Early warning system for Douglas-fir tussock moth outbreaks in the Western United States.

Treesearch

Gary E. Daterman; John M. Wenz; Katharine A. Sheehan

2004-01-01

The Early Warning System is a pheromone-based trapping system used to detect outbreaks of Douglas-fir tussock moth (DFTM, Orgyia pseudotsugata) in the western United States. Millions of acres are susceptible to DFTM defoliation, but Early Warning System monitoring focuses attention only on the relatively limited areas where outbreaks may be...

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

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

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

Outbreak detection and evaluation of a school-based influenza-like-illness syndromic surveillance in Tianjin, China.

PubMed

Xu, Wenti; Chen, Tianmu; Dong, Xiaochun; Kong, Mei; Lv, Xiuzhi; Li, Lin

2017-01-01

School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median Runc of 4.62. The interventions in each outbreak had high effectiveness and all Rcon were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.

Detection of Pediatric Respiratory and Diarrheal Outbreaks from Sales of Over-the-counter Electrolyte Products

PubMed Central

Hogan, William R.; Tsui, Fu-Chiang; Ivanov, Oleg; Gesteland, Per H.; Grannis, Shaun; Overhage, J. Marc; Robinson, J. Michael; Wagner, Michael M.

2003-01-01

Objective: To determine whether sales of electrolyte products contain a signal of outbreaks of respiratory and diarrheal disease in children and, if so, how much earlier a signal relative to hospital diagnoses. Design: Retrospective analysis was conducted of sales of electrolyte products and hospital diagnoses for six urban regions in three states for the period 1998 through 2001. Measurements: Presence of signal was ascertained by measuring correlation between electrolyte sales and hospital diagnoses and the temporal relationship that maximized correlation. Earliness was the difference between the date that the exponentially weighted moving average (EWMA) method first detected an outbreak from sales and the date it first detected the outbreak from diagnoses. The coefficient of determination (r2) measured how much variance in earliness resulted from differences in sales' and diagnoses' signal strengths. Results: The correlation between electrolyte sales and hospital diagnoses was 0.90 (95% CI, 0.87–0.93) at a time offset of 1.7 weeks (95% CI, 0.50–2.9), meaning that sales preceded diagnoses by 1.7 weeks. EWMA with a nine-sigma threshold detected the 18 outbreaks on average 2.4 weeks (95% CI, 0.1–4.8 weeks) earlier from sales than from diagnoses. Twelve outbreaks were first detected from sales, four were first detected from diagnoses, and two were detected simultaneously. Only 26% of variance in earliness was explained by the relative strength of the sales and diagnoses signals (r2 = 0.26). Conclusion: Sales of electrolyte products contain a signal of outbreaks of respiratory and diarrheal diseases in children and usually are an earlier signal than hospital diagnoses. PMID:12925542

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.

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 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.

[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.

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

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

Estimating the effectiveness of early control measures through school absenteeism surveillance in observed outbreaks at rural schools in Hubei, China.

PubMed

Fan, Yunzhou; Yang, Mei; Jiang, Hongbo; Wang, Ying; Yang, Wenwen; Zhang, Zhixia; Yan, Weirong; Diwan, Vinod K; Xu, Biao; Dong, Hengjin; Palm, Lars; Liu, Li; Nie, Shaofa

2014-01-01

School absenteeism is a common data source in syndromic surveillance, which allows for the detection of outbreaks at an early stage. Previous studies focused on its correlation with other data sources. In this study, we evaluated the effectiveness of control measures based on early warning signals from school absenteeism surveillance in rural Chinese schools. A school absenteeism surveillance system was established in all 17 primary schools in 3 adjacent towns in the Chinese region of Hubei. Three outbreaks (varicella, mumps, and influenza-like illness) were detected and controlled successfully from April 1, 2012, to January 15, 2014. An impulse susceptible-exposed-infectious-recovered model was used to fit the epidemics of these three outbreaks. Moreover, it simulated the potential epidemics under interventions resulting from traditional surveillance signals. The effectiveness of the absenteeism-based control measures was evaluated by comparing the simulated datasets. The school absenteeism system generated 52 signals. Three outbreaks were verified through epidemiological investigation. Compared to traditional surveillance, the school absenteeism system generated simultaneous signals for the varicella outbreak, but 3 days in advance for the mumps outbreak and 2-4 days in advance for the influenza-like illness outbreak. The estimated excess protection rates of control measures based on early signals were 0.0%, 19.0-44.1%, and 29.0-37.0% for the three outbreaks, respectively. Although not all outbreak control measures can benefit from early signals through school absenteeism surveillance, the effectiveness of early signal-based interventions is obvious. School absenteeism surveillance plays an important role in reducing outbreak spread.

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.

Estimating the Effectiveness of Early Control Measures through School Absenteeism Surveillance in Observed Outbreaks at Rural Schools in Hubei, China

PubMed Central

Fan, Yunzhou; Yang, Mei; Jiang, Hongbo; Wang, Ying; Yang, Wenwen; Zhang, Zhixia; Yan, Weirong; Diwan, Vinod K.; Xu, Biao; Dong, Hengjin; Palm, Lars; Liu, Li; Nie, Shaofa

2014-01-01

Background School absenteeism is a common data source in syndromic surveillance, which allows for the detection of outbreaks at an early stage. Previous studies focused on its correlation with other data sources. In this study, we evaluated the effectiveness of control measures based on early warning signals from school absenteeism surveillance in rural Chinese schools. Methods A school absenteeism surveillance system was established in all 17 primary schools in 3 adjacent towns in the Chinese region of Hubei. Three outbreaks (varicella, mumps, and influenza-like illness) were detected and controlled successfully from April 1, 2012, to January 15, 2014. An impulse susceptible-exposed-infectious-recovered model was used to fit the epidemics of these three outbreaks. Moreover, it simulated the potential epidemics under interventions resulting from traditional surveillance signals. The effectiveness of the absenteeism-based control measures was evaluated by comparing the simulated datasets. Results The school absenteeism system generated 52 signals. Three outbreaks were verified through epidemiological investigation. Compared to traditional surveillance, the school absenteeism system generated simultaneous signals for the varicella outbreak, but 3 days in advance for the mumps outbreak and 2–4 days in advance for the influenza-like illness outbreak. The estimated excess protection rates of control measures based on early signals were 0.0%, 19.0–44.1%, and 29.0–37.0% for the three outbreaks, respectively. Conclusions Although not all outbreak control measures can benefit from early signals through school absenteeism surveillance, the effectiveness of early signal-based interventions is obvious. School absenteeism surveillance plays an important role in reducing outbreak spread. PMID:25250786

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.

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

[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.

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.

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.

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.

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

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

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

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

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

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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

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.

[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.

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.

Early outbreaks of 'epidemic neuromyasthenia'.

PubMed

Parish, J G

1978-11-01

The literature of the outbreaks of 'epidemic neuromyasthenia' (ENM) from 1934 to 1955 has been selected to show that the disease affects other people besides young adult females in hospitals and nursing homes. There have been district epidemics, in which the male: female ratio was almost even and several male outbreaks affecting soldiers in barracks. Some outbreaks appear to have been triggered off by an epidemic of poliomyelitis, and the epidemiology of outbreaks in Iceland in 1948 and 1955 suggests that the normal cytopathological effects of poliomyelitis infection have been suppressed by the new disease. In the Durban epidemic (1955) a toxic metabolite was discovered in the urine of many patients and a markedly increased urinary excretion of creatine was noted in two New York State outbreaks. The results of the transmission of an agent from patients with ENM to monkeys suggest that the neurological disorder might be in the form of mild disseminated lesions scattered throughout the nervous system from the brain to peripheral nerves and associated with perivascular round cell infiltration without significant cellular damage. ENM infection was widespread in the North of England in 1955 and associated with lymphocyte abnormalities, which have persisted in some cases for several years. This suggests a continuous organic process.

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.

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 ...

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.

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.

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.

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.

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

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

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

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.

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.

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.

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

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.

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

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

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.

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.

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...

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.

Bio-ALIRT biosurveillance detection algorithm evaluation.

PubMed

Siegrist, David; Pavlin, J

2004-09-24

Early detection of disease outbreaks by a medical biosurveillance system relies on two major components: 1) the contribution of early and reliable data sources and 2) the sensitivity, specificity, and timeliness of biosurveillance detection algorithms. This paper describes an effort to assess leading detection algorithms by arranging a common challenge problem and providing a common data set. The objectives of this study were to determine whether automated detection algorithms can reliably and quickly identify the onset of natural disease outbreaks that are surrogates for possible terrorist pathogen releases, and do so at acceptable false-alert rates (e.g., once every 2-6 weeks). Historic de-identified data were obtained from five metropolitan areas over 23 months; these data included International Classification of Diseases, Ninth Revision (ICD-9) codes related to respiratory and gastrointestinal illness syndromes. An outbreak detection group identified and labeled two natural disease outbreaks in these data and provided them to analysts for training of detection algorithms. All outbreaks in the remaining test data were identified but not revealed to the detection groups until after their analyses. The algorithms established a probability of outbreak for each day's counts. The probability of outbreak was assessed as an "actual" alert for different false-alert rates. The best algorithms were able to detect all of the outbreaks at false-alert rates of one every 2-6 weeks. They were often able to detect for the same day human investigators had identified as the true start of the outbreak. Because minimal data exists for an actual biologic attack, determining how quickly an algorithm might detect such an attack is difficult. However, application of these algorithms in combination with other data-analysis methods to historic outbreak data indicates that biosurveillance techniques for analyzing syndrome counts can rapidly detect seasonal respiratory and gastrointestinal

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

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.

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

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.

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.

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

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.

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.

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

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.

Toward unsupervised outbreak detection through visual perception of new patterns

PubMed Central

Lévy, Pierre P; Valleron, Alain-Jacques

2009-01-01

Background Statistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available. This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases. Methods The method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2nd version (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest. Results The method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED). Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data. Conclusion Using human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls

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.

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

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

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

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.

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.

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.

Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, USA, 2014-2015.

PubMed

Greene, Sharon K; Peterson, Eric R; Kapell, Deborah; Fine, Annie D; Kulldorff, Martin

2016-10-01

Each day, the New York City Department of Health and Mental Hygiene uses the free SaTScan software to apply prospective space-time permutation scan statistics to strengthen early outbreak detection for 35 reportable diseases. This method prompted early detection of outbreaks of community-acquired legionellosis and shigellosis.

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.

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.

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.

Detecting European Rabbit ( Oryctolagus cuniculus) Disease Outbreaks by Monitoring Digital Media.

PubMed

Peacock, David E; Grillo, Tiggy L

2018-04-18

  Digital media and digital search tools offer simple and effective means to monitor for pathogens and disease outbreaks in target organisms. Using tools such as Rich Site Summary feeds, and Google News and Google Scholar specific key word searches, international digital media were actively monitored from 2012 to 2016 for pathogens and disease outbreaks in the taxonomic order Lagomorpha, with a specific focus on the European rabbit ( Oryctolagus cuniculus). The primary objective was identifying pathogens for assessment as potential new biocontrol agents for Australia's pest populations of the European rabbit. A number of pathogens were detected in digital media reports. Additional benefits arose in the regular provision of case reports and research on myxomatosis and rabbit haemorrhagic disease virus that assisted with current research.

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 detected in samples from two patients, and in berries. Both shared identical partial capsid sequences. Based on the results of epidemiological, trace-back and laboratory investigations it was concluded that one particular batch of frozen raspberries was the source of all outbreaks.

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.

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.

[The application of the prospective space-time statistic in early warning of infectious disease].

PubMed

Yin, Fei; Li, Xiao-Song; Feng, Zi-Jian; Ma, Jia-Qi

2007-06-01

To investigate the application of prospective space-time scan statistic in the early stage of detecting infectious disease outbreaks. The prospective space-time scan statistic was tested by mimicking daily prospective analyses of bacillary dysentery data of Chengdu city in 2005 (3212 cases in 102 towns and villages). And the results were compared with that of purely temporal scan statistic. The prospective space-time scan statistic could give specific messages both in spatial and temporal. The results of June indicated that the prospective space-time scan statistic could timely detect the outbreaks that started from the local site, and the early warning message was powerful (P = 0.007). When the merely temporal scan statistic for detecting the outbreak was sent two days later, and the signal was less powerful (P = 0.039). The prospective space-time scan statistic could make full use of the spatial and temporal information in infectious disease data and could timely and effectively detect the outbreaks that start from the local sites. The prospective space-time scan statistic could be an important tool for local and national CDC to set up early detection surveillance systems.

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

Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data

PubMed Central

Nikolay, Birgit; Salje, Henrik; Sturm-Ramirez, Katharine; Azziz-Baumgartner, Eduardo; Homaira, Nusrat; Iuliano, A. Danielle; Paul, Repon C.; Hossain, M. Jahangir; Cauchemez, Simon; Gurley, Emily S.

2017-01-01

Background The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. Methods and Findings We propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals. We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented. Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and

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

Early-warning signals for an outbreak of the influenza pandemic

NASA Astrophysics Data System (ADS)

Ren, Di; Gao, Jie

2011-12-01

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CGR walk sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.

Algorithms for detecting and predicting influenza outbreaks: metanarrative review of prospective evaluations

PubMed Central

Spreco, A; Timpka, T

2016-01-01

Objectives Reliable monitoring of influenza seasons and pandemic outbreaks is essential for response planning, but compilations of reports on detection and prediction algorithm performance in influenza control practice are largely missing. The aim of this study is to perform a metanarrative review of prospective evaluations of influenza outbreak detection and prediction algorithms restricted settings where authentic surveillance data have been used. Design The study was performed as a metanarrative review. An electronic literature search was performed, papers selected and qualitative and semiquantitative content analyses were conducted. For data extraction and interpretations, researcher triangulation was used for quality assurance. Results Eight prospective evaluations were found that used authentic surveillance data: three studies evaluating detection and five studies evaluating prediction. The methodological perspectives and experiences from the evaluations were found to have been reported in narrative formats representing biodefence informatics and health policy research, respectively. The biodefence informatics narrative having an emphasis on verification of technically and mathematically sound algorithms constituted a large part of the reporting. Four evaluations were reported as health policy research narratives, thus formulated in a manner that allows the results to qualify as policy evidence. Conclusions Awareness of the narrative format in which results are reported is essential when interpreting algorithm evaluations from an infectious disease control practice perspective. PMID:27154479

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China.

PubMed

Liu, Tao; Zhu, Guanghu; He, Jianfeng; Song, Tie; Zhang, Meng; Lin, Hualiang; Xiao, Jianpeng; Zeng, Weilin; Li, Xing; Li, Zhihao; Xie, Runsheng; Zhong, Haojie; Wu, Xiaocheng; Hu, Wenbiao; Zhang, Yonghui; Ma, Wenjun

2017-08-02

Dengue fever is a severe public heath challenge in south China. A dengue outbreak was reported in Chaozhou city, China in 2015. Intensified interventions were implemented by the government to control the epidemic. However, it is still unknown the degree to which intensified control measures reduced the size of the epidemics, and when should such measures be initiated to reduce the risk of large dengue outbreaks developing? We selected Xiangqiao district as study setting because the majority of the indigenous cases (90.6%) in Chaozhou city were from this district. The numbers of daily indigenous dengue cases in 2015 were collected through the national infectious diseases and vectors surveillance system, and daily Breteau Index (BI) data were reported by local public health department. We used a compartmental dynamic SEIR (Susceptible, Exposed, Infected and Removed) model to assess the effectiveness of control interventions, and evaluate the control effect of intervention timing on dengue epidemic. A total of 1250 indigenous dengue cases was reported from Xiangqiao district. The results of SEIR modeling using BI as an indicator of actual control interventions showed a total of 1255 dengue cases, which is close to the reported number (n = 1250). The size and duration of the outbreak were highly sensitive to the intensity and timing of interventions. The more rigorous and earlier the control interventions implemented, the more effective it yielded. Even if the interventions were initiated several weeks after the onset of the dengue outbreak, the interventions were shown to greatly impact the prevalence and duration of dengue outbreak. This study suggests that early implementation of rigorous dengue interventions can effectively reduce the epidemic size and shorten the epidemic duration.

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.

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

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.

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

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

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.

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.

[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.

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.

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

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.

Detection of disease outbreaks by the use of oral manifestations.

PubMed

Torres-Urquidy, M H; Wallstrom, G; Schleyer, T K L

2009-01-01

Oral manifestations of diseases caused by bioterrorist agents could be a potential data source for biosurveillance. This study had the objectives of determining the oral manifestations of diseases caused by bioterrorist agents, measuring the prevalence of these manifestations in emergency department reports, and constructing and evaluating a detection algorithm based on them. We developed a software application to detect oral manifestations in free text and identified positive reports over three years of data. The normal frequency in reports for oral manifestations related to anthrax (including buccal ulcers-sore throat) was 7.46%. The frequency for tularemia was 6.91%. For botulism and smallpox, the frequencies were 0.55% and 0.23%. We simulated outbreaks for these bioterrorism diseases and evaluated the performance of our system. The detection algorithm performed better for smallpox and botulism than for anthrax and tularemia. We found that oral manifestations can be a valuable tool for biosurveillance.

Detecting Disease Outbreaks in Mass Gatherings Using Internet Data

PubMed Central

Yom-Tov, Elad; Cox, Ingemar J; McKendry, Rachel A

2014-01-01

Background Mass gatherings, such as music festivals and religious events, pose a health care challenge because of the risk of transmission of communicable diseases. This is exacerbated by the fact that participants disperse soon after the gathering, potentially spreading disease within their communities. The dispersion of participants also poses a challenge for traditional surveillance methods. The ubiquitous use of the Internet may enable the detection of disease outbreaks through analysis of data generated by users during events and shortly thereafter. Objective The intent of the study was to develop algorithms that can alert to possible outbreaks of communicable diseases from Internet data, specifically Twitter and search engine queries. Methods We extracted all Twitter postings and queries made to the Bing search engine by users who repeatedly mentioned one of nine major music festivals held in the United Kingdom and one religious event (the Hajj in Mecca) during 2012, for a period of 30 days and after each festival. We analyzed these data using three methods, two of which compared words associated with disease symptoms before and after the time of the festival, and one that compared the frequency of these words with those of other users in the United Kingdom in the days following the festivals. Results The data comprised, on average, 7.5 million tweets made by 12,163 users, and 32,143 queries made by 1756 users from each festival. Our methods indicated the statistically significant appearance of a disease symptom in two of the nine festivals. For example, cough was detected at higher than expected levels following the Wakestock festival. Statistically significant agreement (chi-square test, P<.01) between methods and across data sources was found where a statistically significant symptom was detected. Anecdotal evidence suggests that symptoms detected are indeed indicative of a disease that some users attributed to being at the festival. Conclusions Our work

Detecting disease outbreaks in mass gatherings using Internet data.

PubMed

Yom-Tov, Elad; Borsa, Diana; Cox, Ingemar J; McKendry, Rachel A

2014-06-18

Mass gatherings, such as music festivals and religious events, pose a health care challenge because of the risk of transmission of communicable diseases. This is exacerbated by the fact that participants disperse soon after the gathering, potentially spreading disease within their communities. The dispersion of participants also poses a challenge for traditional surveillance methods. The ubiquitous use of the Internet may enable the detection of disease outbreaks through analysis of data generated by users during events and shortly thereafter. The intent of the study was to develop algorithms that can alert to possible outbreaks of communicable diseases from Internet data, specifically Twitter and search engine queries. We extracted all Twitter postings and queries made to the Bing search engine by users who repeatedly mentioned one of nine major music festivals held in the United Kingdom and one religious event (the Hajj in Mecca) during 2012, for a period of 30 days and after each festival. We analyzed these data using three methods, two of which compared words associated with disease symptoms before and after the time of the festival, and one that compared the frequency of these words with those of other users in the United Kingdom in the days following the festivals. The data comprised, on average, 7.5 million tweets made by 12,163 users, and 32,143 queries made by 1756 users from each festival. Our methods indicated the statistically significant appearance of a disease symptom in two of the nine festivals. For example, cough was detected at higher than expected levels following the Wakestock festival. Statistically significant agreement (chi-square test, P<.01) between methods and across data sources was found where a statistically significant symptom was detected. Anecdotal evidence suggests that symptoms detected are indeed indicative of a disease that some users attributed to being at the festival. Our work shows the feasibility of creating a public health

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.

Accounting for seasonal patterns in syndromic surveillance data for outbreak detection.

PubMed

Burr, Tom; Graves, Todd; Klamann, Richard; Michalak, Sarah; Picard, Richard; Hengartner, Nicolas

2006-12-04

Syndromic surveillance (SS) can potentially contribute to outbreak detection capability by providing timely, novel data sources. One SS challenge is that some syndrome counts vary with season in a manner that is not identical from year to year. Our goal is to evaluate the impact of inconsistent seasonal effects on performance assessments (false and true positive rates) in the context of detecting anomalous counts in data that exhibit seasonal variation. To evaluate the impact of inconsistent seasonal effects, we injected synthetic outbreaks into real data and into data simulated from each of two models fit to the same real data. Using real respiratory syndrome counts collected in an emergency department from 2/1/94-5/31/03, we varied the length of training data from one to eight years, applied a sequential test to the forecast errors arising from each of eight forecasting methods, and evaluated their detection probabilities (DP) on the basis of 1000 injected synthetic outbreaks. We did the same for each of two corresponding simulated data sets. The less realistic, nonhierarchical model's simulated data set assumed that "one season fits all," meaning that each year's seasonal peak has the same onset, duration, and magnitude. The more realistic simulated data set used a hierarchical model to capture violation of the "one season fits all" assumption. This experiment demonstrated optimistic bias in DP estimates for some of the methods when data simulated from the nonhierarchical model was used for DP estimation, thus suggesting that at least for some real data sets and methods, it is not adequate to assume that "one season fits all." For the data we analyze, the "one season fits all " assumption is violated, and DP performance claims based on simulated data that assume "one season fits all," for the forecast methods considered, except for moving average methods, tend to be optimistic. Moving average methods based on relatively short amounts of training data are

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.

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

[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.

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

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

Building test data from real outbreaks for evaluating detection algorithms.

PubMed

Texier, Gaetan; Jackson, Michael L; Siwe, Leonel; Meynard, Jean-Baptiste; Deparis, Xavier; Chaudet, Herve

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method-ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals.

Building test data from real outbreaks for evaluating detection algorithms

PubMed Central

Texier, Gaetan; Jackson, Michael L.; Siwe, Leonel; Meynard, Jean-Baptiste; Deparis, Xavier; Chaudet, Herve

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method—ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals. PMID

'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.

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

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.

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.

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

networks, and scaled up to national and international levels for early detection and control of outbreaks.

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...

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

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.

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

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

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.

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.

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.

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

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.

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.

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

Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection.

PubMed

Galar, Alicia; Kulldorff, Martin; Rudnick, Wallis; O'Brien, Thomas F; Stelling, John

2013-01-01

Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis. 4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms. The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available

Biochemical Phenotypes to Discriminate Microbial Subpopulations and Improve Outbreak Detection

PubMed Central

Galar, Alicia; Kulldorff, Martin; Rudnick, Wallis; O'Brien, Thomas F.; Stelling, John

2013-01-01

Background Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Methodology/Principal Findings Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis. Results: 4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as “nuisance” biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms. Conclusions The statistical approaches explored can improve the

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

Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Chari, Suresh T.; Kelly, Kimberly; Hollingsworth, Michael A.; Thayer, Sarah P.; Ahlquist, David A.; Andersen, Dana K.; Batra, Surinder K.; Brentnall, Teresa A.; Canto, Marcia; Cleeter, Deborah F.; Firpo, Matthew A.; Gambhir, Sanjiv Sam; Go, Vay Liang W.; Hines, O. Joe; Kenner, Barbara J.; Klimstra, David S.; Lerch, Markus M.; Levy, Michael J.; Maitra, Anirban; Mulvihill, Sean J.; Petersen, Gloria M.; Rhim, Andrew D.; Simeone, Diane M.; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I.; Wong, David

2015-01-01

Abstract Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC. PMID:25931254

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.

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

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

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 ...

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

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

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

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.

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

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

Constructing rigorous and broad biosurveillance networks for detecting emerging zoonotic outbreaks

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

Brown, Mac; Moore, Leslie; McMahon, Benjamin

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities ofmore » potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.« less

Constructing Rigorous and Broad Biosurveillance Networks for Detecting Emerging Zoonotic Outbreaks

PubMed Central

Brown, Mac; Moore, Leslie; McMahon, Benjamin; Powell, Dennis; LaBute, Montiago; Hyman, James M.; Rivas, Ariel; Jankowski, Mark; Berendzen, Joel; Loeppky, Jason; Manore, Carrie; Fair, Jeanne

2015-01-01

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities of potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic. PMID:25946164

Constructing rigorous and broad biosurveillance networks for detecting emerging zoonotic outbreaks

DOE PAGES

Brown, Mac; Moore, Leslie; McMahon, Benjamin; ...

2015-05-06

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities ofmore » potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.« less

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.

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

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.

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.

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.

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

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

PubMed Central

Cheng, Karen Elizabeth; Crary, David J; Ray, Jaideep; Safta, Cosmin

2013-01-01

Objective We discuss the use of structural models for the analysis of biosurveillance related data. Methods and results Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm. Conclusions Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data. PMID:23037798

Early Detection | Division of Cancer Prevention

Cancer.gov

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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.

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.

Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks

PubMed Central

Thompson, Robin N.; Gilligan, Christopher A.; Cunniffe, Nik J.

2016-01-01

We assess how presymptomatic infection affects predictability of infectious disease epidemics. We focus on whether or not a major outbreak (i.e. an epidemic that will go on to infect a large number of individuals) can be predicted reliably soon after initial cases of disease have appeared within a population. For emerging epidemics, significant time and effort is spent recording symptomatic cases. Scientific attention has often focused on improving statistical methodologies to estimate disease transmission parameters from these data. Here we show that, even if symptomatic cases are recorded perfectly, and disease spread parameters are estimated exactly, it is impossible to estimate the probability of a major outbreak without ambiguity. Our results therefore provide an upper bound on the accuracy of forecasts of major outbreaks that are constructed using data on symptomatic cases alone. Accurate prediction of whether or not an epidemic will occur requires records of symptomatic individuals to be supplemented with data concerning the true infection status of apparently uninfected individuals. To forecast likely future behavior in the earliest stages of an emerging outbreak, it is therefore vital to develop and deploy accurate diagnostic tests that can determine whether asymptomatic individuals are actually uninfected, or instead are infected but just do not yet show detectable symptoms. PMID:27046030

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

Food-Borne Outbreak Investigation and Molecular Typing: High Diversity of Staphylococcus aureus Strains and Importance of Toxin Detection

PubMed Central

Denayer, Sarah; Nia, Yacine; Botteldoorn, Nadine

2017-01-01

Staphylococcus aureus is an important aetiological agent of food intoxications in the European Union as it can cause gastro-enteritis through the production of various staphylococcal enterotoxins (SEs) in foods. Reported enterotoxin dose levels causing food-borne illness are scarce and varying. Three food poisoning outbreaks due to enterotoxin-producing S. aureus strains which occurred in 2013 in Belgium are described. The outbreaks occurred in an elderly home, at a barbecue event and in a kindergarten and involved 28, 18, and six cases, respectively. Various food leftovers contained coagulase positive staphylococci (CPS). Low levels of staphylococcal enterotoxins ranging between 0.015 ng/g and 0.019 ng/g for enterotoxin A (SEA), and corresponding to 0.132 ng/g for SEC were quantified in the food leftovers for two of the reported outbreaks. Molecular typing of human and food isolates using pulsed-field gel electrophoresis (PFGE) and enterotoxin gene typing, confirmed the link between patients and the suspected foodstuffs. This also demonstrated the high diversity of CPS isolates both in the cases and in healthy persons carrying enterotoxin genes encoding emetic SEs for which no detection methods currently exist. For one outbreak, the investigation pointed out to the food handler who transmitted the outbreak strain to the food. Tools to improve staphylococcal food poisoning (SFP) investigations are presented. PMID:29261162

[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.

Outbreak of invasive group A streptococcus: investigations using agar settle plates detect perineal shedding from a healthcare worker.

PubMed

Mahida, N; Prescott, K; Yates, C; Spencer, F; Weston, V; Boswell, T

2018-03-29

Outbreaks of group A streptococcus (GAS) infections may occur in healthcare settings. Transmission to patients is sometimes linked to colonized healthcare workers (HCWs) and/or a contaminated environment. To describe the investigation and control of an outbreak of healthcare-associated GAS on an elderly care medical ward, over six months. Four patients developed septicaemia due to GAS infection without a clinically obvious site of infection. The outbreak team undertook an investigation involving a retrospective review of GAS cases, prospective case finding, HCW screening and environmental sampling using both swabs and settle plates. Immediate control measures included source isolation and additional cleaning of the ward environment with a chlorine disinfectant and hydrogen peroxide. Prospective patient screening identified one additional patient with throat GAS carriage. Settle plate positivity for GAS was strongly associated with the presence of one individual HCW on the ward, who was subsequently found to have GAS perineal carriage. Contamination of a fabric-upholstered chair in an office adjacent to the ward, used by the HCW, was also detected. In total, three asymptomatic HCWs had throat GAS carriage and one HCW had both perineal and throat carriage. All isolates were typed as emm 28. This is the first outbreak report demonstrating the use of settle plates in a GAS outbreak investigation on a medical ward, to identify the likely source of the outbreak. Based on this report we recommend that both throat and perineal sites should be sampled if HCW screening is undertaken during an outbreak of GAS. Fabric, soft furnishings should be excluded from clinical areas as well as any adjacent offices because pathogenic bacteria such as GAS may contaminate this environment. Copyright © 2018 The Healthcare Infection Society. Published by Elsevier Ltd. 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.

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.

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.

Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Kenner, Barbara J.; Chari, Suresh T.; Cleeter, Deborah F.; Go, Vay Liang W.

2015-01-01

Abstract Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer. PMID:25938853

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.

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

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.

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.

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.

Occurrence of infectious laryngotracheitis outbreaks in commercial layer hens detected by ELISA.

PubMed

Aras, Zeki; Yavuz, Orhan; Sanioğlu Gölen, Gökçenur

2018-02-09

Infectious laryngotracheitis (ILT) is an acute respiratory disease of chickens and a cause of great economic loss in commercial layers. The aims of this study were to investigate the prevalence of ILT in the field outbreaks and to compare the characteristics of ILT-infected and free flocks of commercial layers. A total of 625 blood serum samples were collected from 25 different layer flocks. The presence of antibodies against infectious laryngotracheitis virus (ILTV) in each sample was determined by ELISA. Of the 625 serum samples, 266 (42.56%) were found to be positive for ILTV antibodies. A total of 16 (64%) flocks were detected ILT positive by ELISA method. The mortality of infected flocks was statistically higher (P < 0.05) than uninfected flocks. The egg production of positive flocks was lower than that of the free flocks, but this difference was not statistically significant. The average live weight of hens in infected flocks was lower (P > 0.05) than hens in free flocks. In conclusion, the results of this study indicated a high prevalence of ILT infection in the commercial layer flocks in Konya region, Turkey. In outbreaks, ILT significantly increased the mortality rate and decreased the average live weight in layer hens.

Electronic network for monitoring travellers' diarrhoea and detection of an outbreak caused by Salmonella enteritidis among overseas travellers.

PubMed

Osaka, K; Inouye, S; Okabe, N; Taniguchi, K; Izumiya, H; Watanabe, H; Matsumoto, Y; Yokota, T; Hashimoto, S; Sagara, H

1999-12-01

The Traveller's Diarrhoea Network, by which the Infectious Disease Surveillance Center is electronically connected with two major airport quarantine stations and three infectious disease hospitals, was launched in February 1988 in Japan. The data on travellers' diarrhoea detected is reported weekly by e-mail. Two clusters of infection among travellers returning from Italy were reported by two airport quarantine stations at the end of September 1998. A total of 12 salmonella isolates from 2 clusters were examined. All were identified as Salmonella enteritidis, phage type 4 and showed identical banding patterns on pulsed-field gel electrophoresis. A case-control study showed that the scrambled eggs served at the hotel restaurant in Rome were the likely source of this outbreak. This outbreak could not have been detected promptly and investigated easily without the e-mail network. International exchange of data on travellers' diarrhoea is important for preventing and controlling food-borne illnesses infected abroad.

Life expectancy and the value of early detection.

PubMed

Howard, David H

2005-09-01

This paper presents a model of the benefits and costs of early detection of asymptomatic disease as they vary by age. The benefits of early detection tend toward zero as the risk of death from competing causes increases. Costs per detected case also decline with age, assuming that disease incidence rises with age, but are always strictly positive. On balance, there is always an age limit beyond which the costs associated with early detection outweigh the benefits. Application of the model to prostate cancer screening suggests that early detection above age 70 or so is not cost-effective.

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

Early detection: the impact of genomics.

PubMed

van Lanschot, M C J; Bosch, L J W; de Wit, M; Carvalho, B; Meijer, G A

2017-08-01

The field of genomics has shifted our view on disease development by providing insights in the molecular and functional processes encoded in the genome. In the case of cancer, many alterations in the DNA accumulate that enable tumor growth or even metastatic dissemination. Identification of molecular signatures that define different stages of progression towards cancer can enable early tumor detection. In this review, the impact of genomics will be addressed using early detection of colorectal cancer (CRC) as an example. Increased understanding of the adenoma-to-carcinoma progression has led to the discovery of several diagnostic biomarkers. This combined with technical advancements, has facilitated the development of molecular tests for non-invasive early CRC detection in stool and blood samples. Even though several tests have already made it to clinical practice, sensitivity and specificity for the detection of precancerous lesions still need improvement. Besides the diagnostic qualities, also the accuracy of the intermediate endpoint is an important issue on how the effectiveness of a novel test is perceived. Here, progression biomarkers may provide a more precise measure than the currently used morphologically based features. Similar developments in biomarker use for early detection have taken place in other cancer types.

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.

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.

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.

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.

Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system.

PubMed

Merkord, Christopher L; Liu, Yi; Mihretie, Abere; Gebrehiwot, Teklehaymanot; Awoke, Worku; Bayabil, Estifanos; Henebry, Geoffrey M; Kassa, Gebeyaw T; Lake, Mastewal; Wimberly, Michael C

2017-02-23

Early indication of an emerging malaria epidemic can provide an opportunity for proactive interventions. Challenges to the identification of nascent malaria epidemics include obtaining recent epidemiological surveillance data, spatially and temporally harmonizing this information with timely data on environmental precursors, applying models for early detection and early warning, and communicating results to public health officials. Automated web-based informatics systems can provide a solution to these problems, but their implementation in real-world settings has been limited. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) computer system was designed and implemented to integrate disease surveillance with environmental monitoring in support of operational malaria forecasting in the Amhara region of Ethiopia. A co-design workshop was held with computer scientists, epidemiological modelers, and public health partners to develop an initial list of system requirements. Subsequent updates to the system were based on feedback obtained from system evaluation workshops and assessments conducted by a steering committee of users in the public health sector. The system integrated epidemiological data uploaded weekly by the Amhara Regional Health Bureau with remotely-sensed environmental data freely available from online archives. Environmental data were acquired and processed automatically by the EASTWeb software program. Additional software was developed to implement a public health interface for data upload and download, harmonize the epidemiological and environmental data into a unified database, automatically update time series forecasting models, and generate formatted reports. Reporting features included district-level control charts and maps summarizing epidemiological indicators of emerging malaria outbreaks, environmental risk factors, and forecasts of future malaria risk. Successful implementation and

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.

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

Alkaline peptone water enrichment with a dipstick test to quickly detect and monitor cholera outbreaks.

PubMed

Bwire, Godfrey; Orach, Christopher Garimoi; Abdallah, Dauda; Debes, Amanda Kay; Kagirita, Atek; Ram, Malathi; Sack, David A

2017-11-21

Detection, confirmation and monitoring of cholera outbreaks in many developing countries including Uganda is a big challenge due to lack of the required resources and the time the test takes. Culture method which takes 24-48 h to get the feedback and requires highly skilled laboratory staff plus other complex resources is the standard test. This study evaluated the new cholera rapid detection method that relies on Crystal VC dipsticks after enrichment with alkaline peptone water (APW) against the culture method for monitoring the progress of cholera outbreaks in rural setting. We conducted the study between March and June 2015. Fresh stool samples and rectal swabs were incubated in 1% APW for 6 h at room temperature before testing with RDT following the manufacturer's instruction. The same stool sample was cultured to isolate V. cholerae in the standard manner. We also reviewed patient registers to epidemiologically describe the cholera epidemic. We tested stool from 102 consenting suspected cholera patients reporting during daytime at Bwera Hospital (n = 69), Kilembe Mines Hospital (n = 4) and Kinyabwama Health Centre (n = 29). Ninety one (91) samples were positive and nine samples were negative according to both methods. One (1) sample was positive only by dipstick and one sample was positive only by culture (sensitivity of 99%, specificity of 90%, Positive Predictive Value of 99% and Negative Predictive Value of 90%). Overall, 146 suspected cholera cases and two deaths, (case fatality rate of 1.36%) were recorded during the study period. Among the cases aged 1-9 years, 63% (50/79) were males while in those aged 20-49 years, 76% (34/45) were females. Our findings showed that the modified dipstick test after enrichment with 1% APW had high level of accuracy in detection of V. cholerae and is quick, affordable alternative cholera outbreak monitoring tool in resource constrained settings. However, culture method should remain for cholera epidemic

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

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.

Rubella outbreak and outbreak management in a school setting, China, 2014.

PubMed

Chang, Caiyun; Ma, Huilai; Liang, Wenjia; Hu, Pei; Mo, Xianghuan; An, Zhijie; Zheng, Huizhen

2017-04-03

An active response to a rubella outbreak may interrupt disease transmission, and outbreak response immunization (ORI) can increase immunity among persons who might otherwise not be protected. On March 17, 2014, a rubella outbreak was reported in a middle school in Guangzhou city, China. We conducted an investigation to assess impact of a policy of exclusion of cases from school and of ORI. Active surveillance was used to find cases of rubella. Investigators interviewed teachers and reviewed the absentee records to determine implementation details of school exclusion. ORI was recommended on 2 occasions during the outbreak, one small-scale and one large-scale. Laboratory confirmation tests included serum IgM and IgG measurements to distinguish between acute infection and immunity. A serological survey in 4 classes was used to determine immunity status and identify symptomatic and asymptomatic cases. From February 17 to May 23, 2014, 162 rubella cases (24 laboratory-confirmed and 138 epidemiologically linked) were detected among 1,621 students. Cases ultimately occurred in 27 classes (72.97%) across 37 classes. In 11 classes in which exclusion from school was delayed by 1 or more days, the secondary attack rate was 12.30%, compared with 2.35% in 15 classes with immediate exclusion. ORI increased vaccine coverage from 25.83 % to 86.92%, and the final case of the epidemic was reported one month later. A serological survey of 91 students in 4 classes identified 15 cases, 6 of which were asymptomatic. The outbreak happened in school with low rubella-containing vaccination coverage. Exclusion from school upon rash/fever onset was associated with lowering the secondary attack rate, but school exclusion alone was not able to stop this outbreak - a large ORI was needed. Assuring complete vaccination upon entry to school is likely to be necessary to ensure coverage is above the herd immunity threshold and prevent outbreaks from happening.

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

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

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.

[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.

Early detection of sporadic pancreatic cancer: summative review.

PubMed

Chari, Suresh T; Kelly, Kimberly; Hollingsworth, Michael A; Thayer, Sarah P; Ahlquist, David A; Andersen, Dana K; Batra, Surinder K; Brentnall, Teresa A; Canto, Marcia; Cleeter, Deborah F; Firpo, Matthew A; Gambhir, Sanjiv Sam; Go, Vay Liang W; Hines, O Joe; Kenner, Barbara J; Klimstra, David S; Lerch, Markus M; Levy, Michael J; Maitra, Anirban; Mulvihill, Sean J; Petersen, Gloria M; Rhim, Andrew D; Simeone, Diane M; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I; Wong, David

2015-07-01

Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC.

Gastrointestinal Cancers: Screening and Early Detection.

PubMed

Griffin-Sobel, Joyce P

2017-05-01

To present an overview of current practices in the screening and early detection of gastrointestinal cancers. Literature reviews. Screening for gastrointestinal cancers is less than desirable, particularly in underserved populations. There are inadequate methods of screening for early detection of esophageal and gastric cancers. Education of patients is needed to reinforce the importance of screening for gastrointestinal cancers. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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

Real-Time Whole-Genome Sequencing for Routine Typing, Surveillance, and Outbreak Detection of Verotoxigenic Escherichia coli

PubMed Central

Scheutz, Flemming; Lund, Ole; Hasman, Henrik; Kaas, Rolf S.; Nielsen, Eva M.; Aarestrup, Frank M.

2014-01-01

Fast and accurate identification and typing of pathogens are essential for effective surveillance and outbreak detection. The current routine procedure is based on a variety of techniques, making the procedure laborious, time-consuming, and expensive. With whole-genome sequencing (WGS) becoming cheaper, it has huge potential in both diagnostics and routine surveillance. The aim of this study was to perform a real-time evaluation of WGS for routine typing and surveillance of verocytotoxin-producing Escherichia coli (VTEC). In Denmark, the Statens Serum Institut (SSI) routinely receives all suspected VTEC isolates. During a 7-week period in the fall of 2012, all incoming isolates were concurrently subjected to WGS using IonTorrent PGM. Real-time bioinformatics analysis was performed using web-tools (www.genomicepidemiology.org) for species determination, multilocus sequence type (MLST) typing, and determination of phylogenetic relationship, and a specific VirulenceFinder for detection of E. coli virulence genes was developed as part of this study. In total, 46 suspected VTEC isolates were characterized in parallel during the study. VirulenceFinder proved successful in detecting virulence genes included in routine typing, explicitly verocytotoxin 1 (vtx1), verocytotoxin 2 (vtx2), and intimin (eae), and also detected additional virulence genes. VirulenceFinder is also a robust method for assigning verocytotoxin (vtx) subtypes. A real-time clustering of isolates in agreement with the epidemiology was established from WGS, enabling discrimination between sporadic and outbreak isolates. Overall, WGS typing produced results faster and at a lower cost than the current routine. Therefore, WGS typing is a superior alternative to conventional typing strategies. This approach may also be applied to typing and surveillance of other pathogens. PMID:24574290

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.

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

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.

[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.

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

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.

Social media in Ebola outbreak.

PubMed

Hossain, L; Kam, D; Kong, F; Wigand, R T; Bossomaier, T

2016-07-01

The West African 2014 Ebola outbreak has highlighted the need for a better information network. Hybrid information networks, an integration of both hierarchical and formalized command control-driven and community-based, or ad hoc emerging networks, could assist in improving public health responses. By filling the missing gaps with social media use, the public health response could be more proactive rather than reactive in responding to such an outbreak of global concern. This article provides a review of the current social media use specifically in this outbreak by systematically collecting data from ProQuest Newsstand, Dow Jones Factiva, Program for Monitoring Emerging Diseases (ProMED) as well as Google Trends. The period studied is from 19 March 2014 (first request for information on ProMED) to 15 October 2014, a total of 31 weeks. The term 'Ebola' was used in the search for media reports. The outcome of the review shows positive results for social media use in effective surveillance response mechanisms - for improving the detection, preparedness and response of the outbreak - as a complement to traditional, filed, work-based surveillance approach.

Pre-outbreak forest conditions mediate the effects of spruce beetle outbreaks on fuels in subalpine forests of Colorado.

PubMed

Mietkiewicz, Nathan; Kulakowski, Dominik; Veblen, Thomas T

2018-03-01

Over the past 30 years, forest disturbances have increased in size, intensity, and frequency globally, and are predicted to continue increasing due to climate change, potentially relaxing the constraints of vegetation properties on disturbance regimes. However, the consequences of the potentially declining importance of vegetation in determining future disturbance regimes are not well understood. Historically, bark beetles preferentially attack older trees and stands in later stages of development. However, as climate warming intensifies outbreaks by promoting growth of beetle populations and compromising tree defenses, smaller diameter trees and stands in early stages of development now are being affected by outbreaks. To date, no study has considered how stand age and other pre-outbreak forest conditions mediate the effects of outbreaks on surface and aerial fuel arrangements. We collected fuels data across a chronosequence of post-outbreak sites affected by spruce beetle (SB) between the 1940s and the 2010s, stratified by young (<130 yr) and old (>130 yr) post-fire stands. Canopy and surface fuel loads were calculated for each tree and stand, and available crown fuel load, crown bulk density, and canopy bulk densities were estimated. Canopy bulk density and density of live canopy individuals were reduced in all stands affected by SB, though foliage loss was proportionally greater in old stands as compared to young stands. Fine surface fuel loads in young stands were three times greater shortly (<30 yr) following outbreak as compared to young stands not affected by outbreak, after which the abundance of fine surface fuels decreased to below endemic (i.e., non-outbreak) levels. In both young and old stands, the net effect of SB outbreaks during the 20th and 21st centuries reduced total canopy fuels and increased stand-scale spatial heterogeneity of canopy fuels following outbreak. Importantly, the decrease in canopy fuels following outbreaks was greater in

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.

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

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

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.

Development of methods to detect "Norwalk-like viruses" (NLVs) and hepatitis A virus in delicatessen foods: application to a food-borne NLV outbreak.

PubMed

Schwab, K J; Neill, F H; Fankhauser, R L; Daniels, N A; Monroe, S S; Bergmire-Sweat, D A; Estes, M K; Atmar, R L

2000-01-01

"Norwalk-like viruses" (NLVs) and hepatitis A virus (HAV) are the most common causes of virus-mediated food-borne illness. Epidemiological investigations of outbreaks associated with these viruses have been hindered by the lack of available methods for the detection of NLVs and HAV in foodstuffs. Although reverse transcription (RT)-PCR methods have been useful in detecting NLVs and HAV in bivalve mollusks implicated in outbreaks, to date such methods have not been available for other foods. To address this need, we developed a method to detect NLVs and HAV recovered from food samples. The method involves washing of food samples with a guanidinium-phenol-based reagent, extraction with chloroform, and precipitation in isopropanol. Recovered viral RNA is amplified with HAV- or NLV-specific primers in RT-PCRs, using a viral RNA internal standard control to identify potential sample inhibition. By this method, 10 to 100 PCR units (estimated to be equivalent to 10(2) to 10(3) viral genome copies) of HAV and Norwalk virus seeded onto ham, turkey, and roast beef were detected. The method was applied to food samples implicated in an NLV-associated outbreak at a university cafeteria. Sliced deli ham was positive for a genogroup II NLV as determined by using both polymerase- and capsid-specific primers and probes. Sequence analysis of the PCR-amplified capsid region of the genome indicated that the sequence was identical to the sequence from virus detected in the stools of ill students. The developed method is rapid, simple, and efficient.

Pseudo-outbreak of Actinomyces graevenitzii associated with bronchoscopy.

PubMed

Peaper, David R; Havill, Nancy L; Aniskiewicz, Michael; Callan, Deborah; Pop, Olivia; Towle, Dana; Boyce, John M

2015-01-01

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. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Detection by PCR of Enteroviruses in Cerebrospinal Fluid during a Summer Outbreak of Aseptic Meningitis in Switzerland

PubMed Central

Gorgievski-Hrisoho, Meri; Schumacher, Jean-Daniel; Vilimonovic, Nevenka; Germann, Daniel; Matter, Lukas

1998-01-01

Enteroviruses (EV) are among the most common causes of aseptic meningitis. Standard diagnostic techniques are often too slow and lack sensitivity to be of clinical relevance. EV RNA can be detected within 5 h by a commercially available reverse transcription-PCR (RT-PCR) test kit. Cerebrospinal fluid (CSF) samples from 68 patients presenting with aseptic meningitis during a summer outbreak in Switzerland were examined in parallel with cell culture and commercial RT-PCR. RT-PCR was positive in all 16 CSF specimens positive by cell culture (100%). In addition, 42 of 52 (80%) CSF samples negative by cell culture were PCR positive. In 26 of these 42 (62%) patients, viral culture from other sites (throat swab or stool) was also positive. The CSF virus culture took 3 to 7 days to become positive. Echovirus 30 was the type most often isolated in this outbreak. The sensitivity of CSF RT-PCR based on clinical diagnosis during this aseptic meningitis outbreak in patients with negative bacterial culture results was 85%, i.e., considerably higher than the sensitivity of CSF virus culture (24%). We conclude that this commercial RT-PCR assay allows a positive diagnosis with minimal delay and may thus influence clinical decisions. PMID:9705364

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.

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

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.

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.

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...

Detection and analysis of recombination in GII.4 norovirus strains causing gastroenteritis outbreaks in Alberta.

PubMed

Hasing, Maria E; Hazes, Bart; Lee, Bonita E; Preiksaitis, Jutta K; Pang, Xiaoli L

2014-10-01

Recombination is an important mechanism generating genetic diversity in norovirus (NoV) that occurs commonly at the NoV polymerase-capsid (ORF1/2) junction. The genotyping method based on partial ORF2 sequences currently used to characterize circulating NoV strains in gastroenteritis outbreaks in Alberta cannot detect such recombination events and provides only limited information on NoV genetic evolution. The objective of this study was to determine whether any NoV GII.4 strains causing outbreaks in Alberta are recombinants. Twenty stool samples collected during outbreaks occurring between July 2004 and January 2012 were selected to include the GII.4 variants Farmington Hills 2002, Hunter 2004, Yerseke 2006a, Den Haag 2006b, Apeldoorn 2007, New Orleans 2009, and Sydney 2012 based on previous NoV ORF2-genotyping results. Near full-length NoV genome sequences were obtained, aligned with reference sequences from GenBank and analyzed with RDPv4.13. Two sequences corresponding to Apeldoorn 2007, and Sydney 2012 were identified as recombinants with breakpoints near the ORF1/2 junction and putative parental strains as previously reported. We also identified, for the first time, a non-recombinant sequence resembling the ORF2-3 parent of the recombinant cluster Sydney 2012 responsible for the most recent pandemic. Our results confirmed the presence of recombinant NoV GII.4 strains in Alberta, and highlight the importance of including additional genomic regions in surveillance studies to trace the evolution of pandemic NoV GII.4 strains. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

Development of Methods To Detect “Norwalk-Like Viruses” (NLVs) and Hepatitis A Virus in Delicatessen Foods: Application to a Food-Borne NLV Outbreak

PubMed Central

Schwab, Kellogg J.; Neill, Frederick H.; Fankhauser, Rebecca L.; Daniels, Nicholas A.; Monroe, Stephan S.; Bergmire-Sweat, David A.; Estes, Mary K.; Atmar, Robert L.

2000-01-01

“Norwalk-like viruses” (NLVs) and hepatitis A virus (HAV) are the most common causes of virus-mediated food-borne illness. Epidemiological investigations of outbreaks associated with these viruses have been hindered by the lack of available methods for the detection of NLVs and HAV in foodstuffs. Although reverse transcription (RT)-PCR methods have been useful in detecting NLVs and HAV in bivalve mollusks implicated in outbreaks, to date such methods have not been available for other foods. To address this need, we developed a method to detect NLVs and HAV recovered from food samples. The method involves washing of food samples with a guanidinium-phenol-based reagent, extraction with chloroform, and precipitation in isopropanol. Recovered viral RNA is amplified with HAV- or NLV-specific primers in RT-PCRs, using a viral RNA internal standard control to identify potential sample inhibition. By this method, 10 to 100 PCR units (estimated to be equivalent to 102 to 103 viral genome copies) of HAV and Norwalk virus seeded onto ham, turkey, and roast beef were detected. The method was applied to food samples implicated in an NLV-associated outbreak at a university cafeteria. Sliced deli ham was positive for a genogroup II NLV as determined by using both polymerase- and capsid-specific primers and probes. Sequence analysis of the PCR-amplified capsid region of the genome indicated that the sequence was identical to the sequence from virus detected in the stools of ill students. The developed method is rapid, simple, and efficient. PMID:10618226

Early Outbreak of 2009 Influenza A (H1N1) in Mexico Prior to Identification of pH1N1 Virus

PubMed Central

Hsieh, Ying-Hen; Ma, Stefan; Velasco Hernandez, Jorge X.; Lee, Vernon J.; Lim, Wei Yen

2011-01-01

Background In the aftermath of the global spread of 2009 influenza A (pH1N1) virus, still very little is known of the early stages of the outbreak in Mexico during the early months of the year, before the virus was identified. Methodology/Main Findings We fit a simple mathematical model, the Richards model, to the number of excess laboratory-confirmed influenza cases in Mexico and Mexico City during the first 15 weeks in 2009 over the average influenza case number of the previous five baseline years of 2004-2008 during the same period to ascertain the turning point (or the peak incidence) of a wave of early influenza infections, and to estimate the transmissibility of the virus during these early months in terms of its basic reproduction number. The results indicate that there may have been an early epidemic in Mexico City as well as in all of Mexico during February/March. Based on excess influenza cases, the estimated basic reproduction number R0 for the early outbreak was 1.59 (0.55 to 2.62) for Mexico City during weeks 5–9, and 1.25 (0.76, 1.74) for all of Mexico during weeks 5–14. Conclusions We established the existence of an early epidemic in Mexico City and in all of Mexico during February/March utilizing the routine influenza surveillance data, although the location of seeding is unknown. Moreover, estimates of R0 as well as the time of peak incidence (the turning point) for Mexico City and all of Mexico indicate that the early epidemic in Mexico City in February/March had been more transmissible (larger R0) and peaked earlier than the rest of the country. Our conclusion lends support to the possibility that the virus could have already spread to other continents prior to the identification of the virus and the reporting of lab-confirmed pH1N1 cases in North America in April. PMID:21909366

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.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Anthrax Outbreaks in Bangladesh, 2009–2010

PubMed Central

Chakraborty, Apurba; Khan, Salah Uddin; Hasnat, Mohammed Abul; Parveen, Shahana; Islam, M. Saiful; Mikolon, Andrea; Chakraborty, Ranjit Kumar; Ahmed, Be-Nazir; Ara, Khorsed; Haider, Najmul; Zaki, Sherif R.; Hoffmaster, Alex R.; Rahman, Mahmudur; Luby, Stephen P.; Hossain, M. Jahangir

2012-01-01

During August 2009–October 2010, a multidisciplinary team investigated 14 outbreaks of animal and human anthrax in Bangladesh to identify the etiology, pathway of transmission, and social, behavioral, and cultural factors that led to these outbreaks. The team identified 140 animal cases of anthrax and 273 human cases of cutaneous anthrax. Ninety one percent of persons in whom cutaneous anthrax developed had history of butchering sick animals, handling raw meat, contact with animal skin, or were present at slaughtering sites. Each year, Bacillus anthracis of identical genotypes were isolated from animal and human cases. Inadequate livestock vaccination coverage, lack of awareness of the risk of anthrax transmission from animal to humans, social norms and poverty contributed to these outbreaks. Addressing these challenges and adopting a joint animal and human health approach could contribute to detecting and preventing such outbreaks in the future. PMID:22492157

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

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.

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

Human angiostrongyliasis outbreak in Dali, China.

PubMed

Lv, Shan; Zhang, Yi; Chen, Shao-Rong; Wang, Li-Bo; Fang, Wen; Chen, Feng; Jiang, Jin-Yong; Li, Yuan-Lin; Du, Zun-Wei; Zhou, Xiao-Nong

2009-09-22

Several angiostrongyliasis outbreaks have been reported in recent years but the disease continues to be neglected in public health circles. We describe an outbreak in Dali, southwest China in order to highlight some key problems for the control of this helminth infection. All available medical records of suspected angiostrongyliasis patients visiting hospitals in Dali in the period 1 October 2007-31 March 2008 were reviewed, and tentative diagnoses of varying strengths were reached according to given sets of criteria. Snails collected from local markets, restaurants and natural habitats were also screened for the presence of Angiostrongylus cantonensis. A total of 33 patients met criteria for infection, and 11 among them were classified as clinically confirmed. An additional eight patients were identified through a surveillance system put in operation in response to the outbreak. The epidemic lasted for 8 months with its peak in February 2008. Of the 33 patients, 97.0% complained of severe headache. 84.8% patients had high eosinophil cell counts either in the peripheral blood or in cerebrospinal fluid (CSF). Three-quarters of the patients were treated with a combination of albendazole and corticosteroids, resulting in significantly improved overall conditions. Twenty-two patients reported the consumption of raw or undercooked snails prior to the onset of the symptoms, and approximately 1.0% of the Pomacea canaliculata snails on sale were found to be infected with A. cantonensis. The snails were also found in certain habitats around Dali but no parasites were detected in these populations. The import and sale of infected P. canaliculata is the likely trigger for this angiostrongyliasis outbreak. Awareness of angiostrongyliasis must be raised, and standardized diagnosis and treatment are needed in order to provide clinicians with a guide to address this disease. Health education campaigns could limit the risk, and a hospital-based surveillance system should be

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.

[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.

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.

Computer-aided diagnosis with potential application to rapid detection of disease outbreaks.

PubMed

Burr, Tom; Koster, Frederick; Picard, Rick; Forslund, Dave; Wokoun, Doug; Joyce, Ed; Brillman, Judith; Froman, Phil; Lee, Jack

2007-04-15

Our objectives are to quickly interpret symptoms of emergency patients to identify likely syndromes and to improve population-wide disease outbreak detection. We constructed a database of 248 syndromes, each syndrome having an estimated probability of producing any of 85 symptoms, with some two-way, three-way, and five-way probabilities reflecting correlations among symptoms. Using these multi-way probabilities in conjunction with an iterative proportional fitting algorithm allows estimation of full conditional probabilities. Combining these conditional probabilities with misdiagnosis error rates and incidence rates via Bayes theorem, the probability of each syndrome is estimated. We tested a prototype of computer-aided differential diagnosis (CADDY) on simulated data and on more than 100 real cases, including West Nile Virus, Q fever, SARS, anthrax, plague, tularaemia and toxic shock cases. We conclude that: (1) it is important to determine whether the unrecorded positive status of a symptom means that the status is negative or that the status is unknown; (2) inclusion of misdiagnosis error rates produces more realistic results; (3) the naive Bayes classifier, which assumes all symptoms behave independently, is slightly outperformed by CADDY, which includes available multi-symptom information on correlations; as more information regarding symptom correlations becomes available, the advantage of CADDY over the naive Bayes classifier should increase; (4) overlooking low-probability, high-consequence events is less likely if the standard output summary is augmented with a list of rare syndromes that are consistent with observed symptoms, and (5) accumulating patient-level probabilities across a larger population can aid in biosurveillance for disease outbreaks. c 2007 John Wiley & Sons, Ltd.

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.

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.

Early detection and intervention for attention-deficit/hyperactivity disorder.

PubMed

Sonuga-Barke, Edmund J S; Koerting, Johanna; Smith, Elizabeth; McCann, Donna C; Thompson, Margaret

2011-04-01

Attention-deficit/hyperactivity disorder (ADHD) is a high-cost/high-burden disorder. Early detection and intervention may prevent or ameliorate the development of the disorder and reduce its long-term impact. In this article, we set out a rationale for an early detection and intervention program. First, we highlight the costs of the condition and second, we discuss the limitations of the current treatments. We then outline the potential value of an early detection and intervention program. We review evidence on predictors of poor outcomes for early ADHD signs and discuss how these might allow us to target early intervention more cost-effectively. We then examine potential barriers to engagement with at-risk samples. This leads to a discussion of possible intervention approaches and how these could be improved. Finally, we describe the Program for Early Detection and Intervention for ADHD (PEDIA), a 5-year program of research supported by the UK National Institute for Health Research and conducted at the University of Southampton (Southampton, UK), which aims to develop and evaluate a strategy for early intervention.

Designing and implementing an electronic dashboard for disease outbreaks response - Case study of the 2013-2014 Somalia Polio outbreak response dashboard

PubMed Central

Kamadjeu, Raoul; Gathenji, Caroline

2017-01-01

In April 2013, a case of wild polio virus (WPV) was detected in the Somalia capital Mogadishu. This inaugurated what is now referred to as the 2013-2014 Horn of Africa Polio outbreak with cases reported in Somalia, Kenya and Ethiopia. By the notification of the last polio case in August 2014, 223 cases of WPV had been reported in Somalia, Kenya and Ethiopia of which 199 in Somalia alone. The outbreak response required timely exchange of information between the outbreak response coordination unit (in Nairobi) and local staff located in multiple locations inside the country. The need to track and timely respond to information requests, to satisfy the information/data needs of polio partners and to track key outbreak response performance indicators dictated the need to urgently set up an online dashboard. The Somalia Polio Room dashboard provided a graphical display of the polio outbreak data to track progress and inform decision making. The system was designed using free and open sources components and seamlessly integrated existing polio surveillance data for real time monitoring of key outbreak response performance indicators. In this article, we describe the design and operation of an electronic dashboard for disease surveillance in an outbreak situation and used the lessons learned to propose key design considerations and functional requirements for online electronic dashboards for disease outbreak response. PMID:29296157

Designing and implementing an electronic dashboard for disease outbreaks response - Case study of the 2013-2014 Somalia Polio outbreak response dashboard.

PubMed

Kamadjeu, Raoul; Gathenji, Caroline

2017-01-01

In April 2013, a case of wild polio virus (WPV) was detected in the Somalia capital Mogadishu. This inaugurated what is now referred to as the 2013-2014 Horn of Africa Polio outbreak with cases reported in Somalia, Kenya and Ethiopia. By the notification of the last polio case in August 2014, 223 cases of WPV had been reported in Somalia, Kenya and Ethiopia of which 199 in Somalia alone. The outbreak response required timely exchange of information between the outbreak response coordination unit (in Nairobi) and local staff located in multiple locations inside the country. The need to track and timely respond to information requests, to satisfy the information/data needs of polio partners and to track key outbreak response performance indicators dictated the need to urgently set up an online dashboard. The Somalia Polio Room dashboard provided a graphical display of the polio outbreak data to track progress and inform decision making. The system was designed using free and open sources components and seamlessly integrated existing polio surveillance data for real time monitoring of key outbreak response performance indicators. In this article, we describe the design and operation of an electronic dashboard for disease surveillance in an outbreak situation and used the lessons learned to propose key design considerations and functional requirements for online electronic dashboards for disease outbreak response.

A Context-sensitive Approach to Anonymizing Spatial Surveillance Data: Impact on Outbreak Detection

PubMed Central

Cassa, Christopher A.; Grannis, Shaun J.; Overhage, J. Marc; Mandl, Kenneth D.

2006-01-01

Objective: The use of spatially based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health data sets by transposing their spatial locations through a process informed by the underlying population density. Further, we measure the impact of the skew on detection of spatial clustering as measured by a spatial scanning statistic. Design: Cases were emergency department (ED) visits for respiratory illness. Baseline ED visit data were injected with artificially created clusters ranging in magnitude, shape, and location. The geocoded locations were then transformed using a de-identification algorithm that accounts for the local underlying population density. Measurements: A total of 12,600 separate weeks of case data with artificially created clusters were combined with control data and the impact on detection of spatial clustering identified by a spatial scan statistic was measured. Results: The anonymization algorithm produced an expected skew of cases that resulted in high values of data set k-anonymity. De-identification that moves points an average distance of 0.25 km lowers the spatial cluster detection sensitivity by less than 4% and lowers the detection specificity less than 1%. Conclusion: A population-density–based Gaussian spatial blurring markedly decreases the ability to identify individuals in a data set while only slightly decreasing the performance of a standardly used outbreak detection tool. These findings suggest new approaches to anonymizing data for spatial epidemiology and surveillance. PMID:16357353

Discovering network behind infectious disease outbreak

NASA Astrophysics Data System (ADS)

Maeno, Yoshiharu

2010-11-01

Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on the SARS outbreak.

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.

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

Detection of a chikungunya outbreak in Central Italy, August to September 2017.

PubMed

Venturi, Giulietta; Di Luca, Marco; Fortuna, Claudia; Remoli, Maria Elena; Riccardo, Flavia; Severini, Francesco; Toma, Luciano; Del Manso, Martina; Benedetti, Eleonora; Caporali, Maria Grazia; Amendola, Antonello; Fiorentini, Cristiano; De Liberato, Claudio; Giammattei, Roberto; Romi, Roberto; Pezzotti, Patrizio; Rezza, Giovanni; Rizzo, Caterina

2017-09-01

An autochthonous chikungunya outbreak is ongoing near Anzio, a coastal town in the province of Rome. The virus isolated from one patient and mosquitoes lacks the A226V mutation and belongs to an East Central South African strain. As of 20 September, 86 cases are laboratory-confirmed. The outbreak proximity to the capital, its late summer occurrence, and diagnostic delays, are favouring transmission. Vector control, enhanced surveillance and restricted blood donations are being implemented in affected areas.

Detection, Isolation, and Molecular Subtyping of Escherichia coli O157:H7 and Campylobacter jejuni Associated with a Large Waterborne Outbreak

PubMed Central

Bopp, Dianna J.; Sauders, Brian D.; Waring, Alfred L.; Ackelsberg, Joel; Dumas, Nellie; Braun-Howland, Ellen; Dziewulski, David; Wallace, Barbara J.; Kelly, Molly; Halse, Tanya; Musser, Kimberlee Aruda; Smith, Perry F.; Morse, Dale L.; Limberger, Ronald J.

2003-01-01

The largest reported outbreak of waterborne Escherichia coli O157:H7 in the United States occurred in upstate New York following a county fair in August 1999. Culture methods were used to isolate E. coli O157:H7 from specimens from 128 of 775 patients with suspected infections. Campylobacter jejuni was also isolated from stools of 44 persons who developed diarrheal illness after attending this fair. There was one case of a confirmed coinfection with E. coli O157:H7 and C. jejuni. Molecular detection of stx1 and stx2 Shiga toxin genes, immunomagnetic separation (IMS), and selective culture enrichment were utilized to detect and isolate E. coli O157:H7 from an unchlorinated well and its distribution points, a dry well, and a nearby septic tank. PCR for stx1 and stx2 was shown to provide a useful screen for toxin-producing E. coli O157:H7, and IMS subculture improved recovery. Pulsed-field gel electrophoresis (PFGE) was used to compare patient and environmental E. coli O157:H7 isolates. Among patient isolates, 117 of 128 (91.5%) were type 1 or 1a (three or fewer bands different). Among the water distribution system isolates, 13 of 19 (68%) were type 1 or 1a. Additionally, PFGE of C. jejuni isolates revealed that 29 of 35 (83%) had indistinguishable PFGE patterns. The PFGE results implicated the water distribution system as the main source of the E. coli O157:H7 outbreak. This investigation demonstrates the potential for outbreaks involving more than one pathogen and the importance of analyzing isolates from multiple patients and environmental samples to develop a better understanding of bacterial transmission during an outbreak. PMID:12517844

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

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

Talathi, S. S.

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizuremore » detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.« less

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

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.

Estimation for aerial detection effectiveness with cooperation efficiency factors of early-warning aircraft in early-warning detection SoS under BSC framework

NASA Astrophysics Data System (ADS)

Zhu, Feng; Hu, Xiaofeng; He, Xiaoyuan; Guo, Rui; Li, Kaiming; Yang, Lu

2017-11-01

In the military field, the performance evaluation of early-warning aircraft deployment or construction is always an important problem needing to be explored. As an effective approach of enterprise management and performance evaluation, Balanced Score Card (BSC) attracts more and more attentions and is studied more and more widely all over the world. It can also bring feasible ideas and technical approaches for studying the issue of the performance evaluation of the deployment or construction of early-warning aircraft which is the important component in early-warning detection system of systems (SoS). Therefore, the deep explored researches are carried out based on the previously research works. On the basis of the characteristics of space exploration and aerial detection effectiveness of early-warning detection SoS and the cardinal principle of BSC are analyzed simply, and the performance evaluation framework of the deployment or construction of early-warning aircraft is given, under this framework, aimed at the evaluation issue of aerial detection effectiveness of early-warning detection SoS with the cooperation efficiency factors of the early-warning aircraft and other land based radars, the evaluation indexes are further designed and the relative evaluation model is further established, especially the evaluation radar chart being also drawn to obtain the evaluation results from a direct sight angle. Finally, some practical computer simulations are launched to prove the validity and feasibility of the research thinking and technologic approaches which are proposed in the paper.

About the Early Detection Research Group | Division of Cancer Prevention

Cancer.gov

The Early Detection Research Group supports research that seeks to determine the effectiveness, operating characteristics and clinical impact (harms as well as benefits) of cancer early detection technologies and practices, such as imaging and molecular biomarker approaches.   The group ran two large-scale early detection trials for which data and biospecimens are available

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.

Evaluating Fluorscence-Based Metrics for Early Detection of ...

EPA Pesticide Factsheets

Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification

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).

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

Trends of major disease outbreaks in the African region, 2003-2007.

PubMed

Kebede, Senait; Duales, Sambe; Yokouide, Allarangar; Alemu, Wondimagegnehu

2010-03-01

) 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.

Outbreak of human metapneumovirus infection in psychiatric inpatients: implications for directly observed use of alcohol hand rub in prevention of nosocomial outbreaks.

PubMed

Cheng, V C C; Wu, A K L; Cheung, C H Y; Lau, S K P; Woo, P C Y; Chan, K H; Li, K S M; Ip, I K S; Dunn, E L W; Lee, R A; Yam, L Y C; Yuen, K Y

2007-12-01

Nosocomial outbreaks of infectious diseases in psychiatric facilities are not uncommon but the implementation of infection control measures is often difficult. Here, we report an outbreak of an acute respiratory illness in a psychiatric ward between 29 July and 20 August 2005 involving 31 patients. Human metapneumovirus was detected in seven (23%) patients by reverse transcription-polymerase chain reaction and nucleotide sequencing. A review of outbreak surveillance records showed that six nosocomial outbreaks occurred in the year 2005, of which four (67%) were confirmed or presumably related to a respiratory viral infection. Directly observed deliveries of alcohol hand rub 4-hourly during daytime to all psychiatric patients was instituted in December 2005. Only one nosocomial respiratory viral outbreak occurred in the following year. The total number of patients and staff involved in nosocomial outbreaks due to presumed or proven respiratory virus infections decreased significantly from 60 to six (P<0.001), whereas those due to all types of nosocomial outbreaks also decreased from 70 to 24 (P=0.004). Alcohol hand rub has been shown to have potent bactericidal and virucidal activity against a wide range of nosocomial pathogens. Regular use of directly observed alcohol hand rub may decrease the incidence and scale of nosocomial outbreaks due to enveloped respiratory viruses especially in mentally incapacitated patients.

[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.

Structural and Functional Evaluations for the Early Detection of Glaucoma.

PubMed

Lucy, Katie A; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection.

Structural and Functional Evaluations for the Early Detection of Glaucoma

PubMed Central

Lucy, Katie A.; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection. PMID:28603546

Detection of fungal DNA in human body fluids and tissues during a multistate outbreak of fungal meningitis and other infections.

PubMed

Gade, Lalitha; Scheel, Christina M; Pham, Cau D; Lindsley, Mark D; Iqbal, Naureen; Cleveland, Angela Ahlquist; Whitney, Anne M; Lockhart, Shawn R; Brandt, Mary E; Litvintseva, Anastasia P

2013-05-01

Exserohilum rostratum was the major cause of an outbreak of fungal infections linked to injections of contaminated methylprednisolone acetate. Because almost 14,000 persons were exposed to product that was possibly contaminated with multiple fungal pathogens, there was unprecedented need for a rapid throughput diagnostic test that could detect both E. rostratum and other unusual agents of fungal infection. Here we report development of a novel PCR test that allowed for rapid and specific detection of fungal DNA in cerebrospinal fluid (CSF), other body fluids and tissues of infected individuals. The test relied on direct purification of free-circulating fungal DNA from fluids and subsequent PCR amplification and sequencing. Using this method, we detected Exserohilum rostratum DNA in 123 samples from 114 case-patients (28% of 413 case-patients for whom 627 samples were available), and Cladosporium DNA in one sample from one case-patient. PCR with novel Exserohilum-specific ITS-2 region primers detected 25 case-patients with samples that were negative using broad-range ITS primers. Compared to fungal culture, this molecular test was more sensitive: of 139 case-patients with an identical specimen tested by culture and PCR, E. rostratum was recovered in culture from 19 (14%), but detected by PCR in 41 (29%), showing a diagnostic sensitivity of 29% for PCR compared to 14% for culture in this patient group. The ability to rapidly confirm the etiologic role of E. rostratum in these infections provided an important contribution in the public health response to this outbreak.

A campylobacter outbreak associated with stir-fried food.

PubMed Central

Evans, M. R.; Lane, W.; Frost, J. A.; Nylen, G.

1998-01-01

An outbreak of gastrointestinal illness affecting 12 of 29 customers of a 'Hawaiian' theme restaurant specializing in stir-fried food occurred in Cardiff, Wales in February 1997. Campylobacter jejuni serotype HS50 phage type 49 (PT49) was isolated from 5 cases. A total of 47 isolates of C. jejuni HS50 PT49 were identified from Wales during 1997, of which 11 were isolated in late February or early March and from the Cardiff area. In the outbreak, illness was associated with eating stir-fried chicken pieces (relative risk 4.81, 95% confidence interval (CI) 0.76-30.44, P=0.03) and a dose-response relationship between risk of illness and amount of chicken consumed was observed (chi2-test for linear trend 3.96, P=0.047). Undercooking of chicken was probably due to a combination of inadequate cooking time and use of large chicken pieces. This is the first time that stir-fried food has been associated with a campylobacter outbreak. The incident also illustrates the value of routine campylobacter subtyping in supporting outbreak investigation. PMID:9825777

Large outbreak caused by methicillin resistant Staphylococcus pseudintermedius ST71 in a Finnish Veterinary Teaching Hospital--from outbreak control to outbreak prevention.

PubMed

Grönthal, Thomas; Moodley, Arshnee; Nykäsenoja, Suvi; Junnila, Jouni; Guardabassi, Luca; Thomson, Katariina; Rantala, Merja

2014-01-01

The purpose of this study was to describe a nosocomial outbreak caused by methicillin resistant Staphylococcus pseudintermedius (MRSP) ST71 SCCmec II-III in dogs and cats at the Veterinary Teaching Hospital of the University of Helsinki in November 2010 - January 2012, and to determine the risk factors for acquiring MRSP. In addition, measures to control the outbreak and current policy for MRSP prevention are presented. Data of patients were collected from the hospital patient record software. MRSP surveillance data were acquired from the laboratory information system. Risk factors for MRSP acquisition were analyzed from 55 cases and 213 controls using multivariable logistic regression in a case-control study design. Forty-seven MRSP isolates were analyzed by pulsed field gel electrophoresis and three were further analyzed with multi-locus sequence and SCCmec typing. Sixty-three MRSP cases were identified, including 27 infections. MRSPs from the cases shared a specific multi-drug resistant antibiogram and PFGE-pattern indicated clonal spread. Four risk factors were identified; skin lesion (OR = 6.2; CI95% 2.3-17.0, P = 0.0003), antimicrobial treatment (OR = 3.8, CI95% 1.0-13.9, P = 0.0442), cumulative number of days in the intensive care unit (OR = 1.3, CI95% 1.1-1.6, P = 0.0007) or in the surgery ward (OR = 1.1, CI95% 1.0-1.3, P = 0.0401). Tracing and screening of contact patients, enhanced hand hygiene, cohorting and barrier nursing, as well as cleaning and disinfection were used to control the outbreak. To avoid future outbreaks and spread of MRSP a search-and-isolate policy was implemented. Currently nearly all new MRSP findings are detected in screening targeted to risk patients on admission. Multidrug resistant MRSP is capable of causing a large outbreak difficult to control. Skin lesions, antimicrobial treatment and prolonged hospital stay increase the probability of acquiring MRSP. Rigorous control measures were needed to control the outbreak. We recommend

[Outbreaks of viral hepatitis E in the Czech Republic?].

PubMed

Trmal, Josef; Pavlík, Ivo; Vasícková, Petra; Matejícková, Ladislava; Simůnková, Lenka; Luks, Stanislav; Pazderková, Jana

2012-05-01

Until recently, viral hepatitis E (VHE) has typically been an imported infection, related to travel to developing countries. A number of travel-unrelated VHE cases currently diagnosed in the Czech Republic. Outcomes of the epidemiological investigations of two VHE outbreaks associated with the consumption of pork and pork products at pig-slaughtering feasts are presented. Thirteen cases have been reported in the first outbreak and eight cases in the second outbreak. The epidemiological investigations are described and the experience gained in analysing suspected biological specimens is presented. The source of infection has not been identified in the first outbreak while in the other one, a link between human cases and infection in farm pigs was revealed for the first time. Although the epidemiological investigation may not always lead to the detection of the VHE source, it must be conducted in any outbreak and can only be successful when done in cooperation of the public health authorities with the veterinary health agency.

Serratia marcescens outbreak due to contaminated 2% aqueous chlorhexidine.

PubMed

de Frutos, Mónica; López-Urrutia, Luis; Domínguez-Gil, Marta; Arias, Marta; Muñoz-Bellido, Juan Luis; Eiros, José María; Ramos, Carmen

2017-12-01

An outbreak of Serratia marcescens infections outbreak is described, as well as the epidemiological study that linked the outbreak to the use of 2% aqueous chlorhexidine antiseptic. In late November 2014 an increasing incidence of S. marcescens isolates was detected in patients treated in the emergency department. It was considered a possible outbreak, and an epidemiological investigation was started. S. marcescens was isolated in 23 samples from 16 patients and in all new bottles of two lots of 2% aqueous chlorhexidine. The contaminated disinfectant was withdrawn, and the Spanish Drugs Agency was alerted (COS 2/2014). The epidemiological study showed that strains isolated from clinical samples and from chlorhexidine belonged to the same clone. No further isolates were obtained once the disinfectant was withdrawn. The suspicion of an outbreak and the epidemiological study were essential to control the incidence. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

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.

Strategies for early detection of resectable pancreatic cancer

PubMed Central

Okano, Keiichi; Suzuki, Yasuyuki

2014-01-01

Pancreatic cancer is difficult to diagnose at an early stage and generally has a poor prognosis. Surgical resection is the only potentially curative treatment for pancreatic carcinoma. To improve the prognosis of this disease, it is essential to detect tumors at early stages, when they are resectable. The optimal approach to screening for early pancreatic neoplasia has not been established. The International Cancer of the Pancreas Screening Consortium has recently finalized several recommendations regarding the management of patients who are at an increased risk of familial pancreatic cancer. In addition, there have been notable advances in research on serum markers, tissue markers, gene signatures, and genomic targets of pancreatic cancer. To date, however, no biomarkers have been established in the clinical setting. Advancements in imaging modalities touch all aspects of the clinical management of pancreatic diseases, including the early detection of pancreatic masses, their characterization, and evaluations of tumor resectability. This article reviews strategies for screening high-risk groups, biomarkers, and current advances in imaging modalities for the early detection of resectable pancreatic cancer. PMID:25170207

Mumps outbreak and laboratory diagnosis.

PubMed

Maillet, Mylène; Bouvat, Eric; Robert, Nicole; Baccard-Longère, Monique; Morel-Baccard, Christine; Morand, Patrice; Vabret, Astrid; Stahl, Jean-Paul

2015-01-01

Several mumps outbreaks have been reported in Europe and in the United States among highly vaccinated populations. Biological diagnosis is classically based on the detection of mumps-specific IgM, but the ability of serological tests to confirm mumps infection seems to be limited among vaccinated patients. We aim to report a mumps outbreak in an engineering school in Grenoble, France, from February to June 2013 and results of the biological testing. WHO definitions were used to define cases. Mumps--specific IgM and IgG were assessed by a commercially available EIA. Mumps RNA detection by real time reverse transcriptase polymerase chain reaction tests (RT-PCR) and mumps genotyping were performed by the French National Reference Centre for Paramyxoviridae. Sixty two mumps patient-cases were identified using WHO case definitions, 20 being biologically explored, of which 17 were confirmed by biological tests. Vaccination status was documented for 27 patients/62: 4 (14.8%) patients had received one dose of MMR vaccine, and 23 (85.2) two doses of MMR vaccine. Among the biologically explored patients, 83% had a positive RT PCR at the first sampling whereas only 45% had positive or equivocal IgM. All the genotyped strains were genotype G. Mumps laboratory diagnosis in a highly vaccinated population is challenging. Serological tests among vaccinated patients should be interpreted cautiously and confirmed by RT-PCR tests at the beginning of a mumps outbreak. Copyright © 2014 Elsevier B.V. All rights reserved.

Early detection of non-native fishes using fish larvae

EPA Science Inventory

Our objective was to evaluate the use of fish larvae for early detection of non-native fishes, comparing traditional and molecular taxonomy approaches to investigate potential efficiencies. Fish larvae present an interesting opportunity for non-native fish early detection. First,...

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.

An outbreak of Burkholderia stabilis colonization in a nasal ward.

PubMed

Wang, Lijun; Wang, Mei; Zhang, Junyi; Wu, Wei; Lu, Yuan; Fan, Yanyan

2015-04-01

The aim of this study was to describe an outbreak of Burkholderia stabilis colonization among patients in a nasal ward. Multilocus sequence typing (MLST) was used for the molecular typing of B. stabilis isolates. Microbiological records were reviewed to delineate the colonization outbreak period. One hundred seventy-one cultures of environment and equipment samples from the nasal ward were performed to trace the source of contamination. Infection control measures were taken in order to end the outbreak. All B. stabilis isolates were identified as a new MLST type, ST821. A total of 53 patients carried this B. stabilis in the nasal ward between March and September 2013, which was defined as the outbreak period. The source of the colonization was not determined because all environment cultures were negative for Burkholderia cepacia complex. No further B. stabilis carriers have been found in the ward since the implementation of interventions. Attention must be paid to asymptomatic colonization in order to identify outbreaks early. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

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.

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...

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

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

Molecular Characterization of Two Major Dengue Outbreaks in Costa Rica

PubMed Central

Soto-Garita, Claudio; Somogyi, Teresita; Vicente-Santos, Amanda; Corrales-Aguilar, Eugenia

2016-01-01

Dengue virus (DENV) (Flavivirus, Flaviviridae) is a reemerging arthropod-borne virus with a worldwide circulation, transmitted mainly by Aedes aegypti and Aedes albopictus mosquitoes. Since the first detection of its main transmitting vector in 1992 and the invasion of DENV-1 in 1993, Costa Rica has faced dengue outbreaks yearly. In 2007 and 2013, Costa Rica experienced two of the largest outbreaks in terms of total and severe cases. To provide genetic information about the etiologic agents producing these outbreaks, we conducted phylogenetic analysis of viruses isolated from human samples. A total of 23 DENV-1 and DENV-2 sequences were characterized. These analyses signaled that DENV-1 genotype V and DENV-2 American/Asian genotype were circulating in those outbreaks. Our results suggest that the 2007 and 2013 outbreak viral strains of DENV-1 and DENV-2 originated from nearby countries and underwent in situ microevolution. PMID:27139442

Streptococcus pyogenes outbreak in a long-term care facility.

PubMed

Harkness, G A; Bentley, D W; Mottley, M; Lee, J

1992-06-01

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.

Measles & rubella outbreaks in Maharashtra State, India.

PubMed

Vaidya, Sunil R; Kamble, Madhukar B; Chowdhury, Deepika T; Kumbhar, Neelakshi S

2016-02-01

Under the outbreak-based measles surveillance in Maharashtra State the National Institute of Virology at Pune receives 3-5 serum samples from each outbreak and samples from the local hospitals in Pune for laboratory diagnosis. This report describes one year data on the measles and rubella serology, virus isolation and genotyping. Maharashtra State Health Agencies investigated 98 suspected outbreaks between January-December 2013 in the 20 districts. Altogether, 491 serum samples were received from 20 districts and 126 suspected cases from local hospitals. Samples were tested for the measles and rubella IgM antibodies by commercial enzyme immunoassay (EIA). To understand the diagnostic utility, a subset of serum samples (n=53) was tested by measles focus reduction neutralization test (FRNT). Further, 37 throat swabs and 32 urine specimens were tested by measles reverse transcription (RT)-PCR and positive products were sequenced. Virus isolation was performed in Vero hSLAM cells. Of the 98 suspected measles outbreaks, 61 were confirmed as measles, 12 as rubella and 21 confirmed as the mixed outbreaks. Four outbreaks remained unconfirmed. Of the 126 cases from the local hospitals, 91 were confirmed for measles and three for rubella. Overall, 93.6 per cent (383/409) confirmed measles cases were in the age group of 0-15 yr. Measles virus was detected in 18 of 38 specimens obtained from the suspected cases. Sequencing of PCR products revealed circulation of D4 (n=9) and D8 (n=9) strains. Four measles viruses (three D4 & one D8) were isolated. Altogether, 94 measles and rubella outbreaks were confirmed in 2013 in the State of Maharasthra indicating the necessity to increase measles vaccine coverage in the State.

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.

[The comparison of two different types of baseline data regarding the performance of aberration detection algorithm for infectious disease outbreaks].

PubMed

Lai, Sheng-jie; Li, Zhong-jie; Zhang, Hong-long; Lan, Ya-jia; Yang, Wei-zhong

2011-06-01

To compare the performance of aberration detection algorithm for infectious disease outbreaks, based on two different types of baseline data. Cases and outbreaks of hand-foot-and-mouth disease (HFMD) reported by six provinces of China in 2009 were used as the source of data. Two types of baseline data on algorithms of C1, C2 and C3 were tested, by distinguishing the baseline data of weekdays and weekends. Time to detection (TTD) and false alarm rate (FAR) were adopted as two evaluation indices to compare the performance of 3 algorithms based on these two types of baseline data. A total of 405 460 cases of HFMD were reported by 6 provinces in 2009. On average, each county reported 1.78 cases per day during the weekdays and 1.29 cases per day during weekends, with significant difference (P < 0.01) between them. When using the baseline data without distinguish weekdays and weekends, the optimal thresholds for C1, C2 and C3 was 0.2, 0.4 and 0.6 respectively while the TTD of C1, C2 and C3 was all 1 day and the FARs were 5.33%, 4.88% and 4.50% respectively. On the contrast, when using the baseline data to distinguish the weekdays and weekends, the optimal thresholds for C1, C2 and C3 became 0.4, 0.6 and 1.0 while the TTD of C1, C2 and C3 also appeared equally as 1 day. However, the FARs became 4.81%, 4.75% and 4.16% respectively, which were lower than the baseline data from the first type. The number of HFMD cases reported in weekdays and weekends were significantly different, suggesting that when using the baseline data to distinguish weekdays and weekends, the FAR of C1, C2 and C3 algorithm could effectively reduce so as to improve the accuracy of outbreak detection.

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

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.

[Enzyme-linked immunosorbent assay (ELISA) for detection of antibodies to Salmonella Typhi lipopolysaccharide O and capsular polysaccharide Vi antigens in persons from outbreak of typhoid fever].

PubMed

Rastawicki, Waldemar; Kałużewski, Stanisław

2015-01-01

The laboratory diagnosis of typhoid fever is dependent upon either isolation of S. Typhi from a clinical sample or the detection of raised titers of serum antibodies in the Widal test or the passive hemagglutination assay (PHA). In this study we evaluated the usefulness of ELISA for detection of antibodies to S. Typhi lipopolysaccharide O and capsular polysaccharide Vi antigens in the sera of persons from outbreak of typhoid fever. Fifteen serum samples from patients with laboratory confirmed typhoid fever and 140 sera from persons suspected for contact with typhoid fever patients from outbreak in 1974/75 in Poland were tested by ELISA. Additionally, as the control group, we tested 115 sera from blood donors for the presence of S. Typhi anti-LPS and anti-Vi antibodies. Anti-LPS and anti-Vi antibodies were detected in 80% and 53.3% of sera obtained from patients with laboratory confirmed typhoid fever, respectively. The high percentages of positive results in ELISA were also noted in the group of persons suspected for contact with typhoid fever patients (51.4% and 45%) but not in the group of blood donors (7.8% and 6.1%, respectively). The ELISA could be a useful tool for the serological diagnosis of typhoid fever in patients who have clinical symptoms but are culture negative, especially during massive outbreaks of typhoid fever.

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...

Strategies for early melanoma detection: approaches to the patient with nevi

PubMed Central

Goodson, Agnessa G.; Grossman, Douglas

2009-01-01

Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Although there are no non-invasive techniques for definitive diagnosis of melanoma, and the “gold standard” remains biopsy with histologic examination, a variety of modalities may facilitate early melanoma diagnosis and the detection of new and changing nevi. This article reviews general clinical principles of early melanoma detection, and various modalities that are currently available or on the horizon, providing the clinician with an up-to-date understanding of management strategies for their patients with numerous or atypical nevi. Learning objectives At the conclusion of this learning activity, participants should: 1) understand the clinical importance of early melanoma detection; 2) appreciate the challenges of early melanoma diagnosis and which patients are at highest risk; 3) know general principles of early melanoma detection; 4) be familiar with current and emerging modalities that may facilitate early melanoma diagnosis and the detection of new and changing nevi; 5) know the advantages and limitations of each modality; and 6) be able to practice a combined approach to the patient with numerous or clinically atypical nevi. PMID:19389517

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

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

The Methanol Poisoning Outbreaks in Libya 2013 and Kenya 2014

PubMed Central

Rostrup, Morten; Edwards, Jeffrey K.; Abukalish, Mohamed; Ezzabi, Masoud; Some, David; Ritter, Helga; Menge, Tom; Abdelrahman, Ahmed; Rootwelt, Rebecca; Janssens, Bart; Lind, Kyrre; Paasma, Raido; Hovda, Knut Erik

2016-01-01

Background Outbreaks of methanol poisoning occur frequently on a global basis, affecting poor and vulnerable populations. Knowledge regarding methanol is limited, likely many cases and even outbreaks go unnoticed, with patients dying unnecessarily. We describe findings from the first three large outbreaks of methanol poisoning where Médecins Sans Frontières (MSF) responded, and evaluate the benefits of a possible future collaboration between local health authorities, a Non-Governmental Organisation and international expertise. Methods Retrospective study of three major methanol outbreaks in Libya (2013) and Kenya (May and July 2014). Data were collected from MSF field personnel, local health personnel, hospital files, and media reports. Findings In Tripoli, Libya, over 1,000 patients were poisoned with a reported case fatality rate of 10% (101/1,066). In Kenya, two outbreaks resulted in approximately 341 and 126 patients, with case fatality rates of 29% (100/341) and 21% (26/126), respectively. MSF launched an emergency team with international experts, medications and equipment, however, the outbreaks were resolving by the time of arrival. Interpretation Recognition of an outbreak of methanol poisoning and diagnosis seem to be the most challenging tasks, with significant delay from time of first presentations to public health warnings being issued. In spite of the rapid response from an emergency team, the outbreaks were nearly concluded by the time of arrival. A major impact on the outcome was not seen, but large educational trainings were conducted to increase awareness and knowledge about methanol poisoning. Based on this training, MSF was able to send a local emergency team during the second outbreak, supporting that such an approach could improve outcomes. Basic training, simplified treatment protocols, point-of-care diagnostic tools, and early support when needed, are likely the most important components to impact the consequences of methanol poisoning

The Methanol Poisoning Outbreaks in Libya 2013 and Kenya 2014.

PubMed

Rostrup, Morten; Edwards, Jeffrey K; Abukalish, Mohamed; Ezzabi, Masoud; Some, David; Ritter, Helga; Menge, Tom; Abdelrahman, Ahmed; Rootwelt, Rebecca; Janssens, Bart; Lind, Kyrre; Paasma, Raido; Hovda, Knut Erik

2016-01-01

Outbreaks of methanol poisoning occur frequently on a global basis, affecting poor and vulnerable populations. Knowledge regarding methanol is limited, likely many cases and even outbreaks go unnoticed, with patients dying unnecessarily. We describe findings from the first three large outbreaks of methanol poisoning where Médecins Sans Frontières (MSF) responded, and evaluate the benefits of a possible future collaboration between local health authorities, a Non-Governmental Organisation and international expertise. Retrospective study of three major methanol outbreaks in Libya (2013) and Kenya (May and July 2014). Data were collected from MSF field personnel, local health personnel, hospital files, and media reports. In Tripoli, Libya, over 1,000 patients were poisoned with a reported case fatality rate of 10% (101/1,066). In Kenya, two outbreaks resulted in approximately 341 and 126 patients, with case fatality rates of 29% (100/341) and 21% (26/126), respectively. MSF launched an emergency team with international experts, medications and equipment, however, the outbreaks were resolving by the time of arrival. Recognition of an outbreak of methanol poisoning and diagnosis seem to be the most challenging tasks, with significant delay from time of first presentations to public health warnings being issued. In spite of the rapid response from an emergency team, the outbreaks were nearly concluded by the time of arrival. A major impact on the outcome was not seen, but large educational trainings were conducted to increase awareness and knowledge about methanol poisoning. Based on this training, MSF was able to send a local emergency team during the second outbreak, supporting that such an approach could improve outcomes. Basic training, simplified treatment protocols, point-of-care diagnostic tools, and early support when needed, are likely the most important components to impact the consequences of methanol poisoning outbreaks in these challenging contexts.

Molecular Characterization of Two Major Dengue Outbreaks in Costa Rica.

PubMed

Soto-Garita, Claudio; Somogyi, Teresita; Vicente-Santos, Amanda; Corrales-Aguilar, Eugenia

2016-07-06

Dengue virus (DENV) (Flavivirus, Flaviviridae) is a reemerging arthropod-borne virus with a worldwide circulation, transmitted mainly by Aedes aegypti and Aedes albopictus mosquitoes. Since the first detection of its main transmitting vector in 1992 and the invasion of DENV-1 in 1993, Costa Rica has faced dengue outbreaks yearly. In 2007 and 2013, Costa Rica experienced two of the largest outbreaks in terms of total and severe cases. To provide genetic information about the etiologic agents producing these outbreaks, we conducted phylogenetic analysis of viruses isolated from human samples. A total of 23 DENV-1 and DENV-2 sequences were characterized. These analyses signaled that DENV-1 genotype V and DENV-2 American/Asian genotype were circulating in those outbreaks. Our results suggest that the 2007 and 2013 outbreak viral strains of DENV-1 and DENV-2 originated from nearby countries and underwent in situ microevolution. © The American Society of Tropical Medicine and Hygiene.

Red-breasted nuthatches detect early increases in spruce budworm populations

Treesearch

Hewlette S. Crawford; Daniel T. Jennings; Timothy L. Stone

1990-01-01

Early suppression .of increasing spruce budworm populations is essential to prevent epidemics; however, early changes in budworm numbers are difficult to detect. An effective and inexpensive method to detect early increases is needed. Red-breasted nuthatches eat more spruce budworm larvae and pupae as the insect increases in number. We estimated the number of large...

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.

Sweet-spot training for early esophageal cancer detection

NASA Astrophysics Data System (ADS)

van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Over the past decade, the imaging tools for endoscopists have improved drastically. This has enabled physicians to visually inspect the intestinal tissue for early signs of malignant lesions. Besides this, recent studies show the feasibility of supportive image analysis for endoscopists, but the analysis problem is typically approached as a segmentation task where binary ground truth is employed. In this study, we show that the detection of early cancerous tissue in the gastrointestinal tract cannot be approached as a binary segmentation problem and it is crucial and clinically relevant to involve multiple experts for annotating early lesions. By employing the so-called sweet spot for training purposes as a metric, a much better detection performance can be achieved. Furthermore, a multi-expert-based ground truth, i.e. a golden standard, enables an improved validation of the resulting delineations. For this purpose, besides the sweet spot we also propose another novel metric, the Jaccard Golden Standard (JIGS) that can handle multiple ground-truth annotations. Our experiments involving these new metrics and based on the golden standard show that the performance of a detection algorithm of early neoplastic lesions in Barrett's esophagus can be increased significantly, demonstrating a 10 percent point increase in the resulting F1 detection score.

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

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

Fresh Produce-Associated Listeriosis Outbreaks, Sources of Concern, Teachable Moments, and Insights.

PubMed

Garner, Danisha; Kathariou, Sophia

2016-02-01

Foodborne transmission of Listeria monocytogenes was first demonstrated through the investigation of the 1981 Maritime Provinces outbreak involving coleslaw. In the following two decades, most listeriosis outbreaks involved foods of animal origin, e.g., deli meats, hot dogs, and soft cheeses. L. monocytogenes serotype 4b, especially epidemic clones I, II, and Ia, were frequently implicated in these outbreaks. However, since 2008 several outbreaks have been linked to diverse types of fresh produce: sprouts, celery, cantaloupe, stone fruit, and apples. The 2011 cantaloupe-associated outbreak was one of the deadliest foodborne outbreaks in recent U.S. history. This review discusses produce-related outbreaks of listeriosis with a focus on special trends, unusual findings, and potential paradigm shifts. With the exception of sprouts, implicated produce types were novel, and outbreaks were one-time events. Several involved serotype 1/2a, and in the 2011 cantaloupe-associated outbreak, serotype 1/2b was for the first time conclusively linked to a common-source outbreak of invasive listeriosis. Also in this outbreak, for the first time multiple strains were implicated in a common-source outbreak. In 2014, deployment of whole genome sequencing as part of outbreak investigation validated this technique as a pivotal tool for outbreak detection and speedy resolution. In spite of the unusual attributes of produce-related outbreaks, in all but one of the investigated cases (the possible exception being the coleslaw outbreak) contamination was traced to the same sources as those for outbreaks associated with other vehicles (e.g., deli meats), i.e., the processing environment and equipment. The public health impact of farm-level contamination remains uncharacterized. This review highlights knowledge gaps regarding virulence and other potentially unique attributes of produce outbreak strains, the potential for novel fresh produce items to become unexpectedly implicated in outbreaks

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.

[Norovirus outbreaks in hospitals and nursing homes in Catalonia, Spain].

PubMed

Godoy, Pere; Domínguez, Angela; Alvarez, Josep; Camps, Neus; Barrabeig, Irene; Bartolomé, Rosa; Sala, María Rosa; Ferre, Dolors; Pañella, Helena; Torres, Joan; Minguell, Sofía; Alsedà, Miquel; Pumares, Analía

2009-01-01

The low infectious dose and multiple transmission routes favour the appearance of norovirus outbreaks. The objective of this study was to compare the incidence of norovirus outbreaks in hospitals and nursing homes in Catalonia. A descriptive study of norovirus outbreaks between 15/10/2004 and 30/10/2005 was carried out. An epidemiological survey was completed for each outbreak. Norovirus in clinical samples was determined by PCR techniques. The incidence in each centre and the annual incidence of outbreaks by centre were calculated. Differences were calculated using the chi-square test and the Student's t test, taking a p value of > 0.05 as significant. Seventeen outbreaks (6 in hospitals and 11 in nursing homes) were detected. The global attack rate was 33.4% (652/1951) and was slightly higher in nursing homes (35.2%) than in hospitals (31.4%). A total of 94.1% (16/17) of outbreaks were caused by person-to-person transmission and only 5.9% (1/17) by foods. The mean number of days between the first and last case was 11.4 (SD = 6.9). The mean duration of symptoms was 2.39 days (SD=1.6), and was higher hospitals, 2.63 (SD=1.7), than in nursing homes, 1.97 (SD=1.7) (p < 0.0001). Norovirus is responsible for a large number of outbreaks due to person-to-person transmission. Control should be standardized to reduce the number and duration of 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

Tularaemia outbreaks in Sakarya, Turkey: case-control and environmental studies.

PubMed

Meric, M; Sayan, M; Dundar, D; Willke, A

2010-08-01

Tularaemia is an important zoonotic disease that leads to outbreaks. This study aimed to compare the epidemiological characteristics of two tularaemia outbreaks that occurred in the Sakarya region of Turkey, analyse the risk factors for the development of outbreaks and identify Francisella (F.) tularensis in the water samples. Two tularaemia outbreaks occurred in the Kocadongel village in 2005 and 2006. A field investigation and a case-control study with 47 cases and 47 healthy households were performed during the second outbreak. Clinical samples from the patients and filtrated water samples were analysed for F. tularensis via real-time polymerase chain reaction. From the two outbreaks, a total of 58 patients were diagnosed with oropharyngeal tularaemia based on their clinical and serological results. Both outbreaks occurred between the months of January and April, and the number of patients peaked in February. Logistic regression analysis revealed that the consumption of natural spring water was the only significant risk factor for tularaemia infection (odds ratio 3.5, confidence interval 1.23-10.07). F. tularensis was detected in eight clinical samples and in the filtrated natural spring water. This study is the first report of tularaemia from this region. The results show that both tularaemia outbreaks were related to the consumption of untreated natural spring water. To prevent waterborne tularaemia, community water supplies should be treated and checked periodically.

Developing a disease outbreak event corpus.

PubMed

Conway, Mike; Kawazoe, Ai; Chanlekha, Hutchatai; Collier, Nigel

2010-09-28

In recent years, there has been a growth in work on the use of information extraction technologies for tracking disease outbreaks from online news texts, yet publicly available evaluation standards (and associated resources) for this new area of research have been noticeably lacking. This study seeks to create a "gold standard" data set against which to test how accurately disease outbreak information extraction systems can identify the semantics of disease outbreak events. Additionally, we hope that the provision of an annotation scheme (and associated corpus) to the community will encourage open evaluation in this new and growing application area. We developed an annotation scheme for identifying infectious disease outbreak events in news texts. An event--in the context of our annotation scheme--consists minimally of geographical (eg, country and province) and disease name information. However, the scheme also allows for the rich encoding of other domain salient concepts (eg, international travel, species, and food contamination). The work resulted in a 200-document corpus of event-annotated disease outbreak reports that can be used to evaluate the accuracy of event detection algorithms (in this case, for the BioCaster biosurveillance online news information extraction system). In the 200 documents, 394 distinct events were identified (mean 1.97 events per document, range 0-25 events per document). We also provide a download script and graphical user interface (GUI)-based event browsing software to facilitate corpus exploration. In summary, we present an annotation scheme and corpus that can be used in the evaluation of disease outbreak event extraction algorithms. The annotation scheme and corpus were designed both with the particular evaluation requirements of the BioCaster system in mind as well as the wider need for further evaluation resources in this growing research area.

The Global Outbreak Alert and Response Network

PubMed Central

Mackenzie, John S.; Drury, Patrick; Arthur, Ray R.; Ryan, Michael J.; Grein, Thomas; Slattery, Raphael; Suri, Sameera; Domingo, Christine Tiffany; Bejtullahu, Armand

2014-01-01

The Global Outbreak Alert and Response Network (GOARN) was established in 2000 as a network of technical institutions, research institutes, universities, international health organisations and technical networks willing to contribute and participate in internationally coordinated responses to infectious disease outbreaks. It reflected a recognition of the need to strengthen and coordinate rapid mobilisation of experts in responding to international outbreaks and to overcome the sometimes chaotic and fragmented operations characterising previous responses. The network partners agreed that the World Health Organization would coordinate the network and provide a secretariat, which would also function as the operational support team. The network has evolved to comprise 153 institutions/technical partners and 37 additional networks, the latter encompassing a further 355 members and has been directly involved in 137 missions to 79 countries, territories or areas. Future challenges will include supporting countries to achieve the capacity to detect and respond to outbreaks of international concern, as required by the International Health Regulations (2005). GOARN's increasing regional focus and expanding geographic composition will be central to meeting these challenges. The paper summarises some of network's achievements over the past 13 years and presents some of the future challenges. PMID:25186571

The global outbreak alert and response network.

PubMed

Mackenzie, John S; Drury, Patrick; Arthur, Ray R; Ryan, Michael J; Grein, Thomas; Slattery, Raphael; Suri, Sameera; Domingo, Christine Tiffany; Bejtullahu, Armand

2014-01-01

The Global Outbreak Alert and Response Network (GOARN) was established in 2000 as a network of technical institutions, research institutes, universities, international health organisations and technical networks willing to contribute and participate in internationally coordinated responses to infectious disease outbreaks. It reflected a recognition of the need to strengthen and coordinate rapid mobilisation of experts in responding to international outbreaks and to overcome the sometimes chaotic and fragmented operations characterising previous responses. The network partners agreed that the World Health Organization would coordinate the network and provide a secretariat, which would also function as the operational support team. The network has evolved to comprise 153 institutions/technical partners and 37 additional networks, the latter encompassing a further 355 members and has been directly involved in 137 missions to 79 countries, territories or areas. Future challenges will include supporting countries to achieve the capacity to detect and respond to outbreaks of international concern, as required by the International Health Regulations (2005). GOARN's increasing regional focus and expanding geographic composition will be central to meeting these challenges. The paper summarises some of network's achievements over the past 13 years and presents some of the future challenges.

Measles & rubella outbreaks in Maharashtra State, India

PubMed Central

Vaidya, Sunil R.; Kamble, Madhukar B.; Chowdhury, Deepika T.; Kumbhar, Neelakshi S.

2016-01-01

Background & objectives: Under the outbreak-based measles surveillance in Maharashtra State the National Institute of Virology at Pune receives 3-5 serum samples from each outbreak and samples from the local hospitals in Pune for laboratory diagnosis. This report describes one year data on the measles and rubella serology, virus isolation and genotyping. Methods: Maharashtra State Health Agencies investigated 98 suspected outbreaks between January-December 2013 in the 20 districts. Altogether, 491 serum samples were received from 20 districts and 126 suspected cases from local hospitals. Samples were tested for the measles and rubella IgM antibodies by commercial enzyme immunoassay (EIA). To understand the diagnostic utility, a subset of serum samples (n=53) was tested by measles focus reduction neutralization test (FRNT). Further, 37 throat swabs and 32 urine specimens were tested by measles reverse transcription (RT)-PCR and positive products were sequenced. Virus isolation was performed in Vero hSLAM cells. Results: Of the 98 suspected measles outbreaks, 61 were confirmed as measles, 12 as rubella and 21 confirmed as the mixed outbreaks. Four outbreaks remained unconfirmed. Of the 126 cases from the local hospitals, 91 were confirmed for measles and three for rubella. Overall, 93.6 per cent (383/409) confirmed measles cases were in the age group of 0-15 yr. Measles virus was detected in 18 of 38 specimens obtained from the suspected cases. Sequencing of PCR products revealed circulation of D4 (n=9) and D8 (n=9) strains. Four measles viruses (three D4 & one D8) were isolated. Interpretation & conclusions: Altogether, 94 measles and rubella outbreaks were confirmed in 2013 in the State of Maharasthra indicating the necessity to increase measles vaccine coverage in the State. PMID:27121521

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

Liquid biopsy for early detection of lung cancer.

PubMed

Hofman, Paul

2017-01-01

The possibility of complete recovery for a lung cancer patient depends on very early diagnosis, as it allows total surgical resection. Screening for this cancer in a high-risk population can be performed using a radiological approach, but this holds a certain number of limitations. Liquid biopsy could become an alternative and complementary screening approach to chest imaging for early diagnosis of lung cancer. Several circulating biomarkers indicative of lung cancer can be investigated in blood, such as circulating tumor cells, circulating free nucleic acids (RNA and DNA) and proteins. However, none of these biomarkers have yet been adopted in routine clinical practice and studies are ongoing to confirm or not the usefulness and practical interest in routine early diagnosis and screening for lung cancers. Several potential circulating biomarkers for the early detection of lung cancer exist. When coupled to thoracic imaging, these biomarkers must give diagnosis of a totally resectable lung cancer and potentially provide new recommendations for surveillance by imagery of high-risk populations without a detectable nodule. Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques is essential before considering for daily practice a liquid biopsy as an early diagnostic tool, or possibly as a predictive test, of lung cancer.

Inferring rubella outbreak risk from seroprevalence data in Belgium.

PubMed

Abrams, Steven; Kourkouni, Eleni; Sabbe, Martine; Beutels, Philippe; Hens, Niel

2016-12-07

Rubella is usually a mild disease for which infections often pass by unnoticed. In approximately 50% of the cases, there are no or only few clinical symptoms. However, rubella contracted during early pregnancy could lead to spontaneous abortion, to central nervous system defects, or to one of a range of other serious and debilitating conditions in a newborn such as the congenital rubella syndrome. Before the introduction of mass vaccination, rubella was a common childhood infection occurring all over the world. However, since the introduction of rubella antigen-containing vaccines, the incidence of rubella has declined dramatically in high-income countries. Recent large-scale mumps outbreaks, one of the components in the combined measles-mumps-rubella vaccine, occurring in countries throughout Europe with high vaccination coverage, provide evidence of pathogen-specific waning of vaccine-induced immunity and primary vaccine failure. In addition, recent measles outbreaks affecting populations with suboptimal vaccination coverages stress the importance of maintaining high vaccination coverages. In this paper, we focus on the assessment of rubella outbreak risk using a previously developed method to identify geographic regions of high outbreak potential. The methodology relies on 2006 rubella seroprevalence data and vaccination coverage data from Belgium and information on primary and secondary vaccine failure obtained from extensive literature reviews. We estimated the rubella outbreak risk in Belgium to be low, however maintaining high levels of immunisation and surveillance are of utmost importance to avoid future outbreaks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Kidney Disease: Early Detection and Treatment

MedlinePlus

... Bar Home Current Issue Past Issues Special Section Kidney Disease: Early Detection and Treatment Past Issues / Winter ... called a "urine albumin-to-creatinine ratio." Treating Kidney Disease Kidney disease is usually a progressive disease, ...

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.

Outbreak investigations--a perspective.

PubMed Central

Reingold, A. L.

1998-01-01

Outbreak investigations, an important and challenging component of epidemiology and public health, can help identify the source of ongoing outbreaks and prevent additional cases. Even when an outbreak is over, a thorough epidemiologic and environmental investigation often can increase our knowledge of a given disease and prevent future outbreaks. Finally, outbreak investigations provide epidemiologic training and foster cooperation between the clinical and public health communities. PMID:9452395

Large Outbreak Caused by Methicillin Resistant Staphylococcus pseudintermedius ST71 in a Finnish Veterinary Teaching Hospital – From Outbreak Control to Outbreak Prevention

PubMed Central

Grönthal, Thomas; Moodley, Arshnee; Nykäsenoja, Suvi; Junnila, Jouni; Guardabassi, Luca; Thomson, Katariina; Rantala, Merja

2014-01-01

Introduction The purpose of this study was to describe a nosocomial outbreak caused by methicillin resistant Staphylococcus pseudintermedius (MRSP) ST71 SCCmec II-III in dogs and cats at the Veterinary Teaching Hospital of the University of Helsinki in November 2010 – January 2012, and to determine the risk factors for acquiring MRSP. In addition, measures to control the outbreak and current policy for MRSP prevention are presented. Methods Data of patients were collected from the hospital patient record software. MRSP surveillance data were acquired from the laboratory information system. Risk factors for MRSP acquisition were analyzed from 55 cases and 213 controls using multivariable logistic regression in a case-control study design. Forty-seven MRSP isolates were analyzed by pulsed field gel electrophoresis and three were further analyzed with multi-locus sequence and SCCmec typing. Results Sixty-three MRSP cases were identified, including 27 infections. MRSPs from the cases shared a specific multi-drug resistant antibiogram and PFGE-pattern indicated clonal spread. Four risk factors were identified; skin lesion (OR = 6.2; CI95% 2.3–17.0, P = 0.0003), antimicrobial treatment (OR = 3.8, CI95% 1.0–13.9, P = 0.0442), cumulative number of days in the intensive care unit (OR = 1.3, CI95% 1.1–1.6, P = 0.0007) or in the surgery ward (OR = 1.1, CI95% 1.0–1.3, P = 0.0401). Tracing and screening of contact patients, enhanced hand hygiene, cohorting and barrier nursing, as well as cleaning and disinfection were used to control the outbreak. To avoid future outbreaks and spread of MRSP a search-and-isolate policy was implemented. Currently nearly all new MRSP findings are detected in screening targeted to risk patients on admission. Conclusion Multidrug resistant MRSP is capable of causing a large outbreak difficult to control. Skin lesions, antimicrobial treatment and prolonged hospital stay increase the probability of acquiring

Early bronchiectasis in cystic fibrosis detected by surveillance CT.

PubMed

Pillarisetti, Naveen; Linnane, Barry; Ranganathan, Sarath

2010-08-01

There is emerging evidence that cystic fibrosis lung disease begins early in infancy. Newborn screening allows early detection and surveillance of pulmonary disease and the possibility of early intervention in this life-shortening condition. We report two children with cystic fibrosis who underwent a comprehensive assessment from diagnosis that included measurement of lung function, limited-slice high-resolution CT and BAL performed annually. Early aggressive surveillance enabled significant lung disease and bronchiectasis to be detected during the first few years of life and led to a change in management, highlighting a clinical role for CT scanning during the preschool years in children with cystic fibrosis.

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

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

Review of Avian Influenza Outbreaks in South Korea from 1996 to 2014.

PubMed

Mo, In-Pil; Bae, Yeon-Ji; Lee, Seung-Baek; Mo, Jong-Suk; Oh, Kwang-Hyun; Shin, Jeong-Hwa; Kang, Hyun-Mi; Lee, Youn-Jeong

2016-05-01

Since the first outbreak of low pathogenic avian influenza (LPAI) in 1996, outbreaks of LPAI have become more common in Korea, leading to the development of a nationwide mass vaccination program in 2007. In the case of highly pathogenic avian influenza (HPAI), four outbreaks took place in 2003-04, 2006-07, 2008, and 2010-11; a fifth outbreak began in 2014 and was ongoing at the time of this writing. The length of the four previous outbreaks varied, ranging from 42 days (2008) to 139 days (2010-11). The number of cases reported by farmers that were subsequently confirmed as HPAI also varied, from seven cases in 2006-07 to 53 in 2010-11. The number of farms affected by the outbreaks varied, from a low of 286 (2006-07) with depopulation of 6,473,000 birds, to a high of 1500 farms (2008) with depopulation of 10,200,000 birds. Government compensation for bird depopulation ranged from $253 million to $683 million in the five outbreaks. Despite the damage caused by the five HPAI outbreaks, efficient control strategies have yet to be established. Meanwhile, the situation in the field worsens. Analysis of the five HPAI outbreaks revealed horizontal farm-to-farm transmission as the main factor effecting major economic losses. However, horizontal transmission could not be efficiently prevented because of insufficient transparency within the poultry industry, especially within the duck industry, which is reluctant to report suspicious cases early. Moreover, the experiences and expertise garnered in previous outbreaks has yet to be effectively applied to the management of new outbreaks. Considering the magnitude of the economic damage caused by avian influenza and the increasing likelihood of its endemicity, careful and quantitative analysis of outbreaks and the establishment of control policies are urgently needed.

Evaluation of a Real-Time Reverse Transcription-PCR Assay for Detection of Enterovirus D68 in Clinical Samples from an Outbreak in New York State in 2014.

PubMed

Zhuge, Jian; Vail, Eric; Bush, Jeffrey L; Singelakis, Lauren; Huang, Weihua; Nolan, Sheila M; Haas, Janet P; Engel, Helen; Della Posta, Millicent; Yoon, Esther C; Fallon, John T; Wang, Guiqing

2015-06-01

An outbreak of severe respiratory illness associated with enterovirus D68 (EV-D68) infection was reported in mid-August 2014 in the United States. In this study, we evaluated the diagnostic utility of an EV-D68-specific real-time reverse transcription-PCR (rRT-PCR) that was recently developed by the Centers for Disease Control and Prevention in clinical samples. Nasopharyngeal (NP) swab specimens from patients in a recent outbreak of respiratory illness in the lower Hudson Valley, New York State, were collected and examined for the presence of human rhinovirus or enterovirus using the FilmArray Respiratory Panel (RP) assay. Samples positive by RP were assessed using EV-D68 rRT-PCR, and the data were compared to results from sequencing analysis of partial VP1 and 5' untranslated region (5'-UTR) sequences of the EV genome. A total of 285 RP-positive NP specimens (260 from the 2014 outbreak and 25 from 2013) were analyzed by rRT-PCR; EV-D68 was detected in 74 of 285 (26.0%) specimens examined. Data for comparisons between rRT-PCR and sequencing analysis were obtained from 194 NP specimens. EV-D68 detection was confirmed by sequencing analysis in 71 of 74 positive and in 1 of 120 randomly selected negative specimens by rRT-PCR. The EV-D68 rRT-PCR showed diagnostic sensitivity and specificity of 98.6% and 97.5%, respectively. Our data suggest that the EV-D68 rRT-PCR is a reliable assay for detection of EV-D68 in clinical samples and has a potential to be used as a tool for rapid diagnosis and outbreak investigation of EV-D68-associated infections in clinical and public health laboratories. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Evaluation of a Real-Time Reverse Transcription-PCR Assay for Detection of Enterovirus D68 in Clinical Samples from an Outbreak in New York State in 2014

PubMed Central

Zhuge, Jian; Vail, Eric; Bush, Jeffrey L.; Singelakis, Lauren; Huang, Weihua; Nolan, Sheila M.; Haas, Janet P.; Engel, Helen; Della Posta, Millicent; Yoon, Esther C.; Fallon, John T.

2015-01-01

An outbreak of severe respiratory illness associated with enterovirus D68 (EV-D68) infection was reported in mid-August 2014 in the United States. In this study, we evaluated the diagnostic utility of an EV-D68-specific real-time reverse transcription-PCR (rRT-PCR) that was recently developed by the Centers for Disease Control and Prevention in clinical samples. Nasopharyngeal (NP) swab specimens from patients in a recent outbreak of respiratory illness in the lower Hudson Valley, New York State, were collected and examined for the presence of human rhinovirus or enterovirus using the FilmArray Respiratory Panel (RP) assay. Samples positive by RP were assessed using EV-D68 rRT-PCR, and the data were compared to results from sequencing analysis of partial VP1 and 5′ untranslated region (5′-UTR) sequences of the EV genome. A total of 285 RP-positive NP specimens (260 from the 2014 outbreak and 25 from 2013) were analyzed by rRT-PCR; EV-D68 was detected in 74 of 285 (26.0%) specimens examined. Data for comparisons between rRT-PCR and sequencing analysis were obtained from 194 NP specimens. EV-D68 detection was confirmed by sequencing analysis in 71 of 74 positive and in 1 of 120 randomly selected negative specimens by rRT-PCR. The EV-D68 rRT-PCR showed diagnostic sensitivity and specificity of 98.6% and 97.5%, respectively. Our data suggest that the EV-D68 rRT-PCR is a reliable assay for detection of EV-D68 in clinical samples and has a potential to be used as a tool for rapid diagnosis and outbreak investigation of EV-D68-associated infections in clinical and public health laboratories. PMID:25854481

Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

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

DETECTION OF OUTBREAK-ASSOCIATED HUMAN CALICIVIRUSES IN GROUNDWATER BY RT-PCR

EPA Science Inventory

Human caliciviruses (HuCV) are a major worldwide cause of food and waterborne outbreaks of acute nonbacterial gastroenteritis, and have been placed on the U.S. Environmental Protection Agency's (U.S. EPA) Contaminant Candidate List (CCL) of agents to be considered for regulatory ...

Missed, Misused, or Mismanaged: Improving Early Detection Systems to Optimize Child Outcomes

ERIC Educational Resources Information Center

Macy, Marisa; Marks, Kevin; Towle, Alexander

2014-01-01

Early detection efforts have been shown to vary greatly in practice, and there is a general lack of systematic accountability built into monitoring early detection effort impact. This article reviews current early detection practices and the drawbacks of these practices, with particular attention given to prevalent issues of mismeasurement,…

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

Detection and management of the first human anthrax outbreak in Togo.

PubMed

Patassi, Akouda Akessiwe; Saka, Bayaki; Landoh, Dadja Essoya; Agbenoko, Kodjo; Tamekloe, Tsidi; Salmon-Ceron, Dominique

2016-07-01

The aim of this study was to describe and define an outbreak of human anthrax in two villages in the northern savannah region of Togo. In December 2009, localised groups of deaths occurred among villagers and their livestock, confirmed to be due to anthrax at the district hospital of Dapaong in Northern Togo. The National Disease Control department undertook an investigation to describe the epidemiological, clinical and bacteriological characteristics of this outbreak. Thirty-four individuals presented with clinical manifestations of anthrax. All patients were known to have consumed meat from cattle who had died of unknown causes or had been killed as a result of unknown illness. All patients presented with muco-cutaneous lesions; some had gastro-intestinal, neurological or meningeal symptoms, or septicaemia. One patient was co-infected with Plasmodium falciparum. Six deaths (17.6%) were reported at the beginning of the epidemic; 28 patients were successfully treated with a 10-day course of intravenous Penicillin or oral Amoxicillin. The two factors that contributed to the ultimate resolution of the anthrax outbreak were the increase of community awareness toward health promotion and vaccination of all farm animals. Although six deaths occurred among families' members who were infected, new human anthrax cases were prevented by rapid treatment of victims as well as aggressive public health interventions. However the risk of re-emergence of infection and exposure still exists as there are no existing epidemiological mapping and no identification of infected zones; and furthermore, no functional anthrax surveillance system exists in the affected region. © The Author(s) 2015.

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.

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.

Effort and Potential Efficiencies for Aquatic Non-native Species Early Detection

EPA Science Inventory

This manuscript is based on the early aquatic non-native species detection research in the Duluth-Superior harbor. The problem of early detection is essentially that of a "needle in a haystack" - to detect a newly arrived and presumably rare non-native species with a high probabi...

Understanding of and possible strategies to avian influenza outbreak.

PubMed

Shen, Junkang; Zhang, Andy; Xu, Huifen; Sirois, Pierre; Zhang, Jia; Li, Kai; Xiao, Li

2013-01-01

Swine flu and avian flu outbreaks have occurred in recent years in addition to seasonal flu. As mortality rate records are not available at the early stage of an outbreak, two parameters may be useful to assess the viral virulence : 1. the time required for the first domestic case in a newly involved region, and 2. the doubling time of new infected cases. Viral virulence is one of the most important factors in guiding short term and immediate responses. Although routine surveillance and repeated vaccination are useful efforts, some novel strategies that may be relevant to prevent and control the spread of influenza among human beings and domestic animals are discussed.

Advances in pancreatic cancer research: moving towards early detection.

PubMed

He, Xiang-Yi; Yuan, Yao-Zong

2014-08-28

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have been significant. However, most patients (nearly 80%) who present with locally advanced or metastatic disease have an extremely poor prognosis. Survival is better for those with malignant disease localized to the pancreas, because surgical resection at present offers the only chance of cure. Therefore, the early detection of pancreatic cancer may benefit patients with PDAC. However, its low rate of incidence and the limitations of current screening strategies make early detection difficult. Recent advances in the understanding of the pathogenesis of PDAC suggest that it is possible to detect PDAC in early stages and even identify precursor lesions. The presence of new-onset diabetes mellitus in the early phase of pancreatic cancer may provide clues for its early diagnosis. Advances in the identification of novel circulating biomarkers including serological signatures, autoantibodies, epigenetic markers, circulating tumor cells and microRNAs suggest that they can be used as potential tools for the screening of precursors and early stage PDAC in the future. However, proper screening strategies based on effective screening methodologies need to be tested for clinical application.

Performance of Rapid Influenza Diagnostic Testing in Outbreak Settings

PubMed Central

Winter, Anne-Luise; King, Eddie-Chong; Blair, Joanne; Gubbay, Jonathan B.

2014-01-01

Rapid influenza diagnostic tests (RIDTs) may be useful during institutional respiratory disease outbreaks to identify influenza and enable antivirals to be rapidly administered to patients and for the prophylactic treatment of those exposed to the virus but not yet symptomatic. The performance of RIDTs at the outbreak level is not well documented in the literature. This study aimed to evaluate the performance of RIDTs in comparison with that of real-time reverse transcription (rRT)-PCR in the context of institutional respiratory disease outbreaks. This study included outbreak-related respiratory specimens tested for influenza virus at Public Health Ontario Laboratories by both RIDT and rRT-PCR, from 1 September 2010 to 30 April 2013. At the outbreak level, performance testing of RIDTs compared to rRT-PCR for the detection of any influenza virus type demonstrated an overall sensitivity of 76.5%, a specificity of 99.7%, a positive predictive value (PPV) of 99.5%, and a negative predictive value of 85.3%. Because of their high specificity and PPV, even outside of the influenza season, RIDTs can play a role in screening for influenza virus in outbreaks and instituting antiviral therapy in a timely manner when positive. RIDTs can also be useful in remote settings where molecular virology testing is not easily accessible. Suboptimal sensitivity of RIDTs can be addressed by the use of molecular testing. PMID:25320225

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830

Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

Surveillance for waterborne-disease outbreaks--United States, 1995-1996.

PubMed

Levy, D A; Bens, M S; Craun, G F; Calderon, R L; Herwaldt, B L

1998-12-11

Since 1971, CDC and the U.S. Environmental Protection Agency have maintained a collaborative surveillance system for collecting and periodically reporting data that relate to occurrences and causes of waterborne-disease outbreaks (WBDOs). This summary includes data for January 1995 through December 1996 and previously unreported outbreaks in 1994. The surveillance system includes data about outbreaks associated with drinking water and recreational water. State, territorial, and local public health departments are primarily responsible for detecting and investigating WBDOs and for voluntarily reporting them to CDC on a standard form. For the period 1995-1996, 13 states reported a total of 22 outbreaks associated with drinking water. These outbreaks caused an estimated total of 2,567 persons to become ill. No deaths were reported. The microbe or chemical that caused the outbreak was identified for 14 (63.6%) of the 22 outbreaks. Giardia lamblia and Shigella sonnei each caused two (9.1%) of the 22 outbreaks; Escherichia coli O157:H7, Plesiomonas shigelloides, and a small round structured virus were implicated for one outbreak (4.5%) each. One of the two outbreaks of giardiasis involved the largest number of cases, with an estimated 1,449 ill persons. Seven outbreaks (31.8% of 22) of chemical poisoning, which involved a total of 90 persons, were reported. Copper and nitrite were associated with two outbreaks (9.1% of 22) each and sodium hydroxide, chlorine, and concentrated liquid soap with one outbreak (4.5%) each. Eleven (50.0%) of the 22 outbreaks were linked to well water, eight in noncommunity and three in community systems. Only three of the 10 outbreaks associated with community water systems were caused by problems at water treatment plants; the other seven resulted from problems in the water distribution systems and plumbing of individual facilities (e.g., a restaurant). Six of the seven outbreaks were associated with chemical contamination of the drinking

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.

An outbreak of Salmonella Typhimurium infections in Denmark, Norway and Sweden, 2008.

PubMed

Bruun, T; Sørensen, G; Forshell, L P; Jensen, T; Nygard, K; Kapperud, G; Lindstedt, B A; Berglund, T; Wingstrand, A; Petersen, R F; Müller, L; Kjelsø, C; Ivarsson, S; Hjertqvist, M; Löfdahl, S; Ethelberg, S

2009-03-12

In November-December 2008, Norway and Denmark independently identified outbreaks of Salmonella Typhimurium infections characterised in the multiple-locus variable number of tandem repeats analysis (MLVA) by a distinct profile. Outbreak investigations were initiated independently in the two countries. In Denmark, a total of 37 cases were identified, and multiple findings of the outbreak strain in pork and pigs within the same supply chain led to the identification of pork in various forms as the source. In Norway, ten cases were identified, and the outbreak investigation quickly indicated meat bought in Sweden as the probable source and the Swedish authorities were alerted. Investigations in Sweden identified four human cases and two isolates from minced meat with the distinct profile. Subsequent trace-back of the meat showed that it most likely originated from Denmark. Through international alert from Norway on 19 December, it became clear that the Danish and Norwegian outbreak strains were identical and, later on, that the source of the outbreaks in all three countries could be traced back to Danish pork. MLVA was instrumental in linking the outbreaks in the different countries and tracing the source. This outbreak illustrates that good international communication channels, early alerting mechanisms, inter-sectoral collaboration between public health and food safety authorities and harmonised molecular typing tools are important for effective identification and management of cross-border outbreaks. Differences in legal requirements for food safety in neighbouring countries may be a challenge in terms of communication with consumers in areas where cross-border shopping is common.

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.

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

[Multiplex PCR strategy for the simultaneous identification of Staphylococcus aureus and detection of staphylococcal enterotoxins in isolates from food poisoning outbreaks].

PubMed

Brizzio, Aníbal A; Tedeschi, Fabián A; Zalazar, Fabián E

2013-01-01

Staphylococcal food poisoning is the most frequent type of food poisoning around the world. Staphylococcus aureus enterotoxins cause significant loss of water in the intestinal lumen, followed by vomiting and diarrhea. To report a fast, reliable and inexpensive strategy based on multiplex PCR for the simultaneous identification of S. aureus and detection of five classical S. aureus enterotoxin genes ( sea, seb, sec, sed, see ) in Staphylococcus spp. strains isolated from food poisoning outbreaks. We analyzed isolates from 12 food poisoning outbreaks occurred in Santa Fe province (Argentina). Isolation and phenotypic characterization were carried out by standard procedures. Genotypic analysis was performed by multiplex PCR, using primers for nuc , sea-see and 16S rRNA genes simultaneously. Of all the strains tested, 58% were found to carry toxigenic genes. Sea and seb toxins were found at the same percentage (29%) while sec, sed and see genes were found in a lower and identical proportion (14%). We did not find more than one different type of S. aureus enterotoxin in the isolates analyzed. The multiplex PCR strategy designed in this work has enabled us to identify strains of S. aureus and detect -at the same time- their enterotoxigenic ability. At present, our efforts are devoted to the detection of genes encoding enterotoxins other than the classical ones, in order to know their impact on staphylococcal food poisoning, as well as to investigate their relevance to our country's public health.

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.

Early detection of emerging forest disease using dispersal estimation and ecological niche modeling.

PubMed

Meentemeyer, Ross K; Anacker, Brian L; Mark, Walter; Rizzo, David M

2008-03-01

Distinguishing the manner in which dispersal limitation and niche requirements control the spread of invasive pathogens is important for prediction and early detection of disease outbreaks. Here, we use niche modeling augmented by dispersal estimation to examine the degree to which local habitat conditions vs. force of infection predict invasion of Phytophthora ramorum, the causal agent of the emerging infectious tree disease sudden oak death. We sampled 890 field plots for the presence of P. ramorum over a three-year period (2003-2005) across a range of host and abiotic conditions with variable proximities to known infections in California, USA. We developed and validated generalized linear models of invasion probability to analyze the relative predictive power of 12 niche variables and a negative exponential dispersal kernel estimated by likelihood profiling. Models were developed incrementally each year (2003, 2003-2004, 2003-2005) to examine annual variability in model parameters and to create realistic scenarios for using models to predict future infections and to guide early-detection sampling. Overall, 78 new infections were observed up to 33.5 km from the nearest known site of infection, with slightly increasing rates of prevalence across time windows (2003, 6.5%; 2003-2004, 7.1%; 2003-2005, 9.6%). The pathogen was not detected in many field plots that contained susceptible host vegetation. The generalized linear modeling indicated that the probability of invasion is limited by both dispersal and niche constraints. Probability of invasion was positively related to precipitation and temperature in the wet season and the presence of the inoculum-producing foliar host Umbellularia californica and decreased exponentially with distance to inoculum sources. Models that incorporated niche and dispersal parameters best predicted the locations of new infections, with accuracies ranging from 0.86 to 0.90, suggesting that the modeling approach can be used to forecast

Giardiasis Outbreak Associated with Asymptomatic Food Handlers in New York State, 2015.

PubMed

Figgatt, Mary; Mergen, Kimberly; Kimelstein, Deborah; Mahoney, Danielle M; Newman, Alexandra; Nicholas, David; Ricupero, Kristen; Cafiero, Theresa; Corry, Daniel; Ade, Julius; Kurpiel, Philip; Madison-Antenucci, Susan; Anand, Madhu

2017-04-12

Giardia duodenalis is a protozoan that causes a gastrointestinal illness called giardiasis. Giardiasis outbreaks in the United States are most commonly associated with waterborne transmission and are less commonly associated with food, person-to-person, and zoonotic transmission. During June to September 2015, an outbreak of 20 giardiasis cases occurred and were epidemiologically linked to a local grocery store chain on Long Island, New York. Further investigation revealed three asymptomatic food handlers were infected with G. duodenalis , and one food handler and one case were coinfected with Cryptosporidium spp. Although G. duodenalis was not detected in food samples, Cryptosporidium was identified in samples of spinach dip and potato salad. The G. duodenalis assemblage and subtype from one of the food handlers matched two outbreak cases for which genotyping could be performed. This outbreak highlights the potential role of asymptomatically infected food handlers in giardiasis outbreaks.

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.

Induced plant defenses, host–pathogen interactions, and forest insect outbreaks

PubMed Central

Elderd, Bret D.; Rehill, Brian J.; Haynes, Kyle J.; Dwyer, Greg

2013-01-01

Cyclic outbreaks of defoliating insects devastate forests, but their causes are poorly understood. Outbreak cycles are often assumed to be driven by density-dependent mortality due to natural enemies, because pathogens and predators cause high mortality and because natural-enemy models reproduce fluctuations in defoliation data. The role of induced defenses is in contrast often dismissed, because toxic effects of defenses are often weak and because induced-defense models explain defoliation data no better than natural-enemy models. Natural-enemy models, however, fail to explain gypsy moth outbreaks in North America, in which outbreaks in forests with a higher percentage of oaks have alternated between severe and mild, whereas outbreaks in forests with a lower percentage of oaks have been uniformly moderate. Here we show that this pattern can be explained by an interaction between induced defenses and a natural enemy. We experimentally induced hydrolyzable-tannin defenses in red oak, to show that induction reduces variability in a gypsy moth’s risk of baculovirus infection. Because this effect can modulate outbreak severity and because oaks are the only genus of gypsy moth host tree that can be induced, we extended a natural-enemy model to allow for spatial variability in inducibility. Our model shows alternating outbreaks in forests with a high frequency of oaks, and uniform outbreaks in forests with a low frequency of oaks, matching the data. The complexity of this effect suggests that detecting effects of induced defenses on defoliator cycles requires a combination of experiments and models. PMID:23966566

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...

Outbreak of caliciviruses in the Singapore military, 2015.

PubMed

Neo, Freddy Jun Xian; Loh, Jimmy Jin Phang; Ting, Peijun; Yeo, Wei Xin; Gao, Christine Qiu Han; Lee, Vernon Jian Ming; Tan, Boon Huan; Ng, Ching Ging

2017-11-14

From 31 August to 9 September 2015, a total of 150 military personnel at a military institution in Singapore were infected with acute gastroenteritis (AGE) with an attack rate of approximately 3%. This study aimed to determine the epidemiology of the outbreak, investigate its origins, and discuss measures to prevent future occurrences. After the AGE outbreak was declared on 31 August 2015, symptom surveys, hygiene inspections, and the testing of water, food, and stool samples were initiated. We collected 86 stool samples from AGE cases and 58 samples from food-handlers during the course of the outbreak and these stool samples were tested for 8 bacterial pathogens and 2 viral pathogens (i.e., norovirus and sapovirus). We detected Sapovirus (SaV), group I Norovirus (NoV GI) and group II Norovirus (NoV GII) from the stool samples of AGE cases. Further sequence analyses showed that the AGE outbreak in August was caused mainly by three rarely reported calicivirus novel genotypes: NoV GI.7, NoV GII.17 and SaV GII.3. Control measures implemented focused on the escalation of personal and environmental hygiene, which included the separation of affected and unaffected soldiers, enforcement of rigorous hand-washing and hygiene, raising awareness of food and water safety, and disinfection of communal areas with bleach. This study identified both NoV and SaV as the causative agents for an AGE outbreak at a Singapore military camp in August 2015. This study is also the first to report SaV as one of the main causative agents, highlighting the importance of caliciviruses as causative agents of AGE outbreaks in the Singapore military. As there are no commercially available vaccines against caliciviruses, strict personal hygiene and proper disinfection of environmental surfaces remain crucial to prevent calicivirus outbreak and transmission.

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.

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.

Prevention of secondary household transmission during Shiga toxin-producing Escherichia coli outbreaks.

PubMed

Tokuda, K; Yahata, Y; Sunagawa, T

2016-10-01

Prevention of secondary household transmission of Shiga toxin-producing Escherichia coli (STEC) is important in outbreak settings. We examined factors contributing to secondary household transmission during STEC outbreaks in daycare centres in Japan. Suspected STEC outbreaks in daycare centres were identified by the National Epidemiological Surveillance of Infectious Diseases. Questionnaires were sent to local health centres that responded to outbreaks. Secondary household transmission rates were calculated, and factors affecting secondary household transmission rate were analysed by multilevel analysis. The secondary household transmission rates in 16 outbreaks ranged from 0% to 34·4% (median 4·4%). The highest rate (23·0%) was observed in siblings aged 6-9 years, and the infection rate was significantly higher for mothers than for fathers and grandparents (P < 0·05). Using multilevel analysis, the following variables were selected in the best model: information provided face-to-face (vs. letter or telephone) to families of children in daycare centres (at initial response), STEC type and lag time (days) between onset and providing information. Early response and hygiene education by visiting local health centre staff may be effective measures to prevent secondary household transmission in STEC outbreaks. Hygiene education should be emphasized for children aged 6-9 years, as well as for younger children.

Comparison of sexual mixing patterns for syphilis in endemic and outbreak settings.

PubMed

Doherty, Irene A; Adimora, Adaora A; Muth, Stephen Q; Serre, Marc L; Leone, Peter A; Miller, William C

2011-05-01

In a largely rural region of North Carolina during 1998-2002, outbreaks of heterosexually transmitted syphilis occurred, 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 sexually transmitted infections (STIs). Using contact tracing data collected by disease intervention specialists, we estimated Newman assortativity coefficients and compared values in counties experiencing syphilis outbreaks to nonoutbreak 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). Individuals in the outbreak counties had more contacts and mixing by the number of sex partners was disassortative in outbreak counties and assortative nonoutbreak counties. Although mixing by syphilis disease stage was minimally assortative in outbreak counties, it was disassortative in nonoutbreak areas. Partnerships were relatively discordant by age, especially among older white men, who often chose considerably younger female partners. 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.

Two pseudo-outbreaks of infectious mononucleosis.

PubMed

Armstrong, C W; Hackler, R L; Miller, G B

1986-01-01

Two outbreaks of suspected infectious mononucleosis (IM) were investigated. In the first outbreak IM was diagnosed in nine children attending a day care center. They had been tested in physicians' offices for heterophile antibody using rapid differential slide tests; all tests had been reported positive. On retesting, none of the suspected cases had detectable serum heterophile antibody. The initial test results had been falsely positive as a result of poor laboratory technique. In the second outbreak IM had been diagnosed in 285 college students. Suspected cases had been found to have serum IgG antibody to the viral capsid antigen of Epstein-Barr virus, but most had not been tested for the presence of heterophile antibody. Retesting of 64 students within 1 month of initial testing yielded only one with heterophile antibody. With the exception of young children (less than 4 years of age), differential slide tests for heterophile antibody are sensitive and specific for recent Epstein-Barr virus infection if properly performed. Viral capsid antigen to Epstein-Barr virus (IgG) titers are of limited usefulness in diagnosing acute IM. The misdiagnosis of IM can be prevented by the appropriate selection, performance and interpretation of diagnostic laboratory tests.

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