statistics suggest that prevention efforts based on these research findings have been effective in reducing outbreak risks especially for surface water systems.

Improved tools and strategies for the prevention and control of arboviral diseases: A research-to-policy forum.

PubMed

Olliaro, Piero; Fouque, Florence; Kroeger, Axel; Bowman, Leigh; Velayudhan, Raman; Santelli, Ana Carolina; Garcia, Diego; Skewes Ramm, Ronald; Sulaiman, Lokman H; Tejeda, Gustavo Sanchez; Morales, Fabiàn Correa; Gozzer, Ernesto; Garrido, César Basso; Quang, Luong Chan; Gutierrez, Gamaliel; Yadon, Zaida E; Runge-Ranzinger, Silvia

2018-02-01

Research has been conducted on interventions to control dengue transmission and respond to outbreaks. A summary of the available evidence will help inform disease control policy decisions and research directions, both for dengue and, more broadly, for all Aedes-borne arboviral diseases. A research-to-policy forum was convened by TDR, the Special Programme for Research and Training in Tropical Diseases, with researchers and representatives from ministries of health, in order to review research findings and discuss their implications for policy and research. The participants reviewed findings of research supported by TDR and others. Surveillance and early outbreak warning. Systematic reviews and country studies identify the critical characteristics that an alert system should have to document trends reliably and trigger timely responses (i.e., early enough to prevent the epidemic spread of the virus) to dengue outbreaks. A range of variables that, according to the literature, either indicate risk of forthcoming dengue transmission or predict dengue outbreaks were tested and some of them could be successfully applied in an Early Warning and Response System (EWARS). Entomological surveillance and vector management. A summary of the published literature shows that controlling Aedes vectors requires complex interventions and points to the need for more rigorous, standardised study designs, with disease reduction as the primary outcome to be measured. House screening and targeted vector interventions are promising vector management approaches. Sampling vector populations, both for surveillance purposes and evaluation of control activities, is usually conducted in an unsystematic way, limiting the potentials of entomological surveillance for outbreak prediction. Combining outbreak alert and improved approaches of vector management will help to overcome the present uncertainties about major risk groups or areas where outbreak response should be initiated and where resources for vector management should be allocated during the interepidemic period. The Forum concluded that the evidence collected can inform policy decisions, but also that important research gaps have yet to be filled.

Improved tools and strategies for the prevention and control of arboviral diseases: A research-to-policy forum

PubMed Central

Olliaro, Piero; Fouque, Florence; Kroeger, Axel; Bowman, Leigh; Velayudhan, Raman; Santelli, Ana Carolina; Garcia, Diego; Skewes Ramm, Ronald; Sulaiman, Lokman H.; Tejeda, Gustavo Sanchez; Morales, Fabiàn Correa; Gozzer, Ernesto; Garrido, César Basso; Quang, Luong Chan; Gutierrez, Gamaliel; Yadon, Zaida E.

2018-01-01

Background Research has been conducted on interventions to control dengue transmission and respond to outbreaks. A summary of the available evidence will help inform disease control policy decisions and research directions, both for dengue and, more broadly, for all Aedes-borne arboviral diseases. Method A research-to-policy forum was convened by TDR, the Special Programme for Research and Training in Tropical Diseases, with researchers and representatives from ministries of health, in order to review research findings and discuss their implications for policy and research. Results The participants reviewed findings of research supported by TDR and others. Surveillance and early outbreak warning. Systematic reviews and country studies identify the critical characteristics that an alert system should have to document trends reliably and trigger timely responses (i.e., early enough to prevent the epidemic spread of the virus) to dengue outbreaks. A range of variables that, according to the literature, either indicate risk of forthcoming dengue transmission or predict dengue outbreaks were tested and some of them could be successfully applied in an Early Warning and Response System (EWARS). Entomological surveillance and vector management. A summary of the published literature shows that controlling Aedes vectors requires complex interventions and points to the need for more rigorous, standardised study designs, with disease reduction as the primary outcome to be measured. House screening and targeted vector interventions are promising vector management approaches. Sampling vector populations, both for surveillance purposes and evaluation of control activities, is usually conducted in an unsystematic way, limiting the potentials of entomological surveillance for outbreak prediction. Combining outbreak alert and improved approaches of vector management will help to overcome the present uncertainties about major risk groups or areas where outbreak response should be initiated and where resources for vector management should be allocated during the interepidemic period. Conclusions The Forum concluded that the evidence collected can inform policy decisions, but also that important research gaps have yet to be filled. PMID:29389959

Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis

PubMed Central

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-01-01

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places. PMID:28933396

Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore

PubMed Central

Shi, Yuan; Liu, Xu; Kok, Suet-Yheng; Rajarethinam, Jayanthi; Liang, Shaohong; Yap, Grace; Chong, Chee-Seng; Lee, Kim-Sung; Tan, Sharon S.Y.; Chin, Christopher Kuan Yew; Lo, Andrew; Kong, Waiming; Ng, Lee Ching; Cook, Alex R.

2015-01-01

Background: With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. Objectives: We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. Methods: We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Results: Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore’s dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Conclusions: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Citation: Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak alerts and policy decision support in Singapore. Environ Health Perspect 124:1369–1375; http://dx.doi.org/10.1289/ehp.1509981 PMID:26662617

Functional Characterization of Adaptive Mutations during the West African Ebola Virus Outbreak.

PubMed

Dietzel, Erik; Schudt, Gordian; Krähling, Verena; Matrosovich, Mikhail; Becker, Stephan

2017-01-15

The Ebola virus (EBOV) outbreak in West Africa started in December 2013, claimed more than 11,000 lives, threatened to destabilize a whole region, and showed how easily health crises can turn into humanitarian disasters. EBOV genomic sequences of the West African outbreak revealed nonsynonymous mutations, which induced considerable public attention, but their role in virus spread and disease remains obscure. In this study, we investigated the functional significance of three nonsynonymous mutations that emerged early during the West African EBOV outbreak. Almost 90% of more than 1,000 EBOV genomes sequenced during the outbreak carried the signature of three mutations: a D759G substitution in the active center of the L polymerase, an A82V substitution in the receptor binding domain of surface glycoprotein GP, and an R111C substitution in the self-assembly domain of RNA-encapsidating nucleoprotein NP. Using a newly developed virus-like particle system and reverse genetics, we found that the mutations have an impact on the functions of the respective viral proteins and on the growth of recombinant EBOVs. The mutation in L increased viral transcription and replication, whereas the mutation in NP decreased viral transcription and replication. The mutation in the receptor binding domain of the glycoprotein GP improved the efficiency of GP-mediated viral entry into target cells. Recombinant EBOVs with combinations of the three mutations showed a growth advantage over the prototype isolate Makona C7 lacking the mutations. This study showed that virus variants with improved fitness emerged early during the West African EBOV outbreak. The dimension of the Ebola virus outbreak in West Africa was unprecedented. Amino acid substitutions in the viral L polymerase, surface glycoprotein GP, and nucleocapsid protein NP emerged, were fixed early in the outbreak, and were found in almost 90% of the sequences. Here we showed that these mutations affected the functional activity of viral proteins and improved viral growth in cell culture. Our results demonstrate emergence of adaptive changes in the Ebola virus genome during virus circulation in humans and prompt further studies on the potential role of these changes in virus transmissibility and pathogenicity. Copyright © 2017 American Society for Microbiology.

An outbreak of Brucella abortus biovar 2 in Canadian cattle

PubMed Central

Forbes, Lorry B.; Steele, Thomas B.

1989-01-01

An outbreak of brucellosis caused by Brucella abortus biovar 2 was identified in cattle in Alberta in December 1986. This was the only clinical infection discovered since the national cattle herd was declared brucellosisfree in 1985. It was the first report of B. abortus biovar 2 in Canadian cattle. The outbreak, involving three herds containing purebred Hereford cattle, was spread by the private treaty sale of untested cattle, and was identified following investigation of an abortion. The source of infection for the outbreak was not established, but several possibilities were identified including infected herds present in the area during the mid-1970's, latent infection originating in a Saskatchewan herd during the early 1960's, American cattle imported during the early 1970's, and brucellosis-infected bison in Wood Buffalo National Park. The containment and elimination of this nidus of infection appears to have been successful, and the national cattle herd at the time of writing is free of the disease. PMID:17423457

A neighborhood susceptibility index for planning of local physical interventions in response to pandemic influenza outbreaks

PubMed Central

Timpka, Toomas; Eriksson, Henrik; Strömgren, Magnus; Eriksson, Olle; Ekberg, Joakim; Grimvall, Anders; Nyce, James; Gursky, Elin; Holm, Einar

2010-01-01

The global spread of a novel A (H1N1) influenza virus in 2009 has highlighted the possibility of a devastating pandemic similar to the ‘Spanish flu’ of 1917–1918. Responding to such pandemics requires careful planning for the early phases where there is no availability of pandemic vaccine. We set out to compute a Neighborhood Influenza Susceptibility Index (NISI) describing the vulnerability of local communities of different geo-socio-physical structure to a pandemic influenza outbreak. We used a spatially explicit geo-physical model of Linköping municipality (pop. 136,240) in Sweden, and employed an ontology-modeling tool to define simulation models and transmission settings. We found considerable differences in NISI between neighborhoods corresponding to primary care areas with regard to early progress of the outbreak, as well as in terms of the total accumulated share of infected residents counted after the outbreak. The NISI can be used in local preparations of physical response measures during pandemics. PMID:21347087

Outbreak of acute respiratory disease caused by human adenovirus type 7 in a military training camp in Shaanxi, China.

PubMed

Yu, Pengbo; Ma, Chaofeng; Nawaz, Muhammad; Han, Lei; Zhang, Jianfang; Du, Quanli; Zhang, Lixia; Feng, Qunling; Wang, Jingjun; Xu, Jiru

2013-08-01

Outbreaks of ARD associated with HAdV have been reported in military populations in many countries. Here, we report an ARD outbreak caused by HAdV-7 in a military training camp in Shaanxi Province, China, from February to March of 2012. Epidemic data and samples from the patients were collected, and viral nucleotides from samples and viral isolations were detected and sequenced. IgG and IgA antibodies against HAdV, and the neutralization antibodies against the viral strain isolated in this outbreak, were detected. Epidemiological study showed that all personnel affected were males with an average age of 19.1 years. Two peaks appeared on the epicurve and there was an 8-day interval between peaks. Laboratory results of viral nucleotide detection carried out with clinical specimens were positive for HAdV (83.33%, 15/18). Further study through serum antibody assay, virus isolation and phylogenetic analysis showed that HAdV-7 was the etiological agent responsible for the outbreak. IgA antibody began to appear on the 4th day after the onset and showed 100% positivity on the 8th day. The virus strain in the present outbreak was highly similar to the virus isolated in Hanzhong Shaanxi in 2009. We conclude that HAdV-7 was the pathogen corresponding to the outbreak, and this is the first report of an ARD outbreak caused by HAdV-7 in military persons in China. Vaccine development, as well as enhanced epidemiological and virological surveillance of HAdV infections in China should be emphasized. © 2013 The Societies and Wiley Publishing Asia Pty Ltd.

Biosurveillance applying scan statistics with multiple, disparate data sources.

PubMed

Burkom, Howard S

2003-06-01

Researchers working on the Department of Defense Global Emerging Infections System (DoD-GEIS) pilot system, the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE), have applied scan statistics for early outbreak detection using both traditional and nontraditional data sources. These sources include medical data indexed by International Classification of Disease, 9th Revision (ICD-9) diagnosis codes, as well as less-specific, but potentially timelier, indicators such as records of over-the-counter remedy sales and of school absenteeism. Early efforts employed the Kulldorff scan statistic as implemented in the SaTScan software of the National Cancer Institute. A key obstacle to this application is that the input data streams are typically based on time-varying factors, such as consumer behavior, rather than simply on the populations of the component subregions. We have used both modeling and recent historical data distributions to obtain background spatial distributions. Data analyses have provided guidance on how to condition and model input data to avoid excessive clustering. We have used this methodology in combining data sources for both retrospective studies of known outbreaks and surveillance of high-profile events of concern to local public health authorities. We have integrated the scan statistic capability into a Microsoft Access-based system in which we may include or exclude data sources, vary time windows separately for different data sources, censor data from subsets of individual providers or subregions, adjust the background computation method, and run retrospective or simulated studies.

Environmental data analysis and remote sensing for early detection of dengue and malaria

NASA Astrophysics Data System (ADS)

Rahman, Md Z.; Roytman, Leonid; Kadik, Abdelhamid; Rosy, Dilara A.

2014-06-01

Malaria and dengue fever are the two most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for malaria and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities. We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of malaria and dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where malaria and dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria and dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.

Current and Emerging Legionella Diagnostics for Laboratory and Outbreak Investigations

PubMed Central

Mercante, Jeffrey W.

2015-01-01

SUMMARY Legionnaires' disease (LD) is an often severe and potentially fatal form of bacterial pneumonia caused by an extensive list of Legionella species. These ubiquitous freshwater and soil inhabitants cause human respiratory disease when amplified in man-made water or cooling systems and their aerosols expose a susceptible population. Treatment of sporadic cases and rapid control of LD outbreaks benefit from swift diagnosis in concert with discriminatory bacterial typing for immediate epidemiological responses. Traditional culture and serology were instrumental in describing disease incidence early in its history; currently, diagnosis of LD relies almost solely on the urinary antigen test, which captures only the dominant species and serogroup, Legionella pneumophila serogroup 1 (Lp1). This has created a diagnostic “blind spot” for LD caused by non-Lp1 strains. This review focuses on historic, current, and emerging technologies that hold promise for increasing LD diagnostic efficiency and detection rates as part of a coherent testing regimen. The importance of cooperation between epidemiologists and laboratorians for a rapid outbreak response is also illustrated in field investigations conducted by the CDC with state and local authorities. Finally, challenges facing health care professionals, building managers, and the public health community in combating LD are highlighted, and potential solutions are discussed. PMID:25567224

Methods for genotyping verotoxin-producing Escherichia coli.

PubMed

Karama, M; Gyles, C L

2010-12-01

Verotoxin-producing Escherichia coli (VTEC) is annually incriminated in more than 100,000 cases of enteric foodborne human disease and in losses amounting to $US 2.5 billion every year. A number of genotyping methods have been developed to track VTEC infections and determine diversity and evolutionary relationships among these microorganisms. These methods have facilitated monitoring and surveillance of foodborne VTEC outbreaks and early identification of outbreaks or clusters of outbreaks. Pulsed-field gel electrophoresis (PFGE) has been used extensively to track and differentiate VTEC because of its high discriminatory power, reproducibility and ease of standardization. Multiple-locus variable-number tandem-repeats analysis (MLVA) and microarrays are the latest genotyping methods that have been applied to discriminate VTEC. MLVA, a simpler and less expensive method, is proving to have a discriminatory power comparable to that of PFGE. Microarrays are successfully being applied to differentiate VTEC and make inferences on genome diversification. Novel methods that are being evaluated for subtyping VTEC include the detection of single nucleotide polymorphisms and optical mapping. This review discusses the principles, applications, advantages and disadvantages of genotyping methods that have been used to differentiate VTEC strains. These methods have been mainly used to differentiate strains of O157:H7 VTEC and to a lesser extent non-O157 VTEC. © 2009 Blackwell Verlag GmbH.

Implementation of Nationwide Real-time Whole-genome Sequencing to Enhance Listeriosis Outbreak Detection and Investigation.

PubMed

Jackson, Brendan R; Tarr, Cheryl; Strain, Errol; Jackson, Kelly A; Conrad, Amanda; Carleton, Heather; Katz, Lee S; Stroika, Steven; Gould, L Hannah; Mody, Rajal K; Silk, Benjamin J; Beal, Jennifer; Chen, Yi; Timme, Ruth; Doyle, Matthew; Fields, Angela; Wise, Matthew; Tillman, Glenn; Defibaugh-Chavez, Stephanie; Kucerova, Zuzana; Sabol, Ashley; Roache, Katie; Trees, Eija; Simmons, Mustafa; Wasilenko, Jamie; Kubota, Kristy; Pouseele, Hannes; Klimke, William; Besser, John; Brown, Eric; Allard, Marc; Gerner-Smidt, Peter

2016-08-01

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Effects of gypsy moth outbreaks on North American woodpeckers

Treesearch

Walter D. Koenig; Eric L. Walters; Andrew M. Liebhold

2011-01-01

We examined the effects of the introduced gypsy moth (Lymantria dispar) on seven species of North American woodpeckers by matching spatially explicit data on gypsy moth outbreaks with data on breeding and wintering populations. In general, we detected modest effects during outbreaks: during the breeding season one species, the Red-headed Woodpecker...

Whole genome sequencing may not be adequate to determine genome relatedness for surveillance and outbreak investigation of foodborne pathogens

USDA-ARS?s Scientific Manuscript database

Introduction: Advances in genomic technologies have improve the speed and precision of foodborne disease outbreak detection and response. For the past two decades, pulsed field gel electrophoresis (PFGE) has been the method of choice for surveillance and outbreak investigation with foodborne pathoge...

Characterization of an outbreak of Clostridium perfringens food poisoning by quantitative fecal culture and fecal enterotoxin measurement.

PubMed Central

Birkhead, G; Vogt, R L; Heun, E M; Snyder, J T; McClane, B A

1988-01-01

Published criteria for implicating Clostridium perfringens as the cause of food-poisoning outbreaks include finding a median fecal C. perfringens spore count of greater than 10(6)/g among specimens from ill persons. We investigated a food-poisoning outbreak with the epidemiologic characteristics of C. perfringens-related disease in a nursing home in which the median fecal spore count for ill patients (2.5 X 10(7)/g) was similar to that for well patients (4.0 X 10(6)/g), making the etiology of the outbreak uncertain. All ill and well patients tested had eaten turkey, the implicated food item. C. perfringens enterotoxin was detected by reverse passive latex agglutination in fecal specimens from six of six ill and none of four well patients who had eaten turkey (P = 0.005), suggesting that this organism had caused the outbreak. This investigation suggests that detection of fecal C. perfringens enterotoxin is a specific way to identify this organism as the causative agent in food-poisoning outbreaks. PMID:2895776

Syndromic surveillance system based on near real-time cattle mortality monitoring.

PubMed

Torres, G; Ciaravino, V; Ascaso, S; Flores, V; Romero, L; Simón, F

2015-05-01

Early detection of an infectious disease incursion will minimize the impact of outbreaks in livestock. Syndromic surveillance based on the analysis of readily available data can enhance traditional surveillance systems and allow veterinary authorities to react in a timely manner. This study was based on monitoring the number of cattle carcasses sent for rendering in the veterinary unit of Talavera de la Reina (Spain). The aim was to develop a system to detect deviations from expected values which would signal unexpected health events. Historical weekly collected dead cattle (WCDC) time series stabilized by the Box-Cox transformation and adjusted by the minimum least squares method were used to build the univariate cycling regression model based on a Fourier transformation. Three different models, according to type of production system, were built to estimate the baseline expected number of WCDC. Two types of risk signals were generated: point risk signals when the observed value was greater than the upper 95% confidence interval of the expected baseline, and cumulative risk signals, generated by a modified cumulative sum algorithm, when the cumulative sums of reported deaths were above the cumulative sum of expected deaths. Data from 2011 were used to prospectively validate the model generating seven risk signals. None of them were correlated to infectious disease events but some coincided, in time, with very high climatic temperatures recorded in the region. The harvest effect was also observed during the first week of the study year. Establishing appropriate risk signal thresholds is a limiting factor of predictive models; it needs to be adjusted based on experience gained during the use of the models. To increase the sensitivity and specificity of the predictions epidemiological interpretation of non-specific risk signals should be complemented by other sources of information. The methodology developed in this study can enhance other existing early detection surveillance systems. Syndromic surveillance based on mortality monitoring can reduce the detection time for certain disease outbreaks associated with mild mortality only detected at regional level. The methodology can be adapted to monitor other parameters routinely collected at farm level which can be influenced by communicable diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

A Study of Failure Events in Drinking Water Systems As a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse Schemes

PubMed Central

Onyango, Laura A.; Quinn, Chloe; Tng, Keng H.; Wood, James G.; Leslie, Greg

2015-01-01

Potable reuse is implemented in several countries around the world to augment strained water supplies. This article presents a public health perspective on potable reuse by comparing the critical infrastructure and institutional capacity characteristics of two well-established potable reuse schemes with conventional drinking water schemes in developed nations that have experienced waterborne outbreaks. Analysis of failure events in conventional water systems between 2003 and 2013 showed that despite advances in water treatment technologies, drinking water outbreaks caused by microbial contamination were still frequent in developed countries and can be attributed to failures in infrastructure or institutional practices. Numerous institutional failures linked to ineffective treatment protocols, poor operational practices, and negligence were detected. In contrast, potable reuse schemes that use multiple barriers, online instrumentation, and operational measures were found to address the events that have resulted in waterborne outbreaks in conventional systems in the past decade. Syndromic surveillance has emerged as a tool in outbreak detection and was useful in detecting some outbreaks; increases in emergency department visits and GP consultations being the most common data source, suggesting potential for an increasing role in public health surveillance of waterborne outbreaks. These results highlight desirable characteristics of potable reuse schemes from a public health perspective with potential for guiding policy on surveillance activities. PMID:27053920

A Study of Failure Events in Drinking Water Systems As a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse Schemes.

PubMed

Onyango, Laura A; Quinn, Chloe; Tng, Keng H; Wood, James G; Leslie, Greg

2015-01-01

Potable reuse is implemented in several countries around the world to augment strained water supplies. This article presents a public health perspective on potable reuse by comparing the critical infrastructure and institutional capacity characteristics of two well-established potable reuse schemes with conventional drinking water schemes in developed nations that have experienced waterborne outbreaks. Analysis of failure events in conventional water systems between 2003 and 2013 showed that despite advances in water treatment technologies, drinking water outbreaks caused by microbial contamination were still frequent in developed countries and can be attributed to failures in infrastructure or institutional practices. Numerous institutional failures linked to ineffective treatment protocols, poor operational practices, and negligence were detected. In contrast, potable reuse schemes that use multiple barriers, online instrumentation, and operational measures were found to address the events that have resulted in waterborne outbreaks in conventional systems in the past decade. Syndromic surveillance has emerged as a tool in outbreak detection and was useful in detecting some outbreaks; increases in emergency department visits and GP consultations being the most common data source, suggesting potential for an increasing role in public health surveillance of waterborne outbreaks. These results highlight desirable characteristics of potable reuse schemes from a public health perspective with potential for guiding policy on surveillance activities.

Noroviruses associated with acute gastroenteritis in a children's day care facility in Rio de Janeiro, Brazil.

PubMed

Gallimore, C I; Barreiros, M A B; Brown, D W G; Nascimento, J P; Leite, J P G

2004-03-01

Noroviruses (Norwalk-like viruses) are an important cause of gastroenteritis worldwide. They are the most common cause of outbreaks of gastroenteritis in the adult population and occur in nursing homes for the elderly, geriatric wards, medical wards, and in hotel and restaurant settings. Food-borne outbreaks have also occurred following consumption of contaminated oysters. This study describes the application of a reverse transcription-polymerase chain reaction (RT-PCR) assay using random primers (PdN6) and specific Ni and E3 primers, directed at a small region of the RNA-dependent RNA polymerase-coding region of the norovirus genome, and DNA sequencing for the detection and preliminary characterisation of noroviruses in outbreaks of gastroenteritis in children in Brazil. The outbreak samples were collected from children <5 years of age at the Bertha Lutz children's day care facility at Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, that occurred between 1996 and 1998, where no pathogen had been identified. At the Bertha Lutz day care center facility, only Fiocruz's employee children are provided for, and they come from different social, economic and cultural backgrounds. Three distinct genogroup II strains were detected in three outbreaks in 1997/98 and were most closely related to genotypes GII-3 (Mexico virus) and GII-4 (Grimsby virus), both of which have been detected in paediatric and adult outbreaks of gastroenteritis worldwide.

First detection of foot-and-mouth disease virus O/Ind-2001d in Vietnam.

PubMed

Vu, Le T; Long, Ngo T; Brito, Barbara; Stenfeldt, Carolina; Phuong, Nguyen T; Hoang, Bui H; Pauszek, Steven J; Hartwig, Ethan J; Smoliga, George R; Vu, Pham P; Quang, Le T V; Hung, Vo V; Tho, Nguyen D; Dong, Pham V; Minh, Phan Q; Bertram, Miranda; Fish, Ian H; Rodriguez, Luis L; Dung, Do H; Arzt, Jonathan

2017-01-01

In recent years, foot-and-mouth disease virus (FMDV) serotype O, topotype Middle East-South Asia (ME-SA), lineage Ind-2001d has spread from the Indian subcontinent to the Middle East, North Africa, and Southeast Asia. In the current report, we describe the first detection of this lineage in Vietnam in May, 2015 in Đắk Nông province. Three subsequent outbreaks caused by genetically related viruses occurred between May-October, 2015 after which the virus was not detected in clinical outbreaks for at least 15 subsequent months. The observed outbreaks affected (in chronological order): cattle in Đắk Nông province, pigs in Đắk Lắk province and Đắk Nông province, and cattle in Ninh Thuận province. The clinical syndromes associated with these outbreaks were consistent with typical FMD in the affected species. Overall attack rate on affected premises was 0.85 in pigs and 0.93 in cattle over the course of the outbreak. Amongst 378 pigs at risk on affected premises, 85 pigs died during the outbreaks; there were no deaths among cattle. The manner in which FMDV/O/ME-SA/Ind-2001d was introduced into Vietnam remains undetermined; however, movement of live cattle is the suspected route. This incursion has substantial implications for epidemiology and control of FMD in Southeast Asia.

Re-emerging Lassa fever outbreaks in Nigeria: Re-enforcing "One Health" community surveillance and emergency response practice.

PubMed

Tambo, Ernest; Adetunde, Oluwasegun T; Olalubi, Oluwasogo A

2018-04-28

We evaluated the impact of man-made conflict events and climate change impact in guiding evidence-based community "One Health" epidemiology and emergency response practice against re-/emerging epidemics. Increasing evidence of emerging and re-emerging zoonotic diseases including recent Lassa fever outbreaks in almost 20 states in Nigeria led to 101 deaths and 175 suspected and confirmed cases since August 2015. Of the 75 laboratory confirmed cases, 90 deaths occurred representing 120% laboratory-confirmed case fatality. The outbreak has been imported into neighbouring country such as Benin, where 23 deaths out of 68 cases has also been reported. This study assesses the current trends in re-emerging Lassa fever outbreak in understanding spatio-geographical reservoir(s), risk factors pattern and Lassa virus incidence mapping, inherent gaps and raising challenges in health systems. It is shown that Lassa fever peak endemicity incidence and prevalence overlap the dry season (within January to March) and reduced during the wet season (of May to November) annually in Sierra Leone, Senegal to Eastern Nigeria. We documented a scarcity of consistent data on rodent (reservoirs)-linked Lassa fever outbreak, weak culturally and socio-behavioural effective prevention and control measures integration, weak or limited community knowledge and awareness to inadequate preparedness capacity and access to affordable case management in affected countries. Hence, robust sub/regional leadership commitment and investment in Lassa fever is urgently needed in building integrated and effective community "One Health" surveillance and rapid response approach practice coupled with pest management and phytosanitation measures against Lassa fever epidemic. This offers new opportunities in understanding human-animal interactions in strengthening Lassa fever outbreak early detection and surveillance, warning alerts and rapid response implementation in vulnerable settings. Leveraging on Africa CDC centre, advances in cloud-sourcing and social media tools and solutions is core in developing and integrating evidence-based and timely risk communication, and reporting systems in improving contextual community-based immunization and control decision making policy to effectively defeat Lassa fever outbreak and other emerging pandemics public health emergencies in Africa and worldwide.

Quick control of bubonic plague outbreak in Uttar Kashi, India.

PubMed

Mittal, Veena; Rana, U V S; Jain, S K; Kumar, Kaushal; Pal, I S; Arya, R C; Ichhpujani, R L; Lal, Shiv; Agarwal, S P

2004-12-01

A localized outbreak of bubonic plague occurred in village Dangud (population 332), district Uttar Kashi, Uttaranchal, India in the second week of October 2004. 8 cases were considered outbreak associated based on their clinical and epidemiological characteristics; 3 (27.3%) of them died within 48 hours of developing illness. All the 3 fatal cases and five surviving cases had enlargement of inguinal lymph nodes. None of them had pneumonia. The age of the cases ranged from 23-70 years and both sexes were affected. No such illness was reported from adjoining villages. The outbreak was fully contained within two weeks of its onset by supervised comprehensive chemoprophylaxis using tetracycline. A total of approximately 1250 persons were given chemoprophylaxis in three villages. There was no clear history of rat fall in the village. No flea was found on rodents or animals. 16 animal serum samples were found to be negative for antibodies against F-1 antigen of Y. pestis. However, Y. pestis was isolated from two rodents (Rattus rattus and Mus musculus) trapped in the village. One case and three animal sera showed borderline sero-positivity against rickettsial infection. The diagnosis of plague was confirmed by detection of four fold rise of antibody titre against F-1 antigen of Yersinia pestis in paired sera of three cases (one of the WHO approved criteria of diagnosis of confirmed plague). This outbreak and the occurrence of earlier outbreaks of plague in Surat (Gujarat) and Beed (Maharashtra) in 1994 and in district Shimla (Himachal Pradesh) in 2002 confirm that plague infection continue to exist in sylvatic foci in many parts of India which is transmitted to humans occasionally. Thus, there is a strong need for the States to monitor the plague activity in known sylvatic foci regularly and have a system of surveillance to facilitate prompt diagnosis and treatment of cases to control the disease. This investigation highlights that with high index of suspicion the disease can be diagnosed early and mounting of supervised comprehensive response can prevent the disease to proceed to pneumonic stage where man to man transmission gets established and outbreak assumes larger dimensions.

The transmissibility estimation of influenza with early stage data of small-scale outbreaks in Changsha, China, 2005-2013.

PubMed

Chen, T M; Chen, Q P; Liu, R C; Szot, A; Chen, S L; Zhao, J; Zhou, S S

2017-02-01

Hundreds of small-scale influenza outbreaks in schools are reported in mainland China every year, leading to a heavy disease burden which seriously impacts the operation of affected schools. Knowing the transmissibility of each outbreak in the early stage has become a major concern for public health policy-makers and primary healthcare providers. In this study, we collected all the small-scale outbreaks in Changsha (a large city in south central China with ~7·04 million population) from January 2005 to December 2013. Four simple and popularly used models were employed to calculate the reproduction number (R) of these outbreaks. Given that the duration of a generation interval Tc = 2·7 and the standard deviation (s.d.) σ = 1·1, the mean R estimated by an epidemic model, normal distribution and delta distribution were 2·51 (s.d. = 0·73), 4·11 (s.d. = 2·20) and 5·88 (s.d. = 5·00), respectively. When Tc = 2·9 and σ = 1·4, the mean R estimated by the three models were 2·62 (s.d. = 0·78), 4·72 (s.d. = 2·82) and 6·86 (s.d. = 6·34), respectively. The mean R estimated by gamma distribution was 4·32 (s.d. = 2·47). We found that the values of R in small-scale outbreaks in schools were higher than in large-scale outbreaks in a neighbourhood, city or province. Normal distribution, delta distribution, and gamma distribution models seem to more easily overestimate the R of influenza outbreaks compared to the epidemic model.

Molecular evolution of H5N1 in Thailand between 2004 and 2008.

PubMed

Suwannakarn, Kamol; Amonsin, Alongkorn; Sasipreeyajan, Jiroj; Kitikoon, Pravina; Tantilertcharoen, Rachod; Parchariyanon, Sujira; Chaisingh, Arunee; Nuansrichay, Bandit; Songserm, Thaweesak; Theamboonlers, Apiradee; Poovorawan, Yong

2009-09-01

Highly pathogenic avian influenza (HPAI) H5N1 viruses have seriously affected the Asian poultry industry since their occurrence in 2004. Thailand has been one of those countries exposed to HPAI H5N1 outbreaks. This project was designed to compare the molecular evolution of HPAI H5N1 in Thailand between 2004 and 2008. Viruses with clade 1 hemagglutinin (HA) were first observed in early 2004 and persisted until 2008. Viruses with clade 2.3.4 HA were first observed in the northeastern region of Thailand between 2006 and 2007. Phylogenetic analysis among Thai isolates indicated that clade 1 viruses in Thailand consist of three distinct lineages: CUK2-like, PC168-like, and PC170-like viruses. The CUK2-like virus represents the predominant lineage and has been circulating throughout the course of the 4-year outbreaks. Analysis of recently isolated viruses has shown that the genetic distance was slightly different from viruses of the early outbreak and that CUK2-like viruses comprise the native strain. Between 2005 and 2007, PC168-like and PC170-like viruses were first observed in several areas around central and lower northern Thailand. In 2008, viruses reassorted from these two lineages, PC168-like and PC170-like viruses, were initially isolated in the lower northern provinces of Thailand and subsequently spread to the upper central part of Thailand. On the other hand, CUK2-like viruses were still detected around the lower northern and the upper central part of Thailand. Furthermore, upon emergence of the reassorted viruses, the PC168-like and PC170-like lineages could not be detected, suggesting that the only predominant strains still circulating in Thailand were CUK2-like and reassorted viruses. The substitution rate among clade 1 viruses in Thailand was lower. The virus being limited to the same area might explain the lower nucleotide substitution rate. This study has demonstrated that nationwide attempts to monitor the virus may help curb access and propagation of new HPAI viral genes.

Proposal of a framework for evaluating military surveillance systems for early detection of outbreaks on duty areas

PubMed Central

Meynard, Jean-Baptiste; Chaudet, Herve; Green, Andrew D; Jefferson, Henry L; Texier, Gaetan; Webber, Daniel; Dupuy, Bruce; Boutin, Jean-Paul

2008-01-01

Background In recent years a wide variety of epidemiological surveillance systems have been developed to provide early identification of outbreaks of infectious disease. Each system has had its own strengths and weaknesses. In 2002 a Working Group of the Centers for Disease Control and Prevention (CDC) produced a framework for evaluation, which proved suitable for many public health surveillance systems. However this did not easily adapt to the military setting, where by necessity a variety of different parameters are assessed, different constraints placed on the systems, and different objectives required. This paper describes a proposed framework for evaluation of military syndromic surveillance systems designed to detect outbreaks of disease on operational deployments. Methods The new framework described in this paper was developed from the cumulative experience of British and French military syndromic surveillance systems. The methods included a general assessment framework (CDC), followed by more specific methods of conducting evaluation. These included Knowledge/Attitude/Practice surveys (KAP surveys), technical audits, ergonomic studies, simulations and multi-national exercises. A variety of military constraints required integration into the evaluation. Examples of these include the variability of geographical conditions in the field, deployment to areas without prior knowledge of naturally-occurring disease patterns, the differences in field sanitation between locations and over the length of deployment, the mobility of military forces, turnover of personnel, continuity of surveillance across different locations, integration with surveillance systems from other nations working alongside each other, compatibility with non-medical information systems, and security. Results A framework for evaluation has been developed that can be used for military surveillance systems in a staged manner consisting of initial, intermediate and final evaluations. For each stage of the process parameters for assessment have been defined and methods identified. Conclusion The combined experiences of French and British syndromic surveillance systems developed for use in deployed military forces has allowed the development of a specific evaluation framework. The tool is suitable for use by all nations who wish to evaluate syndromic surveillance in their own military forces. It could also be useful for civilian mobile systems or for national security surveillance systems. PMID:18447944

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009-2010.

PubMed

Shak, Emma B; France, Anne Marie; Cowan, Lauren; Starks, Angela M; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009-December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups.

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009–2010

PubMed Central

Shak, Emma B.; Cowan, Lauren; Starks, Angela M.; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009–December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups. PMID:26556930

Characteristics of Clusters of Salmonella and Escherichia coli O157 Detected by Pulsed-Field Gel Electrophoresis that Predict Identification of Outbreaks.

PubMed

Jones, Timothy F; Sashti, Nupur; Ingram, Amanda; Phan, Quyen; Booth, Hillary; Rounds, Joshua; Nicholson, Cyndy S; Cosgrove, Shaun; Crocker, Kia; Gould, L Hannah

2016-12-01

Molecular subtyping of pathogens is critical for foodborne disease outbreak detection and investigation. Many clusters initially identified by pulsed-field gel electrophoresis (PFGE) are not confirmed as point-source outbreaks. We evaluated characteristics of clusters that can help prioritize investigations to maximize effective use of limited resources. A multiagency collaboration (FoodNet) collected data on Salmonella and Escherichia coli O157 clusters for 3 years. Cluster size, timing, extent, and nature of epidemiologic investigations were analyzed to determine associations with whether the cluster was identified as a confirmed outbreak. During the 3-year study period, 948 PFGE clusters were identified; 849 (90%) were Salmonella and 99 (10%) were E. coli O157. Of those, 192 (20%) were ultimately identified as outbreaks (154 [18%] of Salmonella and 38 [38%] of E. coli O157 clusters). Successful investigation was significantly associated with larger cluster size, more rapid submission of isolates (e.g., for Salmonella, 6 days for outbreaks vs. 8 days for nonoutbreaks) and PFGE result reporting to investigators (16 days vs. 29 days, respectively), and performance of analytic studies (completed in 33% of Salmonella outbreaks vs. 1% of nonoutbreaks) and environmental investigations (40% and 1%, respectively). Intervals between first and second cases in a cluster did not differ significantly between outbreaks and nonoutbreaks. Molecular subtyping of pathogens is a rapidly advancing technology, and successfully identifying outbreaks will vary by pathogen and methods used. Understanding criteria for successfully investigating outbreaks is critical for efficiently using limited resources.

Detection of macroalgae blooms by complex SAR imagery.

PubMed

Shen, Hui; Perrie, William; Liu, Qingrong; He, Yijun

2014-01-15

Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Selection tool for foodborne norovirus outbreaks.

PubMed

Verhoef, Linda P B; Kroneman, Annelies; van Duynhoven, Yvonne; Boshuizen, Hendriek; van Pelt, Wilfrid; Koopmans, Marion

2009-01-01

Detection of pathogens in the food chain is limited mainly to bacteria, and the globalization of the food industry enables international viral foodborne outbreaks to occur. Outbreaks from 2002 through 2006 recorded in a European norovirus surveillance database were investigated for virologic and epidemiologic indicators of food relatedness. The resulting validated multivariate logistic regression model comparing foodborne (n = 224) and person-to-person (n = 654) outbreaks was used to create a practical web-based tool that can be limited to epidemiologic parameters for nongenotyping countries. Non-genogroup-II.4 outbreaks, higher numbers of cases, and outbreaks in restaurants or households characterized (sensitivity = 0.80, specificity = 0.86) foodborne outbreaks and reduced the percentage of outbreaks requiring source-tracing to 31%. The selection tool enabled prospectively focused follow-up. Use of this tool is likely to improve data quality and strain typing in current surveillance systems, which is necessary for identification of potential international foodborne outbreaks.

Coccidioidomycosis Outbreaks, United States and Worldwide, 1940-2015.

PubMed

Freedman, Michael; Jackson, Brendan R; McCotter, Orion; Benedict, Kaitlin

2018-03-01

Coccidioidomycosis causes substantial illness and death in the United States each year. Although most cases are sporadic, outbreaks provide insight into the clinical and environmental features of coccidioidomycosis, high-risk activities, and the geographic range of Coccidioides fungi. We identified reports published in English of 47 coccidioidomycosis outbreaks worldwide that resulted in 1,464 cases during 1940-2015. Most (85%) outbreaks were associated with environmental exposures; the 2 largest outbreaks resulted from an earthquake and a large dust storm. More than one third of outbreaks occurred in areas where the fungus was not previously known to be endemic, and more than half of outbreaks involved occupational exposures. Coccidioidomycosis outbreaks can be difficult to detect and challenging to prevent given the unknown effectiveness of environmental control methods and personal protective equipment; therefore, increased awareness of coccidioidomycosis outbreaks is needed among public health professionals, healthcare providers, and the public.

Coccidioidomycosis Outbreaks, United States and Worldwide, 1940–2015

PubMed Central

Freedman, Michael; Jackson, Brendan R.; McCotter, Orion

2018-01-01

Coccidioidomycosis causes substantial illness and death in the United States each year. Although most cases are sporadic, outbreaks provide insight into the clinical and environmental features of coccidioidomycosis, high-risk activities, and the geographic range of Coccidioides fungi. We identified reports published in English of 47 coccidioidomycosis outbreaks worldwide that resulted in 1,464 cases during 1940–2015. Most (85%) outbreaks were associated with environmental exposures; the 2 largest outbreaks resulted from an earthquake and a large dust storm. More than one third of outbreaks occurred in areas where the fungus was not previously known to be endemic, and more than half of outbreaks involved occupational exposures. Coccidioidomycosis outbreaks can be difficult to detect and challenging to prevent given the unknown effectiveness of environmental control methods and personal protective equipment; therefore, increased awareness of coccidioidomycosis outbreaks is needed among public health professionals, healthcare providers, and the public. PMID:29460741

[Outbreaks of acute gastroenteritis caused by small round structured viruses in Tokyo].

PubMed

Sekine, S; Hayashi, Y; Ando, T; Ohta, K; Miki, T; Okada, S

1992-07-01

Of 34 non-bacterial gastroenteritis outbreaks which occurred at day-care centers, kindergartens, elementary and secondary schools in Tokyo during the period from February 1985 to June 1991, 28 outbreaks from which small round structured viruses (SRSV) were detected in the patients' stool specimens by electron microscopy were subjected to an epidemiological investigation. The outbreaks tended to occur frequently in the cold season; twenty-two (79%) of these outbreaks from November through April. Though detailed epidemiological informations was not obtained from all outbreaks, the common source of infection were presumed to be present in many of the outbreaks, judged from the incidence as to time course of patients. Food doubted to be incriminated as transmission vehicles in these outbreaks was served at schools, kindergartens, and lodgings. In some outbreaks, SRSV was detected from stool specimens of food handlers, or they were seroconverted to SRSV, suggesting that food was incriminated as a transmission vehicle. The symptoms of patients differ slightly from age to age: in the age range of 0 to 6 years, vomiting 90%, fever 41% and diarrhea 32%; in the 6 to 12 year-olds, nausea 61%, vomiting 48%, abdominal pain 65%, diarrhea 20% and fever 29%; and in the 12 to 15 year-olds, nausea 69%, vomiting 42%, abdominal pain 60%, diarrhea 30% and fever 34%. The lower the age of patient vomiting was more frequently observed. In these lower age groups, the frequency of nausea and vomiting tended to exceed that of diarrhea.

Steep rise in norovirus cases and emergence of a new recombinant strain GII.P16-GII.2, Germany, winter 2016.

PubMed

Niendorf, S; Jacobsen, S; Faber, M; Eis-Hübinger, A M; Hofmann, J; Zimmermann, O; Höhne, M; Bock, C T

2017-01-26

Since early November 2016, the number of laboratory-confirmed norovirus infections reported in Germany has been increasing steeply. Here, we report the detection and genetic characterisation of an emerging norovirus recombinant, GII.P16-GII.2. This strain was frequently identified as the cause of sporadic cases as well as outbreaks in nine federal states of Germany. Our findings suggest that the emergence of GII.P16-GII.2 contributed to rising case numbers of norovirus gastroenteritis in Germany. This article is copyright of The Authors, 2017.

Quantification and molecular characterization of Salmonella isolated from food samples involved in salmonellosis outbreaks in Rio Grande do Sul, Brazil

PubMed Central

Mürmann, Lisandra; dos Santos, Maria Cecília; Longaray, Solange Mendes; Both, Jane Mari Corrêa; Cardoso, Marisa

2008-01-01

Data concerning the prevalence and populations of Salmonella in foods implicated in outbreaks may be important to the development of quantitative microbial risk assessments of individual food products. In this sense, the objective of the present study was to assess the amount of Salmonella sp. in different foods implicated in foodborne outbreaks in Rio Grande do Sul occurred in 2005 and to characterize the isolated strains using phenotypic and genotypic methods. Nineteen food samples involved in ten foodborne outbreaks occurred in 2005, and positive on Salmonella isolation at the Central Laboratory of the Health Department of the State of Rio Grande do Sul, were included in this study. Food samples were submitted to estimation of Salmonella using the Most Probable Number (MPN) technique. Moreover, one confirmed Salmonella colony of each food sample was serotyped, characterized by its XbaI-macrorestriction profile, and submitted to antimicrobial resistance testing. Foods containing eggs, mayonnaise or chicken were contaminated with Salmonella in eight outbreaks. Higher counts (>107 MPN.g-1) of Salmonella were detected mostly in foods containing mayonnaise. The isolation of Salmonella from multiple food items in five outbreaks probably resulted from the cross-contamination, and the high Salmonella counts detected in almost all analyzed samples probably resulted from storing in inadequate temperature. All strains were identified as S. Enteritidis, and presented a unique macrorestriction profile, demonstrating the predominance of one clonal group in foods involved in the salmonellosis outbreaks. A low frequency of antimicrobial resistant S. Enteritidis strains was observed and nalidixic acid was the only resistance marker detected. PMID:24031261

Using demographic characteristics of populations to detect spatial fragmentation following suspected ebola outbreaks in great apes.

PubMed

Genton, Céline; Cristescu, Romane; Gatti, Sylvain; Levréro, Florence; Bigot, Elodie; Motsch, Peggy; Le Gouar, Pascaline; Pierre, Jean-Sébastien; Ménard, Nelly

2017-09-01

Demographic crashes due to emerging diseases can contribute to population fragmentation and increase extinction risk of small populations. Ebola outbreaks in 2002-2004 are suspected to have caused a decline of more than 80% in some Western lowland gorilla (Gorilla gorilla gorilla) populations. We investigated whether demographic indicators of this event allowed for the detection of spatial fragmentation in gorilla populations. We collected demographic data from two neighbouring populations: the Lokoué population, suspected to have been affected by an Ebola outbreak (followed from 2001 to 2014), and the Romani population, of unknown demographic status before Ebola outbreaks (followed from 2005 to 2014). Ten years after the outbreak, the Lokoué population is slowly recovering and the short-term demographic indicators of a population crash were no longer detectable. The Lokoué population has not experienced any additional demographic perturbation over the past decade. The Romani population did not show any of the demographic indicators of a population crash over the past decade. Its demographic structure remained similar to that of unaffected populations. Our results highlighted that the Ebola disease could contribute to fragmentation of gorilla populations due to the spatially heterogeneous impact of its outbreaks. The demographic structure of populations (i.e., age-sex and group structure) can be useful indicators of a possible occurrence of recent Ebola outbreaks in populations without known history, and may be more broadly used in other emerging disease/species systems. Longitudinal data are critical to our understanding of the impact of emerging diseases on wild populations and their conservation. © 2017 Wiley Periodicals, Inc.

Role of healthcare workers in early epidemic spread of Ebola: policy implications of prophylactic compared to reactive vaccination policy in outbreak prevention and control.

PubMed

Coltart, Cordelia E M; Johnson, Anne M; Whitty, Christopher J M

2015-10-19

Ebola causes severe illness in humans and has epidemic potential. How to deploy vaccines most effectively is a central policy question since different strategies have implications for ideal vaccine profile. More than one vaccine may be needed. A vaccine optimised for prophylactic vaccination in high-risk areas but when the virus is not actively circulating should be safe, well tolerated, and provide long-lasting protection; a two- or three-dose strategy would be realistic. Conversely, a reactive vaccine deployed in an outbreak context for ring-vaccination strategies should have rapid onset of protection with one dose, but longevity of protection is less important. In initial cases, before an outbreak is recognised, healthcare workers (HCWs) are at particular risk of acquiring and transmitting infection, thus potentially augmenting early epidemics. We hypothesise that many early outbreak cases could be averted, or epidemics aborted, by prophylactic vaccination of HCWs. This paper explores the potential impact of prophylactic versus reactive vaccination strategies of HCWs in preventing early epidemic transmissions. To do this, we use the limited data available from Ebola epidemics (current and historic) to reconstruct transmission trees and illustrate the theoretical impact of these vaccination strategies. Our data suggest a substantial potential benefit of prophylactic versus reactive vaccination of HCWs in preventing early transmissions. We estimate that prophylactic vaccination with a coverage >99% and theoretical 100% efficacy could avert nearly two-thirds of cases studied; 75% coverage would still confer clear benefit (40% cases averted), but reactive vaccination would be of less value in the early epidemic. A prophylactic vaccination campaign for front-line HCWs is not a trivial undertaking; whether to prioritise long-lasting vaccines and provide prophylaxis to HCWs is a live policy question. Prophylactic vaccination is likely to have a greater impact on the mitigation of future epidemics than reactive strategies and, in some cases, might prevent them. However, in a confirmed outbreak, reactive vaccination would be an essential humanitarian priority. The value of HCW Ebola vaccination is often only seen in terms of personal protection of the HCW workforce. A prophylactic vaccination strategy is likely to bring substantial additional benefit by preventing early transmission and might abort some epidemics. This has implications both for policy and for the optimum product profile for vaccines currently in development.

Vermont management in focal areas

Treesearch

Judy Rosovsky; Bruce L. Parker; Luke Curtis

1991-01-01

Following the 1979 outbreak of gypsy moths Lymantria dispar L. in Vermont, state personnel began monitoring a number of focal areas for signs of increase in gypsy moth populations. In 1986 data from this early warning system indicated an incipient outbreak. We took advantage of this increase to test an experimental management technique. Would...

TRACKING A SALMONELLA SEROVAR TYPHIMURIUM OUTBREAK IN GIDEON, MISSOURI: ROLE OF CONTAMINANT PROPAGATION MODELLING

EPA Science Inventory

In early 12/93, a waterborne disease outbreak was identified in Gideon, MO. Initially 6-9 cases of diarrhoea were identified at a local nursing home. By 1/8/94, 31 cases with lbarotory confirmed salmonellosis had been identified. Seven nursing home residents exhibiting diarrhoeal...

A new prior for bayesian anomaly detection: application to biosurveillance.

PubMed

Shen, Y; Cooper, G F

2010-01-01

Bayesian anomaly detection computes posterior probabilities of anomalous events by combining prior beliefs and evidence from data. However, the specification of prior probabilities can be challenging. This paper describes a Bayesian prior in the context of disease outbreak detection. The goal is to provide a meaningful, easy-to-use prior that yields a posterior probability of an outbreak that performs at least as well as a standard frequentist approach. If this goal is achieved, the resulting posterior could be usefully incorporated into a decision analysis about how to act in light of a possible disease outbreak. This paper describes a Bayesian method for anomaly detection that combines learning from data with a semi-informative prior probability over patterns of anomalous events. A univariate version of the algorithm is presented here for ease of illustration of the essential ideas. The paper describes the algorithm in the context of disease-outbreak detection, but it is general and can be used in other anomaly detection applications. For this application, the semi-informative prior specifies that an increased count over baseline is expected for the variable being monitored, such as the number of respiratory chief complaints per day at a given emergency department. The semi-informative prior is derived based on the baseline prior, which is estimated from using historical data. The evaluation reported here used semi-synthetic data to evaluate the detection performance of the proposed Bayesian method and a control chart method, which is a standard frequentist algorithm that is closest to the Bayesian method in terms of the type of data it uses. The disease-outbreak detection performance of the Bayesian method was statistically significantly better than that of the control chart method when proper baseline periods were used to estimate the baseline behavior to avoid seasonal effects. When using longer baseline periods, the Bayesian method performed as well as the control chart method. The time complexity of the Bayesian algorithm is linear in the number of the observed events being monitored, due to a novel, closed-form derivation that is introduced in the paper. This paper introduces a novel prior probability for Bayesian outbreak detection that is expressive, easy-to-apply, computationally efficient, and performs as well or better than a standard frequentist method.

Outbreaks and Investigations

MedlinePlus

... on Facebook Tweet Share Compartir Disease detectives collecting soil samples to test for fungus When fungal disease ... a hydroelectric dam Source: related to disruption of soil contaminated with bat droppings Outbreak investigation partners: Dominican ...

Detection of West Nile Virus - Lineage 2 in Culex pipiens mosquitoes, associated with disease outbreak in Greece, 2017.

PubMed

Mavridis, Konstantinos; Fotakis, Emmanouil A; Kioulos, Ilias; Mpellou, Spiridoula; Konstantas, Spiros; Varela, Evangelia; Gewehr, Sandra; Diamantopoulos, Vasilis; Vontas, John

2018-06-01

During July-October 2017 a WNV outbreak took place in the Peloponnese, Southern Greece with five confirmed deaths. During routine monitoring survey in the Peloponnese, supported by the local Prefecture, we have confirmed the presence of all three Culex pipiens biotypes in the region, with a high percentage of Culex pipiens/molestus hybrids (37.0%) which are considered a highly competent vector of WNV. Kdr mutations related to pyrethroid resistance were found at relatively low levels (14.3% homozygosity) while no mosquitoes harboring the recently identified chitin synthase diflubenzuron-resistance mutations were detected in the region. As an immediate action, following the disease outbreak (within days), we collected a large number of mosquitoes using CO 2 CDC traps from the villages in the Argolis area of the Peloponnese, where high incidence of WNV human infections were reported. WNV lineage 2 was detected in 3 out of 47 Cx. pipiens mosquito pools (detection rate = 6.38%). The virus was not detected in any other mosquito species, such as Aedes albopictus, sampled from the region at the time of the disease outbreak. Our results show that detection of WNV lineage 2 in Cx. pipiens pools is spatially and chronologically associated with human clinical cases, thus implicating Cx. pipiens mosquitoes as the most likely WNV vector. The absence of diflubenzuron resistance mutations and the low frequency of pyrethroid (kdr) resistance mutations indicates the suitability of these insecticides for Cx. pipiens control, in the format of larvicides and/or residual spraying applications respectively, which was indeed the main (evidence based) response, following the disease outbreak. Copyright © 2018 Elsevier B.V. All rights reserved.

Live Bird Exposure among the General Public, Guangzhou, China, May 2013

PubMed Central

Ma, Xiao Wei; Chen, Jian Dong; Liu, Yan Hui; Wang, Chang; Tang, Xiao Ping; Liu, Yu Fei; Zhuo, Li; Leung, Gabriel M.; Zhang, Wei; Cowling, Benjamin J.; Wang, Ming; Fielding, Richard

2015-01-01

Background A novel avian-origin influenza A(H7N9) caused a major outbreak in Mainland China in early 2013. Exposure to live poultry was believed to be the major route of infection. There are limited data on how the general public changes their practices regarding live poultry exposure in response to the early outbreak of this novel influenza and the frequency of population exposure to live poultry in different areas of China. Methodology This study investigated population exposures to live birds from various sources during the outbreak of H7N9 in Guangzhou city, China in 2013 and compared them with those observed during the 2006 influenza A(H5N1) outbreak. Adults were telephone-interviewed using two-stage sampling, stratified by three residential areas of Guangzhou: urban areas and two semi-rural areas in one of which (Zengcheng) A(H7N9) virus was detected in a chicken from wet markets. Logistic regression models were built to describe practices protecting against avian influenza, weighted by age and gender, and then compare these practices across residential areas in 2013 with those from a comparable 2006 survey. Principal Findings Of 1196 respondents, 45% visited wet markets at least daily and 22.0% reported buying live birds from wet markets at least weekly in April-May, 2013, after the H7N9 epidemic was officially declared in late March 2013. Of those buying live birds, 32.3% reported touching birds when buying and 13.7% would slaughter the poultry at home. Although only 10.1% of the respondents reported raising backyard birds, 92.1% of those who did so had physical contact with the birds they raised. Zengcheng respondents were less likely to report buying live birds from wet markets, but more likely to buy from other sources when compared to urban respondents. Compared with the 2006 survey, the prevalence of buying live birds from wet markets, touching when buying and slaughtering birds at home had substantially declined in the 2013 survey. Conclusion/Significance Although population exposures to live poultry were substantially fewer in 2013 compared to 2006, wet markets and backyard poultry remained the two major sources of live bird exposures for the public in Guangzhou in 2013. Zengcheng residents seemed to have reduced buying live birds from wet markets but not from other sources in response to the detection of H7N9 virus in wet markets. PMID:26623646

An analysis of an early-warning system to reduce abortions in dairy cattle in Denmark incorporating both financial and epidemiologic aspects.

PubMed

Carpenter, Tim E; Chrièl, Mariann; Greiner, Matthias

2007-01-16

Emergency preparedness relies on the ability to detect patterns in rare incidents in an early stage of an outbreak in order to implement relevant actions. Early warning of an abortion storm as a result of infection with a notifiable disease, e.g. brucellosis, bovine viral diarrhea (BVD) or infectious bovine rhinotracheitis (IBR), is a significant surveillance tool. This study used data from 507 large Danish dairy herds. A modified two-stage method for detecting an unusual increase in the abortion incidence was applied to the data. An alarm was considered true if an abortion were detected in the month following the alarm month, otherwise false. The total number of abortions that could potentially be avoided if effective action were taken ranged from 769 (22.9%) to 10 (0.3%), as the number of abortions required to set the alarm increased from 1 to 6. The vast majority of abortions could, however, not be predicted, much less prevented, given this early-warning system. The false to true alarm ratio was reduced when the number of abortions that set the alarm increased. The financial scenarios evaluated demonstrated that the value of an abortion, the cost of responding to an alarm and the efficiency of the actions are important for decision making when reporting an alarm. The presented model can readily be extended to other disease problems and multiple-time periods.

Measles Cases during Ebola Outbreak, West Africa, 2013-2106.

PubMed

Colavita, Francesca; Biava, Mirella; Castilletti, Concetta; Quartu, Serena; Vairo, Francesco; Caglioti, Claudia; Agrati, Chiara; Lalle, Eleonora; Bordi, Licia; Lanini, Simone; Guanti, Michela Delli; Miccio, Rossella; Ippolito, Giuseppe; Capobianchi, Maria R; Di Caro, Antonino

2017-06-01

The recent Ebola outbreak in West Africa caused breakdowns in public health systems, which might have caused outbreaks of vaccine-preventable diseases. We tested 80 patients admitted to an Ebola treatment center in Freetown, Sierra Leone, for measles. These patients were negative for Ebola virus. Measles virus IgM was detected in 13 (16%) of the patients.

Evaluating a New Online Course in the Epidemiology of Infectious Diseases by Studying Student Learning Styles

ERIC Educational Resources Information Center

Rogers, James W.; Cox, James R.

2008-01-01

At RMIT University, students may now elect to study infectious diseases through a course called Outbreak--The Detection and Control of Infectious Disease. Outbreak was designed to simulate in an online class the effective teamwork required to bring resolution to outbreak crises and enable frameworks for future prevention. The appropriateness of…

Foodborne illness outbreaks from microbial contaminants in spices, 1973-2010.

PubMed

Van Doren, Jane M; Neil, Karen P; Parish, Mickey; Gieraltowski, Laura; Gould, L Hannah; Gombas, Kathy L

2013-12-01

This review identified fourteen reported illness outbreaks attributed to consumption of pathogen-contaminated spice during the period 1973-2010. Countries reporting outbreaks included Canada, Denmark, England and Wales, France, Germany, New Zealand, Norway, Serbia, and the United States. Together, these outbreaks resulted in 1946 reported human illnesses, 128 hospitalizations and two deaths. Infants/children were the primary population segments impacted by 36% (5/14) of spice-attributed outbreaks. Four outbreaks were associated with multiple organisms. Salmonella enterica subspecies enterica was identified as the causative agent in 71% (10/14) of outbreaks, accounting for 87% of reported illnesses. Bacillus spp. was identified as the causative agent in 29% (4/10) of outbreaks, accounting for 13% of illnesses. 71% (10/14) of outbreaks were associated with spices classified as fruits or seeds of the source plant. Consumption of ready-to-eat foods prepared with spices applied after the final food manufacturing pathogen reduction step accounted for 70% of illnesses. Pathogen growth in spiced food is suspected to have played a role in some outbreaks, but it was not likely a contributing factor in three of the larger Salmonella outbreaks, which involved low-moisture foods. Root causes of spice contamination included contributions from both early and late stages of the farm-to-table continuum. Published by Elsevier Ltd.

Statistical monitoring of the hand, foot and mouth disease in China.

PubMed

Zhang, Jingnan; Kang, Yicheng; Yang, Yang; Qiu, Peihua

2015-09-01

In a period starting around 2007, the Hand, Foot, and Mouth Disease (HFMD) became wide-spreading in China, and the Chinese public health was seriously threatened. To prevent the outbreak of infectious diseases like HFMD, effective disease surveillance systems would be especially helpful to give signals of disease outbreaks as early as possible. Statistical process control (SPC) charts provide a major statistical tool in industrial quality control for detecting product defectives in a timely manner. In recent years, SPC charts have been used for disease surveillance. However, disease surveillance data often have much more complicated structures, compared to the data collected from industrial production lines. Major challenges, including lack of in-control data, complex seasonal effects, and spatio-temporal correlations, make the surveillance data difficult to handle. In this article, we propose a three-step procedure for analyzing disease surveillance data, and our procedure is demonstrated using the HFMD data collected during 2008-2009 in China. Our method uses nonparametric longitudinal data and time series analysis methods to eliminate the possible impact of seasonality and temporal correlation before the disease incidence data are sequentially monitored by a SPC chart. At both national and provincial levels, our proposed method can effectively detect the increasing trend of disease incidence rate before the disease becomes wide-spreading. © 2015, The International Biometric Society.

Outbreaks of infectious intestinal disease associated with person to person spread in hotels and restaurants.

PubMed

McDonnell, R J; Wall, P G; Adak, G K; Evans, H S; Cowden, J M; Caul, E O

1995-09-15

Twenty-eight outbreaks of infectious intestinal disease, reported as being transmitted mainly by the person to person route, were identified in association with retail catering premises, such as hotels, restaurants, and public houses, in England and Wales between 1992 and 1994. Five thousand and forty-eight people were at risk in these outbreaks and 1234 were affected. Most of the outbreaks (over 90%) occurred in hotels. Small round structured viruses were the most commonly detected pathogens. Diarrhoea and vomiting were common symptoms and most of the outbreaks occurred in the summer months. Control measures to contain infectious individuals and improved hygiene measures are necessary to contain such outbreaks.

Communitywide cryptosporidiosis outbreak associated with a surface water-supplied municipal water system--Baker City, Oregon, 2013.

PubMed

DeSilva, M B; Schafer, S; Kendall Scott, M; Robinson, B; Hills, A; Buser, G L; Salis, K; Gargano, J; Yoder, J; Hill, V; Xiao, L; Roellig, D; Hedberg, K

2016-01-01

Cryptosporidium, a parasite known to cause large drinking and recreational water outbreaks, is tolerant of chlorine concentrations used for drinking water treatment. Human laboratory-based surveillance for enteric pathogens detected a cryptosporidiosis outbreak in Baker City, Oregon during July 2013 associated with municipal drinking water. Objectives of the investigation were to confirm the outbreak source and assess outbreak extent. The watershed was inspected and city water was tested for contamination. To determine the community attack rate, a standardized questionnaire was administered to randomly sampled households. Weighted attack rates and confidence intervals (CIs) were calculated. Water samples tested positive for Cryptosporidium species; a Cryptosporidium parvum subtype common in cattle was detected in human stool specimens. Cattle were observed grazing along watershed borders; cattle faeces were observed within watershed barriers. The city water treatment facility chlorinated, but did not filter, water. The community attack rate was 28·3% (95% CI 22·1-33·6), sickening an estimated 2780 persons. Watershed contamination by cattle probably caused this outbreak; water treatments effective against Cryptosporidium were not in place. This outbreak highlights vulnerability of drinking water systems to pathogen contamination and underscores the need for communities to invest in system improvements to maintain multiple barriers to drinking water contamination.

Investigation of a type C/D botulism outbreak in free-range laying hens in France.

PubMed

Souillard, R; Le Maréchal, C; Ballan, V; Rouxel, S; Léon, D; Balaine, L; Poëzevara, T; Houard, E; Robineau, B; Robinault, C; Chemaly, M; Le Bouquin, S

2017-04-01

In 2014, a botulism outbreak in a flock of laying hens was investigated in France. In the flock of 5020 hens, clinical signs of botulism occurred at 46 weeks of age. A type C/D botulism outbreak was confirmed using the mouse lethality assay for detection of botulinum toxin in serum and a real-time PCR test to detect Clostridium botulinum in intestinal contents. The disease lasted one week with a mortality rate of 2.6% without recurrence. Botulism in laying hens has rarely been reported. Five monthly visits were made to the farm between December 2014 and May 2015 for a longitudinal study of the persistence of C. botulinum in the poultry house after the outbreak, and to assess egg contamination by C. botulinum. Several samples were collected on each visit: in the house (from the ventilation circuit, the egg circuit, water and feed, droppings) and the surrounding area. Thirty clean and 30 dirty eggs were also swabbed at each visit. In addition, 12 dirty and 12 clean eggs were collected to analyse eggshell and egg content. The samples were analysed using real-time PCR to detect type C/D C. botulinum. The bacterium was still detected in the house more than 5 months after the outbreak, mostly on the walls and in the egg circuit. Regarding egg contamination, the bacteria were detected only on the shell but not in the content of the eggs. Control measures should therefore be implemented throughout the egg production period to avoid dissemination of the bacteria, particularly during egg collection.

Management of Ebola Virus Disease in Children.

PubMed

Trehan, Indi; De Silva, Stephanie C

2018-03-01

The West African outbreak of 2013 to 2016 was the largest Ebola epidemic in history. With tens of thousands of patients treated during this outbreak, much was learned about how to optimize clinical care for children with Ebola. In anticipation of inevitable future outbreaks, a firsthand summary of the major aspects of pediatric Ebola case management in austere settings is presented. Emphasis is on early and aggressive critical care, including fluid resuscitation, electrolyte repletion, antimicrobial therapy, and nutritional supplementation. Copyright © 2017 Elsevier Inc. All rights reserved.

Pathobiology of Clade 2.3.4.4 H5Nx High-Pathogenicity Avian Influenza Virus Infections in Minor Gallinaceous Poultry Supports Early Backyard Flock Introductions in the Western United States in 2014-2015

PubMed Central

Bertran, Kateri; Lee, Dong-Hun; Pantin-Jackwood, Mary J.; Spackman, Erica; Balzli, Charles; Suarez, David L.

2017-01-01

ABSTRACT In 2014 and 2015, the United States experienced an unprecedented outbreak of Eurasian clade 2.3.4.4 H5 highly pathogenic avian influenza (HPAI) virus. Initial cases affected mainly wild birds and mixed backyard poultry species, while later outbreaks affected mostly commercial chickens and turkeys. The pathogenesis, transmission, and intrahost evolutionary dynamics of initial Eurasian H5N8 and reassortant H5N2 clade 2.3.4.4 HPAI viruses in the United States were investigated in minor gallinaceous poultry species (i.e., species for which the U.S. commercial industries are small), namely, Japanese quail, bobwhite quail, pearl guinea fowl, chukar partridges, and ring-necked pheasants. Low mean bird infectious doses (<2 to 3.7 log10) support direct introduction and infection of these species as observed in mixed backyard poultry during the early outbreaks. Pathobiological features and systemic virus replication in all species tested were consistent with HPAI virus infection. Sustained virus shedding with transmission to contact-exposed birds, alongside long incubation periods, may enable unrecognized dissemination and adaptation to other gallinaceous species, such as chickens and turkeys. Genome sequencing of excreted viruses revealed numerous low-frequency polymorphisms and 20 consensus-level substitutions in all genes and species, but especially in Japanese quail and pearl guinea fowl and in internal proteins PB1 and PB2. This genomic flexibility after only one passage indicates that influenza viruses can continue to evolve in galliform species, increasing their opportunity to adapt to other species. Our findings suggest that these gallinaceous poultry are permissive for infection and sustainable transmissibility with the 2014 initial wild bird-adapted clade 2.3.4.4 virus, with potential acquisition of mutations leading to host range adaptation. IMPORTANCE The outbreak of clade 2.3.4.4 H5 highly pathogenic avian influenza (HPAI) virus that occurred in the United States in 2014 and 2015 represents the worst livestock disease event in the country, with unprecedented socioeconomic and commercial consequences. Epidemiological and molecular investigations can identify transmission pathways of the HPAI virus. However, understanding the pathogenesis, transmission, and intrahost evolutionary dynamics of new HPAI viruses in different avian species is paramount. The significance of our research is in examining the susceptibility of minor gallinaceous species to HPAI virus, as this poultry sector also suffers from HPAI epizootics, and identifying the biological potential of these species as an epidemiological link between the waterfowl reservoir and the commercial chicken and turkey populations, with the ultimate goal of refining surveillance in these populations to enhance early detection, management, and control in future HPAI virus outbreaks. PMID:28794040

Developing the Framework for an Early Warning System for Ebola based on Environmental Conditions

NASA Astrophysics Data System (ADS)

Dartevelle, Sebastien; Nguy-Robertson, Anthony; Bell, Jesse; Chretien, Jean-Paul

2017-04-01

The 2014-2016 Ebola outbreak in West Africa indicated that this lethal disease can become a National Security issue as it crossed boarders and taxed regional health care systems. Ebola symptoms are also similar to other endemic diseases. Thus, forewarning of its possible presence can alert local public health facilities and populations, and may thereby reduce response time. Early work by our group has identified local climate (e.g. temperature, precipitation) and vegetation health (e.g. remote sensing using normalized difference vegetation index, NDVI) variables as leading indicators to known historical Ebola outbreaks. The environmental stress placed on the system as it reaches a climatic tipping point provides optimal conditions for spillover of Ebola virus from the reservoir host (which is unknown but suspected to be bats) to humans. This work outlines a framework for an approach to provide early warning maps based on the present state of the environment. Time series data from Climate Forecast System ver. 2 and AVHRR and MODIS satellite sensors are the basis for the early warning models used. These maps can provide policy makers and local health care professionals timely information for disease surveillance and preparation for future Ebola outbreaks.

Toxin Detection in Patients' Sera by Mass Spectrometry during Two Outbreaks of Type A Botulism in France

PubMed Central

Mazuet, Christelle; Ezan, Eric; Volland, Hervé; Becher, François

2012-01-01

In two outbreaks of food-borne botulism in France, Clostridium botulinum type A was isolated and characterized from incriminated foods. Botulinum neurotoxin type A was detected in the patients' sera by mouse bioassay and in vitro endopeptidase assay with an immunocapture step and identification of the cleavage products by mass spectrometry. PMID:22993181

Metagenomic Analysis of Viruses in Feces from Unsolved Outbreaks of Gastroenteritis in Humans

PubMed Central

Moore, Nicole E.; Wang, Jing; Hewitt, Joanne; Croucher, Dawn; Williamson, Deborah A.; Paine, Shevaun; Yen, Seiha; Greening, Gail E.

2014-01-01

The etiology of an outbreak of gastroenteritis in humans cannot always be determined, and ∼25% of outbreaks remain unsolved in New Zealand. It is hypothesized that novel viruses may account for a proportion of unsolved cases, and new unbiased high-throughput sequencing methods hold promise for their detection. Analysis of the fecal metagenome can reveal the presence of viruses, bacteria, and parasites which may have evaded routine diagnostic testing. Thirty-one fecal samples from 26 gastroenteritis outbreaks of unknown etiology occurring in New Zealand between 2011 and 2012 were selected for de novo metagenomic analysis. A total data set of 193 million sequence reads of 150 bp in length was produced on an Illumina MiSeq. The metagenomic data set was searched for virus and parasite sequences, with no evidence of novel pathogens found. Eight viruses and one parasite were detected, each already known to be associated with gastroenteritis, including adenovirus, rotavirus, sapovirus, and Dientamoeba fragilis. In addition, we also describe the first detection of human parechovirus 3 (HPeV3) in Australasia. Metagenomics may thus provide a useful audit tool when applied retrospectively to determine where routine diagnostic processes may have failed to detect a pathogen. PMID:25339401

Waterborne disease outbreak detection: an integrated approach using health administrative databases.

PubMed

Coly, S; Vincent, N; Vaissiere, E; Charras-Garrido, M; Gallay, A; Ducrot, C; Mouly, D

2017-08-01

Hundreds of waterborne disease outbreaks (WBDO) of acute gastroenteritis (AGI) due to contaminated tap water are reported in developed countries each year. Such outbreaks are probably under-detected. The aim of our study was to develop an integrated approach to detect and study clusters of AGI in geographical areas with homogeneous exposure to drinking water. Data for the number of AGI cases are available at the municipality level while exposure to tap water depends on drinking water networks (DWN). These two geographical units do not systematically overlap. This study proposed to develop an algorithm which would match the most relevant grouping of municipalities with a specific DWN, in order that tap water exposure can be taken into account when investigating future disease outbreaks. A space-time detection method was applied to the grouping of municipalities. Seven hundred and fourteen new geographical areas (groupings of municipalities) were obtained compared with the 1,310 municipalities and the 1,706 DWN. Eleven potential WBDO were identified in these groupings of municipalities. For ten of them, additional environmental investigations identified at least one event that could have caused microbiological contamination of DWN in the days previous to the occurrence of a reported WBDO.

Molecular Analysis of an Outbreak of Lethal Postpartum Sepsis Caused by Streptococcus pyogenes

PubMed Central

Turner, Claire E.; Dryden, Matthew; Holden, Matthew T. G.; Davies, Frances J.; Lawrenson, Richard A.; Farzaneh, Leili; Bentley, Stephen D.; Efstratiou, Androulla

2013-01-01

Sepsis is now the leading direct cause of maternal death in the United Kingdom, and Streptococcus pyogenes is the leading pathogen. We combined conventional and genomic analyses to define the duration and scale of a lethal outbreak. Two postpartum deaths caused by S. pyogenes occurred within 24 h; one was characterized by bacteremia and shock and the other by hemorrhagic pneumonia. The women gave birth within minutes of each other in the same maternity unit 2 days earlier. Seven additional infections in health care and household contacts were subsequently detected and treated. All cluster-associated S. pyogenes isolates were genotype emm1 and were initially indistinguishable from other United Kingdom emm1 isolates. Sequencing of the virulence gene sic revealed that all outbreak isolates had the same unique sic type. Genome sequencing confirmed that the cluster was caused by a unique S. pyogenes clone. Transmission between patients occurred on a single day and was associated with casual contact only. A single isolate from one patient demonstrated a sequence change in sic consistent with longer infection duration. Transmission to health care workers was traced to single clinical contacts with index cases. The last case was detected 18 days after the first case. Following enhanced surveillance, the outbreak isolate was not detected again. Mutations in bacterial regulatory genes played no detectable role in this outbreak, illustrating the intrinsic ability of emm1 S. pyogenes to spread while retaining virulence. This fast-moving outbreak highlights the potential of S. pyogenes to cause a range of diseases in the puerperium with rapid transmission, underlining the importance of immediate recognition and response by clinical infection and occupational health teams. PMID:23616448

Canine Circovirus 1 (CaCV-1) and Canine Parvovirus 2 (CPV-2): Recurrent Dual Infections in a Papillon Breeding Colony.

PubMed

Thaiwong, T; Wise, A G; Maes, R K; Mullaney, T; Kiupel, M

2016-11-01

Recurrent outbreaks of sudden death and bloody diarrhea were reported in March 2013 and February 2014 in a breeding colony of Papillon dogs. During the first outbreak, 1 adult dog and 2 eight-month-old puppies died. During the second outbreak, 2 ten-week-old puppies died. One puppy from the first outbreak and 2 puppies from the second outbreak were examined at necropsy. Histologically, all 3 puppies had severe segmental crypt necrosis of the small intestine and marked lymphoid follicle depletion in the spleen and Peyer's patches. Real-time (RT) polymerase chain reaction (PCR) demonstrated abundant canine parvovirus (CPV-2) DNA (Ct<15) in the affected small intestine, and immunohistochemistry detected large amounts of CPV-2 antigen in intestinal crypt epithelium and Kupffer cells but few positive macrophages in lymphoid organs. All puppies had marked sinusoidal histiocytosis and multifocal granulomatous inflammation in mesenteric lymph nodes and spleen, prompting additional RT-PCR testing for canine circovirus 1 (CaCV-1). Very high levels of CaCV-1 DNA (Ct<13) were detected in small intestine, lymph nodes, and spleen. In situ hybridization for CaCV-1 detected rare positive nuclei of regenerating crypt epithelium but abundant amounts of CaCV-1 nucleic acid in the cytoplasm and nuclei of histiocytes in all lymphoid tissues, including granulomatous inflammatory foci and hepatic Kupffer cells. Significant levels of CaCV-1 DNA were detected in blood and serum (Ct as low as 13) but not feces from 3 surviving dogs at 2 months or 1 year after the outbreak, respectively. We hypothesize that CPV-2 infection predisposed dogs to CaCV-1 infection and ultimately resulted in more severe clinical disease. © The Author(s) 2016.

Noroviruses associated with outbreaks of acute gastroenteritis in the State of Rio Grande do Sul, Brazil, 2004-2011.

PubMed

de Andrade, Juliana da Silva Ribeiro; Rocha, Monica Simões; Carvalho-Costa, Felipe Aníbal; Fioretti, Julia Monassa; Xavier, Maria da Penha Trindade Pinheiro; Nunes, Zenaida Maria Alves; Cardoso, Jeanice; Fialho, Alexandre Madi; Leite, José Paulo Gagliardi; Miagostovich, Marize Pereira

2014-11-01

Acute gastroenteritis norovirus (NoV) in a country of continental dimensions like Brazil has resulted in under-reporting of the number of outbreaks, as well as the genotypes associated. To demonstrate the role of NoV in outbreaks occurring in the State of Rio Grande do Sul, Southern Brazil, we determined its prevalence, as well as the genotypes associated, and evaluated clinical and epidemiological aspects. NoV investigation was carried out in rotavirus group A negative stool samples from 2265 patients from 741 outbreaks that occurred in the State of Rio Grande do Sul, Brazil, during a period of eight years (2004-2011). NoV detection and nucleotide sequencing for genotype characterization was carried by using sets of primers targeting a conservative Rd-Rp polymerase genome region and the viral capsid gene, respectively. NoVs were detected in 817 stool samples (36.1%) and associated with 327 outbreaks (44.1%). NoV GII.2, GII.3, GII.4, GII.6, GII.12, GII.13, GII.14, GII.15, GII.17, GII.21; and GI.1 and GI.3 were characterized. GII.4 was the most frequently detected (72.3%), with five variants identified (Asia_2003, Hunter_2004, Yerseke_2006a, Den_Haag_2006b, New Orleans_2009). This study describes the first detection of GI.1 and GII.13 and GII.15 in Brazil and demonstrates NoV winter-spring seasonality in this region of the country. NoVs were responsible for almost 50% of outbreaks, with about 70% of them resulting from genotype GII.4 and its variants. The seasonality observed could help health authorities to establish a system of active surveillance in order to reduce NoV impact especially in congregate settings. Copyright © 2014 Elsevier B.V. All rights reserved.

Highly Pathogenic Avian Influenza H5N8 Clade 2.3.4.4 Virus: Equivocal Pathogenicity and Implications for Surveillance Following Natural Infection in Breeder Ducks in the United Kingdom.

PubMed

Núñez, A; Brookes, S M; Reid, S M; Garcia-Rueda, C; Hicks, D J; Seekings, J M; Spencer, Y I; Brown, I H

2016-02-01

Since early 2014, several outbreaks involving novel reassortant highly pathogenic avian influenza (HPAI) A(H5N8) viruses have been detected in poultry and wild bird species in Asia, Europe and North America. These viruses have been detected in apparently healthy and dead wild migratory birds, as well as in domestic chickens, turkeys, geese and ducks. In this study, we describe the pathology of an outbreak of H5N8 HPAIV in breeder ducks in the UK. A holding with approximately 6000 breeder ducks, aged approximately 60 weeks, showed a gradual reduction in egg production and increased mortality over a 7-day period. Post-mortem examination revealed frequent fibrinous peritonitis, with severely haemorrhagic ovarian follicles and occasional splenic and pancreatic necrosis and high incidence of mycotic granulomas in the air sacs and lung. Low-to-moderate levels of HPAI H5N8 virus were detected mainly in respiratory and digestive tract, with minor involvement of other organs. Although histopathological examination confirmed the gross pathology findings, intralesional viral antigen detection by immunohistochemistry was not observed. Immunolabelled cells were rarely only present in inflamed air sacs and serosa, usually superficial to granulomatous inflammation. Abundant bacterial microcolonies were observed in haemorrhagic ovaries and oviduct. The limited viral tissue distribution and presence of inter-current fungal and bacterial infections suggest a minor role for HPAIV H5N8 in clinical disease in layer ducks. © 2015 Crown copyright.

Evaluation of Infectivity, Virulence and Transmission of FDMV Field Strains of Serotypes O and A Isolated In 2010 from Outbreaks in the Republic of Korea

PubMed Central

Pacheco, Juan M.; Lee, Kwang-Nyeong; Eschbaumer, Michael; Bishop, Elizabeth A.; Hartwig, Ethan J.; Pauszek, Steven J.; Smoliga, George R.; Kim, Su-Mi; Park, Jong-Hyeon; Ko, Young-Joon; Lee, Hyang-Sim; Tark, Dongseob; Cho, In-Soo; Kim, Byounghan; Rodriguez, Luis L.; Arzt, Jonathan

2016-01-01

Since the early 2000s outbreaks of foot-and-mouth disease (FMD) have been described in several previously FMD-free Asian nations, including the Republic of Korea (South Korea). One outbreak with FMD virus (FDMV) serotype A and two with serotype O occurred in South Korea in 2010/2011. The causative viruses belonged to lineages that had been spreading in South East Asia, far East and East Asia since 2009 and presented a great threat to the countries in that region. Most FMDV strains infect ruminants and pigs, as it happened during the outbreaks of FMDV serotype O in South Korea. Contrastingly, the strain of serotype A affected only ruminants. Based upon these findings, the intention of the work described in the current report was to characterize and compare the infectivity, virulence and transmission of both strains under laboratory conditions in cattle and pigs, by direct inoculation and contact exposure. As expected, FMDV serotype O was highly virulent in both cattle and swine by contact exposure and direct inoculation. Surprisingly, FMDV serotype A was highly virulent in swine, but was less infectious in cattle by contact exposure to infected swine or cattle. Interestingly, similar quantities of aerosolized FMDV RNA were detected during experiments with viruses of serotypes O and A. Specific virus-host interaction of A/SKR/2010 could affect the transmission of this strain to cattle, and this may explain in part the limited spread of the serotype A epizootic. PMID:26735130

Evaluation of Infectivity, Virulence and Transmission of FDMV Field Strains of Serotypes O and A Isolated In 2010 from Outbreaks in the Republic of Korea

DOE PAGES

Pacheco, Juan M.; Lee, Kwang -Nyeong; Eschbaumer, Michael; ...

2016-01-06

Since the early 2000s outbreaks of foot-and-mouth disease (FMD) have been described in several previously FMD-free Asian nations, including the Republic of Korea (South Korea). One outbreak with FMD virus (FDMV) serotype A and two with serotype O occurred in South Korea in 2010/2011. The causative viruses belonged to lineages that had been spreading in South East Asia, far East and East Asia since 2009 and presented a great threat to the countries in that region. Most FMDV strains infect ruminants and pigs, as it happened during the outbreaks of FMDV serotype O in South Korea. Contrastingly, the strain ofmore » serotype A affected only ruminants. Based upon these findings, the intention of the work described in the current report was to characterize and compare the infectivity, virulence and transmission of both strains under laboratory conditions in cattle and pigs, by direct inoculation and contact exposure. As expected, FMDV serotype O was highly virulent in both cattle and swine by contact exposure and direct inoculation. Surprisingly, FMDV serotype A was highly virulent in swine, but was less infectious in cattle by contact exposure to infected swine or cattle. Interestingly, similar quantities of aerosolized FMDV RNA were detected during experiments with viruses of serotypes O and A. Here, specific virus-host interaction of A/SKR/2010 could affect the transmission of this strain to cattle, and this may explain in part the limited spread of the serotype A epizootic« less

A method to identify the areas at risk for the introduction of avian influenza virus into poultry flocks through direct contact with wild ducks.

PubMed

Galletti, G; Santi, A; Guberti, V; Paternoster, G; Licata, E; Loli Piccolomini, L; Procopio, A; Tamba, M

2018-02-22

Wild dabbling ducks are the main reservoir for avian influenza (AI) viruses and pose an ongoing threat to commercial poultry flocks. Combining the (i) size of that population, (ii) their flight distances and (iii) their AI prevalence, the density of AI-infected dabbling ducks (DID) was calculated as a risk factor for the introduction of AI viruses into poultry holdings of Emilia-Romagna region, Northern Italy. Data on 747 poultry holdings and on 39 AI primary outbreaks notified in Emilia-Romagna between 2000 and 2017 were used to validate that risk factor. A multivariable Bayesian logistic regression was performed to assess whether DID could be associated with the occurrence of AI primary outbreaks. DID value, being an outdoor flock, hobby poultry trading, species reared, length of cycle and flock size were used as explanatory variables. Being an outdoor poultry flock was significantly associated with a higher risk of AI outbreak occurrence. The probability of DID to be a risk factor for AI virus introduction was estimated to be 90%. A DID cut-off of 0.23 was identified to define high-risk areas for AI virus introduction. Using this value, the high-risk area covers 43% of the region. Seventy-four per cent of the primary AI outbreaks have occurred in that area, containing 39% of the regional poultry holdings. Poultry holdings located in areas with a high DID value should be included in a risk-based surveillance programme aimed at AI early detection. © 2018 Blackwell Verlag GmbH.

The role of older children and adults in wild poliovirus transmission.

PubMed

Blake, Isobel M; Martin, Rebecca; Goel, Ajay; Khetsuriani, Nino; Everts, Johannes; Wolff, Christopher; Wassilak, Steven; Aylward, R Bruce; Grassly, Nicholas C

2014-07-22

As polio eradication inches closer, the absence of poliovirus circulation in most of the world and imperfect vaccination coverage are resulting in immunity gaps and polio outbreaks affecting adults. Furthermore, imperfect, waning intestinal immunity among older children and adults permits reinfection and poliovirus shedding, prompting calls to extend the age range of vaccination campaigns even in the absence of cases in these age groups. The success of such a strategy depends on the contribution to poliovirus transmission by older ages, which has not previously been estimated. We fit a mathematical model of poliovirus transmission to time series data from two large outbreaks that affected adults (Tajikistan 2010, Republic of Congo 2010) using maximum-likelihood estimation based on iterated particle-filtering methods. In Tajikistan, the contribution of unvaccinated older children and adults to transmission was minimal despite a significant number of cases in these age groups [reproduction number, R = 0.46 (95% confidence interval, 0.42-0.52) for >5-y-olds compared to 2.18 (2.06-2.45) for 0- to 5-y-olds]. In contrast, in the Republic of Congo, the contribution of older children and adults was significant [R = 1.85 (1.83-4.00)], perhaps reflecting sanitary and socioeconomic variables favoring efficient virus transmission. In neither setting was there evidence for a significant role of imperfect intestinal immunity in the transmission of poliovirus. Bringing the immunization response to the Tajikistan outbreak forward by 2 wk would have prevented an additional 130 cases (21%), highlighting the importance of early outbreak detection and response.

Evaluation of Infectivity, Virulence and Transmission of FDMV Field Strains of Serotypes O and A Isolated In 2010 from Outbreaks in the Republic of Korea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pacheco, Juan M.; Lee, Kwang -Nyeong; Eschbaumer, Michael

Since the early 2000s outbreaks of foot-and-mouth disease (FMD) have been described in several previously FMD-free Asian nations, including the Republic of Korea (South Korea). One outbreak with FMD virus (FDMV) serotype A and two with serotype O occurred in South Korea in 2010/2011. The causative viruses belonged to lineages that had been spreading in South East Asia, far East and East Asia since 2009 and presented a great threat to the countries in that region. Most FMDV strains infect ruminants and pigs, as it happened during the outbreaks of FMDV serotype O in South Korea. Contrastingly, the strain ofmore » serotype A affected only ruminants. Based upon these findings, the intention of the work described in the current report was to characterize and compare the infectivity, virulence and transmission of both strains under laboratory conditions in cattle and pigs, by direct inoculation and contact exposure. As expected, FMDV serotype O was highly virulent in both cattle and swine by contact exposure and direct inoculation. Surprisingly, FMDV serotype A was highly virulent in swine, but was less infectious in cattle by contact exposure to infected swine or cattle. Interestingly, similar quantities of aerosolized FMDV RNA were detected during experiments with viruses of serotypes O and A. Here, specific virus-host interaction of A/SKR/2010 could affect the transmission of this strain to cattle, and this may explain in part the limited spread of the serotype A epizootic« less

The effect of school dismissal on rates of influenza-like illness in New York City schools during the spring 2009 novel H1N1 outbreak.

PubMed

Egger, Joseph R; Konty, Kevin J; Wilson, Elisha; Karpati, Adam; Matte, Thomas; Weiss, Don; Barbot, Oxiris

2012-03-01

The effects of individual school dismissal on influenza transmission have not been well studied. During the spring 2009 novel H1N1 outbreak, New York City implemented an individual school dismissal policy intended to limit influenza transmission at schools with high rates of influenza-like illness (ILI). Active disease surveillance data collected by the New York City Health Department on rates of ILI in schools were used to evaluate the impact. Sixty-four schools that met the Health Department's criteria for considering dismissal were included in the analysis. Twenty-four schools that met criteria subsequently dismissed all classes for approximately 1 school week. A regression model was fit to these data, estimating the effect of school dismissal on rates of in-school ILI following reconvening, adjusting for potential confounders. The model estimated that, on average, school dismissal reduced the rate of ILI by 7.1% over the entire average outbreak period. However, a large proportion of in-school ILI occurred before dismissal criteria were met. A separate model estimated that school absenteeism rates were not significantly affected by dismissal. Results suggest that individual school dismissal could be considered in situations where schools have a disproportionate number of high-risk students or may be unable to implement recommended preventive or infection control measures. Future work should focus on developing more sensitive indicators of early outbreak detection in schools and evaluating the impact of school dismissal on community transmission. © 2012, American School Health Association.

The role of older children and adults in wild poliovirus transmission

PubMed Central

Blake, Isobel M.; Martin, Rebecca; Goel, Ajay; Khetsuriani, Nino; Everts, Johannes; Wolff, Christopher; Wassilak, Steven; Aylward, R. Bruce; Grassly, Nicholas C.

2014-01-01

As polio eradication inches closer, the absence of poliovirus circulation in most of the world and imperfect vaccination coverage are resulting in immunity gaps and polio outbreaks affecting adults. Furthermore, imperfect, waning intestinal immunity among older children and adults permits reinfection and poliovirus shedding, prompting calls to extend the age range of vaccination campaigns even in the absence of cases in these age groups. The success of such a strategy depends on the contribution to poliovirus transmission by older ages, which has not previously been estimated. We fit a mathematical model of poliovirus transmission to time series data from two large outbreaks that affected adults (Tajikistan 2010, Republic of Congo 2010) using maximum-likelihood estimation based on iterated particle-filtering methods. In Tajikistan, the contribution of unvaccinated older children and adults to transmission was minimal despite a significant number of cases in these age groups [reproduction number, R = 0.46 (95% confidence interval, 0.42–0.52) for >5-y-olds compared to 2.18 (2.06–2.45) for 0- to 5-y-olds]. In contrast, in the Republic of Congo, the contribution of older children and adults was significant [R = 1.85 (1.83–4.00)], perhaps reflecting sanitary and socioeconomic variables favoring efficient virus transmission. In neither setting was there evidence for a significant role of imperfect intestinal immunity in the transmission of poliovirus. Bringing the immunization response to the Tajikistan outbreak forward by 2 wk would have prevented an additional 130 cases (21%), highlighting the importance of early outbreak detection and response. PMID:25002465

Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Land-Surface Phenology

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.

2010-12-01

A prototype National Early Warning System (EWS) for Forest Disturbances was established in 2010 by producing national maps showing potential forest disturbance across the conterminous United States at 231m resolution every 8 days. Each map is based on Land-Surface Phenology (LSP), calculated using temporally smoothed MODIS MOD13 imagery obtained over the preceding 24-day analysis window. Potential disturbance maps are generated by comparing a spatially and temporally specific historical expectation of normal NDVI "greenness" with NDVI "greenness" from a series of current satellite views. Three different disturbance products are produced using differing lengths of historical baseline periods to calculate the expected normal greenness. The short-term baseline products show only disturbances newer than one year ago, while the intermediate baseline products show disturbances since the prior three years, and the long-term baseline products show all disturbances over the MODIS historical period. A Forest Change Assessment Viewer website, http://ews.forestthreats.org/NPDE/NPDE.html, showcases the three most recent national disturbance maps in full spatial context. Although 2010 was a wet el Nino year without major forest problems, disturbances in 2010 in MI, NY, CO and LA will be highlighted. Forest disturbances caused by wildfire, hurricanes, tornadoes, hail, ice storms, and defoliating insects, including fall cankerworms, forest tent caterpillars, gypsy moths, baldcypress leafrollers and winter moths were successfully detected during the 2009 and 2010 field seasons. The EWS was used in 2010 to detect and alert Forest Health Monitoring (FHM) Aerial Disturbance Survey personnel to an otherwise-unknown outbreak of forest tent caterpillar and baldcypress leafroller in the Atchafalaya and Pearl River regions of southern Louisiana. A local FHM Program Coordinator verified these EWS-detected outbreaks. Many defoliator-induced disturbances were ephemeral, and were followed by recovery in LSP, presumably due to refoliation. 2009 Vegetation Disturbances mapped as percent change in max NDVI from June 10 - July 27 2000-2008

Respiratory virus laboratory pandemic planning and surveillance in central Viet Nam, 2008–2010

PubMed Central

Chien, Bui Trong; Papadakis, Georgina; Druce, Julian; Birch, Chris; Chibo, Doris; An, Truong Phuoc; Trang, Le Thi Kim; Trieu, Nguyen Bao; Thuy, Doan Thi Thanh; Catton, Mike; Mai, Trinh Xuan

2012-01-01

Introduction Laboratory capacity is needed in central Viet Nam to provide early warning to public health authorities of respiratory outbreaks of importance to human health, for example the outbreak of influenza A(H1N1) pandemic in 2009. Polymerase chain reaction (PCR) procedures established as part of a capacity-building process were used to conduct prospective respiratory surveillance in a region where few previous studies have been undertaken. Methods Between October 2008 and September 2010, nose and throat swabs from adults and children (approximately 20 per week) presenting with an acute respiratory illness to the Ninh Hoa General Hospital were collected. Same-day PCR testing and result reporting for 13 respiratory viruses were carried out by locally trained scientists. Results Of 2144 surveillance samples tested, 1235 (57.6%) were positive for at least one virus. The most common were influenza A strains (17.9%), with pandemic influenza A(H1N1) 2009 and seasonal H3N2 strain accounting for 52% and 43% of these, respectively. Other virus detections included: rhinovirus (12.4%), enterovirus (8.9%), influenza B (8.3%), adenovirus (5.3%), parainfluenza (4.7%), respiratory syncytial virus (RSV) (3.9%), human coronavirus (3.0%) and human metapneumovirus (0.3%). The detection rate was greatest in the 0–5 year age group. Viral co-infections were identified in 148 (6.9%) cases. Discussion The outbreak in 2009 of the influenza A(H1N1) pandemic strain provided a practical test of the laboratory’s pandemic plan. This study shows that the availability of appropriate equipment and molecular-based testing can contribute to important individual and public health outcomes in geographical locations susceptible to emerging infections. PMID:23908924

West Nile virus in Tunisia, 2014: First isolation from mosquitoes.

PubMed

Wasfi, F; Dachraoui, K; Cherni, S; Bosworth, A; Barhoumi, W; Dowall, S; Chelbi, I; Derbali, M; Zoghlami, Z; Beier, J C; Zhioua, E

2016-07-01

Several outbreaks of human West Nile virus (WNV) infections were reported in Tunisia during the last two decades. Serological studies on humans as well as on equine showed intensive circulation of WNV in Tunisia. However, no virus screening of mosquitoes for WNV has been performed in Tunisia. In the present study, we collected mosquito samples from Central Tunisia to be examined for the presence of flaviviruses. A total of 102 Culex pipiens mosquitoes were collected in September 2014 from Central Tunisia. Mosquitoes were pooled according to the collection site, date and sex with a maximum of 5 specimens per pool and tested for the presence of flaviviruses by conventional reverse transcription heminested PCR and by a specific West Nile virus real time reverse transcription PCR. Of a total of 21 pools tested, 7 were positive for WNV and no other flavivirus could be evidenced in mosquito pools. In addition, WNV was isolated on Vero cells. Phylogenetic analysis showed that recent Tunisian WNV strains belong to lineage 1 WNV and are closely related to the Tunisian strain 1997 (PAH 001). This is the first detection and isolation of WNV from mosquitoes in Tunisia. Some areas of Tunisia are at high risk for human WNV infections. WNV is likely to cause future sporadic and foreseeable outbreaks. Therefore, it is of major epidemiological importance to set up an entomological surveillance as an early alert system. Timely detection of WNV should prompt vector control to prevent future outbreaks. In addition, education of people to protect themselves from mosquito bites is of major epidemiological importance as preventive measure against WNV infection. Copyright © 2016 Elsevier B.V. All rights reserved.

Nosocomial outbreak of neonatal gastroenteritis caused by a new serotype 4, subtype 4B human rotavirus.

PubMed

Gerna, G; Forster, J; Parea, M; Sarasini, A; Di Matteo, A; Baldanti, F; Langosch, B; Schmidt, S; Battaglia, M

1990-07-01

A nosocomial outbreak of rotavirus gastroenteritis involving 52 newborns occurred between June and September 1988 at the University Children's Hospital of Freiburg, Federal Republic of Germany. Stools from 27 representative patients were examined for rotavirus serotypes, using a monoclonal antibody-based enzyme-linked immunosorbent assay. The electropherotype was also examined by polyacrylamide gel electrophoresis of genomic RNA. As many as 18 patients were found to be infected by serotype 4, subtype 4B strain, and in all of them the same electropherotype was detected. Although rotavirus from the remaining nine patients could not be typed, the electropherotype in four was identical to that of the serotype 4, subtype 4B strain. Thus, most of the patients in the outbreak were infected by the same rotavirus strain. Retrospective epidemiological studies showed that the 4B strain began to circulate at the hospital in January 1988, whereas only rotavirus serotypes 1, 3, and 4A were detected in 1985-1987. The primary case of the outbreak was presumably a newborn with acute gastroenteritis, admitted to the hospital from a small maternity unit in the same urban area. During the outbreak, 12 of 44 healthy newborns in the nurseries of the Children's Hospital and other maternity hospitals were found to be asymptomatic rotavirus carriers, and in three of the newborns the same 4B strain was detected. This is the first reported outbreak caused by a serotype 4, subtype 4B strain.

Field study of pneumonia in vaccinated cattle associated with incorrect vaccination and Pasteurella multocida infection.

PubMed

Crawshaw, W M; Caldow, G L

2015-04-25

This field study used data on the vaccine courses against bovine respiratory disease sold by one pharmaceutical company in conjunction with pharmacovigilance data to explore reported suspected lack of expected efficacy and the reasons for this. The study ran from May 1, 2007, to April 30, 2010, and covered vaccines sold in Scotland and part of Northumberland. In total, 83 groups of cattle reported suspected lack of expected efficacy, representing 1.6 per cent of the 804,618 vaccine courses sold. It was possible to investigate 45 of these outbreaks in depth using a standard questionnaire and diagnostic protocol. Vaccine usage outwith the specific product characteristics (SPC) occurred in 47 per cent of cases (21/45). The proportion of vaccination courses used where a pathogen contained in the vaccine was detected in the diseased cattle and vaccine use was consistent with the SPC was estimated at 0.12 per cent of the courses sold. Pasteurella multocida was the most common pathogen detected and was found in 21 of the outbreaks. For outbreaks where a pathogen contained in the vaccine was detected, P. multocida was found at a significantly greater frequency (P=0.03) where vaccine use was compliant with the SPC (five of six outbreaks) compared with outbreaks where vaccine use had not been compliant with the SPC (one of seven outbreaks). The limitations of the study, including the diagnostic tests employed and definition of vaccination outwith the SPC, are discussed. British Veterinary Association.

Legionella longbeachae detected in an industrial cooling tower linked to a legionellosis outbreak, New Zealand, 2015; possible waterborne transmission?

PubMed

Thornley, C N; Harte, D J; Weir, R P; Allen, L J; Knightbridge, K J; Wood, P R T

2017-08-01

A legionellosis outbreak at an industrial site was investigated to identify and control the source. Cases were identified from disease notifications, workplace illness records, and from clinicians. Cases were interviewed for symptoms and risk factors and tested for legionellosis. Implicated environmental sources were sampled and tested for legionella. We identified six cases with Legionnaires' disease and seven with Pontiac fever; all had been exposed to aerosols from the cooling towers on the site. Nine cases had evidence of infection with either Legionella pneumophila serogroup (sg) 1 or Legionella longbeachae sg1; these organisms were also isolated from the cooling towers. There was 100% DNA sequence homology between cooling tower and clinical isolates of L. pneumophila sg1 using sequence-based typing analysis; no clinical L. longbeachae isolates were available to compare with environmental isolates. Routine monitoring of the towers prior to the outbreak failed to detect any legionella. Data from this outbreak indicate that L. pneumophila sg1 transmission occurred from the cooling towers; in addition, L. longbeachae transmission was suggested but remains unproven. L. longbeachae detection in cooling towers has not been previously reported in association with legionellosis outbreaks. Waterborne transmission should not be discounted in investigations for the source of L. longbeachae infection.

Optimizing the response to surveillance alerts in automated surveillance systems.

PubMed

Izadi, Masoumeh; Buckeridge, David L

2011-02-28

Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Multiple exposures during a norovirus outbreak on a river-cruise sailing through Europe, 2006.

PubMed

Verhoef, L; Boxman, I L; Duizer, E; Rutjes, S A; Vennema, H; Friesema, I H M; de Roda Husman, A M; Koopmans, M

2008-06-12

In the summer of 2006, several cruise-related viral gastroenteritis outbreaks were reported in Europe. One report came from a river-cruise, belonging to a ship-owner who had two other ships with outbreaks. This situation warranted onsite investigation in order to identify a potential common source of infection. A retrospective cohort study was performed among 137 people on board. Epidemiological questionnaire data were analysed using logistic regression. Stool, food, water and surface samples were collected for norovirus detection. Norovirus GGII.4-2006b was responsible for 48 gastroenteritis cases on this ship as confirmed in six patients. Identical norovirus sequences were detected in stool samples, on surfaces and in tap water. Epidemiological and microbiological data indicated multiple exposures contributing to the outbreak. Microbiological results demonstrated person-to-person transmission to be clearly present. Epidemiological results indicated that consuming tap water was a risk factor; however, this could not be concluded definitively on the basis of the available data. A common source for all cruise-related outbreaks was unlikely. The ongoing outbreaks on this ship demonstrated that evidence based guidelines on effective disinfection strategies are needed.

Pre-symptomatic diagnosis and treatment of filovirus diseases

PubMed Central

Shurtleff, Amy C.; Whitehouse, Chris A.; Ward, Michael D.; Cazares, Lisa H.; Bavari, Sina

2015-01-01

Filoviruses are virulent human pathogens which cause severe illness with high case fatality rates and for which there are no available FDA-approved vaccines or therapeutics. Diagnostic tools including antibody- and molecular-based assays, mass spectrometry, and next-generation sequencing are continually under development. Assays using the polymerase chain reaction (PCR) have become the mainstay for the detection of filoviruses in outbreak settings. In many cases, real-time reverse transcriptase-PCR allows for the detection of filoviruses to be carried out with minimal manipulation and equipment and can provide results in less than 2 h. In cases of novel, highly diverse filoviruses, random-primed pyrosequencing approaches have proved useful. Ideally, diagnostic tests would allow for diagnosis of filovirus infection as early as possible after infection, either before symptoms begin, in the event of a known exposure or epidemiologic outbreak, or post-symptomatically. If tests could provide an early definitive diagnosis, then this information may be used to inform the choice of possible therapeutics. Several exciting new candidate therapeutics have been described recently; molecules that have therapeutic activity when administered to animal models of infection several days post-exposure, once signs of disease have begun. The latest data for candidate nucleoside analogs, small interfering RNA (siRNA) molecules, phosphorodiamidate (PMO) molecules, as well as antibody and blood-product therapeutics and therapeutic vaccines are discussed. For filovirus researchers and government agencies interested in making treatments available for a nation’s defense as well as its general public, having the right diagnostic tools to identify filovirus infections, as well as a panel of available therapeutics for treatment when needed, is a high priority. Additional research in both areas is required for ultimate success, but significant progress is being made to reach these goals. PMID:25750638

Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study.

PubMed

Chowell, Gerardo; Abdirizak, Fatima; Lee, Sunmi; Lee, Jonggul; Jung, Eunok; Nishiura, Hiroshi; Viboud, Cécile

2015-09-03

The Middle East respiratory syndrome (MERS) coronavirus has caused recurrent outbreaks in the Arabian Peninsula since 2012. Although MERS has low overall human-to-human transmission potential, there is occasional amplification in the healthcare setting, a pattern reminiscent of the dynamics of the severe acute respiratory syndrome (SARS) outbreaks in 2003. Here we provide a head-to-head comparison of exposure patterns and transmission dynamics of large hospital clusters of MERS and SARS, including the most recent South Korean outbreak of MERS in 2015. To assess the unexpected nature of the recent South Korean nosocomial outbreak of MERS and estimate the probability of future large hospital clusters, we compared exposure and transmission patterns for previously reported hospital clusters of MERS and SARS, based on individual-level data and transmission tree information. We carried out simulations of nosocomial outbreaks of MERS and SARS using branching process models rooted in transmission tree data, and inferred the probability and characteristics of large outbreaks. A significant fraction of MERS cases were linked to the healthcare setting, ranging from 43.5 % for the nosocomial outbreak in Jeddah, Saudi Arabia, in 2014 to 100 % for both the outbreak in Al-Hasa, Saudi Arabia, in 2013 and the outbreak in South Korea in 2015. Both MERS and SARS nosocomial outbreaks are characterized by early nosocomial super-spreading events, with the reproduction number dropping below 1 within three to five disease generations. There was a systematic difference in the exposure patterns of MERS and SARS: a majority of MERS cases occurred among patients who sought care in the same facilities as the index case, whereas there was a greater concentration of SARS cases among healthcare workers throughout the outbreak. Exposure patterns differed slightly by disease generation, however, especially for SARS. Moreover, the distributions of secondary cases per single primary case varied highly across individual hospital outbreaks (Kruskal-Wallis test; P < 0.0001), with significantly higher transmission heterogeneity in the distribution of secondary cases for MERS than SARS. Simulations indicate a 2-fold higher probability of occurrence of large outbreaks (>100 cases) for SARS than MERS (2 % versus 1 %); however, owing to higher transmission heterogeneity, the largest outbreaks of MERS are characterized by sharper incidence peaks. The probability of occurrence of MERS outbreaks larger than the South Korean cluster (n = 186) is of the order of 1 %. Our study suggests that the South Korean outbreak followed a similar progression to previously described hospital clusters involving coronaviruses, with early super-spreading events generating a disproportionately large number of secondary infections, and the transmission potential diminishing greatly in subsequent generations. Differences in relative exposure patterns and transmission heterogeneity of MERS and SARS could point to changes in hospital practices since 2003 or differences in transmission mechanisms of these coronaviruses.

Fatal septicemia caused by the zoonotic bacterium Streptococcus iniae during an outbreak in Caribbean reef fish

USDA-ARS?s Scientific Manuscript database

An outbreak of Streptococcus iniae occurred in the early months of 2008 among wild reef fish in the waters of the Federation of St.Kitts and Nevis, lasting almost 2 months. Moribund and dead fish were collected for gross, histological, bacteriological, and molecular analysis. Necropsy findings inclu...

Evidence for the presence of African swine fever virus in an endemic region of Western Kenya in the absence of any reported outbreak.

PubMed

Thomas, Lian F; Bishop, Richard P; Onzere, Cynthia; Mcintosh, Michael T; Lemire, Karissa A; de Glanville, William A; Cook, E Anne J; Fèvre, Eric M

2016-09-08

African swine fever (ASF), caused by African swine fever virus (ASFV), is a severe haemorrhagic disease of pigs, outbreaks of which can have a devastating impact upon commercial and small-holder pig production. Pig production in western Kenya is characterised by low-input, free-range systems practised by poor farmers keeping between two and ten pigs. These farmers are particularly vulnerable to the catastrophic loss of livestock assets experienced in an ASF outbreak. This study wished to expand our understanding of ASFV epidemiology during a period when no outbreaks were reported. Two hundred and seventy six whole blood samples were analysed using two independent conventional and real time PCR assays to detect ASFV. Despite no recorded outbreak of clinical ASF during this time, virus was detected in 90/277 samples analysed by conventional PCR and 142/209 samples analysed by qPCR. Genotyping of a sub-set of these samples indicated that the viruses associated with the positive samples were classified within genotype IX and that these strains were therefore genetically similar to the virus associated with the 2006/2007 ASF outbreaks in Kenya. The detection of ASFV viral DNA in a relatively high number of pigs delivered for slaughter during a period with no reported outbreaks provides support for two hypotheses, which are not mutually exclusive: (1) that virus prevalence may be over-estimated by slaughter-slab sampling, relative to that prevailing in the wider pig population; (2) that sub-clinical, chronically infected or recovered pigs may be responsible for persistence of the virus in endemic areas.

Trivalent live attenuated intranasal influenza vaccine administered during the 2003-2004 influenza type A (H3N2) outbreak provided immediate, direct, and indirect protection in children.

PubMed

Piedra, Pedro A; Gaglani, Manjusha J; Kozinetz, Claudia A; Herschler, Gayla B; Fewlass, Charles; Harvey, Dianne; Zimmerman, Nadine; Glezen, W Paul

2007-09-01

Live attenuated influenza vaccine may protect against wild-type influenza illness shortly after vaccine administration by innate immunity. The 2003-2004 influenza A (H3N2) outbreak arrived early, and the circulating strain was antigenically distinct from the vaccine strain. The objective of this study was to determine the effectiveness of influenza vaccines for healthy school-aged children when administered during the influenza outbreak. An open-labeled, nonrandomized, community-based influenza vaccine trial was conducted in children 5 to 18 years old. Age-eligible healthy children received trivalent live attenuated influenza vaccine. Trivalent inactivated influenza vaccine was given to children with underlying health conditions. Influenza-positive illness was compared between vaccinated and nonvaccinated children. Medically attended acute respiratory illness and pneumonia and influenza rates for Scott and White Health Plan vaccinees were compared with age-eligible Scott and White Health Plan nonparticipants in the intervention communities. Herd protection was assessed by comparing age-specific medically attended acute respiratory illness rates in Scott and White Health Plan members in the intervention and comparison communities. We administered 1 dose of trivalent live attenuated influenza vaccine or trivalent inactivated influenza vaccine to 6569 and 1040 children, respectively (31.5% vaccination coverage), from October 10 to December 30, 2003. The influenza outbreak occurred from October 12 to December 20, 2003. Significant protection against influenza-positive illness (37.3%) and pneumonia and influenza events (50%) was detected in children who received trivalent live attenuated influenza vaccine but not trivalent inactivated influenza vaccine. Trivalent live attenuated influenza vaccine recipients had similar protection against influenza-positive illness within 14 days compared with >14 days (10 of 25 vs 9 of 30) after vaccination. Indirect effectiveness against medically attended acute respiratory illness was detected in children 5 to 11 and adults 35 to 44 years of age. One dose of trivalent live attenuated influenza vaccine was efficacious in children even when administered during an influenza outbreak and when the dominant circulating influenza virus was antigenically distinct from the vaccine strain. We hypothesize that trivalent live attenuated influenza vaccine provides protection against influenza by both innate and adaptive immune mechanisms.

Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak.

PubMed

Ottesen, Andrea; Ramachandran, Padmini; Reed, Elizabeth; White, James R; Hasan, Nur; Subramanian, Poorani; Ryan, Gina; Jarvis, Karen; Grim, Christopher; Daquiqan, Ninalynn; Hanes, Darcy; Allard, Marc; Colwell, Rita; Brown, Eric; Chen, Yi

2016-11-16

Microbiota that co-enrich during efforts to recover pathogens from foodborne outbreaks interfere with efficient detection and recovery. Here, dynamics of co-enriching microbiota during recovery of Listeria monocytogenes from naturally contaminated ice cream samples linked to an outbreak are described for three different initial enrichment formulations used by the Food and Drug Administration (FDA), the International Organization of Standardization (ISO), and the United States Department of Agriculture (USDA). Enrichment cultures were analyzed using DNA extraction and sequencing from samples taken every 4 h throughout 48 h of enrichment. Resphera Insight and CosmosID analysis tools were employed for high-resolution profiling of 16S rRNA amplicons and whole genome shotgun data, respectively. During enrichment, other bacterial taxa were identified, including Anoxybacillus, Geobacillus, Serratia, Pseudomonas, Erwinia, and Streptococcus spp. Surprisingly, incidence of L. monocytogenes was proportionally greater at hour 0 than when tested 4, 8, and 12 h later with all three enrichment schemes. The corresponding increase in Anoxybacillus and Geobacillus spp.indicated these taxa co-enriched in competition with L. monocytogenes during early enrichment hours. L. monocytogenes became dominant after 24 h in all three enrichments. DNA sequences obtained from shotgun metagenomic data of Listeria monocytogenes at 48 h were assembled to produce a consensus draft genome which appeared to have a similar tracking utility to pure culture isolates of L. monocytogenes. All three methods performed equally well for enrichment of Listeria monocytogenes. The observation of potential competitive exclusion of L. mono by Anoxybacillus and Geobacillus in early enrichment hours provided novel information that may be used to further optimize enrichment formulations. Application of Resphera Insight for high-resolution analysis of 16S amplicon sequences accurately identified L. monocytogenes. Both shotgun and 16S rRNA data supported the presence of three slightly variable genomes of L. monocytogenes. Moreover, the draft assembly of a consensus genome of L. monocytogenes from shotgun metagenomic data demonstrated the potential utility of this approach to expedite trace-back of outbreak-associated strains, although further validation will be needed to confirm this utility.

Dengue outbreak in a large military station: Have we learnt any lesson?

PubMed

Kunwar, R; Prakash, R

2015-01-01

An outbreak was reported from a large military station located in South India in 2013. In spite of instituting the preventive measures early, it took more than 2 months to bring the outbreak under control. This paper brings out lessons learnt and suggests strategy for controlling similar outbreak in future. The Military station comprises of 6 large Regimental Centres and many smaller units. The approximate strength of the serving personnel and their families is 25,000. Besides the unit Regimental Medical Officers, a large tertiary care hospital and a Station Health Organization is available to provide health care. A total of 266 patients including 192 serving personnel and 74 of their dependents were hospitalized for dengue between 15 May 2013 and 28 Jul 2013. Many dependents not having severe symptoms, were not hospitalized and treated on outpatient basis. Health advisories and instructions for constituting Dengue Task Force (DTF) were issued well in advance. Preventive measures were instituted early. But the outbreak was controlled only after intervention from higher administrative authorities. Lessons learnt included correct and timely perception of threat is essential; behavioural change of individuals is desired; availability of adequate health functionaries is mandatory; and complete dataset helps correct perception. Future strategy for control of dengue outbreak should include repeated and timely survey of entire area for correct risk perception, assessment of behavioural change among individuals; operational research to assess the impact of ongoing public health campaign.

Comparison of Sexual Mixing Patterns for Syphilis in Endemic and Outbreak Settings

PubMed Central

Doherty, Irene A; Adimora, Adaora A; Muth, Stephen Q; Serre, Marc L; Leone, Peter A; Miller, William C

2015-01-01

Background In a largely rural region of North Carolina during 1998–2002, outbreaks occurred of heterosexually-transmitted syphilis, tied to crack cocaine use and exchange of sex for drugs and money. Sexual partnership mixing patterns are an important characteristic of sexual networks that relate to transmission dynamics of STIs. Methods Using contact tracing data collected by Disease Intervention Specialists, we estimated Newman assortativity coefficients and compared values in counties experiencing syphilis outbreaks to non-outbreak counties, with respect to race/ethnicity, race/ethnicity and age, and the cases' number of social/sexual contacts, infected contacts, sex partners, and infected sex partners, and syphilis disease stage (primary, secondary, early latent). Results Individuals in the outbreak counties had more contacts and mixing by the number of sex partners was disassortative in outbreak counties and assortative non-outbreak counties. Whereas mixing by syphilis disease stage was minimally assortative in outbreak counties, it was disassortative in non-outbreak areas. Partnerships were relatively discordant by age, especially among older White men, who often chose considerably younger female partners. Conclusions Whether assortative mixing exacerbates or attenuates the reach of STIs into different populations depends on the characteristic/attribute and epidemiologic phase. Examination of sexual partnership characteristics and mixing patterns offers insights into the growth of STI outbreaks that complement other research methods. PMID:21217418

Scabies outbreaks in residential care homes: factors associated with late recognition, burden and impact. A mixed methods study in England.

PubMed

Hewitt, K A; Nalabanda, A; Cassell, J A

2015-05-01

Scabies is an important public health problem in residential care homes. Delayed diagnosis contributes to outbreaks, which may be prolonged and difficult to control. We investigated factors influencing outbreak recognition, diagnosis and treatment, and staff experiences of outbreak control, identifying areas for intervention. We carried out a semi-structured survey of managers, affected residents and staff of seven care homes reporting suspected scabies outbreaks in southern England over a 6-month period. Attack rates ranged from 2% to 50%, and most cases had dementia (37/39, 95%). Cases were diagnosed clinically by GPs (59%) or home staff (41%), none by dermatologists. Most outbreaks were attributable to avoidably late diagnosis of the index case. Participants reported considerable challenges in managing scabies outbreaks, including late diagnosis and recognition of outbreaks; logistically difficult mass treatment; distressing treatment processes and high costs. This study demonstrates the need for improved support for care homes in detecting and managing these outbreaks.

Understanding the early dynamics of the 2014 porcine epidemic diarrhea virus (PEDV) outbreak in Ontario using the incidence decay and exponential adjustment (IDEA) model.

PubMed

Greer, Amy L; Spence, Kelsey; Gardner, Emma

2017-01-05

The United States swine industry was first confronted with porcine epidemic diarrhea virus (PEDV) in 2013. In young pigs, the virus is highly pathogenic and the associated morbidity and mortality has a significant negative impact on the swine industry. We have applied the IDEA model to better understand the 2014 PEDV outbreak in Ontario, Canada. Using our simple, 2-parameter IDEA model, we have evaluated the early epidemic dynamics of PEDV on Ontario swine farms. We estimated the best-fit R 0 and control parameter (d) for the between farm transmission component of the outbreak by fitting the model to publically available cumulative incidence data. We used maximum likelihood to compare model fit estimates for different combinations of the R 0 and d parameters. Using our initial findings from the iterative fitting procedure, we projected the time course of the epidemic using only a subset of the early epidemic data. The IDEA model projections showed excellent agreement with the observed data based on a 7-day generation time estimate. The best-fit estimate for R 0 was 1.87 (95% CI: 1.52 - 2.34) and for the control parameter (d) was 0.059 (95% CI: 0.022 - 0.117). Using data from the first three generations of the outbreak, our iterative fitting procedure suggests that R 0 and d had stabilized sufficiently to project the time course of the outbreak with reasonable accuracy. The emergence and spread of PEDV represents an important agricultural emergency. The virus presents a significant ongoing threat to the Canadian swine industry. Developing an understanding of the important epidemiological characteristics and disease transmission dynamics of a novel pathogen such as PEDV is critical for helping to guide the implementation of effective, efficient, and economically feasible disease control and prevention strategies that are able to help decrease the impact of an outbreak.

Early detection and response for measles and rubella cases through the (Nursery) School Absenteeism Surveillance System in Ibaraki Prefecture.

PubMed

Watanabe, Miki; Kurita, Junko; Takagi, Takeshi; Nagata, Noriko; Nagasu, Natsuki; Sugawara, Tamie; Ohkusa, Yasushi

2016-01-01

Objectives In Ibaraki Prefecture, all (nursery) schools have joined the (Nursery) School Absenteeism Surveillance System (hereafter denoted as (N)SASSy), which is operated by the Japan School Health Association to monitor the prevalence of infectious diseases, the early detection and response for outbreaks, and prevention of large outbreaks. Prefectural government officers also utilize it as a control measure for infectious diseases. In particular, when cases of measles or rubella are registered, (N)SASSy sends e-mails automatically to prefectural government officers to activate control measures. This paper summarizes administrative responses by prefectural government officers for measles or rubella cases using (N)SASSy and discusses the future challenges.Methods We summarized registration, detection, and first response data for measles or rubella cases in (N)SASSy and compared the number of detected and reported cases enforced by the Infectious Diseases Control Law from January 1, 2013 to December 31, 2014.Results The public health center questioned hospitals/clinics and (nursery) schools about all registered measles or rubella cases in (N)SASSy on the same day to check the entered information. In the past 2 years, there were 5 measles and 56 rubella cases in 2013 and 1 measles and 19 rubella cases in 2014 registered with (N)SASSy. All cases were checked and investigated by the public health center. Of all cases detected by (N)SASSy, 7 rubella cases in 2013 and 1 rubella case in 2014 were reported based on the law. No measles cases were reported in the 2 years. The results of investigations and laboratory tests were given as feedback to the (nursery) schools. If the case did not case definition determined by the law, we changed the status in (N)SASSy to suspected or discarded cases.Conclusion Since (N)SASSy assists prefectural government officers with earlier detection of and response for infectious diseases, it definitely contributes to infection control. Immediate feedback of the laboratory test results to the (nursery) schools was also useful to confirm cases of measles or rubella. As data entry in (nursery) schools is needed for stable operation and utilization of (N)SASSy, it is important that workshops for (N)SASSy are held for (nursery) school teachers every year to maintain accuracy. Our future challenges include the coordination among (nursery) schools, hospitals/clinics, and prefectural government and their applications for infection control.

[Epidemiological characteristics of influenza outbreaks in China, 2005-2013].

PubMed

Li, Ming; Feng, Luzhao; Cao, Yu; Peng, Zhibin; Yu, Hongjie

2015-07-01

To understand the epidemiological characteristics of influenza outbreaks in China from 2005 to 2013. The data of influenza-like illness outbreaks involving 10 or more cases were collected through Public Health Emergency Management Information System and National Influenza Surveillance Information System in China, and the influenza outbreaks were identified according to the laboratory detection results. Descriptive epidemiological analysis was conducted to understand the type/subtype of influenza virus and outbreak time, area, place and extent. From 2005 to 2013, a total of 3 252 influenza-like illness outbreaks were reported in the mainland of China, in which 2 915 influenza outbreaks were laboratory confirmed, and influenza A (H1N1) pdm09 virus and influenza B virus were predominant. More influenza outbreaks were reported in the influenza A (H1N1) pandemic during 2009-2010. Influenza outbreaks mainly occurred during winter-spring, and less influenza outbreaks occurred in winter and summer vacations of schools. More influenza outbreaks were reported in southern provinces, accounting for 79% of the total. Influenza outbreaks mainly occurred in primary and middle schools, where 2 763 outbreaks were reported, accounting for 85% of the total. Average 30-99 people were involved in an outbreak. A large number of influenza outbreaks occur during influenza season every year in China, the predominant virus type or subtype varies with season. Primary and middle schools are mainly affected by influenza outbreaks.

Detection of African swine fever, classical swine fever, and foot-and-mouth disease viruses in swine oral fluids by multiplex reverse transcription real-time polymerase chain reaction.

PubMed

Grau, Frederic R; Schroeder, Megan E; Mulhern, Erin L; McIntosh, Michael T; Bounpheng, Mangkey A

2015-03-01

African swine fever (ASF), classical swine fever (CSF), and foot-and-mouth disease (FMD) are highly contagious animal diseases of significant economic importance. Pigs infected with ASF and CSF viruses (ASFV and CSFV) develop clinical signs that may be indistinguishable from other diseases. Likewise, various causes of vesicular disease can mimic clinical signs caused by the FMD virus (FMDV). Early detection is critical to limiting the impact and spread of these disease outbreaks, and the ability to perform herd-level surveillance for all 3 diseases rapidly and cost effectively using a single diagnostic sample and test is highly desirable. This study assessed the feasibility of simultaneous ASFV, CSFV, and FMDV detection by multiplex reverse transcription real-time polymerase chain reaction (mRT-qPCR) in swine oral fluids collected through the use of chewing ropes. Animal groups were experimentally infected independently with each virus, observed for clinical signs, and oral fluids collected and tested throughout the course of infection. All animal groups chewed on the ropes readily before and after onset of clinical signs and before onset of lameness or serious clinical signs. ASFV was detected as early as 3 days postinoculation (dpi), 2-3 days before onset of clinical disease; CSFV was detected at 5 dpi, coincident with onset of clinical disease; and FMDV was detected as early as 1 dpi, 1 day before the onset of clinical disease. Equivalent results were observed in 4 independent studies and demonstrate the feasibility of oral fluids and mRT-qPCR for surveillance of ASF, CSF, and FMD in swine populations. © 2015 The Author(s).

Interagency Coordination in the Case of an Intentional Agroterrorist Incident

DTIC Science & Technology

2009-05-11

and working groups; development of a National Veterinary Stockpile of vaccines needed to respond to animal diseases; and funding of research...outbreak or an intentional incident. They include lack of personnel able to recognize a foreign animal disease outbreak, difficulty with vaccination and... vaccination stockpiling, and difficulty detecting a covert attack and differentiating it from a natural outbreak with the current surveillance and

Gastroenteritis outbreak caused by waterborne norovirus at a New Zealand ski resort.

PubMed

Hewitt, Joanne; Bell, Derek; Simmons, Greg C; Rivera-Aban, Malet; Wolf, Sandro; Greening, Gail E

2007-12-01

In July 2006, public health services investigated an outbreak of acute gastroenteritis among staff and visitors of a popular ski resort in southern New Zealand. The source of the outbreak was a drinking water supply contaminated by human sewage. The virological component of the investigation played a major role in confirming the source of the outbreak. Drinking water, source stream water, and 31 fecal specimens from gastroenteritis outbreak cases were analyzed for the presence of norovirus (NoV). Water samples were concentrated by ultrafiltration, and real-time reverse transcription-PCR (RT-PCR) was used for rapid detection of NoV from both water and fecal samples. The implicated NoV strain was further characterized by DNA sequencing. NoV genogroup GI/5 was identified in water samples and linked case fecal specimens, providing clear evidence of the predominant pathogen and route of exposure. A retrospective cohort study demonstrated that staff who consumed drinking water from the resort supply were twice as likely to have gastroenteritis than those who did not. This is the first time that an outbreak of gastroenteritis in New Zealand has been conclusively linked to NoV detected in a community water supply. To our knowledge, this is the first report of the use of ultrafiltration combined with quantitative real-time RT-PCR and DNA sequencing for investigation of a waterborne NoV outbreak.

Internet-based media coverage on dengue in Sri Lanka between 2007 and 2015.

PubMed

Wilder-Smith, Annelies; Cohn, Emily; Lloyd, David C; Tozan, Yesim; Brownstein, John S

2016-01-01

Internet-based media coverage to explore the extent of awareness of a disease and perceived severity of an outbreak at a national level can be used for early outbreak detection. Dengue has emerged as a major public health problem in Sri Lanka since 2009. To compare Internet references to dengue in Sri Lana with references to other diseases (malaria and influenza) in Sri Lanka and to compare Internet references to dengue in Sri Lanka with notified cases of dengue in Sri Lanka. We examined Internet-based news media articles on dengue queried from HealthMap for Sri Lanka, for the period January 2007 to November 2015. For comparative purposes, we compared hits on dengue with hits on influenza and malaria. There were 565 hits on dengue between 2007 and 2015, with a rapid rise in 2009 and followed by a rising trend ever since. These hits were highly correlated with the national epidemiological trend of dengue. The volume of digital media coverage of dengue was much higher than of influenza and malaria. Dengue in Sri Lanka is receiving increasing media attention. Our findings underpin previous claims that digital media reports reflect national epidemiological trends, both in annual trends and inter-annual seasonal variation, thus acting as proxy biosurveillance to provide early warning and situation awareness of emerging infectious diseases.

Evaluation of Passive Samplers as a Monitoring Tool for Early Warning of Dinophysis Toxins in Shellfish

PubMed Central

Pizarro, Gemita; Moroño, Ángeles; Paz, Beatriz; Franco, José M.; Pazos, Yolanda; Reguera, Beatriz

2013-01-01

From June 2006 to January 2007 passive samplers (solid phase adsorbing toxin tracking, SPATT) were tested as a monitoring tool with weekly monitoring of phytoplankton and toxin content (liquid chromatography–mass spectrometry, LC-MS) in picked cells of Dinophysis and plankton concentrates. Successive blooms of Dinophysis acuminata, D. acuta and D. caudata in 2006 caused a long mussel harvesting closure (4.5 months) in the Galician Rías (NW Spain) and a record (up to 9246 ng·g resin-week−1) accumulation of toxins in SPATT discs. Best fit of a toxin accumulation model was between toxin accumulation in SPATT and the product of cell densities by a constant value, for each species of Dinophysis, of toxin content (average) in picked cells. Detection of Dinophysis populations provided earlier warning of oncoming diarrhetic shellfish poisoning (DSP) outbreaks than the SPATT, which at times overestimated the expected toxin levels in shellfish because: (i) SPATT accumulated toxins did not include biotransformation and depuration loss terms and (ii) accumulation of toxins not available to mussels continued for weeks after Dinophysis cells were undetectable and mussels were toxin-free. SPATT may be a valuable environmental monitoring and research tool for toxin dynamics, in particular in areas with no aquaculture, but does not provide a practical gain for early warning of DSP outbreaks. PMID:24152559

An evaluation of asymptomatic Dengue infections among blood donors during the 2014 Dengue outbreak in Guangzhou, China.

PubMed

Liao, Qiao; Shan, Zhengang; Wang, Min; Huang, Jieting; Xu, Ru; Huang, Ke; Tang, Xi; Zhang, Weiyun; Nelson, Kenrad; Li, Chengyao; Fu, Yongshui; Rong, Xia

2017-11-01

In 2014, an outbreak of dengue virus (DENV) infection led to 45 171 clinical cases diagnosed in Guangdong province, Southern China. However, the potential risk of blood donors asymptomatically infected with DENV has not been evaluated . In the current study we detected anti-DENV IgG antibody and RNA in volunteer Chinese blood donors. We found that anti-DENV IgG antibody was positively detected in 3.4% (51/1500) and two donors were detected as being DENV RNA positive out of 3000 blood samples. We concluded that the presence of potential DENV in blood donors might be potential risk for blood safety. Therefore, screening for DENV infection should be considered in blood donations during a period of dengue outbreak in high epidemic area of China. © 2017 Wiley Periodicals, Inc.

Attempted early detection of influenza A (H1N1) pandemic with surveillance data of influenza‐like illness and unexplained pneumonia

PubMed Central

Qian, Yan‐Hua; Su, Jing; Shi, Ping; He, En‐Qi; Shao, Jie; Sun, Na; Zu, Rong‐Qiang; Yu, Rong‐Bin

2011-01-01

Please cite this paper as: Qian et al. (2011) Attempted early detection of influenza A (H1N1) pandemic with surveillance data of influenza‐like illness and unexplained pneumonia. Influenza and Other Respiratory Viruses 5(6), e479–e486. Background  To collect disease information and provide data for early detection of epidemics, two surveillance systems were established for influenza‐like illness (ILI) and unexplained pneumonia (UP) in Wuxi, People’s Republic of China. Objectives  The current study aims to describe the performance of these surveillance systems during 2004–2009 and to evaluate the value of surveillance data in detection of influenza epidemics. Methods  Two national ILI sentinel hospitals and three UP sentinel hospitals provided data to the surveillance systems. The surveillance data from hospital‐based outpatient clinics and emergency rooms were compared by year. The ILI data of 2009 were further modeled based on previous data using both a control chart method and a moving average regression method. Alarms of potential epidemics would be raised when the input surveillance data surpassed a threshold. Results  In 2009, the proportions of ILI and respiratory illness with fever (one surveillance syndrome of the UP system) to total patient visits (3·40% and 11·76%, respectively) were higher than the previous years. The surveillance data of both systems also showed developing trends similar to the influenza A (H1N1) pandemic in 2009. When the surveillance data of 2009 were fitted in the two detection models, alarms were produced on the occurrence of the first local case of influenza A (H1N1), outbreaks in schools and in general populations. Conclusions  The results indicated the potential for using ILI and UP surveillance data as syndromic indicators to detect and provide an early warning for influenza epidemics. PMID:21668678

Detection of human norovirus from frozen raspberries in a cluster of gastroenteritis outbreaks.

PubMed

Maunula, L; Roivainen, M; Keränen, M; Mäkela, S; Söderberg, K; Summa, M; von Bonsdorff, C H; Lappalainen, M; Korhonen, T; Kuusi, M; Niskanen, T

2009-12-10

We describe a cluster of norovirus outbreaks affecting about 200 people in Southern Finland in September and October 2009. All outbreaks occurred after consumption of imported raspberries from the same batch intended for the catering sector. Human norovirus genotype GI.4 was found in frozen raspberries. The berries were served in toppings of cakes in separate catering settings or mixed in curd cheese as a snack for children in a daycare center. The relative risk for consumption of the berry dish was 3.0 (p

Multinational outbreak of Salmonella Enteritidis infection during an international youth ice hockey competition in Riga, Latvia, preliminary report, March and April 2015.

PubMed

Pesola, A K; Parn, T; Huusko, S; Perevosčikovs, J; Ollgren, J; Salmenlinna, S; Lienemann, T; Gossner, C; Danielsson, N; Rimhanen-Finne, R

2015-05-21

A multinational outbreak of salmonellosis linked to the Riga Cup 2015 junior ice-hockey competition was detected by the Finnish health authorities in mid-April and immediately notified at the European Union level. This prompted an international outbreak investigation supported by the European Centre for Disease Prevention and Control. As of 8 May 2015, seven countries have reported 214 confirmed and suspected cases, among which 122 from Finland. The search for the source of the outbreak is ongoing.

Classical swine fever in India: current status and future perspective.

PubMed

Singh, Vinod Kumar; Rajak, Kaushal Kishore; Kumar, Amit; Yadav, Sharad Kumar

2018-05-04

Classical swine fever (CSF) is a globally significant disease of swine caused by classical swine fever virus. The virus affects the wild boars and pigs of all age groups, leading to acute, chronic, late-onset or in-apparent course of the disease. The disease causes great economic loss to the piggery industry due to mortality, stunted growth, poor reproductive performance, and by impeding the international trade of pig and pig products. In India, CSF outbreaks are reported from most of the states wherever pig rearing is practiced and more frequently from northeast states. In spite of the highly devastating nature and frequent outbreaks, CSF remained underestimated and neglected for decades in India. The country requires rapid and sensitive diagnostic tests for an early detection of infection to limit the spread of the disease. Also, effective prophylactics are required to help in control and eradication of the disease for the development of the piggery industry. This review looks into the economic impact; epidemiology of CSF highlighting the temporal and spatial occurrence of outbreaks in the last two decades, circulation, and emergence of the virus genotypes in and around the country; and the constraints in the disease control, with the aim to update the knowledge of current status of the disease in India. The article also emphasizes the importance of the disease and the need to develop rapid specific diagnostics and effective measures to eradicate the disease.

Strengthened Ebola surveillance in France during a major outbreak in West Africa: March 2014-January 2016.

PubMed

Mailles, A; Noel, H; Pannetier, D; Rapp, C; Yazdanpanah, Y; Vandentorren, S; Chaud, P; Philippe, J M; Worms, B; Bruyand, M; Tourdjman, M; Nahon, M; Belchior, E; Lucas, E; Durand, J; Zurbaran, M; Vaux, S; Coignard, B; DE Valk, H; Baize, S; Quelet, S; Bourdillon, F

2017-12-01

Introduction An unprecedented outbreak of Ebola virus diseases (EVD) occurred in West Africa from March 2014 to January 2016. The French Institute for Public Health implemented strengthened surveillance to early identify any imported case and avoid secondary cases. Febrile travellers returning from an affected country had to report to the national emergency healthcare hotline. Patients reporting at-risk exposures and fever during the 21st following day from the last at-risk exposure were defined as possible cases, hospitalised in isolation and tested by real-time polymerase chain reaction. Asymptomatic travellers reporting at-risk exposures were considered as contact and included in a follow-up protocol until the 21st day after the last at-risk exposure. From March 2014 to January 2016, 1087 patients were notified: 1053 were immediately excluded because they did not match the notification criteria or did not have at-risk exposures; 34 possible cases were tested and excluded following a reliable negative result. Two confirmed cases diagnosed in West Africa were evacuated to France under stringent isolation conditions. Patients returning from Guinea (n = 531; 49%) and Mali (n = 113; 10%) accounted for the highest number of notifications. No imported case of EVD was detected in France. We are confident that our surveillance system was able to classify patients properly during the outbreak period.

Use of media and public-domain Internet sources for detection and assessment of plant health threats

PubMed Central

Thomas, Carla S.; Nelson, Noele P.; Jahn, Gary C.; Niu, Tianchan; Hartley, David M.

2011-01-01

Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance. PMID:24149031

Use of media and public-domain Internet sources for detection and assessment of plant health threats.

PubMed

Thomas, Carla S; Nelson, Noele P; Jahn, Gary C; Niu, Tianchan; Hartley, David M

2011-09-05

Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance.

Absenteeism in schools during the 2009 influenza A(H1N1) pandemic: a useful tool for early detection of influenza activity in the community?

PubMed

Kara, E O; Elliot, A J; Bagnall, H; Foord, D G F; Pnaiser, R; Osman, H; Smith, G E; Olowokure, B

2012-07-01

Certain influenza outbreaks, including the 2009 influenza A(H1N1) pandemic, can predominantly affect school-age children. Therefore the use of school absenteeism data has been considered as a potential tool for providing early warning of increasing influenza activity in the community. This study retrospectively evaluates the usefulness of these data by comparing them with existing syndromic surveillance systems and laboratory data. Weekly mean percentages of absenteeism in 373 state schools (children aged 4-18 years) in Birmingham, UK, from September 2006 to September 2009, were compared with established syndromic surveillance systems including a telephone health helpline, a general practitioner sentinel network and laboratory data for influenza. Correlation coefficients were used to examine the relationship between each syndromic system. In June 2009, school absenteeism generally peaked concomitantly with the existing influenza surveillance systems in England. Weekly school absenteeism surveillance would not have detected pandemic influenza A(H1N1) earlier but daily absenteeism data and the development of baselines could improve the timeliness of the system.

The impact of the disease early warning system in responding to natural disasters and conflict crises in Pakistan.

PubMed

Rahim, M; Kazi, B M; Bile, K M; Munir, M; Khan, A R

2010-01-01

The disease early warning system (DEWS) was introduced in the immediate aftermath of the 2005 earthquake in Pakistan, with the objective to undertake prompt investigation and mitigation of disease outbreaks. The DEWS network was replicated successfully during subsequent flood and earthquake disasters as well as during the 2008-09 internally displaced persons' crisis. DEWS-generated alerts, prompt investigations and timely responses had an effective contribution to the control of epidemics. Through DEWS, 1360 reported alerts during 2005-09 averted the risk of disease outbreaks through pre-emptive necessary measures, while the 187 confirmed outbreaks were effectively controlled. In the aftermath of the disasters, DEWS technology also facilitated the development of a disease-surveillance system that became an integral part of the district health system. This study aims to report the DEWS success and substantiate its lead role as a priority emergency health response intervention.

Characterization of Viral Load, Viability and Persistence of Influenza A Virus in Air and on Surfaces of Swine Production Facilities.

PubMed

Neira, Victor; Rabinowitz, Peter; Rendahl, Aaron; Paccha, Blanca; Gibbs, Shawn G; Torremorell, Montserrat

2016-01-01

Indirect transmission of influenza A virus (IAV) in swine is poorly understood and information is lacking on levels of environmental exposure encountered by swine and people during outbreaks of IAV in swine barns. We characterized viral load, viability and persistence of IAV in air and on surfaces during outbreaks in swine barns. IAV was detected in pigs, air and surfaces from five confirmed outbreaks with 48% (47/98) of oral fluid, 38% (32/84) of pen railing and 43% (35/82) of indoor air samples testing positive by IAV RT-PCR. IAV was isolated from air and oral fluids yielding a mixture of subtypes (H1N1, H1N2 and H3N2). Detection of IAV RNA from air was sustained during the outbreaks with maximum levels estimated between 7 and 11 days from reported onset. Our results indicate that during outbreaks of IAV in swine, aerosols and surfaces in barns contain significant levels of IAV potentially representing an exposure hazard to both swine and people.

Imported dengue from 2013 Angola outbreak: Not just serotype 1 was detected.

PubMed

Abreu, Cândida; Silva-Pinto, André; Lazzara, Daniela; Sobrinho-Simões, Joana; Guimarães, João Tiago; Sarmento, António

2016-06-01

All the reports from Angola's 2013 dengue outbreak revealed serotype 1. However, previously dengue serotypes 1-4 have been reported in Africa and in 2014 serotype 4 was reported in Angola. To report dengue serotypes in patients returning from Angola during 2013 outbreak. Retrospective, cross-sectional study. We serotyped the dengue by an in house Polymerase Chain Reaction technique in randomly selected cases. From the 2013 Angola's dengue outbreak we treated 47 adult patients. None had history of past dengue. A combo kit test for dengue revealed positive NS1 antigen in 39 and IgM antibodies in 8. From 17 randomly patients tested by RNA Real Time-PCR, 11 were positive: 7 for DENV-1, 2 for DENV-2, 1 for DENV-3 (co-infected with DENV-1) and 1 for DENV-4. None had a complicated or fatal evolution. Unlike previous reports the 4 serotypes were detected, and this resulted in a different epidemiological situation, raising the risk of future outbreaks of severe dengue. Copyright © 2016 Elsevier B.V. All rights reserved.

Echovirus 30 meningitis epidemic followed by an outbreak-specific RT-qPCR.

PubMed

Österback, Riikka; Kalliokoski, Teemu; Lähdesmäki, Tuire; Peltola, Ville; Ruuskanen, Olli; Waris, Matti

2015-08-01

An outbreak of enteroviral aseptic meningitis emerged in Southwestern Finland in August 2009. The same enterovirus reappeared with increasing incidence of meningitis in other parts of Finland in 2010. To identify the incidence and molecular epidemiology of enteroviral meningitis outbreak. The causative agent was identified as echovirus 30 (E-30) by sequencing partial viral protein 1 capsid genome, and a virus type-specific RT-qPCR was set up for sensitive detection of the virus in cerebrospinal fluid specimens. Enterovirus positive CSF specimens were subjected to the E-30-specific assay to investigate this unusual occurrence of aseptic meningitis and facilitate case confirmation during the outbreaks between August 2009 and September 2010. E-30 was detected in 106 (72%) enterovirus positive cerebrospinal fluid specimens. All the meningitis cases in 2009 and most of them in 2010 were among adolescents and several were members of sport teams. Between August 2009 and September 2010, E-30 caused an extensive outbreak with two peaks in Finland. Type-specific RT-PCR allowed rapid diagnostic follow-up of the epidemic. Copyright © 2015 Elsevier B.V. All rights reserved.

Mild Illness during Outbreak of Shiga Toxin-Producing Escherichia coli O157 Infections Associated with Agricultural Show, Australia.

PubMed

Vasant, Bhakti R; Stafford, Russell J; Jennison, Amy V; Bennett, Sonya M; Bell, Robert J; Doyle, Christine J; Young, Jeannette R; Vlack, Susan A; Titmus, Paul; El Saadi, Debra; Jarvinen, Kari A J; Coward, Patricia; Barrett, Janine; Staples, Megan; Graham, Rikki M A; Smith, Helen V; Lambert, Stephen B

2017-10-01

During a large outbreak of Shiga toxin-producing Escherichia coli illness associated with an agricultural show in Australia, we used whole-genome sequencing to detect an IS1203v insertion in the Shiga toxin 2c subunit A gene of Shiga toxin-producing E. coli. Our study showed that clinical illness was mild, and hemolytic uremic syndrome was not detected.

US regional tornado outbreaks and their links to spring ENSO phases and North Atlantic SST variability

NASA Astrophysics Data System (ADS)

Lee, Sang-Ki; Wittenberg, Andrew T.; Enfield, David B.; Weaver, Scott J.; Wang, Chunzai; Atlas, Robert

2016-04-01

Recent violent and widespread tornado outbreaks in the US, such as occurred in the spring of 2011, have caused devastating societal impact with significant loss of life and property. At present, our capacity to predict US tornado and other severe weather risk does not extend beyond seven days. In an effort to advance our capability for developing a skillful long-range outlook for US tornado outbreaks, here we investigate the spring probability patterns of US regional tornado outbreaks during 1950-2014. We show that the four dominant springtime El Niño-Southern Oscillation (ENSO) phases (persistent versus early-terminating El Niño and resurgent versus transitioning La Niña) and the North Atlantic sea surface temperature tripole variability are linked to distinct and significant US regional patterns of outbreak probability. These changes in the probability of outbreaks are shown to be largely consistent with remotely forced regional changes in the large-scale atmospheric processes conducive to tornado outbreaks. An implication of these findings is that the springtime ENSO phases and the North Atlantic SST tripole variability may provide seasonal predictability of US regional tornado outbreaks.

African Swine Fever in Uganda: Qualitative Evaluation of Three Surveillance Methods with Implications for Other Resource-Poor Settings.

PubMed

Chenais, Erika; Sternberg-Lewerin, Susanna; Boqvist, Sofia; Emanuelson, Ulf; Aliro, Tonny; Tejler, Emma; Cocca, Giampaolo; Masembe, Charles; Ståhl, Karl

2015-01-01

Animal diseases impact negatively on households and on national economies. In low-income countries, this pertains especially to socio-economic effects on household level. To control animal diseases and mitigate their impact, it is necessary to understand the epidemiology of the disease in its local context. Such understanding, gained through disease surveillance, is often lacking in resource-poor settings. Alternative surveillance methods have been developed to overcome some of the hurdles obstructing surveillance. The objective of this study was to evaluate and qualitatively compare three methods for surveillance of acute infectious diseases using African swine fever in northern Uganda as an example. Report-driven outbreak investigations, participatory rural appraisals (PRAs), and a household survey using a smartphone application were evaluated. All three methods had good disease-detecting capacity, and each of them detected many more outbreaks compared to those reported to the World Organization for Animal Health during the same time period. Apparent mortality rates were similar for the three methods although highest for the report-driven outbreak investigations, followed by the PRAs, and then the household survey. The three methods have different characteristics and the method of choice will depend on the surveillance objective. The optimal situation might be achieved by a combination of the methods: outbreak detection via smartphone-based real-time surveillance, outbreak investigation for collection of biological samples, and a PRA for a better understanding of the epidemiology of the specific outbreak. All three methods require initial investments and continuous efforts. The sustainability of the surveillance system should, therefore, be carefully evaluated before making such investments.

Streptococcus pyogenes outbreak in a long-term care facility.

PubMed

Harkness, G A; Bentley, D W; Mottley, M; Lee, J

1992-06-01

Although outbreaks involving Streptococcus pyogenes have been uncommon among the elderly population, recent reports suggest that this organism is an important nosocomial pathogen among institutionalized older patients and carries significant morbidity and mortality. An outbreak of S. pyogenes, type M12, T12, occurred in a large long-term care institution serving the ill and chronically disabled. The outbreak involved 14 residents of the intermediate care facility and lasted for 4 months. A prospective epidemiologic investigation was initiated at the onset of the outbreak. Pertinent clinical and demographic information regarding both residents and personnel was obtained by interview, review of medical and surveillance records, and examination of patients for lesions. Cultures were obtained within 24 hours of symptom onset from those with characteristic clinical symptoms. Unpaired convalescent sera were tested for group A streptococcal extracellular antigens by a rapid hemagglutination slide test. Control measures included active surveillance of residents and staff for suspicious clinical syndromes, transfer of high-risk patients, elimination of a common seating area, and improved handwashing and hygiene measures. The attack rate was 7.5%, with 64.3% of these patients residing on one unit. S. pyogenes was isolated from eight residents, 5 residents had a characteristic syndrome and an elevated streptozyme hemagglutination titer of 400, and 1 resident died within hours of having cellulitis of the groin. Clinical syndromes included cellulitis, pharyngitis, bronchitis, pneumonia, and septicemia. Seven residents required acute care; two residents died within 3 weeks of the onset, yielding a case fatality rate of 14.3%. The major means of transmission appeared to be direct contact between residents, although transmission from an infected staff member may have accounted for some cases. The hypothesis of long-term colonization was supported by the extended times between infections. The severity of illness and the apparent transmission through direct contact between residents warrants (1) early detection of infected lesions, (2) recognition of invasive illness, (3) prompt effective treatment, and (4) surveillance for S. pyogenes infections among residents and personnel.

Outbreak of syphilis in men who have sex with men living in rural North Wales (UK) associated with the use of social media.

PubMed

Thomas, Daniel Rh; Williams, Christopher J; Andrady, Ushan; Anderson, Valerie; Humphreys, Sioned; Midgley, Claire M; Fina, Laia; Craine, Noel; Porter-Jones, Gary; Wilde, Alison; Whiteside, Chris

2016-08-01

To describe an outbreak of infectious syphilis in rural North Wales and the control measures implemented. Following reports of an increase of syphilis in North Wales, a multidisciplinary Outbreak Control Team (OCT) was established. A multilevel prevention and control response was initiated, including: active case surveillance, partner notification and treatment, sexual network analysis, awareness raising with professionals and affected communities, point-of-care syphilis testing at a sauna and a health promotion campaign targeting users of men who have sex with men (MSM) social network mobile phone applications (apps). Four cases of infectious syphilis were diagnosed in clinics in North Wales per 100 000 population in 2013 compared with a mean of one case per 100 000 in the preceding decade. Diagnosed cases peaked in January 2014, declining in the first half of 2014. Initial cases were clustered in the westerly rural counties of North Wales and were predominantly white men, self-reporting as MSM (median age: 34 years, range: 17-61). Point-of-care testing at a sauna did not identity further new infections, suggesting that the cluster was relatively focused and had probably been detected early. The use of apps to find sexual partners was a feature of the network affected. A health promotion campaign, initiated by the OCT, targeting men using MSM apps reached 92% of the 755 men messaged. The outbreak was successfully controlled. However, it is difficult to determine which of the interventions implemented were most effective. Future outbreaks should be used as an opportunity to evaluate interventions using apps. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A Locust Phase Change Model with Multiple Switching States and Random Perturbation

NASA Astrophysics Data System (ADS)

Xiang, Changcheng; Tang, Sanyi; Cheke, Robert A.; Qin, Wenjie

2016-12-01

Insects such as locusts and some moths can transform from a solitarious phase when they remain in loose populations and a gregarious phase, when they may swarm. Therefore, the key to effective management of outbreaks of species such as the desert locust Schistocercagregaria is early detection of when they are in the threshold state between the two phases, followed by timely control of their hopper stages before they fledge because the control of flying adult swarms is costly and often ineffective. Definitions of gregarization thresholds should assist preventive control measures and avoid treatment of areas that might not lead to gregarization. In order to better understand the effects of the threshold density which represents the gregarization threshold on the outbreak of a locust population, we developed a model of a discrete switching system. The proposed model allows us to address: (1) How frequently switching occurs from solitarious to gregarious phases and vice versa; (2) When do stable switching transients occur, the existence of which indicate that solutions with larger amplitudes can switch to a stable attractor with a value less than the switching threshold density?; and (3) How does random perturbation influence the switching pattern? Our results show that both subsystems have refuge equilibrium points, outbreak equilibrium points and bistable equilibria. Further, the outbreak equilibrium points and bistable equilibria can coexist for a wide range of parameters and can switch from one to another. This type of switching is sensitive to the intrinsic growth rate and the initial values of the locust population, and may result in locust population outbreaks and phase switching once a small perturbation occurs. Moreover, the simulation results indicate that the switching transient patterns become identical after some generations, suggesting that the evolving process of the perturbation system is not related to the initial value after some fixed number of generations for the same stochastic processes. However, the switching frequency and outbreak patterns can be significantly affected by the intensity of noise and the intrinsic growth rate of the locust population.

Chromosomal Rearrangements in Salmonella enterica Serotype Typhi Affecting Molecular Typing in Outbreak Investigations

PubMed Central

Echeita, M. A.; Usera, M. A.

1998-01-01

Salmonella enterica serotype Typhi strains belonging to eight different outbreaks of typhoid fever that occurred in Spain between 1989 and 1994 were analyzed by ribotyping and pulsed-field gel electrophoresis. For three outbreaks, two different patterns were detected for each outbreak. The partial digestion analysis by the intron-encoded endonuclease I-CeuI of the two different strains from each outbreak provided an excellent tool for examining the organization of the genomes of epidemiologically related strains. S. enterica serotype Typhi seems to be more susceptible than other serotypes to genetic rearrangements produced by homologous recombinations between rrn operons; these rearrangements do not substantially alter the stability or survival of the bacterium. We conclude that genetic rearrangements can occur during the emergence of an outbreak. PMID:9650981

Pseudo-Outbreak of Actinomyces graevenitzii Associated with Bronchoscopy

PubMed Central

Peaper, David R.; Havill, Nancy L.; Aniskiewicz, Michael; Callan, Deborah; Pop, Olivia; Towle, Dana

2014-01-01

Outbreaks and pseudo-outbreaks of infection related to bronchoscopy typically involve Gram-negative bacteria, Mycobacterium species or Legionella species. We report an unusual bronchoscopy-related pseudo-outbreak due to Actinomyces graevenitzii. Extensive epidemiological and microbiological investigation failed to identify a common source. Strain typing revealed that the cluster was comprised of heterogeneous strains of A. graevenitzii. A change in laboratory procedures for Actinomyces cultures was coincident with the emergence of the pseudo-outbreak, and we determined that A. graevenitzii isolates more readily adopted a white, dry, molar tooth appearance on anaerobic colistin nalidixic acid (CNA) agar which likely facilitated its detection and identification in bronchoscopic specimens. This unusual pseudo-outbreak was related to frequent requests of bronchoscopists for Actinomyces cultures combined with a change in microbiology laboratory practices. PMID:25355767

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

PubMed Central

Barboza, Philippe; Vaillant, Laetitia; Le Strat, Yann; Hartley, David M.; Nelson, Noele P.; Mawudeku, Abla; Madoff, Lawrence C.; Linge, Jens P.; Collier, Nigel; Brownstein, John S.; Astagneau, Pascal

2014-01-01

Background Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se, p = 013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Conclusion Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p = 00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance. PMID:24599062

Factors influencing performance of internet-based biosurveillance systems used in epidemic intelligence for early detection of infectious diseases outbreaks.

PubMed

Barboza, Philippe; Vaillant, Laetitia; Le Strat, Yann; Hartley, David M; Nelson, Noele P; Mawudeku, Abla; Madoff, Lawrence C; Linge, Jens P; Collier, Nigel; Brownstein, John S; Astagneau, Pascal

2014-01-01

Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems' performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p=0001) whereas other indicators were similar (C-DR: p=020; C-Se, p=013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p=00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance.

Evaluation of a national pharmacy‐based syndromic surveillance system

PubMed Central

Muchaal, PK; Parker, S; Meganath, K; Landry, L; Aramini, J

2015-01-01

Background Traditional public health surveillance provides accurate information but is typically not timely. New early warning systems leveraging timely electronic data are emerging, but the public health value of such systems is still largely unknown. Objective To assess the timeliness and accuracy of pharmacy sales data for both respiratory and gastrointestinal infections and to determine its utility in supporting the surveillance of gastrointestinal illness. Methods To assess timeliness, a prospective and retrospective analysis of data feeds was used to compare the chronological characteristics of each data stream. To assess accuracy, Ontario antiviral prescriptions were compared to confirmed cases of influenza and cases of influenza-like-illness (ILI) from August 2009 to January 2015 and Nova Scotia sales of respiratory over-the-counter products (OTC) were compared to laboratory reports of respiratory pathogen detections from January 2014 to March 2015. Enteric outbreak data (2011-2014) from Nova Scotia were compared to sales of gastrointestinal products for the same time period. To assess utility, pharmacy sales of gastrointestinal products were monitored across Canada to detect unusual increases and reports were disseminated to the provinces and territories once a week between December 2014 and March 2015 and then a follow-up evaluation survey of stakeholders was conducted. Results Ontario prescriptions of antivirals between 2009 and 2015 correlated closely with the onset dates and magnitude of confirmed influenza cases. Nova Scotia sales of respiratory OTC products correlated with increases in non-influenza respiratory pathogens in the community. There were no definitive correlations identified between the occurrence of enteric outbreaks and the sales of gastrointestinal OTCs in Nova Scotia. Evaluation of national monitoring showed no significant increases in sales of gastrointestinal products that could be linked to outbreaks that included more than one province or territory. Conclusion Monitoring of pharmacy-based drug prescriptions and OTC sales can provide a timely and accurate complement to traditional respiratory public health surveillance activities but initial evaluation did not show that tracking gastrointestinal-related OTCs were of value in identifying an enteric disease outbreak in more than one province or territory during the study period. PMID:29769953

Control Measures Used during Lymphogranuloma Venereum Outbreak, Europe

PubMed Central

Hulscher, Marlies E.J.L.; Vos, Dieuwke; van de Laar, Marita J.W.; Fenton, Kevin A.; van Steenbergen, Jim E.; van der Meer, Jos W.M.; Grol, Richard P.T.M.

2008-01-01

To assess the response to the reemergence of lymphogranuloma venereum, we conducted a cross-sectional survey by administering a structured questionnaire to representatives from 26 European countries. Responses were received from 18 countries. The ability to respond quickly and the measures used for outbreak detection and control varied. Evidence-based criteria were not consistently used to develop recommendations. We did not develop criteria to determine the effectiveness of the recommendations. The degree of preparedness for an unexpected outbreak, as well as the ability of countries to respond quickly to alerts, varied, which indicates weaknesses in the ability to control an outbreak. More guidance is needed to implement and evaluate control measures used during international outbreaks. PMID:18394274

Yellow Fever outbreak in Darfur, Sudan in October 2012; the initial outbreak investigation report.

PubMed

Soghaier, Mohammed A; Hagar, Ahmed; Abbas, Mohammed A; Elmangory, Mutasim M; Eltahir, Khalid M; Sall, Amadou A

2013-10-01

Sudan is subject to repeated outbreaks, including Viral Hemorrhagic Fever (VHF), which is considered to be a very serious illness. Yellow Fever (YF) outbreaks in Sudan have been reported from the 1940s through 2005. In 2012, a new outbreak of YF occurred in the Darfur region. To identify the potential for an outbreak, to diagnose the disease and to be able to recognize its cause among the initial reported cases. >This is a descriptive and investigative field study that applies standard communicable disease outbreak investigation steps. The study involved clinical, serological, entomological and environmental surveys. The field investigation confirmed the outbreak and identified its cause to be YF. National surveillance systems should be strong enough to detect VHFs in a timely manner. Local health facilities should be prepared to promptly treat the initial cases because the case fatality ratios (CFRs) are usually very high among the index cases. Copyright © 2013 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Two outbreaks of classical swine fever in wild boar in France.

PubMed

Pol, F; Rossi, S; Mesplède, A; Kuntz-Simon, G; Le Potier, M-F

2008-06-21

In 2002 and 2003, two successive outbreaks of classical swine fever were declared in wild boar in northern France. The first was in Moselle, near the town of Thionville and the border with Luxembourg, and the second was in the northern Vosges area, near the German border. The outbreaks were investigated by serological and virological diagnosis of dead or shot animals. Hunting restrictions were applied to limit the spread of the outbreaks. The virus was detected eight times between April and July 2002 in the Thionville area, an area well delimited by natural or artificial barriers such as rivers or highways. Cooperation between the authorities concerned was good, and hunting restrictions were applied for one year. No virus was detected after July 2002 and the Thionville outbreak was officially considered over in March 2005. In the northern Vosges the situation was different, with no barriers to animal movements, continuous forest, difficulties in establishing hunting restrictions in this huge area, and the circulation of the virus in Germany close to the frontier. Virus of a different strain from that isolated in the Thionville outbreak was still being isolated in the northern Vosges in 2004, and owing to the failure of the hunting restrictions, the French health authorities decided to vaccinate wild boar.

An outbreak of food poisoning due to egg yolk reaction-negative Staphylococcus aureus.

PubMed

Miwa, N; Kawamura, A; Masuda, T; Akiyama, M

2001-03-20

An outbreak of staphylococcal food poisoning due to an egg yolk (EY) reaction-negative strain occurred in Japan. Twenty-one of 53 dam construction workers who ate boxed lunches prepared at their company cafeteria became ill, and eight required hospital treatment. The outbreak showed a typical incubation time (1.5-4 h with a median time of 2.7 h) and symptoms (vomiting and diarrhea) of staphylococcal food poisoning. Staphylococcus aureus, which produces staphylococcal enterotoxin (SE) A, was isolated from four fecal specimens of eight patients tested. Scrambled egg in the boxed lunches contained 20-40 ng/g of SEA, and 3.0 x 10(9)/g of viable S. aureus cells that produced this toxin. All isolates from patients and the food were EY reaction-negative, coagulase type II, and showed the same restriction fragment length polymorphism (RFLP) pattern. We concluded that the outbreak was caused by scrambled egg contaminated with EY reaction-negative S. aureus. In Japan, outbreaks of staphylococcal food poisoning are mainly caused by EY reaction-positive S. aureus, and EY reaction-negative colonies grown on agar plates containing EY are usually not analyzed further for detection of S. aureus. The present outbreak suggested that EY reaction-negative isolates should be subjected to further analysis to detect the causative agents of staphylococcal food poisoning.

Hospital-acquired listeriosis outbreak caused by contaminated diced celery--Texas, 2010.

PubMed

Gaul, Linda Knudson; Farag, Noha H; Shim, Trudi; Kingsley, Monica A; Silk, Benjamin J; Hyytia-Trees, Eija

2013-01-01

Listeria monocytogenes causes often-fatal infections affecting mainly immunocompromised persons. Sources of hospital-acquired listeriosis outbreaks can be difficult to identify. We investigated a listeriosis outbreak spanning 7 months and involving 5 hospitals. Outbreak-related cases were identified by pulsed-field gel electrophoresis (PFGE) and confirmed by multiple-locus variable-number tandem-repeat analysis (MLVA). We conducted patient interviews, medical records reviews, and hospital food source evaluations. Food and environmental specimens were collected at a hospital (hospital A) where 6 patients had been admitted before listeriosis onset; these specimens were tested by culture, polymerase chain reaction (PCR), and PFGE. We collected and tested food and environmental samples at the implicated processing facility. Ten outbreak-related patients were immunocompromised by ≥1 underlying conditions or treatments; 5 died. All patients had been admitted to or visited an acute-care hospital during their possible incubation periods. The outbreak strain of L. monocytogenes was isolated from chicken salad and its diced celery ingredient at hospital A, and in 19 of >200 swabs of multiple surfaces and in 8 of 11 diced celery products at the processing plant. PCR testing detected Listeria in only 3 of 10 environmental and food samples from which it was isolated by culturing. The facility was closed, products were recalled, and the outbreak ended. Contaminated diced celery caused a baffling, lengthy outbreak of hospital-acquired listeriosis. PCR testing often failed to detect the pathogen, suggesting its reliability should be further evaluated. Listeriosis risk should be considered in fresh produce selections for immunocompromised patients.

Satellite data based method for general survey of forest insect disturbance in British Columbia

NASA Astrophysics Data System (ADS)

Ranson, J.; Montesano, P.

2008-12-01

Regional forest disturbances caused by insects are important to monitor and quantify because of their influence on local ecosystems and the global carbon cycle. Local damage to forest trees disrupts food supplies and shelter for a variety of organisms. Changes in the global carbon budget, its sources and its sinks affect the way the earth functions as a whole, and has an impact on global climate. Furthermore, the ability to detect nascent outbreaks and monitor the spread of regional infestations helps managers mitigate the damage done by catastrophic insect outbreaks. While detection is needed at a fine scale to support local mitigation efforts, detection at a broad regional scale is important for carbon flux modeling on the landscape scale, and needed to direct the local efforts. This paper presents a method for routinely detecting insect damage to coniferous forests using MODIS vegetation indices, thermal anomalies and land cover. The technique is validated using insect outbreak maps and accounts for fire disturbance effects. The range of damage detected may be used to interpret and quantify possible forest damage by insects.

Naturally acquired antibodies against Clostridium perfringens epsilon toxin in goats.

PubMed

Veschi, Josir Laine A; Bruzzone, Octavio A; Losada-Eaton, Daniela M; Dutra, Iveraldo S; Fernandez-Miyakawa, Mariano E

2008-09-15

Clostridium perfringens type D-producing epsilon toxin is a common cause of death in sheep and goats worldwide. Although anti-epsilon toxin serum antibodies have been detected in healthy non-vaccinated sheep, the information regarding naturally acquired antibodies in ruminants is scanty. The objective of the present report was to characterize the development of naturally acquired antibodies against C. perfringens epsilon toxin in goats. The levels of anti-epsilon toxin antibodies in blood serum of goat kids from two different herds were examined continuously for 14 months. Goats were not vaccinated against any clostridial disease and received heterologous colostrums from cows that were not vaccinated against any clostridial disease. During the survey one of these flocks suffered an unexpectedly severe C. perfringens type D enterotoxemia outbreak. The results showed that natural acquired antibodies against C. perfringens epsilon toxin can appear as early as 6 weeks in young goats and increase with the age without evidence of clinical disease. The enterotoxemia outbreak was coincident with a significant increase in the level of anti-epsilon toxin antibodies.

Hepatitis A outbreak on a floating restaurant in Florida, 1986.

PubMed

Lowry, P W; Levine, R; Stroup, D F; Gunn, R A; Wilder, M H; Konigsberg, C

1989-01-01

In April and May 1986, the largest reported foodborne outbreak of hepatitis A in Florida state history occurred among patrons and employees of a floating restaurant. A total of 103 cases (97 patrons and six employees) were identified. The exposure period lasted 31 days (March 20-April 19), making this the most prolonged hepatitis A outbreak to occur in a restaurant that to date has been reported to the Centers for Disease Control. The exposure period was divided into time intervals (peak, early, late, and total) for calculation of food-specific attack rates. The authors showed that green salad was an important vehicle of transmission for each phase of the exposure period, with the highest adjusted odds ratio for the three-day peak exposure interval (March 28-30), 6.8 (p = 0.001). Non-salad pantry items and mixed bar drinks were also identified as vehicles of transmission; both were more important during the early interval of the exposure period than during the late interval. Two of six infected employees worked in the pantry and may have sequentially infected patrons. Though rare, this outbreak suggests that hepatitis A infection among employees may allow for transmission to patrons for prolonged periods of time. Prevention of such outbreaks requires prompt reporting of ill patrons with rapid identification of infected employees and correction of food handling practices.

Avian Influenza.

PubMed

Zeitlin, Gary Adam; Maslow, Melanie Jane

2005-05-01

The current epidemic of H5N1 highly pathogenic avian influenza in Southeast Asia raises serious concerns that genetic reassortment will result in the next influenza pandemic. There have been 164 confirmed cases of human infection with avian influenza since 1996. In 2004, there were 45 cases of human H5N1 in Vietnam and Thailand, with a mortality rate more than 70%. In addition to the potential public health hazard, the current zoonotic epidemic has caused severe economic losses. Efforts must be concentrated on early detection of bird outbreaks with aggressive culling, quarantining, and disinfection. To prepare for and prevent an increase in human cases, it is essential to improve detection methods and stockpile effective antivirals. Novel therapeutic modalities, including short-interfering RNAs and new vaccine strategies that use plasmid-based genetic systems, offer promise should a pandemic occur.

The challenges of detecting and responding to a Lassa fever outbreak in an Ebola-affected setting.

PubMed

Hamblion, E L; Raftery, P; Wendland, A; Dweh, E; Williams, G S; George, R N C; Soro, L; Katawera, V; Clement, P; Gasasira, A N; Musa, E; Nagbe, T K

2018-01-01

Lassa fever (LF), a priority emerging pathogen likely to cause major epidemics, is endemic in much of West Africa and is difficult to distinguish from other viral hemorrhagic fevers, including Ebola virus disease (EVD). Definitive diagnosis requires laboratory confirmation, which is not widely available in affected settings. The public health action to contain a LF outbreak and the challenges encountered in an EVD-affected setting are reported herein. In February 2016, a rapid response team was deployed in Liberia in response to a cluster of LF cases. Active case finding, case investigation, contact tracing, laboratory testing, environmental investigation, risk communication, and community awareness raising were undertaken. From January to June 2016, 53 suspected LF cases were reported through the Integrated Disease Surveillance and Response system (IDSR). Fourteen cases (26%) were confirmed for LF, 14 (26%) did not have a sample tested, and 25 (47%) were classified as not a case following laboratory analysis. The case fatality rate in the confirmed cases was 29%. One case of international exportation was reported from Sweden. Difficulties were identified in timely specimen collection, packaging, and transportation (in confirmed cases, the time from sample collection to sample result ranged from 2 to 64 days) and a lack of response interventions for early cases. The delay in response to this outbreak could have been related to a number of challenges in this EVD-affected setting: a need to strengthen the IDSR system, develop preparedness plans, train rapid response teams, and build laboratory capacity. Prioritizing these actions will aid in the timely response to future outbreaks. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

New Influenza A/H1N1 (“Swine Flu”): information needs of airport passengers and staff

PubMed Central

Dickmann, P.; Rubin, G. J.; Gaber, W.; Wessely, S.; Wicker, S.; Serve, H.; Gottschalk, R.

2010-01-01

Please cite this paper as: Dickmann et al. (2010) New Influenza A/H1N1 (“Swine Flu”): information needs of airport passengers and staff. . Influenza and Other Respiratory Viruses 5(1), 39–46. Background  Airports are the entrances of infectious diseases. Particularly at the beginning of an outbreak, information and communication play an important role to enable the early detection of signs or symptoms and to encourage passengers to adopt appropriate preventive behaviour to limit the spread of the disease. Objectives  To determine the adequacy of the information provided to airport passengers and staff in meeting their information needs in relation to their concerns. Methods  At the start of the influenza A/H1N1 epidemic (29–30 April 2009), qualitative semi‐structured interviews (N = 101) were conducted at Frankfurt International Airport with passengers who were either returning from or going to Mexico and with airport staff who had close contact with these passengers. Interviews focused on knowledge about swine flu, information needs and fear or concern about the outbreak. Results  The results showed that a desire for more information was associated with higher concern – the least concerned participants did not want any additional information, while the most concerned participants reported a range of information needs. Airport staff in contact with passengers travelling from the epicentre of the outbreak showed the highest levels of fear or concern, coupled with a desire to be adequately briefed by their employer. Conclusions  Our results suggest that information strategies should address not only the exposed or potentially exposed but also groups that feel at risk. Identifying what information these different passenger and staff groups wish to receive will be an important task in any future infectious disease outbreak. PMID:21138539