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.

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

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.

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

PubMed Central

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

2013-01-01

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

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

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.

Label-Free Detection and Serotyping of Salmonellae by Surface Enhanced Raman Spectroscopy with Immunomagnetic Separation

USDA-ARS?s Scientific Manuscript database

Salmonella spp. are one of the leading causes of foodborne outbreaks in the United States and globally. Current detection and characterization techniques for Salmonella are time consuming and rapid methods could greatly benefit outbreak investigation, new case prevention and disease treatment. In th...

Simultaneous detection and serotyping of Salmonellae by immunomagnetic separation and label-free surface enhanced Raman spectroscopy

USDA-ARS?s Scientific Manuscript database

Salmonella spp. are one of the leading causes of foodborne outbreaks in the United States and globally. Current detection and characterization techniques for Salmonellae are time consuming and costly, and rapid methods could greatly benefit outbreak investigation, new case prevention and disease tre...

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.

Estimating challenge load due to disease outbreaks and other challenges using reproduction records of sows.

PubMed

Mathur, P K; Herrero-Medrano, J M; Alexandri, P; Knol, E F; ten Napel, J; Rashidi, H; Mulder, H A

2014-12-01

A method was developed and tested to estimate challenge load due to disease outbreaks and other challenges in sows using reproduction records. The method was based on reproduction records from a farm with known disease outbreaks. It was assumed that the reduction in weekly reproductive output within a farm is proportional to the magnitude of the challenge. As the challenge increases beyond certain threshold, it is manifested as an outbreak. The reproduction records were divided into 3 datasets. The first dataset called the Training dataset consisted of 57,135 reproduction records from 10,901 sows from 1 farm in Canada with several outbreaks of porcine reproductive and respiratory syndrome (PRRS). The known disease status of sows was regressed on the traits number born alive, number of losses as a combination of still birth and mummified piglets, and number of weaned piglets. The regression coefficients from this analysis were then used as weighting factors for derivation of an index measure called challenge load indicator. These weighting factors were derived with i) a two-step approach using residuals or year-week solutions estimated from a previous step, and ii) a single-step approach using the trait values directly. Two types of models were used for each approach: a logistic regression model and a general additive model. The estimates of challenge load indicator were then compared based on their ability to detect PRRS outbreaks in a Test dataset consisting of records from 65,826 sows from 15 farms in the Netherlands. These farms differed from the Canadian farm with respect to PRRS virus strains, severity and frequency of outbreaks. The single-step approach using a general additive model was best and detected 14 out of the 15 outbreaks. This approach was then further validated using the third dataset consisting of reproduction records of 831,855 sows in 431 farms located in different countries in Europe and America. A total of 41 out of 48 outbreaks detected using data analysis were confirmed based on diagnostic information received from the farms. Among these, 30 outbreaks were due to PRRS while 11 were due to other diseases and challenging conditions. The results suggest that proposed method could be useful for estimation of challenge load and detection of challenge phases such as disease outbreaks.

A Space–Time Permutation Scan Statistic for Disease Outbreak Detection

PubMed Central

Kulldorff, Martin; Heffernan, Richard; Hartman, Jessica; Assunção, Renato; Mostashari, Farzad

2005-01-01

Background The ability to detect disease outbreaks early is important in order to minimize morbidity and mortality through timely implementation of disease prevention and control measures. Many national, state, and local health departments are launching disease surveillance systems with daily analyses of hospital emergency department visits, ambulance dispatch calls, or pharmacy sales for which population-at-risk information is unavailable or irrelevant. Methods and Findings We propose a prospective space–time permutation scan statistic for the early detection of disease outbreaks that uses only case numbers, with no need for population-at-risk data. It makes minimal assumptions about the time, geographical location, or size of the outbreak, and it adjusts for natural purely spatial and purely temporal variation. The new method was evaluated using daily analyses of hospital emergency department visits in New York City. Four of the five strongest signals were likely local precursors to citywide outbreaks due to rotavirus, norovirus, and influenza. The number of false signals was at most modest. Conclusion If such results hold up over longer study times and in other locations, the space–time permutation scan statistic will be an important tool for local and national health departments that are setting up early disease detection surveillance systems. PMID:15719066

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

PubMed

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

2018-04-24

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

Whole genome sequencing may not be adequate to determine genome relatedness for surveillance and outbreak investigation of foodborne pathogens

USDA-ARS?s Scientific Manuscript database

Introduction: Advances in genomic technologies have improve the speed and precision of foodborne disease outbreak detection and response. For the past two decades, pulsed field gel electrophoresis (PFGE) has been the method of choice for surveillance and outbreak investigation with foodborne pathoge...

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

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.

DETECTION OF CRYPTOSPORIDIUM OOCYSTS IN WATER MATRICES

EPA Science Inventory

Since the advent and recognition of waterborne outbreaks of cryptosporidiosis great effort has been expended on development of methods for detecting Cryptosporidium oocysts in water. Oocysts recovery rates using a method originally developed for detecting Giardia cysts ranged fr...

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

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

Optimizing the response to surveillance alerts in automated surveillance systems.

PubMed

Izadi, Masoumeh; Buckeridge, David L

2011-02-28

Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice. Copyright © 2011 John Wiley & Sons, Ltd.

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

PubMed

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

2013-01-01

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

Novel microbiological and spatial statistical methods to improve strength of epidemiological evidence in a community-wide waterborne outbreak.

PubMed

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9-16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak.

Detection of Staphylococcal Enterotoxin in Food

PubMed Central

Casman, Ezra P.; Bennett, Reginald W.

1965-01-01

Methods are described for the extraction and serological detection of trace amounts of enterotoxins A and B in foods incriminated in outbreaks of staphylococcal food poisoning. Evidence is presented for the probable applicability of the methods for the detection of unidentified enterotoxins. PMID:14325876

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.

Satellite data based method for general survey of forest insect disturbance in British Columbia

NASA Astrophysics Data System (ADS)

Ranson, J.; Montesano, P.

2008-12-01

Regional forest disturbances caused by insects are important to monitor and quantify because of their influence on local ecosystems and the global carbon cycle. Local damage to forest trees disrupts food supplies and shelter for a variety of organisms. Changes in the global carbon budget, its sources and its sinks affect the way the earth functions as a whole, and has an impact on global climate. Furthermore, the ability to detect nascent outbreaks and monitor the spread of regional infestations helps managers mitigate the damage done by catastrophic insect outbreaks. While detection is needed at a fine scale to support local mitigation efforts, detection at a broad regional scale is important for carbon flux modeling on the landscape scale, and needed to direct the local efforts. This paper presents a method for routinely detecting insect damage to coniferous forests using MODIS vegetation indices, thermal anomalies and land cover. The technique is validated using insect outbreak maps and accounts for fire disturbance effects. The range of damage detected may be used to interpret and quantify possible forest damage by insects.

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

TESTING METHODS FOR DETECTION OF CRYPTOSPORIDIUM SPP. IN WATER SAMPLES

EPA Science Inventory

A large waterborne outbreak of cryptosporidiosis in Milwaukee, Wisconsin, U.S.A. in 1993 prompted a search for ways to prevent large scale waterborne outbreaks of protozoan parasitoses. Two principle strategies have emerged: risk assessment leading to appropriate treatment and ...

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2008-06-01

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

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

Development of a fast and efficient method for hepatitis A virus concentration from green onion.

PubMed

Zheng, Yan; Hu, Yuan

2017-11-01

Hepatitis A virus (HAV) can cause serious liver disease and even death. HAV outbreaks are associated with the consumption of raw or minimally processed produce, making it a major public health concern. Infections have occurred despite the fact that effective HAV vaccine has been available. Development of a rapid and sensitive HAV detection method is necessary for an investigation of an HAV outbreak. Detection of HAV is complicated by the lack of a reliable culture method. In addition, due to the low infectious dose of HAV, these methods must be very sensitive. Current methods rely on efficient sample preparation and concentration steps followed by sensitive molecular detection techniques. Using green onions which was involved in most recent HAV outbreaks as a representative produce, a method of capturing virus particles was developed using carboxyl-derivatized magnetic beads in this study. Carboxyl beads, like antibody-coated beads or cationic beads, detect HAV at a level as low as 100 pfu/25g of green onions. RNA from virus concentrated in this manner can be released by heat-shock (98°C 5min) for molecular detection without sacrificing sensitivity. Bypassing the RNA extraction procedure saves time and removes multiple manipulation steps, which makes large scale HAV screening possible. In addition, the inclusion of beef extract and pectinase rather than NP40 in the elution buffer improved the HAV liberation from the food matrix over current methods by nearly 10 fold. The method proposed in this study provides a promising tool to improve food risk assessment and protect public health. Published by Elsevier B.V.

Novel Microbiological and Spatial Statistical Methods to Improve Strength of Epidemiological Evidence in a Community-Wide Waterborne Outbreak

PubMed Central

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W.; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9–16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak. PMID:25147923

Multilocus variable-number tandem repeat analysis distinguishes outbreak and sporadic Escherichia coli O157:H7 isolates.

PubMed

Noller, Anna C; McEllistrem, M Catherine; Pacheco, Antonio G F; Boxrud, David J; Harrison, Lee H

2003-12-01

Escherichia coli O157:H7 is a major cause of food-borne illness in the United States. Outbreak detection involves traditional epidemiological methods and routine molecular subtyping by pulsed-field gel electrophoresis (PFGE). PFGE is labor-intensive, and the results are difficult to analyze and not easily transferable between laboratories. Multilocus variable-number tandem repeat (VNTR) analysis (MLVA) is a fast, portable method that analyzes multiple VNTR loci, which are areas of the bacterial genome that evolve quickly. Eighty isolates, including 21 isolates from five epidemiologically well-characterized outbreaks from Pennsylvania and Minnesota, were analyzed by PFGE and MLVA. Strains in PFGE clusters were defined as strains that differed by less than or equal to one band by using XbaI and the confirmatory enzyme SpeI. MLVA was performed by comparing the number of tandem repeats at seven loci. From 6 to 30 alleles were found at the seven loci, resulting in 64 MLVA types among the 80 isolates. MLVA correctly identified the isolates from all five outbreaks if only a single-locus variant was allowed. MLVA differentiated strains with unique PFGE types. Additionally, MLVA discriminated strains within PFGE-defined clusters that were not known to be part of an outbreak. In addition to being a simple and validated method for E. coli O157:H7 outbreak detection, MLVA appears to have a sensitivity equal to that of PFGE and a specificity superior to that of PFGE.

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.

Coccidioidomycosis Outbreaks, United States and Worldwide, 1940-2015.

PubMed

Freedman, Michael; Jackson, Brendan R; McCotter, Orion; Benedict, Kaitlin

2018-03-01

Coccidioidomycosis causes substantial illness and death in the United States each year. Although most cases are sporadic, outbreaks provide insight into the clinical and environmental features of coccidioidomycosis, high-risk activities, and the geographic range of Coccidioides fungi. We identified reports published in English of 47 coccidioidomycosis outbreaks worldwide that resulted in 1,464 cases during 1940-2015. Most (85%) outbreaks were associated with environmental exposures; the 2 largest outbreaks resulted from an earthquake and a large dust storm. More than one third of outbreaks occurred in areas where the fungus was not previously known to be endemic, and more than half of outbreaks involved occupational exposures. Coccidioidomycosis outbreaks can be difficult to detect and challenging to prevent given the unknown effectiveness of environmental control methods and personal protective equipment; therefore, increased awareness of coccidioidomycosis outbreaks is needed among public health professionals, healthcare providers, and the public.

Coccidioidomycosis Outbreaks, United States and Worldwide, 1940–2015

PubMed Central

Freedman, Michael; Jackson, Brendan R.; McCotter, Orion

2018-01-01

Coccidioidomycosis causes substantial illness and death in the United States each year. Although most cases are sporadic, outbreaks provide insight into the clinical and environmental features of coccidioidomycosis, high-risk activities, and the geographic range of Coccidioides fungi. We identified reports published in English of 47 coccidioidomycosis outbreaks worldwide that resulted in 1,464 cases during 1940–2015. Most (85%) outbreaks were associated with environmental exposures; the 2 largest outbreaks resulted from an earthquake and a large dust storm. More than one third of outbreaks occurred in areas where the fungus was not previously known to be endemic, and more than half of outbreaks involved occupational exposures. Coccidioidomycosis outbreaks can be difficult to detect and challenging to prevent given the unknown effectiveness of environmental control methods and personal protective equipment; therefore, increased awareness of coccidioidomycosis outbreaks is needed among public health professionals, healthcare providers, and the public. PMID:29460741

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

A MULTIPLEX REVERSE TRANSCIPTION-PCR METHOD FOR DETECTION OF HUMAN ENTERIC VIRUSES IN GROUNDWATER

EPA Science Inventory

Untreated groundwater is responsible for about half of the waterborne disease outbreaks in the United States. Human enteric viruses are thought to be leading etiological agents of many of these outbreaks, but there is relatively little information on the types and levels of viru...

Data-Driven Risk Assessment from Small Scale Epidemics: Estimation and Model Choice for Spatio-Temporal Data with Application to a Classical Swine Fever Outbreak

PubMed Central

Gamado, Kokouvi; Marion, Glenn; Porphyre, Thibaud

2017-01-01

Livestock epidemics have the potential to give rise to significant economic, welfare, and social costs. Incursions of emerging and re-emerging pathogens may lead to small and repeated outbreaks. Analysis of the resulting data is statistically challenging but can inform disease preparedness reducing potential future losses. We present a framework for spatial risk assessment of disease incursions based on data from small localized historic outbreaks. We focus on between-farm spread of livestock pathogens and illustrate our methods by application to data on the small outbreak of Classical Swine Fever (CSF) that occurred in 2000 in East Anglia, UK. We apply models based on continuous time semi-Markov processes, using data-augmentation Markov Chain Monte Carlo techniques within a Bayesian framework to infer disease dynamics and detection from incompletely observed outbreaks. The spatial transmission kernel describing pathogen spread between farms, and the distribution of times between infection and detection, is estimated alongside unobserved exposure times. Our results demonstrate inference is reliable even for relatively small outbreaks when the data-generating model is known. However, associated risk assessments depend strongly on the form of the fitted transmission kernel. Therefore, for real applications, methods are needed to select the most appropriate model in light of the data. We assess standard Deviance Information Criteria (DIC) model selection tools and recently introduced latent residual methods of model assessment, in selecting the functional form of the spatial transmission kernel. These methods are applied to the CSF data, and tested in simulated scenarios which represent field data, but assume the data generation mechanism is known. Analysis of simulated scenarios shows that latent residual methods enable reliable selection of the transmission kernel even for small outbreaks whereas the DIC is less reliable. Moreover, compared with DIC, model choice based on latent residual assessment correlated better with predicted risk. PMID:28293559

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009-2010.

PubMed

Shak, Emma B; France, Anne Marie; Cowan, Lauren; Starks, Angela M; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009-December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups.

Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009–2010

PubMed Central

Shak, Emma B.; Cowan, Lauren; Starks, Angela M.; Grant, Juliana

2015-01-01

Genotyping of Mycobacterium tuberculosis isolates contributes to tuberculosis (TB) control through detection of possible outbreaks. However, 20% of U.S. cases do not have an isolate for testing, and 10% of cases with isolates do not have a genotype reported. TB outbreaks in populations with incomplete genotyping data might be missed by genotyping-based outbreak detection. Therefore, we assessed the representativeness of TB genotyping data by comparing characteristics of cases reported during January 1, 2009–December 31, 2010, that had a genotype result with those cases that did not. Of 22,476 cases, 14,922 (66%) had a genotype result. Cases without genotype results were more likely to be patients <19 years of age, with unknown HIV status, of female sex, U.S.-born, and with no recent history of homelessness or substance abuse. Although cases with a genotype result are largely representative of all reported U.S. TB cases, outbreak detection methods that rely solely on genotyping data may underestimate TB transmission among certain groups. PMID:26556930

Comparison of Molecular Typing Methods Useful for Detecting Clusters of Campylobacter jejuni and C. coli Isolates through Routine Surveillance

PubMed Central

Taboada, Eduardo; Grant, Christopher C. R.; Blakeston, Connie; Pollari, Frank; Marshall, Barbara; Rahn, Kris; MacKinnon, Joanne; Daignault, Danielle; Pillai, Dylan; Ng, Lai-King

2012-01-01

Campylobacter spp. may be responsible for unreported outbreaks of food-borne disease. The detection of these outbreaks is made more difficult by the fact that appropriate methods for detecting clusters of Campylobacter have not been well defined. We have compared the characteristics of five molecular typing methods on Campylobacter jejuni and C. coli isolates obtained from human and nonhuman sources during sentinel site surveillance during a 3-year period. Comparative genomic fingerprinting (CGF) appears to be one of the optimal methods for the detection of clusters of cases, and it could be supplemented by the sequencing of the flaA gene short variable region (flaA SVR sequence typing), with or without subsequent multilocus sequence typing (MLST). Different methods may be optimal for uncovering different aspects of source attribution. Finally, the use of several different molecular typing or analysis methods for comparing individuals within a population reveals much more about that population than a single method. Similarly, comparing several different typing methods reveals a great deal about differences in how the methods group individuals within the population. PMID:22162562

Waterborne Pathogens: Detection Methods and Challenges

PubMed Central

Ramírez-Castillo, Flor Yazmín; Loera-Muro, Abraham; Jacques, Mario; Garneau, Philippe; Avelar-González, Francisco Javier; Harel, Josée; Guerrero-Barrera, Alma Lilián

2015-01-01

Waterborne pathogens and related diseases are a major public health concern worldwide, not only by the morbidity and mortality that they cause, but by the high cost that represents their prevention and treatment. These diseases are directly related to environmental deterioration and pollution. Despite the continued efforts to maintain water safety, waterborne outbreaks are still reported globally. Proper assessment of pathogens on water and water quality monitoring are key factors for decision-making regarding water distribution systems’ infrastructure, the choice of best water treatment and prevention waterborne outbreaks. Powerful, sensitive and reproducible diagnostic tools are developed to monitor pathogen contamination in water and be able to detect not only cultivable pathogens but also to detect the occurrence of viable but non-culturable microorganisms as well as the presence of pathogens on biofilms. Quantitative microbial risk assessment (QMRA) is a helpful tool to evaluate the scenarios for pathogen contamination that involve surveillance, detection methods, analysis and decision-making. This review aims to present a research outlook on waterborne outbreaks that have occurred in recent years. This review also focuses in the main molecular techniques for detection of waterborne pathogens and the use of QMRA approach to protect public health. PMID:26011827

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2015-08-01

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

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.

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

PubMed

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

2017-06-12

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

Real-Time PCR Typing of Escherichia coli Based on Multiple Single Nucleotide Polymorphisms--a Convenient and Rapid Method.

PubMed

Lager, Malin; Mernelius, Sara; Löfgren, Sture; Söderman, Jan

2016-01-01

Healthcare-associated infections caused by Escherichia coli and antibiotic resistance due to extended-spectrum beta-lactamase (ESBL) production constitute a threat against patient safety. To identify, track, and control outbreaks and to detect emerging virulent clones, typing tools of sufficient discriminatory power that generate reproducible and unambiguous data are needed. A probe based real-time PCR method targeting multiple single nucleotide polymorphisms (SNP) was developed. The method was based on the multi locus sequence typing scheme of Institute Pasteur and by adaptation of previously described typing assays. An 8 SNP-panel that reached a Simpson's diversity index of 0.95 was established, based on analysis of sporadic E. coli cases (ESBL n = 27 and non-ESBL n = 53). This multi-SNP assay was used to identify the sequence type 131 (ST131) complex according to the Achtman's multi locus sequence typing scheme. However, it did not fully discriminate within the complex but provided a diagnostic signature that outperformed a previously described detection assay. Pulsed-field gel electrophoresis typing of isolates from a presumed outbreak (n = 22) identified two outbreaks (ST127 and ST131) and three different non-outbreak-related isolates. Multi-SNP typing generated congruent data except for one non-outbreak-related ST131 isolate. We consider multi-SNP real-time PCR typing an accessible primary generic E. coli typing tool for rapid and uniform type identification.

[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.

Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE.

PubMed

Burkom, Howard S; Elbert, Y; Feldman, A; Lin, J

2004-09-24

Syndromic surveillance systems are used to monitor daily electronic data streams for anomalous counts of features of varying specificity. The monitored quantities might be counts of clinical diagnoses, sales of over-the-counter influenza remedies, school absenteeism among a given age group, and so forth. Basic data-aggregation decisions for these systems include determining which records to count and how to group them in space and time. This paper discusses the application of spatial and temporal data-aggregation strategies for multiple data streams to alerting algorithms appropriate to the surveillance region and public health threat of interest. Such a strategy was applied and evaluated for a complex, authentic, multisource, multiregion environment, including >2 years of data records from a system-evaluation exercise for the Defense Advanced Research Project Agency (DARPA). Multivariate and multiple univariate statistical process control methods were adapted and applied to the DARPA data collection. Comparative parametric analyses based on temporal aggregation were used to optimize the performance of these algorithms for timely detection of a set of outbreaks identified in the data by a team of epidemiologists. The sensitivity and timeliness of the most promising detection methods were tested at empirically calculated thresholds corresponding to multiple practical false-alert rates. Even at the strictest false-alert rate, all but one of the outbreaks were detected by the best method, and the best methods achieved a 1-day median time before alert over the set of test outbreaks. These results indicate that a biosurveillance system can provide a substantial alerting-timeliness advantage over traditional public health monitoring for certain outbreaks. Comparative analyses of individual algorithm results indicate further achievable improvement in sensitivity and specificity.

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

PubMed Central

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

2018-01-01

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

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.

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.

The scenario of norovirus contamination in food and food handlers.

PubMed

Tuan Zainazor, C; Hidayah, M S Noor; Chai, L C; Tunung, R; Ghazali, F Mohamad; Son, R

2010-02-01

Recently, many cases related to viral gastroenteritis outbreaks have been reported all over the world. Noroviruses are found to be leading as the major cause of outbreaks of acute gastroenteritis. Patients with the acute gastroenteritis normally found to be positive with norovirus when stools and vomit were analyzed. This paper reviews various activities and previous reports that describe norovirus contaminated in various food matrixes and relationship between food handlers. Lately, a numbers of norovirus outbreaks have been reported which are involved fresh produce (such as vegetables, fruits), shellfish and prepared food. Food produces by infected food handlers may therefore easily contaminated. In addition, food that required much handling and have been eaten without heat treatment gave the high risk for getting foodborne illnesses. The standard method for detection of norovirus has already been available for stool samples. However, only few methods for detection of norovirus in food samples have been developed until now.

Interdigitated microelectrode based impedance biosensor for detection of salmonella enteritidis in food samples

NASA Astrophysics Data System (ADS)

Kim, G.; Morgan, M.; Hahm, B. K.; Bhunia, A.; Mun, J. H.; Om, A. S.

2008-03-01

Salmonella enteritidis outbreaks continue to occur, and S. enteritidis-related outbreaks from various food sources have increased public awareness of this pathogen. Conventional methods for pathogens detection and identification are labor-intensive and take days to complete. Some immunological rapid assays are developed, but these assays still require prolonged enrichment steps. Recently developed biosensors have shown great potential for the rapid detection of foodborne pathogens. To develop the biosensor, an interdigitated microelectrode (IME) was fabricated by using semiconductor fabrication process. Anti-Salmonella antibodies were immobilized based on avidin-biotin binding on the surface of the IME to form an active sensing layer. To increase the sensitivity of the sensor, three types of sensors that have different electrode gap sizes (2 μm, 5 μm, 10 μm) were fabricated and tested. The impedimetric biosensor could detect 103 CFU/mL of Salmonella in pork meat extract with an incubation time of 5 minutes. This method may provide a simple, rapid and sensitive method to detect foodborne pathogens.

Nosocomial Transmission of Respiratory Syncytial Virus in an Outpatient Cancer Center

PubMed Central

Chu, Helen Y.; Englund, Janet A.; Podczervinski, Sara; Kuypers, Jane; Campbell, Angela P.; Boeckh, Michael; Pergam, Steven A.; Casper, Crey

2014-01-01

Background Respiratory syncytial virus (RSV) outbreaks in inpatient settings are associated with poor outcomes in cancer patients. The use of molecular epidemiology to document RSV transmission in the outpatient setting has not been well described. Methods We performed a retrospective cohort study of two nosocomial outbreaks of RSV at the Seattle Cancer Care Alliance (SCCA). Subjects included patients seen at the SCCA with RSV detected in two outbreaks in 2007-2008 and 2012, and all employees with respiratory viruses detected in the 2007-2008 outbreak. A subset of samples was sequenced using semi-nested polymerase chain reaction targeting the RSV attachment glycoprotein coding region. Results Fifty-one cases of RSV were identified in 2007-2008. Clustering of identical viral strains was detected in 10 (67%) of 15 patients with RSV sequenced from 2007-2008. As part of a multimodal infection control strategy implemented as a response to the outbreak, symptomatic employees had nasal washes collected. Of 254 employee samples, 91 (34%) tested positive for a respiratory virus, including 14 with RSV. In another RSV outbreak in 2012, 24 cases of RSV were identified; nine (90%) of 10 patients had the same viral strain, and 1 (10%) had another viral strain. Conclusions We document spread of clonal strains within an outpatient cancer care setting. Infection control interventions should be implemented in outpatient, as well as inpatient, settings to reduce person-to-person transmission and limit progression of RSV outbreaks. PMID:24607551

Social Network Sensors for Early Detection of Contagious Outbreaks

PubMed Central

Christakis, Nicholas A.; Fowler, James H.

2010-01-01

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

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

PubMed

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

2016-01-29

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

Scabies outbreaks in residential care homes: factors associated with late recognition, burden and impact. A mixed methods study in England.

PubMed

Hewitt, K A; Nalabanda, A; Cassell, J A

2015-05-01

Scabies is an important public health problem in residential care homes. Delayed diagnosis contributes to outbreaks, which may be prolonged and difficult to control. We investigated factors influencing outbreak recognition, diagnosis and treatment, and staff experiences of outbreak control, identifying areas for intervention. We carried out a semi-structured survey of managers, affected residents and staff of seven care homes reporting suspected scabies outbreaks in southern England over a 6-month period. Attack rates ranged from 2% to 50%, and most cases had dementia (37/39, 95%). Cases were diagnosed clinically by GPs (59%) or home staff (41%), none by dermatologists. Most outbreaks were attributable to avoidably late diagnosis of the index case. Participants reported considerable challenges in managing scabies outbreaks, including late diagnosis and recognition of outbreaks; logistically difficult mass treatment; distressing treatment processes and high costs. This study demonstrates the need for improved support for care homes in detecting and managing these outbreaks.

Metagenomic Analysis of Viruses in Feces from Unsolved Outbreaks of Gastroenteritis in Humans

PubMed Central

Moore, Nicole E.; Wang, Jing; Hewitt, Joanne; Croucher, Dawn; Williamson, Deborah A.; Paine, Shevaun; Yen, Seiha; Greening, Gail E.

2014-01-01

The etiology of an outbreak of gastroenteritis in humans cannot always be determined, and ∼25% of outbreaks remain unsolved in New Zealand. It is hypothesized that novel viruses may account for a proportion of unsolved cases, and new unbiased high-throughput sequencing methods hold promise for their detection. Analysis of the fecal metagenome can reveal the presence of viruses, bacteria, and parasites which may have evaded routine diagnostic testing. Thirty-one fecal samples from 26 gastroenteritis outbreaks of unknown etiology occurring in New Zealand between 2011 and 2012 were selected for de novo metagenomic analysis. A total data set of 193 million sequence reads of 150 bp in length was produced on an Illumina MiSeq. The metagenomic data set was searched for virus and parasite sequences, with no evidence of novel pathogens found. Eight viruses and one parasite were detected, each already known to be associated with gastroenteritis, including adenovirus, rotavirus, sapovirus, and Dientamoeba fragilis. In addition, we also describe the first detection of human parechovirus 3 (HPeV3) in Australasia. Metagenomics may thus provide a useful audit tool when applied retrospectively to determine where routine diagnostic processes may have failed to detect a pathogen. PMID:25339401

Waterborne disease outbreak detection: an integrated approach using health administrative databases.

PubMed

Coly, S; Vincent, N; Vaissiere, E; Charras-Garrido, M; Gallay, A; Ducrot, C; Mouly, D

2017-08-01

Hundreds of waterborne disease outbreaks (WBDO) of acute gastroenteritis (AGI) due to contaminated tap water are reported in developed countries each year. Such outbreaks are probably under-detected. The aim of our study was to develop an integrated approach to detect and study clusters of AGI in geographical areas with homogeneous exposure to drinking water. Data for the number of AGI cases are available at the municipality level while exposure to tap water depends on drinking water networks (DWN). These two geographical units do not systematically overlap. This study proposed to develop an algorithm which would match the most relevant grouping of municipalities with a specific DWN, in order that tap water exposure can be taken into account when investigating future disease outbreaks. A space-time detection method was applied to the grouping of municipalities. Seven hundred and fourteen new geographical areas (groupings of municipalities) were obtained compared with the 1,310 municipalities and the 1,706 DWN. Eleven potential WBDO were identified in these groupings of municipalities. For ten of them, additional environmental investigations identified at least one event that could have caused microbiological contamination of DWN in the days previous to the occurrence of a reported WBDO.

Automated real time constant-specificity surveillance for disease outbreaks.

PubMed

Wieland, Shannon C; Brownstein, John S; Berger, Bonnie; Mandl, Kenneth D

2007-06-13

For real time surveillance, detection of abnormal disease patterns is based on a difference between patterns observed, and those predicted by models of historical data. The usefulness of outbreak detection strategies depends on their specificity; the false alarm rate affects the interpretation of alarms. We evaluate the specificity of five traditional models: autoregressive, Serfling, trimmed seasonal, wavelet-based, and generalized linear. We apply each to 12 years of emergency department visits for respiratory infection syndromes at a pediatric hospital, finding that the specificity of the five models was almost always a non-constant function of the day of the week, month, and year of the study (p < 0.05). We develop an outbreak detection method, called the expectation-variance model, based on generalized additive modeling to achieve a constant specificity by accounting for not only the expected number of visits, but also the variance of the number of visits. The expectation-variance model achieves constant specificity on all three time scales, as well as earlier detection and improved sensitivity compared to traditional methods in most circumstances. Modeling the variance of visit patterns enables real-time detection with known, constant specificity at all times. With constant specificity, public health practitioners can better interpret the alarms and better evaluate the cost-effectiveness of surveillance systems.

Category-Specific Comparison of Univariate Alerting Methods for Biosurveillance Decision Support

PubMed Central

Elbert, Yevgeniy; Hung, Vivian; Burkom, Howard

2013-01-01

Objective For a multi-source decision support application, we sought to match univariate alerting algorithms to surveillance data types to optimize detection performance. Introduction Temporal alerting algorithms commonly used in syndromic surveillance systems are often adjusted for data features such as cyclic behavior but are subject to overfitting or misspecification errors when applied indiscriminately. In a project for the Armed Forces Health Surveillance Center to enable multivariate decision support, we obtained 4.5 years of out-patient, prescription and laboratory test records from all US military treatment facilities. A proof-of-concept project phase produced 16 events with multiple evidence corroboration for comparison of alerting algorithms for detection performance. We used the representative streams from each data source to compare sensitivity of 6 algorithms to injected spikes, and we used all data streams from 16 known events to compare them for detection timeliness. Methods The six methods compared were: Holt-Winters generalized exponential smoothing method (1)automated choice between daily methods, regression and an exponential weighted moving average (2)adaptive daily Shewhart-type chartadaptive one-sided daily CUSUMEWMA applied to 7-day means with a trend correction; and7-day temporal scan statistic Sensitivity testing: We conducted comparative sensitivity testing for categories of time series with similar scales and seasonal behavior. We added multiples of the standard deviation of each time series as single-day injects in separate algorithm runs. For each candidate method, we then used as a sensitivity measure the proportion of these runs for which the output of each algorithm was below alerting thresholds estimated empirically for each algorithm using simulated data streams. We identified the algorithm(s) whose sensitivity was most consistently high for each data category. For each syndromic query applied to each data source (outpatient, lab test orders, and prescriptions), 502 authentic time series were derived, one for each reporting treatment facility. Data categories were selected in order to group time series with similar expected algorithm performance: Median > 100 < Median ≤ 10Median = 0Lag 7 Autocorrelation Coefficient ≥ 0.2Lag 7 Autocorrelation Coefficient < 0.2 Timeliness testing: For the timeliness testing, we avoided artificiality of simulated signals by measuring alerting detection delays in the 16 corroborated outbreaks. The multiple time series from these events gave a total of 141 time series with outbreak intervals for timeliness testing. The following measures were computed to quantify timeliness of detection: Median Detection Delay – median number of days to detect the outbreak.Penalized Mean Detection Delay –mean number of days to detect the outbreak with outbreak misses penalized as 1 day plus the maximum detection time. Results Based on the injection results, the Holt-Winters algorithm was most sensitive among time series with positive medians. The adaptive CUSUM and the Shewhart methods were most sensitive for data streams with median zero. Table 1 provides timeliness results using the 141 outbreak-associated streams on sparse (Median=0) and non-sparse data categories. [Insert table #1 here] Data median Detection Delay, days Holt-winters Regression EWMA Adaptive Shewhart Adaptive CUSUM 7-day Trend-adj. EWMA 7-day Temporal Scan Median 0 Median 3 2 4 2 4.5 2 Penalized Mean 7.2 7 6.6 6.2 7.3 7.6 Median >0 Median 2 2 2.5 2 6 4 Penalized Mean 6.1 7 7.2 7.1 7.7 6.6 The gray shading in the table 1 indicates methods with shortest detection delays for sparse and non-sparse data streams. The Holt-Winters method was again superior for non-sparse data. For data with median=0, the adaptive CUSUM was superior for a daily false alarm probability of 0.01, but the Shewhart method was timelier for more liberal thresholds. Conclusions Both kinds of detection performance analysis showed the method based on Holt-Winters exponential smoothing superior on non-sparse time series with day-of-week effects. The adaptive CUSUM and She-whart methods proved optimal on sparse data and data without weekly patterns.

Label-free detection of salmonella typhimurium with ssDNA aptamers

USDA-ARS?s Scientific Manuscript database

Foodborne pathogen Salmonella enterica is one of the major causes of gastrointestinal infections in human and animals. Conventional detection methods are time consuming and not effective enough under emergency circumstances to control outbreaks immediately. Therefore, biosensors that can detect Salm...

The utility and public health implications of PCR and whole genome sequencing for the detection and investigation of an outbreak of Shiga toxin-producing Escherichia coli serogroup O26:H11.

PubMed

Dallman, T J; Byrne, L; Launders, N; Glen, K; Grant, K A; Jenkins, C

2015-06-01

Many serogroups of Shiga toxin-producing Escherichia coli (STEC) other than serogroup O157 (non-O157 STEC), for example STEC O26:H11, are highly pathogenic and capable of causing haemolytic uraemic syndrome. A recent increase in non-O157 STEC cases identified in England, resulting from a change in the testing paradigm, prompted a review of the current methods available for detection and typing of non-O157 STEC for surveillance and outbreak investigations. Nineteen STEC O26:H11 strains, including four from a nursery outbreak were selected to assess typing methods. Serotyping and multilocus sequence typing were not able to discriminate between the stx-producing strains in the dataset. However, genome sequencing provided rapid and robust confirmation that isolates of STEC O26:H11 associated with a nursery outbreak were linked at the molecular level, had a common source and were distinct from the other strains analysed. Virulence gene profiling of DNA extracted from a polymerase chain reaction (PCR)-positive/culture-negative faecal specimen from a case that was epidemiologically linked to the STEC O26:H11 nursery outbreak, provided evidence at the molecular level to support that link. During this study, we describe the utility of PCR and the genome sequencing approach in facilitating surveillance and enhancing the response to outbreaks of non-O157 STEC.

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

PubMed

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

2010-11-01

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

Neglected waterborne parasitic protozoa and their detection in water.

PubMed

Plutzer, Judit; Karanis, Panagiotis

2016-09-15

Outbreak incidents raise the question of whether the less frequent aetiological agents of outbreaks are really less frequent in water. Alternatively, waterborne transmission could be relevant, but the lack of attention and rapid, sensitive methods to recover and detect the exogenous stages in water may keep them under-recognized. High quality information on the prevalence and detection of less frequent waterborne protozoa, such as Cyclospora cayetanensis, Toxoplasma gondii, Isospora belli, Balantidium coli, Blastocystis hominis, Entamoeba histolytica and other free-living amoebae (FLA), are not available. This present paper discusses the detection tools applied for the water surveillance of the neglected waterborne protozoa mentioned above and provides future perspectives. Copyright © 2016 Elsevier Ltd. All rights reserved.

Causes of Pneumonia Epizootics among Bighorn Sheep, Western United States, 2008–2010

PubMed Central

Highland, Margaret A.; Baker, Katherine; Cassirer, E. Frances; Anderson, Neil J.; Ramsey, Jennifer M.; Mansfield, Kristin; Bruning, Darren L.; Wolff, Peregrine; Smith, Joshua B.; Jenks, Jonathan A.

2012-01-01

Epizootic pneumonia of bighorn sheep is a devastating disease of uncertain etiology. To help clarify the etiology, we used culture and culture-independent methods to compare the prevalence of the bacterial respiratory pathogens Mannheimia haemolytica, Bibersteinia trehalosi, Pasteurella multocida, and Mycoplasma ovipneumoniae in lung tissue from 44 bighorn sheep from herds affected by 8 outbreaks in the western United States. M. ovipneumoniae, the only agent detected at significantly higher prevalence in animals from outbreaks (95%) than in animals from unaffected healthy populations (0%), was the most consistently detected agent and the only agent that exhibited single strain types within each outbreak. The other respiratory pathogens were frequently but inconsistently detected, as were several obligate anaerobic bacterial species, all of which might represent secondary or opportunistic infections that could contribute to disease severity. These data provide evidence that M. ovipneumoniae plays a primary role in the etiology of epizootic pneumonia of bighorn sheep. PMID:22377321

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.

Quantification and molecular characterization of Salmonella isolated from food samples involved in salmonellosis outbreaks in Rio Grande do Sul, Brazil

PubMed Central

Mürmann, Lisandra; dos Santos, Maria Cecília; Longaray, Solange Mendes; Both, Jane Mari Corrêa; Cardoso, Marisa

2008-01-01

Data concerning the prevalence and populations of Salmonella in foods implicated in outbreaks may be important to the development of quantitative microbial risk assessments of individual food products. In this sense, the objective of the present study was to assess the amount of Salmonella sp. in different foods implicated in foodborne outbreaks in Rio Grande do Sul occurred in 2005 and to characterize the isolated strains using phenotypic and genotypic methods. Nineteen food samples involved in ten foodborne outbreaks occurred in 2005, and positive on Salmonella isolation at the Central Laboratory of the Health Department of the State of Rio Grande do Sul, were included in this study. Food samples were submitted to estimation of Salmonella using the Most Probable Number (MPN) technique. Moreover, one confirmed Salmonella colony of each food sample was serotyped, characterized by its XbaI-macrorestriction profile, and submitted to antimicrobial resistance testing. Foods containing eggs, mayonnaise or chicken were contaminated with Salmonella in eight outbreaks. Higher counts (>107 MPN.g-1) of Salmonella were detected mostly in foods containing mayonnaise. The isolation of Salmonella from multiple food items in five outbreaks probably resulted from the cross-contamination, and the high Salmonella counts detected in almost all analyzed samples probably resulted from storing in inadequate temperature. All strains were identified as S. Enteritidis, and presented a unique macrorestriction profile, demonstrating the predominance of one clonal group in foods involved in the salmonellosis outbreaks. A low frequency of antimicrobial resistant S. Enteritidis strains was observed and nalidixic acid was the only resistance marker detected. PMID:24031261

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" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected. PMID:19515246

Molecular Characterization of Clostridium botulinum Isolates from Foodborne Outbreaks in Thailand, 2010

PubMed Central

Wangroongsarb, Piyada; Kohda, Tomoko; Jittaprasartsin, Chutima; Suthivarakom, Karun; Kamthalang, Thanitchi; Umeda, Kaoru; Sawanpanyalert, Pathom; Kozaki, Shunji; Ikuta, Kazuyoshi

2014-01-01

Background Thailand has had several foodborne outbreaks of botulism, one of the biggest being in 2006 when laboratory investigations identified the etiologic agent as Clostridium botulinum type A. Identification of the etiologic agent from outbreak samples is laborious using conventional microbiological methods and the neurotoxin mouse bioassay. Advances in molecular techniques have added enormous information regarding the etiology of outbreaks and characterization of isolates. We applied these methods in three outbreaks of botulism in Thailand in 2010. Methodology/Principal Findings A total of 19 cases were involved (seven each in Lampang and Saraburi and five in Maehongson provinces). The first outbreak in Lampang province in April 2010 was associated with C. botulinum type F, which was detected by conventional methods. Outbreaks in Saraburi and Maehongson provinces occurred in May and December were due to C. botulinum type A1(B) and B that were identified by conventional methods and molecular techniques, respectively. The result of phylogenetic sequence analysis showed that C. botulinum type A1(B) strain Saraburi 2010 was close to strain Iwate 2007. Molecular analysis of the third outbreak in Maehongson province showed C. botulinum type B8, which was different from B1–B7 subtype. The nontoxic component genes of strain Maehongson 2010 revealed that ha33, ha17 and botR genes were close to strain Okra (B1) while ha70 and ntnh genes were close to strain 111 (B2). Conclusion/Significance This study demonstrates the utility of molecular genotyping of C. botulinum and how it contributes to our understanding the epidemiology and variation of boNT gene. Thus, the recent botulism outbreaks in Thailand were induced by various C. botulinum types. PMID:24475015

Molecular characterization of Clostridium botulinum isolates from foodborne outbreaks in Thailand, 2010.

PubMed

Wangroongsarb, Piyada; Kohda, Tomoko; Jittaprasartsin, Chutima; Suthivarakom, Karun; Kamthalang, Thanitchi; Umeda, Kaoru; Sawanpanyalert, Pathom; Kozaki, Shunji; Ikuta, Kazuyoshi

2014-01-01

Thailand has had several foodborne outbreaks of botulism, one of the biggest being in 2006 when laboratory investigations identified the etiologic agent as Clostridium botulinum type A. Identification of the etiologic agent from outbreak samples is laborious using conventional microbiological methods and the neurotoxin mouse bioassay. Advances in molecular techniques have added enormous information regarding the etiology of outbreaks and characterization of isolates. We applied these methods in three outbreaks of botulism in Thailand in 2010. A total of 19 cases were involved (seven each in Lampang and Saraburi and five in Maehongson provinces). The first outbreak in Lampang province in April 2010 was associated with C. botulinum type F, which was detected by conventional methods. Outbreaks in Saraburi and Maehongson provinces occurred in May and December were due to C. botulinum type A1(B) and B that were identified by conventional methods and molecular techniques, respectively. The result of phylogenetic sequence analysis showed that C. botulinum type A1(B) strain Saraburi 2010 was close to strain Iwate 2007. Molecular analysis of the third outbreak in Maehongson province showed C. botulinum type B8, which was different from B1-B7 subtype. The nontoxic component genes of strain Maehongson 2010 revealed that ha33, ha17 and botR genes were close to strain Okra (B1) while ha70 and ntnh genes were close to strain 111 (B2). This study demonstrates the utility of molecular genotyping of C. botulinum and how it contributes to our understanding the epidemiology and variation of boNT gene. Thus, the recent botulism outbreaks in Thailand were induced by various C. botulinum types.

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

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.

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.

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

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

PubMed Central

2013-01-01

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

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

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

PubMed

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

2016-05-01

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

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.

Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

Development of a multiplex PCR-based rapid typing method for enterohemorrhagic Escherichia coli O157 strains.

PubMed

Ooka, Tadasuke; Terajima, Jun; Kusumoto, Masahiro; Iguchi, Atsushi; Kurokawa, Ken; Ogura, Yoshitoshi; Asadulghani, Md; Nakayama, Keisuke; Murase, Kazunori; Ohnishi, Makoto; Iyoda, Sunao; Watanabe, Haruo; Hayashi, Tetsuya

2009-09-01

Enterohemorrhagic Escherichia coli O157 (EHEC O157) is a food-borne pathogen that has raised worldwide public health concern. The development of simple and rapid strain-typing methods is crucial for the rapid detection and surveillance of EHEC O157 outbreaks. In the present study, we developed a multiplex PCR-based strain-typing method for EHEC O157, which is based on the variability in genomic location of IS629 among EHEC O157 strains. This method is very simple, in that the procedures are completed within 2 h, the analysis can be performed without the need for special equipment or techniques (requiring only conventional PCR and agarose gel electrophoresis systems), the results can easily be transformed into digital data, and the genes for the major virulence markers of EHEC O157 (the stx(1), stx(2), and eae genes) can be detected simultaneously. Using this method, 201 EHEC O157 strains showing different XbaI digestion patterns in pulsed-field gel electrophoresis (PFGE) analysis were classified into 127 types, and outbreak-related strains showed identical or highly similar banding patterns. Although this method is less discriminatory than PFGE, it may be useful as a primary screening tool for EHEC O157 outbreaks.

Spatial cluster detection using dynamic programming

PubMed Central

2012-01-01

Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm. PMID:22443103

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

PubMed

Bautista, Leonelo E; Herrera, Víctor M

2018-05-24

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

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

PubMed

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

2014-11-01

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

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

PubMed Central

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

2014-01-01

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

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

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 competitive on all three data sets, but are particularly competitive on the real data and on data from the hierarchical model, which are the two data sets that violate the "one season fits all" assumption.

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

PubMed

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

2015-02-21

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

[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.

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.

A systematic approach to novel virus discovery in emerging infectious disease outbreaks.

PubMed

Sridhar, Siddharth; To, Kelvin K W; Chan, Jasper F W; Lau, Susanna K P; Woo, Patrick C Y; Yuen, Kwok-Yung

2015-05-01

The discovery of novel viruses is of great importance to human health-both in the setting of emerging infectious disease outbreaks and in disease syndromes of unknown etiology. Despite the recent proliferation of many efficient virus discovery methods, careful selection of a combination of methods is important to demonstrate a novel virus, its clinical associations, and its relevance in a timely manner. The identification of a patient or an outbreak with distinctive clinical features and negative routine microbiological workup is often the starting point for virus hunting. This review appraises the roles of culture, electron microscopy, and nucleic acid detection-based methods in optimizing virus discovery. Cell culture is generally slow but may yield viable virus. Although the choice of cell line often involves trial and error, it may be guided by the clinical syndrome. Electron microscopy is insensitive but fast, and may provide morphological clues to choice of cell line or consensus primers for nucleic acid detection. Consensus primer PCR can be used to detect viruses that are closely related to known virus families. Random primer amplification and high-throughput sequencing can catch any virus genome but cannot yield an infectious virion for testing Koch postulates. A systematic approach that incorporates carefully chosen combinations of virus detection techniques is required for successful virus discovery. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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.

COMPARISON OF FILTRATION METHODS FOR PRIMARY RECOVERY OF CRYPTOSPORIIDUM PARVUM FROM WATER

EPA Science Inventory

Waterborne disease outbreaks from contaminated drinking water have been linked to the protozoan parasite, Cryptosporidium parvum. To improve monitoring for this agent, the USEPA developed Method 1622 for isolation and detection of Cryptosporidium oocysts in water. Method 1622 i...

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

PubMed

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

2014-03-01

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

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

PubMed Central

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

2014-01-01

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

Spatial cluster detection using dynamic programming.

PubMed

Sverchkov, Yuriy; Jiang, Xia; Cooper, Gregory F

2012-03-25

The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm.

Time series modeling for syndromic surveillance.

PubMed

Reis, Ben Y; Mandl, Kenneth D

2003-01-23

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

Outbreak of G2P[4] rotavirus gastroenteritis in a retirement community, Brazil, 2015: An important public health risk?

PubMed

Luchs, Adriana; Madalosso, Geraldine; Cilli, Audrey; Morillo, Simone Guadagnucci; Martins, Sandra Regina; de Souza, Karen Aparecida Farias; Namiyama, Gislene Mitsue; Gonçalves, Cláudia Regina; Carmona, Rita de Cássia Compagnoli; Timenetsky, Maria do Carmo Sampaio Tavares

The present study described a group A rotavirus (RVA) outbreak in an age-care facility in Brazil, using epidemiologic and molecular diagnostic methods. A descriptive clinical, epidemiological and environmental investigation was conducted. Stool samples were collected and screened for RVA, Norovirus (NoV), Enteric Adenovirus 40/41 (AdV 40/41) and Astrovirus (AstV) using ELISA, RT-PCR, qRT-PCR, electron microscopy and sequencing methods. Outbreak occurred during 26th-29th October, 2015; 28 individuals affected (22 residents; 6 staff). The attack rate was 25.9% and 8.5% among residents (median-age: 85.5 years) and staff (median-age: 28 years), respectively. Female staff was identified as the index case. RVA G2P[4] genotype was detected in 87.5% (7/8). Genetic analysis demonstrated that the outbreak involved one single strain, suggesting a common-source infection. RVA should be considered during outbreaks investigations in residential facilities, and raise the question if the current licensed RVA vaccines for children could also be helpful for the elderly. Copyright © 2016 Elsevier Inc. All rights reserved.

Managing Ebola from rural to urban slum settings: experiences from Uganda.

PubMed

Okware, Sam I; Omaswa, Francis; Talisuna, Ambrose; Amandua, Jacinto; Amone, Jackson; Onek, Paul; Opio, Alex; Wamala, Joseph; Lubwama, Julius; Luswa, Lukwago; Kagwa, Paul; Tylleskar, Thorkild

2015-03-01

Five outbreaks of ebola occurred in Uganda between 2000-2012. The outbreaks were quickly contained in rural areas. However, the Gulu outbreak in 2000 was the largest and complex due to insurgency. It invaded Gulu municipality and the slum- like camps of the internally displaced persons (IDPs). The Bundigugyo district outbreak followed but was detected late as a new virus. The subsequent outbreaks in the districts of Luwero district (2011, 2012) and Kibaale (2012) were limited to rural areas. Detailed records of the outbreak presentation, cases, and outcomes were reviewed and analyzed. Each outbreak was described and the outcomes examined for the different scenarios. Early detection and action provided the best outcomes and results. The ideal scenario occurred in the Luwero outbreak during which only a single case was observed. Rural outbreaks were easier to contain. The community imposed quarantine prevented the spread of ebola following introduction into Masindi district. The outbreak was confined to the extended family of the index case and only one case developed in the general population. However, the outbreak invasion of the town slum areas escalated the spread of infection in Gulu municipality. Community mobilization and leadership was vital in supporting early case detection and isolations well as contact tracing and public education. Palliative care improved survival. Focusing on treatment and not just quarantine should be emphasized as it also enhanced public trust and health seeking behavior. Early detection and action provided the best scenario for outbreak containment. Community mobilization and leadership was vital in supporting outbreak control. International collaboration was essential in supporting and augmenting the national efforts.

[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.

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 confirmation, for monitoring of antibiotic sensitivity and for production of pure isolates for molecular characterization. Further studies should be done to better understand the observed age and sex case distribution, in Kasese district.

DETECTION OF CRYPTOSPORIDIUM OOCYSTS IN SOURCE AND FINISHED WATERS

EPA Science Inventory

Numerous waterborne outbreaks of cryptosporidiosis have occurred with the most notable being the 1993 episode in Milwaukee. As a result, the past decade has seen a massive effort expended on the development of methods to detect Cryptosporidium parvum oocysts in source and finish...

AN IMPROVED METHOD FOR DETECTING VIRUSES IN WATER

EPA Science Inventory

Enteroviruses are important etiological agents of waterborne disease and are responsible for outbreaks of gastroenteritis. However, the prevalence and occurrence of these pathogens in raw drinking water sources is poorly understood. This is primarily due to the limited methods ...

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

PubMed

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

2015-02-01

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

Investigation of Outbreaks of Salmonella enterica Serovar Typhimurium and Its Monophasic Variants Using Whole-Genome Sequencing, Denmark

PubMed Central

Gymoese, Pernille; Sørensen, Gitte; Litrup, Eva; Olsen, John Elmerdal; Nielsen, Eva Møller

2017-01-01

Whole-genome sequencing is rapidly replacing current molecular typing methods for surveillance purposes. Our study evaluates core-genome single-nucleotide polymorphism analysis for outbreak detection and linking of sources of Salmonella enterica serovar Typhimurium and its monophasic variants during a 7-month surveillance period in Denmark. We reanalyzed and defined 8 previously characterized outbreaks from the phylogenetic relatedness of the isolates, epidemiologic data, and food traceback investigations. All outbreaks were identified, and we were able to exclude unrelated and include additional related human cases. We were furthermore able to link possible food and veterinary sources to the outbreaks. Isolates clustered according to sequence types (STs) 19, 34, and 36. Our study shows that core-genome single-nucleotide polymorphism analysis is suitable for surveillance and outbreak investigation for Salmonella Typhimurium (ST19 and ST36), but whole genome–wide analysis may be required for the tight genetic clone of monophasic variants (ST34). PMID:28930002

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

A case-association cluster detection and visualisation tool with an application to Legionnaires’ disease

PubMed Central

Sansom, P; Copley, V R; Naik, F C; Leach, S; Hall, I M

2013-01-01

Statistical methods used in spatio-temporal surveillance of disease are able to identify abnormal clusters of cases but typically do not provide a measure of the degree of association between one case and another. Such a measure would facilitate the assignment of cases to common groups and be useful in outbreak investigations of diseases that potentially share the same source. This paper presents a model-based approach, which on the basis of available location data, provides a measure of the strength of association between cases in space and time and which is used to designate and visualise the most likely groupings of cases. The method was developed as a prospective surveillance tool to signal potential outbreaks, but it may also be used to explore groupings of cases in outbreak investigations. We demonstrate the method by using a historical case series of Legionnaires’ disease amongst residents of England and Wales. PMID:23483594

Characterization of Staphylococcus aureus strains and evidence for the involvement of non-classical enterotoxin genes in food poisoning outbreaks.

PubMed

Ciupescu, Laurentiu-Mihai; Auvray, Frederic; Nicorescu, Isabela Madalina; Meheut, Thomas; Ciupescu, Veronica; Lardeux, Anne-Laure; Tanasuica, Rodica; Hennekinne, Jacques-Antoine

2018-06-05

To an increasing extent, molecular and genetic characterization is now used to investigate foodborne outbreaks. The aim of this study was to seek molecular links among coagulase-positive staphylococci (CPS) isolated from three recent food poisoning outbreaks in Romania using polymerase chain reaction and pulsed-field gel electrophoresis (PFGE) techniques. Nineteen CPS isolates were identified as Staphylococcus aureus by detection of the 23S rDNA gene. Among them, 15 carried at least one staphylococcal enterotoxin-encoding gene (se). The Calarași outbreak strains grouped in pulsotype 2 and were sed/sej/ser-positive, whereas the Arad outbreak strains clustered in pulsotype 17 and were either sed/seg/sei/sej/ser- or seg/sei-positive. The Pitești outbreak strains clustered in pulsotype 1 and, surprisingly, possessed only one enterotoxin gene, i.e. seh. Similar to other European countries, the seh gene has been identified with increasing frequency in Romanian outbreaks; this highlights the importance of considering the application of methods recommended for staphylococcal enterotoxin regulation in Europe.

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

PubMed

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

2009-01-01

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

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

PubMed

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

2013-01-01

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

Automated Biosurveillance Data from England and Wales, 1991–2011

PubMed Central

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

2013-01-01

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

Prevalence and Level of Listeria monocytogenes in Ice Cream Linked to a Listeriosis Outbreak in the United States.

PubMed

Chen, Y I; Burall, Laurel S; Macarisin, Dumitru; Pouillot, Régis; Strain, Errol; DE Jesus, Antonio J; Laasri, Anna; Wang, Hua; Ali, Laila; Tatavarthy, Aparna; Zhang, Guodong; Hu, Lijun; Day, James; Kang, Jihun; Sahu, Surasri; Srinivasan, Devayani; Klontz, Karl; Parish, Mickey; Evans, Peter S; Brown, Eric W; Hammack, Thomas S; Zink, Donald L; Datta, Atin R

2016-11-01

A most-probable-number (MPN) method was used to enumerate Listeria monocytogenes in 2,320 commercial ice cream scoops manufactured on a production line that was implicated in a 2015 listeriosis outbreak in the United States. The analyzed samples were collected from seven lots produced in November 2014, December 2014, January 2015, and March 2015. L. monocytogenes was detected in 99% (2,307 of 2,320) of the tested samples (lower limit of detection, 0.03 MPN/g), 92% of which were contaminated at <20 MPN/g. The levels of L. monocytogenes in these samples had a geometric mean per lot of 0.15 to 7.1 MPN/g. The prevalence and enumeration data from an unprecedented large number of naturally contaminated ice cream products linked to a listeriosis outbreak provided a unique data set for further understanding the risk associated with L. monocytogenes contamination for highly susceptible populations.

The Role of Public Knowledge, Resources, and Innovation in Responding to the Ebola Outbreak.

PubMed

Goldstone, Brian J; Brown, Brandon

2015-10-01

Since the beginning of the recent Ebola outbreak, a sense of fear has developed among the public due to the novelty of our exposure to the virus and the ill-equipped nature of our health care systems. Media sensationalism, coupled with improper knowledge of Ebola, may have contributed to mass hysteria. Most support to tackle Ebola has been direct monetary aid. However, others are working on innovative methods to control the epidemic, including the development of rapid detection methods, experimental treatments, and a viable vaccine. Rapid screening and vaccine ideas are promising, but it is unlikely that they will be ready in the coming months. This raises the question of what other tools and technological innovation can be developed to effectively stem the spread of the outbreak. Although we hope the continued outpouring of aid and health care workers to West Africa will greatly reduce the impact of Ebola, communication, screenings, treatment, and vaccine are of central importance to stop this outbreak.

Case study of early detection and intervention of infectious disease outbreaks in an institution using Nursery School Absenteeism Surveillance Systems (NSASSy) of the Public Health Center.

PubMed

Matsumoto, Kayo; Hirayama, Chifumi; Sakuma, Yoko; Itoi, Yoichi; Sunadori, Asami; Kitamura, Junko; Nakahashi, Takeshi; Sugawara, Tamie; Ohkusa, Yasushi

2016-01-01

Objectives Detecting outbreaks early and then activating countermeasures based on such information is extremely important for infection control at childcare facilities. The Sumida ward began operating the Nursery School Absenteeism Surveillance System (NSASSy) in August 2013, and has since conducted real-time monitoring at nursery schools. The Public Health Center can detect outbreaks early and support appropriate intervention. This paper describes the experiences of Sumida Public Health Center related to early detection and intervention since the initiation of the system.Methods In this study, we investigated infectious disease outbreaks detected at 62 nursery schools in the Sumida ward, which were equipped with NSASSy from early November 2013 through late March 2015. We classified the information sources of the detected outbreak and responses of the public health center. The sources were (1) direct contact from some nursery schools, (2) messages from public officers with jurisdiction over nursery schools, (3) automatic detection by NSASSy, and (4) manual detection by public health center officers using NSASSy. The responses made by the health center were described and classified into 11 categories including verification of outbreak and advice for caregivers.Results The number of outbreaks detected by the aforementioned four information sources was zero, 25, 15, and 7 events, respectively, during the first 5 months after beginning NSASSy. These numbers became 5, 7, 53, and 25 events, respectively, during the subsequent 12 months. The number of outbreaks detected increased by 47% during the first 5 months, and by 87% in the following 12 months. The responses were primarily confirming the situation and offering advice to caregivers.Conclusion The Sumida Public Health Center ward could achieve early detection with automatic or manual detection of NSASSy. This system recently has become an important detection resource, and has contributed greatly to early detection. Because the Public Health Center can use it to achieve real-time monitoring, they can recognize emergent situations and intervene earlier, and thereby give feedback to the nursery schools. The system can contribute to providing effective countermeasures in these settings.

Results of Survey Regarding Prevalence of Adventitial Infections in Mice and Rats at Biomedical Research Facilities.

PubMed

Marx, James O; Gaertner, Diane J; Smith, Abigail L

2017-09-01

Control of rodent adventitial infections in biomedical research facilities is of extreme importance in assuring both animal welfare and high-quality research results. Sixty-three U.S. institutions participated in a survey reporting the methods used to detect and control these infections and the prevalence of outbreaks from 1 January 2014 through 31 December 2015. These results were then compared with the results of 2 similar surveys published in 1998 and 2008. The results of the current survey demonstrated that the rate of viral outbreaks in mouse colonies was decreasing, particularly in barrier facilities, whereas the prevalence of parasitic outbreaks has remained constant. These results will help our profession focus its efforts in the control of adventitial rodent disease outbreaks to the areas of the greatest needs.

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:28863159

Multiplex surface plasmon resonance imaging platform for label-free detection of foodborne pathogens

USDA-ARS?s Scientific Manuscript database

Salmonellae are among the leading causes of foodborne outbreaks in the United States, and more rapid and efficient detection methods are needed. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for rapid and label-free screening of multiple targets simultaneous...

Multistate outbreak of Norwalk-like virus gastroenteritis associated with a common caterer.

PubMed

Anderson, A D; Garrett, V D; Sobel, J; Monroe, S S; Fankhauser, R L; Schwab, K J; Bresee, J S; Mead, P S; Higgins, C; Campana, J; Glass, R I

2001-12-01

In February 2000, an outbreak of gastroenteritis occurred among employees of a car dealership in New York. The same meal was also supplied to 52 dealerships nationwide, and 13 states reported illness at dealerships where the banquet was served. A retrospective cohort study was conducted to identify risk factors associated with the illness. Stool samples were collected to detect Norwalk-like virus, and sera were drawn and tested for immunoglobulin A antibodies to the outbreak strain. By univariate analysis, illness was significantly associated with consumption of any of four salads served at the banquet (relative risk = 3.8, 95% confidence interval: 2.5, 5.6). Norwalk-like virus was detected by reverse transcription-polymerase chain reaction assay in 32 of 59 stool samples from eight states. Nucleotide sequences of a 213-base pair fragment from 16 stool specimens collected from cases in eight states were identical, confirming a common source outbreak. Two of 15 workers at caterer A had elevated immunoglobulin A titers to an antigenically related Norwalk-like virus strain. This study highlights the value of molecular techniques to complement classic epidemiologic methods in outbreak investigations and underscores the critical role of food handlers in the spread of foodborne disease associated with Norwalk-like virus.

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.

High-Resolution Melting-Curve Analysis of Ligation-Mediated Real-Time PCR for Rapid Evaluation of an Epidemiological Outbreak of Extended-Spectrum-Beta-Lactamase-Producing Escherichia coli ▿

PubMed Central

Woksepp, Hanna; Jernberg, Cecilia; Tärnberg, Maria; Ryberg, Anna; Brolund, Alma; Nordvall, Michaela; Olsson-Liljequist, Barbro; Wisell, Karin Tegmark; Monstein, Hans-Jürg; Nilsson, Lennart E.; Schön, Thomas

2011-01-01

Methods for the confirmation of nosocomial outbreaks of bacterial pathogens are complex, expensive, and time-consuming. Recently, a method based on ligation-mediated PCR (LM/PCR) using a low denaturation temperature which produces specific melting-profile patterns of DNA products has been described. Our objective was to further develop this method for real-time PCR and high-resolution melting analysis (HRM) in a single-tube system optimized in order to achieve results within 1 day. Following the optimization of LM/PCR for real-time PCR and HRM (LM/HRM), the method was applied for a nosocomial outbreak of extended-spectrum-beta-lactamase (ESBL)-producing and ST131-associated Escherichia coli isolates (n = 15) and control isolates (n = 29), including four previous clusters. The results from LM/HRM were compared to results from pulsed-field gel electrophoresis (PFGE), which served as the gold standard. All isolates from the nosocomial outbreak clustered by LM/HRM, which was confirmed by gel electrophoresis of the LM/PCR products and PFGE. Control isolates that clustered by LM/PCR (n = 4) but not by PFGE were resolved by confirmatory gel electrophoresis. We conclude that LM/HRM is a rapid method for the detection of nosocomial outbreaks of bacterial infections caused by ESBL-producing E. coli strains. It allows the analysis of isolates in a single-tube system within a day, and the discriminatory power is comparable to that of PFGE. PMID:21956981

High-resolution melting-curve analysis of ligation-mediated real-time PCR for rapid evaluation of an epidemiological outbreak of extended-spectrum-beta-lactamase-producing Escherichia coli.

PubMed

Woksepp, Hanna; Jernberg, Cecilia; Tärnberg, Maria; Ryberg, Anna; Brolund, Alma; Nordvall, Michaela; Olsson-Liljequist, Barbro; Wisell, Karin Tegmark; Monstein, Hans-Jürg; Nilsson, Lennart E; Schön, Thomas

2011-12-01

Methods for the confirmation of nosocomial outbreaks of bacterial pathogens are complex, expensive, and time-consuming. Recently, a method based on ligation-mediated PCR (LM/PCR) using a low denaturation temperature which produces specific melting-profile patterns of DNA products has been described. Our objective was to further develop this method for real-time PCR and high-resolution melting analysis (HRM) in a single-tube system optimized in order to achieve results within 1 day. Following the optimization of LM/PCR for real-time PCR and HRM (LM/HRM), the method was applied for a nosocomial outbreak of extended-spectrum-beta-lactamase (ESBL)-producing and ST131-associated Escherichia coli isolates (n = 15) and control isolates (n = 29), including four previous clusters. The results from LM/HRM were compared to results from pulsed-field gel electrophoresis (PFGE), which served as the gold standard. All isolates from the nosocomial outbreak clustered by LM/HRM, which was confirmed by gel electrophoresis of the LM/PCR products and PFGE. Control isolates that clustered by LM/PCR (n = 4) but not by PFGE were resolved by confirmatory gel electrophoresis. We conclude that LM/HRM is a rapid method for the detection of nosocomial outbreaks of bacterial infections caused by ESBL-producing E. coli strains. It allows the analysis of isolates in a single-tube system within a day, and the discriminatory power is comparable to that of PFGE.

Review of syndromic surveillance: implications for waterborne disease detection

PubMed Central

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

2006-01-01

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

Partial Failure of Milk Pasteurization as a Risk for the Transmission of Campylobacter From Cattle to Humans

PubMed Central

Fernandes, Anand M.; Balasegaram, Sooria; Willis, Caroline; Wimalarathna, Helen M. L.; Maiden, Martin C.; McCarthy, Noel D.

2015-01-01

Background. Cattle are the second most common source of human campylobacteriosis. However, routes to account for this scale of transmission have not been identified. In contrast to chicken, red meat is not heavily contaminated at point of sale. Although effective pasteurization prevents milk-borne infection, apparently sporadic infections may include undetected outbreaks from raw or perhaps incompletely pasteurized milk. Methods. A rise in Campylobacter gastroenteritis in an isolated population was investigated using whole-genome sequencing (WGS), an epidemiological study, and environmental investigations. Results. A single strain was identified in 20 cases, clearly distinguishable from other local strains and a reference population by WGS. A case-case analysis showed association of infection with the outbreak strain and milk from a single dairy (odds ratio, 8; Fisher exact test P value = .023). Despite temperature records indicating effective pasteurization, mechanical faults likely to lead to incomplete pasteurization of part of the milk were identified by further testing and examination of internal components of dairy equipment. Conclusions. Here, milk distribution concentrated on a small area, including school-aged children with low background incidence of campylobacteriosis, facilitated outbreak identification. Low-level contamination of widely distributed milk would not produce as detectable an outbreak signal. Such hidden outbreaks may contribute to the substantial burden of apparently sporadic Campylobacter from cattle where transmission routes are not certain. The effective discrimination of outbreak isolates from a reference population using WGS shows that integrating these data and approaches into surveillance could support the detection as well as investigation of such outbreaks. PMID:26063722

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.

A Qualitative Inquiry About Pruno, an Illicit Alcoholic Beverage Linked to Botulism Outbreaks in United States Prisons

PubMed Central

Sreenivasan, Nandini; Person, Bobbie; Shew, Mark; Wheeler, Daniel; Hall, Julia; Bogdanow, Linda; Leniek, Karyn; Rao, Agam

2015-01-01

Objectives. Since 2011, 3 outbreaks of botulism in US prisons have been attributed to pruno, which is an alcoholic beverage made by inmates. Following 1 outbreak, we conducted a qualitative inquiry to understand pruno brewing and its social context to inform outbreak prevention measures. Methods. We interviewed staff, inmates, and parolees from 1 prison about pruno production methods, the social aspects of pruno, and strategies for communicating the association between botulism and pruno. Results. Twenty-seven inmates and parolees and 13 staff completed interviews. Pruno is fermented from water, fruit, sugar, and miscellaneous ingredients. Knowledge of pruno making was widespread among inmates; staff were familiar with only the most common ingredients and supplies inmates described. Staff and inmates described inconsistent consequences for pruno possession and suggested using graphic health messages from organizations external to the prison to communicate the risk of botulism from pruno. Conclusions. Pruno making was frequent in this prison. Improved staff recognition of pruno ingredients and supplies might improve detection of brewing activities in this and other prisons. Consistent consequences and clear messages about the association between pruno and botulism might prevent outbreaks. PMID:26378846

Strategies for Early Outbreak Detection of Malaria in the Amhara Region of Ethiopia

NASA Astrophysics Data System (ADS)

Nekorchuk, D.; Gebrehiwot, T.; Mihretie, A.; Awoke, W.; Wimberly, M. C.

2017-12-01

Traditional epidemiological approaches to early detection of disease outbreaks are based on relatively straightforward thresholds (e.g. 75th percentile, standard deviations) estimated from historical case data. For diseases with strong seasonality, these can be modified to create separate thresholds for each seasonal time step. However, for disease processes that are non-stationary, more sophisticated techniques are needed to more accurately estimate outbreak threshold values. Early detection for geohealth-related diseases that also have environmental drivers, such as vector-borne diseases, may also benefit from the integration of time-lagged environmental data and disease ecology models into the threshold calculations. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) project has been integrating malaria case surveillance with remotely-sensed environmental data for early detection, warning, and forecasting of malaria epidemics in the Amhara region of Ethiopia, and has five years of weekly time series data from 47 woredas (districts). Efforts to reduce the burden of malaria in Ethiopia has been met with some notable success in the past two decades with major reduction in cases and deaths. However, malaria remains a significant public health threat as 60% of the population live in malarious areas, and due to the seasonal and unstable transmission patterns with cyclic outbreaks, protective immunity is generally low which could cause high morbidity and mortality during the epidemics. This study compared several approaches for defining outbreak thresholds and for identifying a potential outbreak based on deviations from these thresholds. We found that model-based approaches that accounted for climate-driven seasonality in malaria transmission were most effective, and that incorporating a trend component improved outbreak detection in areas with active malaria elimination efforts. An advantage of these early detection techniques is that they can detect climate-driven outbreaks as well as outbreaks driven by social factors such as human migration.

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

PubMed

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

2016-06-01

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

Automatic early warning of tail biting in pigs: 3D cameras can detect lowered tail posture before an outbreak

PubMed Central

Jack, Mhairi; Futro, Agnieszka; Talbot, Darren; Zhu, Qiming; Barclay, David; Baxter, Emma M.

2018-01-01

Tail biting is a major welfare and economic problem for indoor pig producers worldwide. Low tail posture is an early warning sign which could reduce tail biting unpredictability. Taking a precision livestock farming approach, we used Time-of-flight 3D cameras, processing data with machine vision algorithms, to automate the measurement of pig tail posture. Validation of the 3D algorithm found an accuracy of 73.9% at detecting low vs. not low tails (Sensitivity 88.4%, Specificity 66.8%). Twenty-three groups of 29 pigs per group were reared with intact (not docked) tails under typical commercial conditions over 8 batches. 15 groups had tail biting outbreaks, following which enrichment was added to pens and biters and/or victims were removed and treated. 3D data from outbreak groups showed the proportion of low tail detections increased pre-outbreak and declined post-outbreak. Pre-outbreak, the increase in low tails occurred at an increasing rate over time, and the proportion of low tails was higher one week pre-outbreak (-1) than 2 weeks pre-outbreak (-2). Within each batch, an outbreak and a non-outbreak control group were identified. Outbreak groups had more 3D low tail detections in weeks -1, +1 and +2 than their matched controls. Comparing 3D tail posture and tail injury scoring data, a greater proportion of low tails was associated with more injured pigs. Low tails might indicate more than just tail biting as tail posture varied between groups and over time and the proportion of low tails increased when pigs were moved to a new pen. Our findings demonstrate the potential for a 3D machine vision system to automate tail posture detection and provide early warning of tail biting on farm. PMID:29617403

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.

Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France.

PubMed

Pelat, Camille; Bonmarin, Isabelle; Ruello, Marc; Fouillet, Anne; Caserio-Schönemann, Céline; Levy-Bruhl, Daniel; Le Strat, Yann

2017-08-10

The 2014/15 influenza epidemic caused a work overload for healthcare facilities in France. The French national public health agency announced the start of the epidemic - based on indicators aggregated at the national level - too late for many hospitals to prepare. It was therefore decided to improve the influenza alert procedure through (i) the introduction of a pre-epidemic alert level to better anticipate future outbreaks, (ii) the regionalisation of surveillance so that healthcare structures can be informed of the arrival of epidemics in their region, (iii) the standardised use of data sources and statistical methods across regions. A web application was developed to deliver statistical results of three outbreak detection methods applied to three surveillance data sources: emergency departments, emergency general practitioners and sentinel general practitioners. This application was used throughout the 2015/16 influenza season by the epidemiologists of the headquarters and regional units of the French national public health agency. It allowed them to signal the first influenza epidemic alert in week 2016-W03, in Brittany, with 11 other regions in pre-epidemic alert. This application received positive feedback from users and was pivotal for coordinating surveillance across the agency's regional units. This article is copyright of The Authors, 2017.

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 surveillance resources. Conclusion We present a new approach to evaluating the sensitivity and representativeness of hospital-based surveillance, making it possible to predict its ability to detect emerging threats. PMID:28095468

Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records.

PubMed

Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

2015-01-01

We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.

Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records

PubMed Central

Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

2015-01-01

We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events. PMID:26536596

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

PubMed

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

2018-04-23

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

Identification of carriers among individuals recruited in the typhoid registry in Malaysia using stool culture, polymerase chain reaction, and dot enzyme immunoassay as detection tools.

PubMed

Chua, Ang Lim; Aziah, Ismail; Balaram, Prabha; Bhuvanendran, Saatheeyavaane; Anthony, Amy Amilda; Mohmad, Siti Norazura; Nasir, Norhafiza M; Hassan, Haslizai; Naim, Rochman; Meran, Lila P; Hussin, Hani M; Ismail, Asma

2015-03-01

Chronic carriers of Salmonella Typhi act as reservoirs for the organism and become the agents of typhoid outbreaks in a community. In this study, chronic carriers in Kelantan, Malaysia were first identified using the culture and polymerase chain reaction method. Then, a novel serological tool, designated Typhidot-C, was evaluated in retrospect using the detected individuals as control positives. Chronic carriage positive by the culture and polymerase chain reaction method was recorded at 3.6% (4 out of 110) among individuals who previously had acute typhoid fever and a 9.4% (10 out of 106) carriage rate was observed among food handlers screened during outbreaks. The Typhidot-C assay was able to detect all these positive carriers showing its potential as a viable carrier screening tool and can be used for efficient detection of typhoid carriers in an endemic area. These findings were used to establish the first carrier registry for S Typhi carriers in Malaysia. © 2012 APJPH.

Outbreak of Salmonella Oslo Infections Linked to Persian Cucumbers - United States, 2016.

PubMed

Bottichio, Lyndsay; Medus, Carlota; Sorenson, Alida; Donovan, Danielle; Sharma, Reeti; Dowell, Natasha; Williams, Ian; Wellman, Allison; Jackson, Alikeh; Tolar, Beth; Griswold, Taylor; Basler, Colin

2016-12-30

In April 2016, PulseNet, the national molecular subtyping network for foodborne disease surveillance, detected a multistate cluster of Salmonella enterica serotype Oslo infections with an indistinguishable pulsed-field gel electrophoresis (PFGE) pattern (XbaI PFGE pattern OSLX01.0090).* This PFGE pattern was new in the database; no previous infections or outbreaks have been identified. CDC, state and local health and agriculture departments and laboratories, and the Food and Drug Administration (FDA) conducted epidemiologic, traceback, and laboratory investigations to identify the source of this outbreak. A total of 14 patients in eight states were identified, with illness onsets occurring during March 21-April 9, 2016. Whole genome sequencing, a highly discriminating subtyping method, was used to further characterize PFGE pattern OSLX01.0090 isolates. Epidemiologic evidence indicates Persian cucumbers as the source of Salmonella Oslo infections in this outbreak. This is the fourth identified multistate outbreak of salmonellosis associated with cucumbers since 2013. Further research is needed to understand the mechanism and factors that contribute to contamination of cucumbers during growth, harvesting, and processing to prevent future outbreaks.

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.

DEVELOPMENT OF MOLECULAR METHODS TO DETECT EMERGING VIRUSES

EPA Science Inventory

A large number of human enteric viruses are known to cause gastrointestinal illness and waterborne outbreaks. Many of these are emerging viruses that do not grow or grow poorly in cell culture and so molecular detectoin methods based on the polymerase chain reaction (PCR) are be...

Signature-forecasting and early outbreak detection system

PubMed Central

Naumova, Elena N.; MacNeill, Ian B.

2008-01-01

SUMMARY Daily disease monitoring via a public health surveillance system provides valuable information on population risks. Efficient statistical tools for early detection of rapid changes in the disease incidence are a must for modern surveillance. The need for statistical tools for early detection of outbreaks that are not based on historical information is apparent. A system is discussed for monitoring cases of infections with a view to early detection of outbreaks and to forecasting the extent of detected outbreaks. We propose a set of adaptive algorithms for early outbreak detection that does not rely on extensive historical recording. We also include knowledge of infection disease epidemiology into forecasts. To demonstrate this system we use data from the largest water-borne outbreak of cryptosporidiosis, which occurred in Milwaukee in 1993. Historical data are smoothed using a loess-type smoother. Upon receipt of a new datum, the smoothing is updated and estimates are made of the first two derivatives of the smooth curve, and these are used for near-term forecasting. Recent data and the near-term forecasts are used to compute a color-coded warning index, which quantify the level of concern. The algorithms for computing the warning index have been designed to balance Type I errors (false prediction of an epidemic) and Type II errors (failure to correctly predict an epidemic). If the warning index signals a sufficiently high probability of an epidemic, then a forecast of the possible size of the outbreak is made. This longer term forecast is made by fitting a ‘signature’ curve to the available data. The effectiveness of the forecast depends upon the extent to which the signature curve captures the shape of outbreaks of the infection under consideration. PMID:18716671

EPA METHODS FOR VIRUS DETECTION IN WATER

EPA Science Inventory

A number of different types of human enteric viruses cause waterborne outbreaks when individuals are exposed to contaminated drinking and recreational waters. Members of the enterovirus group cause numerous diseases, including gastroenteritis, encephalitis, meningitis, myocard...

Real-time surveillance for abnormal events: the case of influenza outbreaks.

PubMed

Rao, Yao; McCabe, Brendan

2016-06-15

This paper introduces a method of surveillance using deviations from probabilistic forecasts. Realised observations are compared with probabilistic forecasts, and the "deviation" metric is based on low probability events. If an alert is declared, the algorithm continues to monitor until an all-clear is announced. Specifically, this article addresses the problem of syndromic surveillance for influenza (flu) with the intention of detecting outbreaks, due to new strains of viruses, over and above the normal seasonal pattern. The syndrome is hospital admissions for flu-like illness, and hence, the data are low counts. In accordance with the count properties of the observations, an integer-valued autoregressive process is used to model flu occurrences. Monte Carlo evidence suggests the method works well in stylised but somewhat realistic situations. An application to real flu data indicates that the ideas may have promise. The model estimated on a short run of training data did not declare false alarms when used with new observations deemed in control, ex post. The model easily detected the 2009 H1N1 outbreak. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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 shows the feasibility of creating a public health surveillance system for mass gatherings based on Internet data. The use of multiple data sources and analysis methods was found to be advantageous for rejecting false positives. Further studies are required in order to validate our findings with data from public health authorities. PMID:24943128

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

PubMed

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

2013-06-24

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

Rapid MALDI-TOF Mass Spectrometry Strain Typing during a Large Outbreak of Shiga-Toxigenic Escherichia coli

PubMed Central

Christner, Martin; Trusch, Maria; Rohde, Holger; Kwiatkowski, Marcel; Schlüter, Hartmut; Wolters, Manuel; Aepfelbacher, Martin; Hentschke, Moritz

2014-01-01

Background In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Methods Specific peaks in the outbreak strain’s spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Results Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. Conclusions MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow. PMID:25003758

Early outbreak detection by linking health advice line calls to water distribution areas retrospectively demonstrated in a large waterborne outbreak of cryptosporidiosis in Sweden.

PubMed

Bjelkmar, Pär; Hansen, Anette; Schönning, Caroline; Bergström, Jakob; Löfdahl, Margareta; Lebbad, Marianne; Wallensten, Anders; Allestam, Görel; Stenmark, Stephan; Lindh, Johan

2017-04-18

In the winter and spring of 2011 a large outbreak of cryptosporidiosis occurred in Skellefteå municipality, Sweden. This study summarizes the outbreak investigation in terms of outbreak size, duration, clinical characteristics, possible source(s) and the potential for earlier detection using calls to a health advice line. The investigation included two epidemiological questionnaires and microbial analysis of samples from patients, water and other environmental sources. In addition, a retrospective study based on phone calls to a health advice line was performed by comparing patterns of phone calls between different water distribution areas. Our analyses showed that approximately 18,500 individuals were affected by a waterborne outbreak of cryptosporidiosis in Skellefteå in 2011. This makes it the second largest outbreak of cryptosporidiosis in Europe to date. Cryptosporidium hominis oocysts of subtype IbA10G2 were found in patient and sewage samples, but not in raw water or in drinking water, and the initial contamination source could not be determined. The outbreak went unnoticed to authorities for several months. The analysis of the calls to the health advice line provides strong indications early in the outbreak that it was linked to a particular water treatment plant. We conclude that an earlier detection of the outbreak by linking calls to a health advice line to water distribution areas could have limited the outbreak substantially.

DETECTING CCL-RELATED, EMERGING WATERBORNE HUMAN VIRUSES AND VIRAL INDICATORS FOR EXPOSURE ASSESSMENT

EPA Science Inventory

Enteric viruses cause waterborne disease outbreaks in the U.S. and worldwide. The primary focus of this task is to develop methods to measure the occurrence of enteric viruses in environmental and drinking waters. Cell culture- and molecular-based methods are being developed fo...

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

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.

An Epidemiological Network Model for Disease Outbreak Detection

PubMed Central

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

2007-01-01

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

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.

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

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.

Detection of Antigenic Variants of Subtype H3 Swine Influenza A Viruses from Clinical Samples

PubMed Central

Martin, Brigitte E.; Li, Lei; Nolting, Jacqueline M.; Smith, David R.; Hanson, Larry A.

2017-01-01

ABSTRACT A large population of genetically and antigenically diverse influenza A viruses (IAVs) are circulating among the swine population, playing an important role in influenza ecology. Swine IAVs not only cause outbreaks among swine but also can be transmitted to humans, causing sporadic infections and even pandemic outbreaks. Antigenic characterizations of swine IAVs are key to understanding the natural history of these viruses in swine and to selecting strains for effective vaccines. However, influenza outbreaks generally spread rapidly among swine, and the conventional methods for antigenic characterization require virus propagation, a time-consuming process that can significantly reduce the effectiveness of vaccination programs. We developed and validated a rapid, sensitive, and robust method, the polyclonal serum-based proximity ligation assay (polyPLA), to identify antigenic variants of subtype H3N2 swine IAVs. This method utilizes oligonucleotide-conjugated polyclonal antibodies and quantifies antibody-antigen binding affinities by quantitative reverse transcription-PCR (RT-PCR). Results showed the assay can rapidly detect H3N2 IAVs directly from nasal wash or nasal swab samples collected from laboratory-challenged animals or during influenza surveillance at county fairs. In addition, polyPLA can accurately separate the viruses at two contemporary swine IAV antigenic clusters (H3N2 swine IAV-α and H3N2 swine IAV-ß) with a sensitivity of 84.9% and a specificity of 100.0%. The polyPLA can be routinely used in surveillance programs to detect antigenic variants of influenza viruses and to select vaccine strains for use in controlling and preventing disease in swine. PMID:28077698

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 surveillance system for mass gatherings based on Internet data. The use of multiple data sources and analysis methods was found to be advantageous for rejecting false positives. Further studies are required in order to validate our findings with data from public health authorities.

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

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

PubMed

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

2017-11-01

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

Diagnostic Yield of Laboratory Methods and Value of Viral Genotyping during an Outbreak of Mumps in a Partially Vaccinated Population in British Columbia, Canada.

PubMed

Nunn, Alexandra; Masud, Shazia; Krajden, Mel; Naus, Monika; Jassem, Agatha N

2018-05-01

Mumps remains endemic in North America despite routine use of the measles, mumps, and rubella (MMR) vaccine. In 2016, an outbreak of mumps in British Columbia, Canada, provided an opportunity to determine the diagnostic utility of laboratory testing methods. Specimens from patients with clinical mumps were tested for infection using a commercial enzyme-linked immunosorbent assay (ELISA) for antibody detection and an in-house reverse transcriptase PCR (RT-PCR) targeting viral fusion and small hydrophobic (SH) genes. Viral genotyping was performed by SH gene sequencing. Laboratory data was linked with epidemiologic case data. Of the 139 confirmed cases, 94 (68%) had reported or documented history of MMR vaccination. Specimens were typically collected 1 day (for buccal and IgM tests) or 2 days (for urine tests) after symptom onset. Most confirmed cases (69%) were confirmed by buccal swab RT-PCR. Among cases tested by multiple methods, the percent positivity for buccal swab RT-PCR was 90% (96/107) compared to 43% (30/69) for both IgM ELISA and urine RT-PCR. Mumps IgM detection was higher in confirmed cases with no history of vaccination than in those with history (64% versus 34%, P = 0.02). The outbreak strain was identified as genotype G related to MuVi/Sheffield.GBR/1.05 but with conserved variations in five nucleotides within the SH gene that allowed linkage of geographically distinct cases. In conclusion, RT-PCR of buccal specimens had the highest diagnostic yield during a mumps outbreak in a partially vaccinated population. To optimize mumps diagnostic potential, clinicians should collect specimens depending on when the patient presents for care and their immunization history. © Crown copyright 2018.

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.

Public Health Investigation of Two Outbreaks of Shiga Toxin-Producing Escherichia coli O157 Associated with Consumption of Watercress.

PubMed

Jenkins, Claire; Dallman, Timothy J; Launders, Naomi; Willis, Caroline; Byrne, Lisa; Jorgensen, Frieda; Eppinger, Mark; Adak, Goutam K; Aird, Heather; Elviss, Nicola; Grant, Kathie A; Morgan, Dilys; McLauchlin, Jim

2015-06-15

An increase in the number of cases of Shiga toxin-producing Escherichia coli (STEC) O157 phage type 2 (PT2) in England in September 2013 was epidemiologically linked to watercress consumption. Whole-genome sequencing (WGS) identified a phylogenetically related cluster of 22 cases (outbreak 1). The isolates comprising this cluster were not closely related to any other United Kingdom strain in the Public Health England WGS database, suggesting a possible imported source. A second outbreak of STEC O157 PT2 (outbreak 2) was identified epidemiologically following the detection of outbreak 1. Isolates associated with outbreak 2 were phylogenetically distinct from those in outbreak 1. Epidemiologically unrelated isolates on the same branch as the outbreak 2 cluster included those from human cases in England with domestically acquired infection and United Kingdom domestic cattle. Environmental sampling using PCR resulted in the isolation of STEC O157 PT2 from irrigation water at one implicated watercress farm, and WGS showed this isolate belonged to the same phylogenetic cluster as outbreak 2 isolates. Cattle were in close proximity to the watercress bed and were potentially the source of the second outbreak. Transfer of STEC from the field to the watercress bed may have occurred through wildlife entering the watercress farm or via runoff water. During this complex outbreak investigation, epidemiological studies, comprehensive testing of environmental samples, and the use of novel molecular methods proved invaluable in demonstrating that two simultaneous outbreaks of STEC O157 PT2 were both linked to the consumption of watercress but were associated with different sources of contamination. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Public Health Investigation of Two Outbreaks of Shiga Toxin-Producing Escherichia coli O157 Associated with Consumption of Watercress

PubMed Central

Dallman, Timothy J.; Launders, Naomi; Willis, Caroline; Byrne, Lisa; Jorgensen, Frieda; Eppinger, Mark; Adak, Goutam K.; Aird, Heather; Elviss, Nicola; Grant, Kathie A.; Morgan, Dilys; McLauchlin, Jim

2015-01-01

An increase in the number of cases of Shiga toxin-producing Escherichia coli (STEC) O157 phage type 2 (PT2) in England in September 2013 was epidemiologically linked to watercress consumption. Whole-genome sequencing (WGS) identified a phylogenetically related cluster of 22 cases (outbreak 1). The isolates comprising this cluster were not closely related to any other United Kingdom strain in the Public Health England WGS database, suggesting a possible imported source. A second outbreak of STEC O157 PT2 (outbreak 2) was identified epidemiologically following the detection of outbreak 1. Isolates associated with outbreak 2 were phylogenetically distinct from those in outbreak 1. Epidemiologically unrelated isolates on the same branch as the outbreak 2 cluster included those from human cases in England with domestically acquired infection and United Kingdom domestic cattle. Environmental sampling using PCR resulted in the isolation of STEC O157 PT2 from irrigation water at one implicated watercress farm, and WGS showed this isolate belonged to the same phylogenetic cluster as outbreak 2 isolates. Cattle were in close proximity to the watercress bed and were potentially the source of the second outbreak. Transfer of STEC from the field to the watercress bed may have occurred through wildlife entering the watercress farm or via runoff water. During this complex outbreak investigation, epidemiological studies, comprehensive testing of environmental samples, and the use of novel molecular methods proved invaluable in demonstrating that two simultaneous outbreaks of STEC O157 PT2 were both linked to the consumption of watercress but were associated with different sources of contamination. PMID:25841005

Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.

PubMed

Pearce, Madison E; Alikhan, Nabil-Fareed; Dallman, Timothy J; Zhou, Zhemin; Grant, Kathie; Maiden, Martin C J

2018-06-02

Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions. Copyright © 2018. Published by Elsevier B.V.

Pertussis outbreak in Papua New Guinea: the challenges of response in a remote geo-topographical setting.

PubMed

Datta, Siddhartha Sankar; Toikilik, Steven; Ropa, Berry; Chidlow, Glenys; Lagani, William

2012-10-01

A large outbreak of pertussis was detected during March 2011 in Goilala, a remote district of the Central Province in Papua New Guinea, characterized by rugged topography with no road access from the provincial headquarters. This outbreak investigation highlights the difficulties in reporting and responding to outbreaks in these settings. The suspected pertussis cases, reported by health workers from the Ononge health centre area, were investigated and confirmed for the presence of Bordetella pertussis DNA using the polymerase chain reaction (PCR) method. There were 205 suspected pertussis cases, with a case-fatality rate (CFR) of 3%. All cases were unvaccinated. The Central Province conducted a response vaccination programme providing 65% of children less than five years of age with diphtheria-pertussis-tetanus-HepB-Hib vaccine at a cost of US$ 12.62 per child. The incurred cost of vaccination in response to this outbreak was much higher than the US$ 3.80 per child for routine outreach patrol. To prevent further outbreaks of vaccine-preventable diseases in these areas, local health centres must ensure routine vaccination is strengthened through the "Reaching Every District" initiative of the National Department of Health.

[EPIDEMIOLOGIC FEATURES OFNOROVIRUS INFECTION OUTBREAK IN THE REPUBLIC OF NORTH OSSETIA-ALANIA].

PubMed

Maletskaya, O V; Tibilov, A G; Prislegina, D A; Gazieva, G K; Otaraeva, N I; Volynkina, A S; Saveliev, V N; Lyamkin, G I; Zaitsev, A A; Kulichenko, A N

2016-01-01

Analysis of epidemiologic features of a norovirus outbreak in Alagir city of the Republic of North Ossetia-Alania and effectiveness of measures of its liquidation. Data from maps-schemes of water supply system of Alagir city and statistical documentation of Centre of Hygiene and Epidemiology in the Republic of North Ossetia-Alania were used in the study. Indication of norovirus in clinical material and water samples was carried out bypolymerase chain reaction method. Etiological agent of outbreak disease was established--genotype II norovirus. Realization of fecal-oral mechanisms of water transmission pathway of the causative agent of norovirus infection was detected. Conditions facilitating emergence and development of the indicated outbreak were determined--non-satisfactory sanitary-technical condition of water. supply system of the city. The studied water outbreak of norovirus infection was caused by GII.17 genotype virus, that currently gradually displaces GII.IV genotype, and was characterized by an intensive start, involvement of all population age groups into the epidemic process (with primary infection of adults), low family focality, predominance of average severity disease forms in the clinical presentation. The counter-epidemic measures carried out ensured rapid localization and liquidation of the norovirus infection outbreak.

Development of a faster method for detection of Shiga toxin producing E. coli using Tetrahymena thermophila

USDA-ARS?s Scientific Manuscript database

While most STEC outbreaks are caused by E. coli O157, non-O157 STECs are increasingly being implicated. Selective agar for E. coli O157 is commercially available but none detect non-O157 STEC. Currently, regulatory agencies screen for non-O157 STECs by enriching foods overnight, spreading aliquots o...

A polyclonal antibody based immunoassay detects seven subtypes of Shiga toxin 2 produced by escherichia coli in human and environmental samples

USDA-ARS?s Scientific Manuscript database

The increase of outbreaks and illnesses linked to Shiga toxin-producing Escherichia coli (STEC) has necessitated the development of effective detection methods for these pathogens in various matrices. The best way to determine if a bacterial strain is a STEC is to examine the production of Shiga tox...

Strategy for simultaneous molecular detection of the protozoan parasites Toxoplasma, Cryptosporidium and Giardia in food matrices and persistence on leaves of vegetables during storage at 4°C

USDA-ARS?s Scientific Manuscript database

Toxoplasma gondii, Cryptosporidium spp. and Giardia intestinalis are emerging pathogen parasites in the food domain. However, without standardized method for their detection in food matrices, parasitic foodborne outbreaks remain neglected. In this study, a new immunomagnetic separation assay (IMS To...

Applications of immunomagnetic capture and time-resolved fluorescence detection for Salmonella enteriditis in liquid eggs

NASA Astrophysics Data System (ADS)

Tu, Shu-I.; Gehring, Andrew; Paoli, George

2008-04-01

An immuno sandwich method was evaluated for the detection of Salmonella in liquid eggs. Liquid eggs spiked with different out-break strains of Salmonella were mixed with proper enrichment media and incubated at 37 C for 4 to 20 h. After enrichment, immunomagnetic beads (IMB) coated with anti Salmonella antibodies were used to capture the bacteria. Samarium (Sm) labeled anti Salmonella antibodies were then used to form sandwiched complexes with IMB captured bacteria. Sandwiched Salmonella were then treated with Sm-chelator to allow the measurement of the released Sm by time-resolved fluorescence (TRF). The processes ranging from IMB capture to Sm chelation were performed using an automated KingFisher apparatus. With this approach, the presence of ~ 1 CFU of outbreak strains of Salmonella Enteritidis per egg (~50 g of liquid eggs) could be detected after enrichment for 20 h at 37 C. For higher levels of Salmonella Enteritidis contamination, e.g., 10 CFU per 50 g of liquid eggs, the enrichment time could be reduced to 5 h at 37 C. The results demonstrated that a combination of IMB capture and TRF measurement could be a rapid and sensitive method for Salmonella Enteritidis detection in liquid eggs.

Basic examination of nondestructive and noncontact measurement system for fire damage level of concrete wall by using high-intensity aerial ultrasonic waves

NASA Astrophysics Data System (ADS)

Osumi, Ayumu; Ito, Youichi

2012-05-01

A fire site holds important information about the cause of fire outbreak; for instance, a concrete wall can provide a wealth of information and the distribution of fire damage of the wall is particularly valuable. If the distribution of fire damage on concrete walls can be used to trace the flow of fire, it would be possible to identify the fire origin and to clarify the cause of fire outbreak. In this study, we considered a new method based on aerial ultrasonic waves and developed a system that adopts this method for detecting fire damage of concrete walls at fire sites.

Methods for genotyping verotoxin-producing Escherichia coli.

PubMed

Karama, M; Gyles, C L

2010-12-01

Verotoxin-producing Escherichia coli (VTEC) is annually incriminated in more than 100,000 cases of enteric foodborne human disease and in losses amounting to $US 2.5 billion every year. A number of genotyping methods have been developed to track VTEC infections and determine diversity and evolutionary relationships among these microorganisms. These methods have facilitated monitoring and surveillance of foodborne VTEC outbreaks and early identification of outbreaks or clusters of outbreaks. Pulsed-field gel electrophoresis (PFGE) has been used extensively to track and differentiate VTEC because of its high discriminatory power, reproducibility and ease of standardization. Multiple-locus variable-number tandem-repeats analysis (MLVA) and microarrays are the latest genotyping methods that have been applied to discriminate VTEC. MLVA, a simpler and less expensive method, is proving to have a discriminatory power comparable to that of PFGE. Microarrays are successfully being applied to differentiate VTEC and make inferences on genome diversification. Novel methods that are being evaluated for subtyping VTEC include the detection of single nucleotide polymorphisms and optical mapping. This review discusses the principles, applications, advantages and disadvantages of genotyping methods that have been used to differentiate VTEC strains. These methods have been mainly used to differentiate strains of O157:H7 VTEC and to a lesser extent non-O157 VTEC. © 2009 Blackwell Verlag GmbH.

Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

PubMed

Shen, Yanna; Cooper, Gregory F

2012-09-01

This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A Qualitative Inquiry About Pruno, an Illicit Alcoholic Beverage Linked to Botulism Outbreaks in United States Prisons.

PubMed

Walters, Maroya Spalding; Sreenivasan, Nandini; Person, Bobbie; Shew, Mark; Wheeler, Daniel; Hall, Julia; Bogdanow, Linda; Leniek, Karyn; Rao, Agam

2015-11-01

Since 2011, 3 outbreaks of botulism in US prisons have been attributed to pruno, which is an alcoholic beverage made by inmates. Following 1 outbreak, we conducted a qualitative inquiry to understand pruno brewing and its social context to inform outbreak prevention measures. We interviewed staff, inmates, and parolees from 1 prison about pruno production methods, the social aspects of pruno, and strategies for communicating the association between botulism and pruno. Twenty-seven inmates and parolees and 13 staff completed interviews. Pruno is fermented from water, fruit, sugar, and miscellaneous ingredients. Knowledge of pruno making was widespread among inmates; staff were familiar with only the most common ingredients and supplies inmates described. Staff and inmates described inconsistent consequences for pruno possession and suggested using graphic health messages from organizations external to the prison to communicate the risk of botulism from pruno. Pruno making was frequent in this prison. Improved staff recognition of pruno ingredients and supplies might improve detection of brewing activities in this and other prisons. Consistent consequences and clear messages about the association between pruno and botulism might prevent outbreaks.

Oviposition traps to survey eggs of Lambdina fiscellaria (Lepidoptera: Geometridae).

PubMed

Hébert, Christian; Jobin, Luc; Auger, Michel; Dupont, Alain

2003-06-01

Outbreaks of the hemlock looper, Lambdina fiscellaria (Gueneé), are characterized by rapid increase and patchy distribution over widespread areas, which make it difficult to detect impending outbreaks. This is a major problem with this insect. Population forecasting is based on tedious and expensive egg surveys in which eggs are extracted from 1-m branches; careful observation is needed to avoid counting old unhatched eggs of previous year populations. The efficacy of artificial substrates as oviposition traps to sample hemlock looper eggs was tested as a means of improving outbreak detection and population forecasting. A white polyurethane foam substrate (1,095 lb/ft3) used with the Luminoc insect trap, a portable light trap, was highly efficient in sampling eggs of the hemlock looper. Foam strips placed on tree trunks at breast height were less efficient but easier and less expensive to use for the establishment of extensive survey networks. Estimates based on oviposition traps were highly correlated with those obtained from the 1-m branch extraction method. The oviposition trap is a standard, inexpensive, easy, and robust method that can be used by nonspecialists. This technique makes it possible to sample higher numbers of plots in widespread monitoring networks, which is crucial for improving the management of hemlock looper populations.

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

PubMed

Newkirk, Ryan W; Hedberg, Craig W

2012-02-01

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

Finding Outbreaks Faster

PubMed Central

Smolinski, Mark S.; Olsen, Jennifer M.

2017-01-01

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

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

PubMed

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

2014-05-12

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

Next-generation sequencing for typing and detection of resistance genes: performance of a new commercial method during an outbreak of extended-spectrum-beta-lactamase-producing Escherichia coli.

PubMed

Veenemans, J; Overdevest, I T; Snelders, E; Willemsen, I; Hendriks, Y; Adesokan, A; Doran, G; Bruso, S; Rolfe, A; Pettersson, A; Kluytmans, J A J W

2014-07-01

Next-generation sequencing (NGS) has the potential to provide typing results and detect resistance genes in a single assay, thus guiding timely treatment decisions and allowing rapid tracking of transmission of resistant clones. We evaluated the performance of a new NGS assay (Hospital Acquired Infection BioDetection System; Pathogenica) during an outbreak of sequence type 131 (ST131) Escherichia coli infections in a nursing home in The Netherlands. The assay was performed on 56 extended-spectrum-beta-lactamase (ESBL) E. coli isolates collected during 2 prevalence surveys (March and May 2013). Typing results were compared to those of amplified fragment length polymorphism (AFLP), whereby we visually assessed the agreement of the BioDetection phylogenetic tree with clusters defined by AFLP. A microarray was considered the gold standard for detection of resistance genes. AFLP identified a large cluster of 31 indistinguishable isolates on adjacent departments, indicating clonal spread. The BioDetection phylogenetic tree showed that all isolates of this outbreak cluster were strongly related, while the further arrangement of the tree also largely agreed with other clusters defined by AFLP. The BioDetection assay detected ESBL genes in all but 1 isolate (sensitivity, 98%) but was unable to discriminate between ESBL and non-ESBL TEM and SHV beta-lactamases or to specify CTX-M genes by group. The performance of the hospital-acquired infection (HAI) BioDetection System for typing of E. coli isolates compared well with the results of AFLP. Its performance with larger collections from different locations, and for typing of other species, was not evaluated and needs further study. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays▿ †

PubMed Central

Lin, Baochuan; Malanoski, Anthony P.; Wang, Zheng; Blaney, Kate M.; Long, Nina C.; Meador, Carolyn E.; Metzgar, David; Myers, Christopher A.; Yingst, Samuel L.; Monteville, Marshall R.; Saad, Magdi D.; Schnur, Joel M.; Tibbetts, Clark; Stenger, David A.

2009-01-01

Zoonotic microbes have historically been, and continue to emerge as, threats to human health. The recent outbreaks of highly pathogenic avian influenza virus in bird populations and the appearance of some human infections have increased the concern of a possible new influenza pandemic, which highlights the need for broad-spectrum detection methods for rapidly identifying the spread or outbreak of all variants of avian influenza virus. In this study, we demonstrate that high-density resequencing pathogen microarrays (RPM) can be such a tool. The results from 37 influenza virus isolates show that the RPM platform is an effective means for detecting and subtyping influenza virus, while simultaneously providing sequence information for strain resolution, pathogenicity, and drug resistance without additional analysis. This study establishes that the RPM platform is a broad-spectrum pathogen detection and surveillance tool for monitoring the circulation of prevalent influenza viruses in the poultry industry and in wild birds or incidental exposures and infections in humans. PMID:19279171

Impact of the choice of reference genome on the ability of the core genome SNV methodology to distinguish strains of Salmonella enterica serovar Heidelberg.

PubMed

Usongo, Valentine; Berry, Chrystal; Yousfi, Khadidja; Doualla-Bell, Florence; Labbé, Genevieve; Johnson, Roger; Fournier, Eric; Nadon, Celine; Goodridge, Lawrence; Bekal, Sadjia

2018-01-01

Salmonella enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. The core genome single nucleotide variant pipeline (cgSNV) is one of several whole genome based sequence typing methods used for the laboratory investigation of foodborne pathogens. SNV detection using this method requires a reference genome. The purpose of this study was to investigate the impact of the choice of the reference genome on the cgSNV-informed phylogenetic clustering and inferred isolate relationships. We found that using a draft or closed genome of S. Heidelberg as reference did not impact the ability of the cgSNV methodology to differentiate among 145 S. Heidelberg isolates involved in foodborne outbreaks. We also found that using a distantly related genome such as S. Dublin as choice of reference led to a loss in resolution since some sporadic isolates were found to cluster together with outbreak isolates. In addition, the genetic distances between outbreak isolates as well as between outbreak and sporadic isolates were overall reduced when S. Dublin was used as the reference genome as opposed to S. Heidelberg.

Sequential detection of influenza epidemics by the Kolmogorov-Smirnov test

PubMed Central

2012-01-01

Background Influenza is a well known and common human respiratory infection, causing significant morbidity and mortality every year. Despite Influenza variability, fast and reliable outbreak detection is required for health resource planning. Clinical health records, as published by the Diagnosticat database in Catalonia, host useful data for probabilistic detection of influenza outbreaks. Methods This paper proposes a statistical method to detect influenza epidemic activity. Non-epidemic incidence rates are modeled against the exponential distribution, and the maximum likelihood estimate for the decaying factor λ is calculated. The sequential detection algorithm updates the parameter as new data becomes available. Binary epidemic detection of weekly incidence rates is assessed by Kolmogorov-Smirnov test on the absolute difference between the empirical and the cumulative density function of the estimated exponential distribution with significance level 0 ≤ α ≤ 1. Results The main advantage with respect to other approaches is the adoption of a statistically meaningful test, which provides an indicator of epidemic activity with an associated probability. The detection algorithm was initiated with parameter λ0 = 3.8617 estimated from the training sequence (corresponding to non-epidemic incidence rates of the 2008-2009 influenza season) and sequentially updated. Kolmogorov-Smirnov test detected the following weeks as epidemic for each influenza season: 50−10 (2008-2009 season), 38−50 (2009-2010 season), weeks 50−9 (2010-2011 season) and weeks 3 to 12 for the current 2011-2012 season. Conclusions Real medical data was used to assess the validity of the approach, as well as to construct a realistic statistical model of weekly influenza incidence rates in non-epidemic periods. For the tested data, the results confirmed the ability of the algorithm to detect the start and the end of epidemic periods. In general, the proposed test could be applied to other data sets to quickly detect influenza outbreaks. The sequential structure of the test makes it suitable for implementation in many platforms at a low computational cost without requiring to store large data sets. PMID:23031321

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.

Data quality and timeliness of outbreak reporting system among countries in Greater Mekong subregion: Challenges for international data sharing

PubMed Central

Kaewkungwal, Jaranit; Khamsiriwatchara, Amnat; Sovann, Ly; Sreng, Bun; Phommasack, Bounlay; Kitthiphong, Viengsavanh; Lwin Nyein, Soe; Win Myint, Nyan; Dang Vung, Nguyen; Hung, Pham; S. Smolinski, Mark; W. Crawley, Adam; Ko Oo, Moe

2018-01-01

Cross-border disease transmission is a key challenge for prevention and control of outbreaks. Variation in surveillance structure and national guidelines used in different countries can affect their data quality and the timeliness of outbreak reports. This study aimed to evaluate timeliness and data quality of national outbreak reporting for four countries in the Mekong Basin Disease Surveillance network (MBDS). Data on disease outbreaks occurring from 2010 to 2015 were obtained from the national disease surveillance reports of Cambodia, Lao PDR, Myanmar, and Vietnam. Data included total cases, geographical information, and dates at different timeline milestones in the outbreak detection process. Nine diseases or syndromes with public health importance were selected for the analysis including: dengue, food poisoning & diarrhea, severe diarrhea, diphtheria, measles, H5N1 influenza, H1N1 influenza, rabies, and pertussis. Overall, 2,087 outbreaks were reported from the four countries. The number of outbreaks and number of cases per outbreak varied across countries and diseases, depending in part on the outbreak definition used in each country. Dates on index onset, report, and response were >95% complete in all countries, while laboratory confirmation dates were 10%-100% incomplete in most countries. Inconsistent and out of range date data were observed in 1%-5% of records. The overall timeliness of outbreak report, response, and public communication was within 1–15 days, depending on countries and diseases. Diarrhea and severe diarrhea outbreaks showed the most rapid time to report and response, whereas diseases such as rabies, pertussis and diphtheria required a longer time to report and respond. The hierarchical structure of the reporting system, data collection method, and country’s resources could affect the data quality and timeliness of the national outbreak reporting system. Differences in data quality and timeliness of outbreak reporting system among member countries should be considered when planning data sharing strategies within a regional network. PMID:29694372

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

PubMed Central

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

2017-01-01

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

Development of a Salmonella screening tool for consumer complaint-based foodborne illness surveillance systems.

PubMed

Li, John; Maclehose, Rich; Smith, Kirk; Kaehler, Dawn; Hedberg, Craig

2011-01-01

Foodborne illness surveillance based on consumer complaints detects outbreaks by finding common exposures among callers, but this process is often difficult. Laboratory testing of ill callers could also help identify potential outbreaks. However, collection of stool samples from all callers is not feasible. Methods to help screen calls for etiology are needed to increase the efficiency of complaint surveillance systems and increase the likelihood of detecting foodborne outbreaks caused by Salmonella. Data from the Minnesota Department of Health foodborne illness surveillance database (2000 to 2008) were analyzed. Complaints with identified etiologies were examined to create a predictive model for Salmonella. Bootstrap methods were used to internally validate the model. Seventy-one percent of complaints in the foodborne illness database with known etiologies were due to norovirus. The predictive model had a good discriminatory ability to identify Salmonella calls. Three cutoffs for the predictive model were tested: one that maximized sensitivity, one that maximized specificity, and one that maximized predictive ability, providing sensitivities and specificities of 32 and 96%, 100 and 54%, and 89 and 72%, respectively. Development of a predictive model for Salmonella could help screen calls for etiology. The cutoff that provided the best predictive ability for Salmonella corresponded to a caller reporting diarrhea and fever with no vomiting, and five or fewer people ill. Screening calls for etiology would help identify complaints for further follow-up and result in identifying Salmonella cases that would otherwise go unconfirmed; in turn, this could lead to the identification of more outbreaks.

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

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

NASA Astrophysics Data System (ADS)

Shamkhali Chenar, S.; Deng, Z.

2017-12-01

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

Advances in Significance Testing for Cluster Detection

NASA Astrophysics Data System (ADS)

Coleman, Deidra Andrea

Over the past two decades, much attention has been given to data driven project goals such as the Human Genome Project and the development of syndromic surveillance systems. A major component of these types of projects is analyzing the abundance of data. Detecting clusters within the data can be beneficial as it can lead to the identification of specified sequences of DNA nucleotides that are related to important biological functions or the locations of epidemics such as disease outbreaks or bioterrorism attacks. Cluster detection techniques require efficient and accurate hypothesis testing procedures. In this dissertation, we improve upon the hypothesis testing procedures for cluster detection by enhancing distributional theory and providing an alternative method for spatial cluster detection using syndromic surveillance data. In Chapter 2, we provide an efficient method to compute the exact distribution of the number and coverage of h-clumps of a collection of words. This method involves defining a Markov chain using a minimal deterministic automaton to reduce the number of states needed for computation. We allow words of the collection to contain other words of the collection making the method more general. We use our method to compute the distributions of the number and coverage of h-clumps in the Chi motif of H. influenza.. In Chapter 3, we provide an efficient algorithm to compute the exact distribution of multiple window discrete scan statistics for higher-order, multi-state Markovian sequences. This algorithm involves defining a Markov chain to efficiently keep track of probabilities needed to compute p-values of the statistic. We use our algorithm to identify cases where the available approximation does not perform well. We also use our algorithm to detect unusual clusters of made free throw shots by National Basketball Association players during the 2009-2010 regular season. In Chapter 4, we give a procedure to detect outbreaks using syndromic surveillance data while controlling the Bayesian False Discovery Rate (BFDR). The procedure entails choosing an appropriate Bayesian model that captures the spatial dependency inherent in epidemiological data and considers all days of interest, selecting a test statistic based on a chosen measure that provides the magnitude of the maximumal spatial cluster for each day, and identifying a cutoff value that controls the BFDR for rejecting the collective null hypothesis of no outbreak over a collection of days for a specified region.We use our procedure to analyze botulism-like syndrome data collected by the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

Evaluation and comparison of rapid methods for the detection of Salmonella in naturally contaminated pine nuts using different pre enrichment media.

PubMed

Wang, Hua; Gill, Vikas S; Cheng, Chorng-Ming; Gonzalez-Escalona, Narjol; Irvin, Kari A; Zheng, Jie; Bell, Rebecca L; Jacobson, Andrew P; Hammack, Thomas S

2015-04-01

Foodborne outbreaks, involving pine nuts and peanut butter, illustrate the need to rapidly detect Salmonella in low moisture foods. However, the current Bacteriological Analytical Manual (BAM) culture method for Salmonella, using lactose broth (LB) as a pre enrichment medium, has not reliably supported real-time quantitative PCR (qPCR) assays for certain foods. We evaluated two qPCR assays in LB and four other pre enrichment media: buffered peptone water (BPW), modified BPW (mBPW), Universal Pre enrichment broth (UPB), and BAX(®) MP media to detect Salmonella in naturally-contaminated pine nuts (2011 outbreak). A four-way comparison among culture method, Pathatrix(®) Auto, VIDAS(®) Easy SLM, and qPCR was conducted. Automated DNA extraction techniques were compared with manual extraction methods (boiling or InstaGene™). There were no significant differences (P > 0.05) among the five pre enrichment media for pine nuts using the culture method. While both qPCR assays produced significantly (P ≤ 0.05) higher false negatives in 24 h pre enriched LB than in the other four media, they were as sensitive as the culture method in BPW, mBPW, UPB, and BAX media. The VIDAS Easy and qPCR were equivalent; Pathatrix was the least effective method. The Automatic PrepSEQ™ DNA extraction, using 1000 μL of pre enrichment, was as effective as manual extraction methods. Published by Elsevier Ltd.

Optimized MOL-PCR for Characterization of Microbial Pathogens.

PubMed

Wuyts, Véronique; Roosens, Nancy H C; Bertrand, Sophie; Marchal, Kathleen; De Keersmaecker, Sigrid C J

2016-01-06

Characterization of microbial pathogens is necessary for surveillance, outbreak detection, and tracing of outbreak sources. This unit describes a multiplex oligonucleotide ligation-PCR (MOL-PCR) optimized for characterization of microbial pathogens. With MOL-PCR, different types of markers, like unique sequences, single-nucleotide polymorphisms (SNPs) and indels, can be simultaneously analyzed in one assay. This assay consists of a multiplex ligation for detection of the markers, a singleplex PCR for signal amplification, and hybridization to MagPlex-TAG beads for readout on a Luminex platform after fluorescent staining. The current protocol describes the MOL-PCR, as well as methods for DNA isolation, probe design, and data interpretation and it is based on an optimized MOL-PCR assay for subtyping of Salmonella Typhimurium. Copyright © 2016 John Wiley & Sons, Inc.

A natural outbreak of Aujeszky's disease in farm animals.

PubMed

Salwa, A

2004-01-01

An outbreak of Aujeszky's disease (AD) occurred in a herd of domestic animals that led to the death of seven cattle, three goats, three sheep, two cats and one dog, all of them with CNS signs. The animals were not in direct contact with swine. The ADV was detected in the tissue of affected animals by celi culture methods and PCR. Genome strains of ADV were characterized by restriction endonuclease analysis using BamH I. The results indicated that the strains of virus were identical and belonged to the type genome I of AD. Compared with vaccine and isolated strains obtained from the pig in the same region, considerable differences in DNA patterns were detected. Interestingly, the strains isolated from the dead animals were similar to Buk T-900 reference strains.

Detection of Antigenic Variants of Subtype H3 Swine Influenza A Viruses from Clinical Samples.

PubMed

Martin, Brigitte E; Bowman, Andrew S; Li, Lei; Nolting, Jacqueline M; Smith, David R; Hanson, Larry A; Wan, Xiu-Feng

2017-04-01

A large population of genetically and antigenically diverse influenza A viruses (IAVs) are circulating among the swine population, playing an important role in influenza ecology. Swine IAVs not only cause outbreaks among swine but also can be transmitted to humans, causing sporadic infections and even pandemic outbreaks. Antigenic characterizations of swine IAVs are key to understanding the natural history of these viruses in swine and to selecting strains for effective vaccines. However, influenza outbreaks generally spread rapidly among swine, and the conventional methods for antigenic characterization require virus propagation, a time-consuming process that can significantly reduce the effectiveness of vaccination programs. We developed and validated a rapid, sensitive, and robust method, the polyclonal serum-based proximity ligation assay (polyPLA), to identify antigenic variants of subtype H3N2 swine IAVs. This method utilizes oligonucleotide-conjugated polyclonal antibodies and quantifies antibody-antigen binding affinities by quantitative reverse transcription-PCR (RT-PCR). Results showed the assay can rapidly detect H3N2 IAVs directly from nasal wash or nasal swab samples collected from laboratory-challenged animals or during influenza surveillance at county fairs. In addition, polyPLA can accurately separate the viruses at two contemporary swine IAV antigenic clusters (H3N2 swine IAV-α and H3N2 swine IAV-ß) with a sensitivity of 84.9% and a specificity of 100.0%. The polyPLA can be routinely used in surveillance programs to detect antigenic variants of influenza viruses and to select vaccine strains for use in controlling and preventing disease in swine. Copyright © 2017 American Society for Microbiology.

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

PubMed

Osemek, Paweł; Kocik, Janusz; Paśnik, Krzysztof

2009-12-01

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

Detection of human Norovirus in cherry tomatoes, blueberries and vegetable salad by using a receptor binding based capture and magnetic sequestration(RBCMS) method

USDA-ARS?s Scientific Manuscript database

Contaminated produce related norovirus (NoV) outbreak is a major public health concern. The establishment of a simple assay for concentrating and detecting NoV contamination in fresh produce that can be performed in a single day would be of great benefit to the producers and regulators of produce pr...

PCR assay detects Mannheimia haemolytica in culture-negative pneumonic lung tissues of bighorn sheep (Ovis canadensis) from outbreaks in the western USA, 2009-2010.

PubMed

Shanthalingam, Sudarvili; Goldy, Andrea; Bavananthasivam, Jegarubee; Subramaniam, Renuka; Batra, Sai Arun; Kugadas, Abirami; Raghavan, Bindu; Dassanayake, Rohana P; Jennings-Gaines, Jessica E; Killion, Halcyon J; Edwards, William H; Ramsey, Jennifer M; Anderson, Neil J; Wolff, Peregrine L; Mansfield, Kristin; Bruning, Darren; Srikumaran, Subramaniam

2014-01-01

Mannheimia haemolytica consistently causes severe bronchopneumonia and rapid death of bighorn sheep (Ovis canadensis) under experimental conditions. However, Bibersteinia trehalosi and Pasteurella multocida have been isolated from pneumonic bighorn lung tissues more frequently than M. haemolytica by culture-based methods. We hypothesized that assays more sensitive than culture would detect M. haemolytica in pneumonic lung tissues more accurately. Therefore, our first objective was to develop a PCR assay specific for M. haemolytica and use it to determine if this organism was present in the pneumonic lungs of bighorns during the 2009-2010 outbreaks in Montana, Nevada, and Washington, USA. Mannheimia haemolytica was detected by the species-specific PCR assay in 77% of archived pneumonic lung tissues that were negative by culture. Leukotoxin-negative M. haemolytica does not cause fatal pneumonia in bighorns. Therefore, our second objective was to determine if the leukotoxin gene was also present in the lung tissues as a means of determining the leukotoxicity of M. haemolytica that were present in the lungs. The leukotoxin-specific PCR assay detected leukotoxin gene in 91% of lung tissues that were negative for M. haemolytica by culture. Mycoplasma ovipneumoniae, an organism associated with bighorn pneumonia, was detected in 65% of pneumonic bighorn lung tissues by PCR or culture. A PCR assessment of distribution of these pathogens in the nasopharynx of healthy bighorns from populations that did not experience an all-age die-off in the past 20 yr revealed that M. ovipneumoniae was present in 31% of the animals whereas leukotoxin-positive M. haemolytica was present in only 4%. Taken together, these results indicate that culture-based methods are not reliable for detection of M. haemolytica and that leukotoxin-positive M. haemolytica was a predominant etiologic agent of the pneumonia outbreaks of 2009-2010.

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

PubMed

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

2008-02-01

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

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

PubMed Central

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

2008-01-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2014-11-01

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

Multilocus Variable-Number-Tandem-Repeats Analysis (MLVA) distinguishes a clonal complex of Clavibacter michiganensis subsp. michiganensis strains isolated from recent outbreaks of bacterial wilt and canker in Belgium

PubMed Central

2013-01-01

Background Clavibacter michiganensis subsp. michiganensis (Cmm) causes bacterial wilt and canker in tomato. Cmm is present nearly in all European countries. During the last three years several local outbreaks were detected in Belgium. The lack of a convenient high-resolution strain-typing method has hampered the study of the routes of transmission of Cmm and epidemiology in tomato cultivation. In this study the genetic relatedness among a worldwide collection of Cmm strains and their relatives was approached by gyrB and dnaA gene sequencing. Further, we developed and applied a multilocus variable number of tandem repeats analysis (MLVA) scheme to discriminate among Cmm strains. Results A phylogenetic analysis of gyrB and dnaA gene sequences of 56 Cmm strains demonstrated that Belgian Cmm strains from recent outbreaks of 2010–2012 form a genetically uniform group within the Cmm clade, and Cmm is phylogenetically distinct from other Clavibacter subspecies and from non-pathogenic Clavibacter-like strains. MLVA conducted with eight minisatellite loci detected 25 haplotypes within Cmm. All strains from Belgian outbreaks, isolated between 2010 and 2012, together with two French strains from 2010 seem to form one monomorphic group. Regardless of the isolation year, location or tomato cultivar, Belgian strains from recent outbreaks belonged to the same haplotype. On the contrary, strains from diverse geographical locations or isolated over longer periods of time formed mostly singletons. Conclusions We hypothesise that the introduction might have originated from one lot of seeds or contaminated tomato seedlings that was the source of the outbreak in 2010 and that these Cmm strains persisted and induced infection in 2011 and 2012. Our results demonstrate that MLVA is a promising typing technique for a local surveillance and outbreaks investigation in epidemiological studies of Cmm. PMID:23738754

[Two Outbreaks of Yersinia enterocolitica O:8 Infections in Tokyo and the Characterization of Isolates].

PubMed

Konishi, Noriko; Ishitsuka, Rie; Yokoyama, Keiko; Saiki, Dai; Akase, Satoru; Monma, Chie; Hirai, Akihiko; Sadamasu, Kenji; Kai, Akemi

2016-01-01

Although the number of outbreaks caused by Yersinia enterocolitica has been very small in Japan, 4 outbreaks were occurred during the 2 years between 2012 and 2013. We describe herein 2 outbreaks which were examined in Tokyo in the present study. Outbreak 1: A total of 39 people (37 high school students and 2 staff) stayed at a hotel in mountain area in Japan had experienced abdominal pain, diarrhea and fever in August, 2012. The Y. enterocolitica serogroup O:8 was isolated from 18 (64.3%) out of 28 fecal specimens of 28 patients. The infection roots could not be revealed because Y. enterocolitica was not detected from any meals at the hotel or its environment. Outbreak 2: A total of 52 students at a dormitory had diarrhea and fever in April, 2013. The results of the bacteriological and virological examinations of fecal specimens of patients showed that the Y. enterocolitica serogroup O:8 was isolated from 24 fecal specimens of 21 patients and 3 kitchen staff. We performed bacteriological and virological examination of the stored and preserved foods at the kitchen of the dormitory to reveal the suspect food. For the detection of Y. enterocolitica, food samples. together with phosphate buffered saline (PBS) were incubated at 4 degrees C for 21 days. Then, a screening test for Y. enterocolitica using realtime-PCR targeting the ail gene was performed against the PBS culture. One sample (fresh vegetable salad) tested was positive on realtime-PCR. No Y. enterocolitica was isolated on CIN agar from the PBS culture because many bacteria colonies other than Y. enterocolitica appeared on the CIN agar. After the alkaline-treatments of the culture broth or the immunomagnetic beads concentration method using anti-Y. enterocolitica O:8 antibodies, Y. enterocolitica O:8 which was the same serogroup as the patients' isolates was successfully isolated from the PBS culture. The fresh vegetable salad was confirmed as the incrimination food of this outbreak.

Multilocus variable-number-tandem-repeats analysis (MLVA) distinguishes a clonal complex of Clavibacter michiganensis subsp. michiganensis strains isolated from recent outbreaks of bacterial wilt and canker in Belgium.

PubMed

Zaluga, Joanna; Stragier, Pieter; Van Vaerenbergh, Johan; Maes, Martine; De Vos, Paul

2013-06-05

Clavibacter michiganensis subsp. michiganensis (Cmm) causes bacterial wilt and canker in tomato. Cmm is present nearly in all European countries. During the last three years several local outbreaks were detected in Belgium. The lack of a convenient high-resolution strain-typing method has hampered the study of the routes of transmission of Cmm and epidemiology in tomato cultivation. In this study the genetic relatedness among a worldwide collection of Cmm strains and their relatives was approached by gyrB and dnaA gene sequencing. Further, we developed and applied a multilocus variable number of tandem repeats analysis (MLVA) scheme to discriminate among Cmm strains. A phylogenetic analysis of gyrB and dnaA gene sequences of 56 Cmm strains demonstrated that Belgian Cmm strains from recent outbreaks of 2010-2012 form a genetically uniform group within the Cmm clade, and Cmm is phylogenetically distinct from other Clavibacter subspecies and from non-pathogenic Clavibacter-like strains. MLVA conducted with eight minisatellite loci detected 25 haplotypes within Cmm. All strains from Belgian outbreaks, isolated between 2010 and 2012, together with two French strains from 2010 seem to form one monomorphic group. Regardless of the isolation year, location or tomato cultivar, Belgian strains from recent outbreaks belonged to the same haplotype. On the contrary, strains from diverse geographical locations or isolated over longer periods of time formed mostly singletons. We hypothesise that the introduction might have originated from one lot of seeds or contaminated tomato seedlings that was the source of the outbreak in 2010 and that these Cmm strains persisted and induced infection in 2011 and 2012. Our results demonstrate that MLVA is a promising typing technique for a local surveillance and outbreaks investigation in epidemiological studies of Cmm.

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.

IMPROVING DETECTION METHODS FOR ENTERIC WATERBORNE VIRUSES

EPA Science Inventory

Waterborne viruses are a significant cause of illness, both within the US and worldwide. These illnesses can occur as the result of outbreaks, potentially affecting hundreds or thousands of people, or as a part of a background level of endemic infection. While many of these out...

DEVELOPMENT OF A MOLECULAR METHOD TO DETECT ASTROVIRUS

EPA Science Inventory

Astrovirus is a common cause of gastroenteritis that has been determined to be responsible for several outbreaks. Since astrovirus can be waterborne, there is interest in testing environmental water for astrovirus and we have developed a sensitive RT-PCR assay that is designed t...

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.

Prevalence and evaluation strategies for viral contamination in food products: Risk to human health-a review.

PubMed

Shukla, Shruti; Cho, Hyunjeong; Kwon, O Jun; Chung, Soo Hyun; Kim, Myunghee

2018-02-11

Nowadays, viruses of foodborne origin such as norovirus and hepatitis A are considered major causes of foodborne gastrointestinal illness with widespread distribution worldwide. A number of foodborne outbreaks associated with food products of animal and non-animal origins, which often involve multiple cases of variety of food streams, have been reported. Although several viruses, including rotavirus, adenovirus, astrovirus, parvovirus, and other enteroviruses, significantly contribute to incidence of gastrointestinal diseases, systematic information on the role of food in transmitting such viruses is limited. Most of the outbreak cases caused by infected food handlers were the source of 53% of total outbreaks. Therefore, prevention and hygiene measures to reduce the frequency of foodborne virus outbreaks should focus on food workers and production site of food products. Pivotal strategies, such as proper investigation, surveillance, and reports on foodborne viral illnesses, are needed in order to develop more accurate measures to detect the presence and pathogenesis of viral infection with detailed descriptions. Moreover, molecular epidemiology and surveillance of food samples may help analysis of public health hazards associated with exposure to foodborne viruses. In this present review, we discuss different aspects of foodborne viral contamination and its impact on human health. This review also aims to improve understanding of foodborne viral infections as major causes of human illness as well as provide descriptions of their control and prevention strategies and rapid detection by advanced molecular techniques. Further, a brief description of methods available for the detection of viruses in food and related matrices is provided.

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

USDA-ARS?s Scientific Manuscript database

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

Rapid Detection and Characterization of Emerging Foreign Animal Disease Pathogens

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

Jaing, C.

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

Sub-typing of extended-spectrum-β-lactamase-producing isolates from a nosocomial outbreak: application of a 10-loci generic Escherichia coli multi-locus variable number tandem repeat analysis.

PubMed

Karami, Nahid; Helldal, Lisa; Welinder-Olsson, Christina; Ahrén, Christina; Moore, Edward R B

2013-01-01

Extended-spectrum β-lactamase producing Escherichia coli (ESBL-E. coli) were isolated from infants hospitalized in a neonatal, post-surgery ward during a four-month-long nosocomial outbreak and six-month follow-up period. A multi-locus variable number tandem repeat analysis (MLVA), using 10 loci (GECM-10), for 'generic' (i.e., non-STEC) E. coli was applied for sub-species-level (i.e., sub-typing) delineation and characterization of the bacterial isolates. Ten distinct GECM-10 types were detected among 50 isolates, correlating with the types defined by pulsed-field gel electrophoresis (PFGE), which is recognized to be the 'gold-standard' method for clinical epidemiological analyses. Multi-locus sequence typing (MLST), multiplex PCR genotyping of bla CTX-M, bla TEM, bla OXA and bla SHV genes and antibiotic resistance profiling, as well as a PCR assay specific for detecting isolates of the pandemic O25b-ST131 strain, further characterized the outbreak isolates. Two clusters of isolates with distinct GECM-10 types (G06-04 and G07-02), corresponding to two major PFGE types and the MLST-based sequence types (STs) 131 and 1444, respectively, were confirmed to be responsible for the outbreak. The application of GECM-10 sub-typing provided reliable, rapid and cost-effective epidemiological characterizations of the ESBL-producing isolates from a nosocomial outbreak that correlated with and may be used to replace the laborious PFGE protocol for analyzing generic E. coli.

The Application of New Molecular Methods in the Investigation of a Waterborne Outbreak of Norovirus in Denmark, 2012

PubMed Central

Schultz, Anna Charlotte; Fonager, Jannik; Ethelberg, Steen; Dalgaard, Camilla; Adelhardt, Marianne; Engberg, Jørgen H.; Fischer, Thea Kølsen; Lassen, Sofie Gillesberg

2014-01-01

In December 2012, an outbreak of acute gastrointestinal illness occurred in a geographical distinct area in Denmark covering 368 households. A combined microbiological, epidemiological and environmental investigation was initiated to understand the outbreak magnitude, pathogen(s) and vehicle in order to control the outbreak. Norovirus GII.4 New Orleans 2009 variant was detected in 15 of 17 individual stool samples from 14 households. Norovirus genomic material from water samples was detected and quantified and sequencing of longer parts of the viral capsid region (>1000 nt) were applied to patient and water samples. All five purposely selected water samples tested positive for norovirus GII in levels up to 1.8×104 genomic units per 200 ml. Identical norovirus sequences were found in all 5 sequenced stool samples and 1 sequenced water sample, a second sequenced water sample showed 1 nt (<0.1%) difference. In a cohort study, including 256 participants, cases were defined as residents of the area experiencing diarrhoea or vomiting onset on 12–14 December 2012. We found an attack rate of 51%. Being a case was associated with drinking tap-water on 12–13 December (relative risk = 6.0, 95%CI: 1.6–22) and a dose-response relation for the mean glasses of tap-water consumed was observed. Environmental investigations suggested contamination from a sewage pipe to the drinking water due to fall in pressure during water supply system renovations. The combined microbiological, epidemiological and environmental investigations strongly indicates the outbreak was caused by norovirus contamination of the water supply system. PMID:25222495

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

PubMed

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

2014-06-01

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

Crow deaths as a sentinel surveillance system for West Nile virus in the northeastern United States, 1999

USGS Publications Warehouse

Eidson, M.; Komar, N.; Sorhage, F.; Nelson, R.; Talbot, T.; Mostashari, F.; McLean, R.; ,

2001-01-01

In addition to human encephalitis and meningitis cases, the West Nile (WN) virus outbreak in the summer and fall of 1999 in New York State resulted in bird deaths in New York, New Jersey, and Connecticut. From August to December 1999, 295 dead birds were laboratory-confirmed with WN virus infection; 262 (89%) were American Crows (Corvus brachyrhynchos). The New York State Department of Health received reports of 17,339 dead birds, including 5,697 (33%) crows; in Connecticut 1,040 dead crows were reported. Bird deaths were critical in identifying WN virus as the cause of the human outbreak and defining its geographic and temporal limits. If established before a WN virus outbreak, a surveillance system based on bird deaths may provide a sensitive method of detecting WN virus.

Evaluation of Immunomagnetic Separation Method for the Recovery of Hepatitis A Virus and GI.1 and GII.4 Norovirus Strains Seeded on Oyster and Mussel.

PubMed

Ha, Ji-Hyoung; Choi, Changsun; Ha, Sang-Do

2014-12-01

Outbreaks of viral diseases are frequently associated with the consumption of minimally processed shellfish. Among the viruses in these outbreaks, hepatitis A virus (HAV) and human norovirus (NoV) have been increasingly reported as the most common food-borne pathogens. These viruses must be concentrated in tested samples in order to be detected. In this study, a method for the detection of NoV and HAV in shellfish using an immuno-magnetic separation (IMS) procedure combined with reverse transcriptase (RT)-PCR was developed. The IMS/RT-PCR method was applied to investigate the recovery rates of HAV, NoV GI.1, and GII.4 from oyster and mussel. Based on IMS/RT-PCR results, recovery rates for HAV from oyster and mussel test samples were 2.4 and 1.1%, respectively. The NoV GI.1 recovery rates from oyster and mussel samples were 4.9-9.2% (mean 6.9%) and 4.3-8.6% (mean 6.2%), respectively, and the NoV GII.4 recovery rates were 8.8 and 8.5%, respectively. These results verified that HAV, NoV GI.1, and GII.4 can be detected in all the test samples using the IMS/RT-PCR method, although the three inoculated viruses were recovered with low efficiency. In conclusion, the IMS/RT-PCR method can be used to efficiently and rapidly detect viruses such as HAV and NoV in shellfish such as oyster and mussel.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-06-06

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

Gastrointestinal Illness Associated with Rancid Tortilla Chips at a Correctional Facility - Wyoming, 2015.

PubMed

Lupcho, Tiffany; Harrist, Alexia; Van Houten, Clay

2016-10-28

On October 12, 2015, a county health department notified the Wyoming Department of Health of an outbreak of gastrointestinal illness among residents and staff members at a local correctional facility. The majority of ill persons reported onset of symptoms within 1-3 hours after eating lunch served at the facility cafeteria at noon on October 11. Residents and staff members reported that tortilla chips served at the lunch tasted and smelled like chemicals. The Wyoming Department of Health and county health department personnel conducted case-control studies to identify the outbreak source. Consuming lunch at the facility on October 11 was highly associated with illness; multivariate logistic regression analysis found that tortilla chips were the only food item associated with illness. Hexanal and peroxide, markers for rancidity, were detected in tortilla chips and composite food samples from the lunch. No infectious agent was detected in human stool specimens or food samples. Extensive testing of lunch items did not identify any unusual chemical. Epidemiologic and laboratory evidence implicated rancid tortilla chips as the most likely source of illness. This outbreak serves as a reminder to consider alternative food testing methods during outbreaks of unusual gastrointestinal illness when typical foodborne pathogens are not identified. For interpretation of alternative food testing results, samples of each type of food not suspected to be contaminated are needed to serve as controls.

Comparison and optimization of detection methods for noroviruses in frozen strawberries containing different amounts of RT-PCR inhibitors.

PubMed

Bartsch, Christina; Szabo, Kathrin; Dinh-Thanh, Mai; Schrader, Christina; Trojnar, Eva; Johne, Reimar

2016-12-01

Frozen berries have been repeatedly identified as vehicles for norovirus (NoV) transmission causing large gastroenteritis outbreaks. However, virus detection in berries is often hampered by the presence of RT-PCR-inhibiting substances. Here, several virus extraction methods for subsequent real-time RT-PCR-based NoV-RNA detection in strawberries were compared and optimized. NoV recovery rates (RRs) between 0.21 ± 0.13% and 10.29 ± 6.03% were found when five different artificially contaminated strawberry batches were analyzed by the ISO/TS15216-2 method indicating the presence of different amounts of RT-PCR inhibitors. A comparison of five different virus extraction methods using artificially contaminated strawberries containing high amounts of RT-PCR inhibitors revealed the best NoV RRs for the ISO/TS15216 method. Further improvement of NoV RRs from 2.83 ± 2.92% to 15.28 ± 9.73% was achieved by the additional use of Sephacryl(®)-based columns for RNA purification. Testing of 22 frozen strawberry samples from a batch involved in a gastroenteritis outbreak resulted in 5 vs. 13 NoV GI-positive and in 9 vs. 20 NoV GII-positive samples using the original ISO/TS15216 method vs. the extended protocol, respectively. It can be concluded that the inclusion of an additional RNA purification step can increase NoV detection by the ISO/TS15216-2 method in frozen berries containing high amounts of RT-PCR inhibitors. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

DuPont Qualicon BAX System polymerase chain reaction assay. Performance Tested Method 100201.

PubMed

Tice, George; Andaloro, Bridget; Fallon, Dawn; Wallace, F Morgan

2009-01-01

A recent outbreak of Salmonella in peanut butter has highlighted the need for validation of rapid detection methods. A multilaboratory study for detecting Salmonella in peanut butter was conducted as part of the AOAC Research Institute Emergency Response Validation program for methods that detect outbreak threats to food safety. Three sites tested spiked samples from the same master mix according to the U.S. Food and Drug Administration's Bacteriological Analytical Manual (FDA-BAM) method and the BAX System method. Salmonella Typhimurium (ATCC 14028) was grown in brain heart infusion for 24 h at 37 degrees C, then diluted to appropriate levels for sample inoculation. Master samples of peanut butter were spiked at high and low target levels, mixed, and allowed to equilibrate at room temperature for 2 weeks. Spike levels were low [1.08 most probable number (MPN)/25 g]; high (11.5 MPN/25 g) and unspiked to serve as negative controls. Each master sample was divided into 25 g portions and coded to blind the samples. Twenty portions of each spiked master sample and five portions of the unspiked sample were tested at each site. At each testing site, samples were blended in 25 g portions with 225 mL prewarmed lactose broth until thoroughly homogenized, then allowed to remain at room temperature for 55-65 min. Samples were adjusted to a pH of 6.8 +/- 0.2, if necessary, and incubated for 22-26 h at 35 degrees C. Across the three reporting laboratories, the BAX System detected Salmonella in 10/60 low-spike samples and 58/60 high-spike samples. The reference FDA-BAM method yielded positive results for 11/60 low-spike and 58/60 high-spike samples. Neither method demonstrated positive results for any of the 15 unspiked samples.

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

Phage typing or CRISPR typing for epidemiological surveillance of Salmonella Typhimurium?

PubMed

Mohammed, Manal

2017-11-07

Salmonella Typhimurium is the most dominant Salmonella serovar around the world. It is associated with foodborne gastroenteritis outbreaks but has recently been associated with invasive illness and deaths. Characterization of S. Typhimurium is therefore very crucial for epidemiological surveillance. Phage typing has been used for decades for subtyping of S. Typhimurium to determine the epidemiological relation among isolates. Recent studies however have suggested that high throughput clustered regular interspaced short palindromic repeats (CRISPR) typing has the potential to replace phage typing. This study aimed to determine the efficacy of high-throughput CRISPR typing over conventional phage typing in epidemiological surveillance and outbreak investigation of S. Typhimurium. In silico analysis of whole genome sequences (WGS) of well-documented phage types of S. Typhimurium reveals the presence of different CRISPR type among strains belong to the same phage type. Furthermore, different phage types of S. Typhimurium share identical CRISPR type. Interestingly, identical spacers were detected among outbreak and non-outbreak associated DT8 strains of S. Typhimurium. Therefore, CRISPR typing is not useful for the epidemiological surveillance and outbreak investigation of S. Typhimurium and phage typing, until it is replaced by WGS, is still the gold standard method for epidemiological surveillance of S. Typhimurium.

Point source outbreaks of Campylobacter jejuni infection--are they more common than we think and what might cause them?

PubMed Central

Gillespie, I. A.; O'Brien, S. J.; Adak, G. K.; Tam, C. C.; Frost, J. A.; Bolton, F. J.; Tompkins, D. S.

2003-01-01

Despite being the commonest bacterial cause of infectious intestinal disease (IID) in England and Wales, outbreaks of campylobacter infection are rarely reported. However, data from the Campylobacter Sentinel Surveillance Scheme suggested that outbreaks might be more common than was previously suspected, since a high proportion of cases reported other illness in the home or in the community at the same time as their illness. To identify factors that might lead to these apparent outbreaks, the exposures of cases of Campylobacter jejuni infection reporting other illness, either in the home or the community, were compared with those for cases not reporting other illness using case-case methodology. Illness in the home was associated with consuming organic meats in the winter, having contact with a pet suffering from diarrhoea or visiting a farm in the 2 weeks before the onset of symptoms. Illness in the community was associated with the consumption of foods in restaurants or drinking unpasteurized milk. Prevention of campylobacter infection requires that better methods of outbreak detection and investigation are developed, which in turn should lead to a better understanding of risk factors. PMID:12825720

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.

A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

PubMed Central

Katz, Lee S.; Griswold, Taylor; Williams-Newkirk, Amanda J.; Wagner, Darlene; Petkau, Aaron; Sieffert, Cameron; Van Domselaar, Gary; Deng, Xiangyu; Carleton, Heather A.

2017-01-01

Modern epidemiology of foodborne bacterial pathogens in industrialized countries relies increasingly on whole genome sequencing (WGS) techniques. As opposed to profiling techniques such as pulsed-field gel electrophoresis, WGS requires a variety of computational methods. Since 2013, United States agencies responsible for food safety including the CDC, FDA, and USDA, have been performing whole-genome sequencing (WGS) on all Listeria monocytogenes found in clinical, food, and environmental samples. Each year, more genomes of other foodborne pathogens such as Escherichia coli, Campylobacter jejuni, and Salmonella enterica are being sequenced. Comparing thousands of genomes across an entire species requires a fast method with coarse resolution; however, capturing the fine details of highly related isolates requires a computationally heavy and sophisticated algorithm. Most L. monocytogenes investigations employing WGS depend on being able to identify an outbreak clade whose inter-genomic distances are less than an empirically determined threshold. When the difference between a few single nucleotide polymorphisms (SNPs) can help distinguish between genomes that are likely outbreak-associated and those that are less likely to be associated, we require a fine-resolution method. To achieve this level of resolution, we have developed Lyve-SET, a high-quality SNP pipeline. We evaluated Lyve-SET by retrospectively investigating 12 outbreak data sets along with four other SNP pipelines that have been used in outbreak investigation or similar scenarios. To compare these pipelines, several distance and phylogeny-based comparison methods were applied, which collectively showed that multiple pipelines were able to identify most outbreak clusters and strains. Currently in the US PulseNet system, whole genome multi-locus sequence typing (wgMLST) is the preferred primary method for foodborne WGS cluster detection and outbreak investigation due to its ability to name standardized genomic profiles, its central database, and its ability to be run in a graphical user interface. However, creating a functional wgMLST scheme requires extended up-front development and subject-matter expertise. When a scheme does not exist or when the highest resolution is needed, SNP analysis is used. Using three Listeria outbreak data sets, we demonstrated the concordance between Lyve-SET SNP typing and wgMLST. Availability: Lyve-SET can be found at https://github.com/lskatz/Lyve-SET. PMID:28348549

Burkholderia stabilis outbreak associated with contaminated commercially-available washing gloves, Switzerland, May 2015 to August 2016

PubMed Central

Sommerstein, Rami; Führer, Urs; Lo Priore, Elia; Casanova, Carlo; Meinel, Dominik M; Seth-Smith, Helena MB; Kronenberg, Andreas; Koch, Daniel; Senn, Laurence; Widmer, Andreas F; Egli, Adrian; Marschall, Jonas

2017-01-01

We describe an outbreak of Burkholderia stabilis associated with contaminated washing gloves, a commercially available Class I medical device. Triggered by an increase in Burkholderia cepacia complex (BCC) bacteremias and the detection of BCC in unopened packages of washing gloves, an ad hoc national outbreak committee comprising representatives of a public health organisation, a regulatory agency, and an expert association convened and commissioned an outbreak investigation. The investigation included retrospective case finding across Switzerland and whole genome sequencing (WGS) of isolates from cases and gloves. The investigation revealed that BCC were detected in clinical samples of 46 cases aged 17 to 91 years (33% females) from nine institutions between May 2015 and August 2016. Twenty-two isolates from case patients and 16 from washing gloves underwent WGS. All available outbreak isolates clustered within a span of < 19 differing alleles, while 13 unrelated clinical isolates differed by > 1,500 alleles. This BCC outbreak was rapidly identified, communicated, investigated and halted by an ad hoc collaboration of multiple stakeholders. WGS served as useful tool for confirming the source of the outbreak. This outbreak also highlights current regulatory limitations regarding Class I medical devices and the usefulness of a nationally coordinated outbreak response. PMID:29233255

There's No Place Like Home: Crown-of-Thorns Outbreaks in the Central Pacific Are Regionally Derived and Independent Events

PubMed Central

Timmers, Molly A.; Bird, Christopher E.; Skillings, Derek J.; Smouse, Peter E.; Toonen, Robert J.

2012-01-01

One of the most significant biological disturbances on a tropical coral reef is a population outbreak of the fecund, corallivorous crown-of-thorns sea star, Acanthaster planci. Although the factors that trigger an initial outbreak may vary, successive outbreaks within and across regions are assumed to spread via the planktonic larvae released from a primary outbreak. This secondary outbreak hypothesis is predominantly based on the high dispersal potential of A. planci and the assertion that outbreak populations (a rogue subset of the larger population) are genetically more similar to each other than they are to low-density non-outbreak populations. Here we use molecular techniques to evaluate the spatial scale at which A. planci outbreaks can propagate via larval dispersal in the central Pacific Ocean by inferring the location and severity of gene flow restrictions from the analysis of mtDNA control region sequence (656 specimens, 17 non-outbreak and six outbreak locations, six archipelagos, and three regions). Substantial regional, archipelagic, and subarchipelagic-scale genetic structuring of A. planci populations indicate that larvae rarely realize their dispersal potential and outbreaks in the central Pacific do not spread across the expanses of open ocean. On a finer scale, genetic partitioning was detected within two of three islands with multiple sampling sites. The finest spatial structure was detected at Pearl & Hermes Atoll, between the lagoon and forereef habitats (<10 km). Despite using a genetic marker capable of revealing subtle partitioning, we found no evidence that outbreaks were a rogue genetic subset of a greater population. Overall, outbreaks that occur at similar times across population partitions are genetically independent and likely due to nutrient inputs and similar climatic and ecological conditions that conspire to fuel plankton blooms. PMID:22363570

GHOST: global hepatitis outbreak and surveillance technology.

PubMed

Longmire, Atkinson G; Sims, Seth; Rytsareva, Inna; Campo, David S; Skums, Pavel; Dimitrova, Zoya; Ramachandran, Sumathi; Medrzycki, Magdalena; Thai, Hong; Ganova-Raeva, Lilia; Lin, Yulin; Punkova, Lili T; Sue, Amanda; Mirabito, Massimo; Wang, Silver; Tracy, Robin; Bolet, Victor; Sukalac, Thom; Lynberg, Chris; Khudyakov, Yury

2017-12-06

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

ELISA Methods for the Detection of Ebolavirus Infection.

PubMed

Cross, Robert W; Ksiazek, Thomas G

2017-01-01

Ebola viruses are high-priority pathogens first discovered in rural Africa associated with sporadic outbreaks of severe hemorrhagic disease in humans and nonhuman primates. Little is known about the disease ecology or the prevalence of past exposure of human populations to any of the five species of the genus Ebolavirus. The use of immunologic means of detection for either virus antigens or the host's immune response to antigen associated with prior infections offers a powerful approach at understanding the epidemiology and epizootiology of these agents. Here we describe methods for preparing antigen detection sandwich enzyme-linked immunosorbent assays (ELISAs) as well as IgG and IgM ELISAs for the detection of ebolavirus antigens or antibodies in biological samples.

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

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

PubMed Central

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

2014-01-01

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

Development of a social-hydrological-health framework for understanding risks of occurrence of diarrheal diseases

NASA Astrophysics Data System (ADS)

Khan, M. R. H.; Jutla, A.; Colwell, R. R.

2015-12-01

Diarrheal diseases continue to pose a severe health threat in regions where sanitation facilities remain marginal and are prone to destruction. With limited efficacy of vaccines, it is important to device alternate methods to determine environmental conditions favorable for diarrheal diseases. Several vibrios (V. cholerae., V. vulnificus, V. parahaemolyticus) have characteristic signatures that are associated with large scale climatic processes. The interactions of vibrios with humans eventually lead to outbreak of diseases. Here, using cholera as one of the signature diarrheal disease, we present a framework coupling social, hydrological and microbiological understanding with satellite remote sensing data to predict environmental conditions associated with outbreak of disease in several regions of sub-Saharan Africa. Hydroclimatic processes, primarily precipitation and temperature are found to be strongly associated with epidemic and episodic outbreak of cholera. We will present an algorithm to classify regions susceptible to risks of outbreak cholera using profile method in five epidemic regions of Mozambique, Central African Republic, Cameroon, South Sudan and Rwanda. Conditions for occurrence of cholera were detectable at least one month in advance. Using spatial land surface temperature (LST) data from satellites along with water accessibility data and population data, the implementation of the algorithm aid in classification of cholera risk regions.

[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.

A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests

USDA-ARS?s Scientific Manuscript database

Pathogenic invasions are a major disruptive source of change in both agricultural and natural ecosystems. In forests, fungal pathogens can kill habitat-generating plant species such as canopy trees, but methods for remote detection, mapping and monitoring of such outbreaks are poorly developed. Cera...

Testing Feeds for Salmonella.

USDA-ARS?s Scientific Manuscript database

Human salmonellosis outbreaks have been linked to contamination of animal feeds. Thus it is crucial to employ sensitive Salmonella detection methods for animal feeds. Based on a review of the literature, Salmonella sustains acid injury at about pH 4.0 to5.0. Low pH can also alter the metabolism of S...

OCCURRENCE OF VIRTUENCE FACTOR ACTIVITY RELATIONSHIP (VFAR) IN ESCHERICHIA COLI ISOLATED FROM MUNICIPAL WASTEWATER

EPA Science Inventory

Escherichia coli O157 H:7 has been linked to waterborne outbreaks in the United States and abroad. Methods employed to detect this pathogen typically are cultural based and take advantage of phenotypic traits that are specific for this serotype. These phenotypic characteristics...

OCCURRENCE OF VIRULENCE FACTOR ACTIVITY RELATIONSHIP (VFAR) IN ESCHERICHIA COLI ISOLATED FROM MUNICIPAL WASTEWATER EFFLUENTS

EPA Science Inventory

Escherichia coli O157:H7 has been linked to waterborne outbreaks in the United States and abroad. Methods employed to detect this pathogen typically are cultural based and take advantage of phenotypic traits that are specific for this serotype, including slow sorbitol fermentati...

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.

Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

PubMed Central

Pei, Sen; Tang, Shaoting; Zheng, Zhiming

2015-01-01

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods. PMID:25950181

In vitro detection and quantification of botulinum neurotoxin type E activity in avian blood

USGS Publications Warehouse

Piazza, T.M.; Blehert, D.S.; Dunning, F.M.; Berlowski-Zier, B. M.; Zeytin, F.N.; Samuel, M.D.; Tucker, W.C.

2011-01-01

Botulinum neurotoxin serotype E (BoNT/E) outbreaks in the Great Lakes region cause large annual avian mortality events, with an estimated 17,000 bird deaths reported in 2007 alone. During an outbreak investigation, blood collected from bird carcasses is tested for the presence of BoNT/E using the mouse lethality assay. While sensitive, this method is labor-intensive and low throughput and can take up to 7 days to complete. We developed a rapid and sensitive in vitro assay, the BoTest Matrix E assay, that combines immunoprecipitation with high-affinity endopeptidase activity detection by F??rster resonance energy transfer (FRET) to rapidly quantify BoNT/E activity in avian blood with detection limits comparable to those of the mouse lethality assay. On the basis of the analysis of archived blood samples (n = 87) collected from bird carcasses during avian mortality investigations, BoTest Matrix E detected picomolar quantities of BoNT/E following a 2-h incubation and femtomolar quantities of BoNT/E following extended incubation (24 h) with 100% diagnostic specificity and 91% diagnostic sensitivity. ?? 2011, American Society for Microbiology.

In vitro detection and quantification of botulinum neurotoxin type E activity in avian blood

USGS Publications Warehouse

Piazza, Timothy M.; Blehert, David S.; Dunning, F. Mark; Berlowski-Zier, Brenda M.; Zeytin, Fusun N.; Samuel, Michael D.; Tucker, Ward C.

2011-01-01

Botulinum neurotoxin serotype E (BoNT/E) outbreaks in the Great Lakes region cause large annual avian mortality events, with an estimated 17,000 bird deaths reported in 2007 alone. During an outbreak investigation, blood collected from bird carcasses is tested for the presence of BoNT/E using the mouse lethality assay. While sensitive, this method is labor-intensive and low throughput and can take up to 7 days to complete. We developed a rapid and sensitive in vitro assay, the BoTest Matrix E assay, that combines immunoprecipitation with high-affinity endopeptidase activity detection by Förster resonance energy transfer (FRET) to rapidly quantify BoNT/E activity in avian blood with detection limits comparable to those of the mouse lethality assay. On the basis of the analysis of archived blood samples (n = 87) collected from bird carcasses during avian mortality investigations, BoTest Matrix E detected picomolar quantities of BoNT/E following a 2-h incubation and femtomolar quantities of BoNT/E following extended incubation (24 h) with 100% diagnostic specificity and 91% diagnostic sensitivity.

In Vitro Detection and Quantification of Botulinum Neurotoxin Type E Activity in Avian Blood▿

PubMed Central

Piazza, Timothy M.; Blehert, David S.; Dunning, F. Mark; Berlowski-Zier, Brenda M.; Zeytin, Füsûn N.; Samuel, Michael D.; Tucker, Ward C.

2011-01-01

Botulinum neurotoxin serotype E (BoNT/E) outbreaks in the Great Lakes region cause large annual avian mortality events, with an estimated 17,000 bird deaths reported in 2007 alone. During an outbreak investigation, blood collected from bird carcasses is tested for the presence of BoNT/E using the mouse lethality assay. While sensitive, this method is labor-intensive and low throughput and can take up to 7 days to complete. We developed a rapid and sensitive in vitro assay, the BoTest Matrix E assay, that combines immunoprecipitation with high-affinity endopeptidase activity detection by Förster resonance energy transfer (FRET) to rapidly quantify BoNT/E activity in avian blood with detection limits comparable to those of the mouse lethality assay. On the basis of the analysis of archived blood samples (n = 87) collected from bird carcasses during avian mortality investigations, BoTest Matrix E detected picomolar quantities of BoNT/E following a 2-h incubation and femtomolar quantities of BoNT/E following extended incubation (24 h) with 100% diagnostic specificity and 91% diagnostic sensitivity. PMID:21908624

Diagnostic sensitivity and specificity of a participatory disease surveillance method for highly pathogenic avian influenza in household chicken flocks in Indonesia.

PubMed

Robyn, M; Priyono, W B; Kim, L M; Brum, E

2012-06-01

A study was conducted to assess the diagnostic sensitivity and specificity of a disease surveillance method for diagnosis of highly pathogenic avian influenza (HPAI) outbreaks in household chicken flocks used by participatory disease surveillance (PDS) teams in Yogyakarta Province, Indonesia. The Government of Indonesia, in partnership with the Food and Agriculture Organization of the United Nations, has implemented a PDS method for the detection of HPAI outbreaks in poultry since 2006. The PDS method in Indonesia utilizes both a clinical case definition (CD) and the result of a commercial rapid antigen test kit Yogyakarta 55611, to diagnose HPAI outbreaks, primarily in backyard chicken flocks. The following diagnostic sensitivities and specificities were obtained relative to real-time reverse transcription-PCR as the gold standard diagnostic test: 1) 89% sensitivity (CI95: 75%-97%) and 96% specificity (CI95: 89%-99%) for the PDS CD alone; 2) 86% sensitivity (CI95: 71%-95%) and 99% specificity (CI95: 94%-100%) for the rapid antigen test alone; and 3) 84% sensitivity (CI95: 68%-94%) and 100% specificity (CI95: 96%-100%) for the PDS CD result combined with the rapid antigen test result. Based on these results, HPAI outbreaks in extensively raised household chickens can be diagnosed with sufficient sensitivity and specificity using the PDS method as implemented in Indonesia. Subject to further field evaluation, data from this study suggest that the diagnostic sensitivity of the PDS method may be improved by expanding the PDS CD to include more possible clinical presentations of HPAI and by increasing the number of rapid antigen tests to three different birds with HPAI-compatible signs of same flock.

Plasmodium falciparum Malaria, Southern Algeria, 2007

PubMed Central

Gassen, Ibrahim; Khechache, Yacine; Lamali, Karima; Tchicha, Boualem; Brengues, Cécile; Menegon, Michela; Severini, Carlo; Fontenille, Didier; Harrat, Zoubir

2010-01-01

An outbreak of Plasmodium falciparum malaria occurred in Tinzaouatine in southern Algeria in 2007. The likely vector, Anopheles gambiae mosquitoes, had not been detected in Algeria. Genes for resistance to chloroquine were detected in the parasite. The outbreak shows the potential for an increase in malaria vectors in Algeria. PMID:20113565

Epidemiology of Acute Gastroenteritis Outbreaks Caused by Human Calicivirus (Norovirus and Sapovirus) in Catalonia: A Two Year Prospective Study, 2010-2011

PubMed Central

Martinez, Ana; Moreno, Antonio; Camps, Neus

2016-01-01

Background The epidemiology of cases of acute gastroenteritis (AGE) of viral etiology is a relevant public health issue. Due to underreporting, the study of outbreaks is an accepted approach to investigate their epidemiology. The objective of this study was to investigate the epidemiological characteristics of AGE outbreaks due to norovirus (NoV) and sapovirus (SV) in Catalonia. Material and Methods Prospective study of AGE outbreaks of possible viral etiology notified during two years in Catalonia. NoV and SV were detected by real time reverse transcription polymerase (RT-PCR). Results A total of 101 outbreaks were registered affecting a total of 2756 persons and 12 hospitalizations (hospitalization rate: 0.8x1,000,000 persons-year); 49.5% of outbreaks were foodborne, 45.5% person to person and 5% waterborne. The distribution of outbreaks according to the setting showed a predominance of catering services (39.6%), nursing homes and long term care facilities (26.8%) and schools (11.9%). The median number of cases per outbreak was 17 (range 2–191). The total Incidence rate (IR) was 18.3 per 100,000 persons-years (95%CI: 17.6–19.0). The highest IR was in persons aged ≥65 years (43.6x100,000 (95% CI: 41.0–46.2)) (p<0.001). A total of 1065 samples were analyzed with a positivity rate of 60.8%. 98% of positive samples were NoV (GII 56.3%; GI 4.2%; GII+GI 4.2%; non- typable 33.0%). SV was identified in two person-to-person transmission outbreaks in children. Conclusions These results confirm the relevance of viral AGE outbreaks, both foodborne and person-to-person, especially in institutionalized persons. SV should be taken into account when investigating viral AGE outbreaks. PMID:27120472

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

PubMed

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

2016-06-27

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

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.

Legionnaires’ disease from a cooling tower in a community outbreak in Lidköping, Sweden- epidemiological, environmental and microbiological investigation supported by meteorological modelling

PubMed Central

2012-01-01

Background An outbreak of Legionnaires’ Disease took place in the Swedish town Lidköping on Lake Vänern in August 2004 and the number of pneumonia cases at the local hospital increased markedly. As soon as the first patients were diagnosed, health care providers were informed and an outbreak investigation was launched. Methods Classical epidemiological investigation, diagnostic tests, environmental analyses, epidemiological typing and meteorological methods. Results Thirty-two cases were found. The median age was 62 years (range 36 – 88) and 22 (69%) were males. No common indoor exposure was found. Legionella pneumophila serogroup 1 was found at two industries, each with two cooling towers. In one cooling tower exceptionally high concentrations, 1.2 × 109 cfu/L, were found. Smaller amounts were also found in the other tower of the first industry and in one tower of the second plant. Sero- and genotyping of isolated L. pneumophila serogroup 1 from three patients and epidemiologically suspected environmental strains supported the cooling tower with the high concentration as the source. In all, two L. pneumophila strains were isolated from three culture confirmed cases and both these strains were detected in the cooling tower, but one strain in another cooling tower as well. Meteorological modelling demonstrated probable spread from the most suspected cooling tower towards the town centre and the precise location of four cases that were stray visitors to Lidköping. Conclusions Classical epidemiological, environmental and microbiological investigation of an LD outbreak can be supported by meteorological modelling methods. The broad competence and cooperation capabilities in the investigation team from different authorities were of paramount importance in stopping this outbreak. PMID:23171054

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

Long-Term Dynamics of Bluetongue Virus in Wild Ruminants: Relationship with Outbreaks in Livestock in Spain, 2006-2011

PubMed Central

Lorca-Oró, Cristina; López-Olvera, Jorge Ramón; Ruiz-Fons, Francisco; Acevedo, Pelayo; García-Bocanegra, Ignacio; Oleaga, Álvaro; Gortázar, Christian; Pujols, Joan

2014-01-01

Wild and domestic ruminants are susceptible to Bluetongue virus (BTV) infection. Three BTV serotypes (BTV-4, BTV-1 and BTV-8) have been detected in Spain in the last decade. Even though control strategies have been applied to livestock, BTV circulation has been frequently detected in wild ruminant populations in Spain. The aim of the present study is to assess the role for wild ruminants in maintaining BTV after the vaccination programs in livestock in mainland Spain. A total of 931 out 1,914 (48.6%) serum samples, collected from eight different wild ruminant species between 2006 and 2011, were BTV positive by ELISA. In order to detect specific antibodies against BTV-1, BTV-4 and BTV-8, positive sera were also tested by serumneutralisation test (SNT). From the ELISA positive samples that could be tested by SNT (687 out of 931), 292 (42.5%) showed neutralising antibodies against one or two BTV serotypes. For each BTV seroptype, the number of outbreaks in livestock (11,857 outbreaks in total) was modelled with pure autoregressive models and the resulting smoothed values, representing the predicted number of BTV outbreaks in livestock at municipality level, were positively correlated with BTV persistence in wild species. The strength of this relationship significantly decreased as red deer (Cervus elaphus) population abundance increased. In addition, BTV RNA was detected by real time RT-PCR in 32 out of 311 (10.3%) spleen samples from seropositive animals. Although BT outbreaks in livestock have decreased substantially after vaccination campaigns, our results indicated that wild ruminants have been exposed to BTV in territories where outbreaks in domestic animals occurred. The detection of BTV RNA and spatial association between BT outbreaks in livestock and BTV rates in red deer are consistent with the hypothesis of virus circulation and BTV maintenance within Iberian wild ruminant populations. PMID:24940879

Detection and molecular characterization of norovirus from oysters implicated in outbreaks in the US.

PubMed

Woods, Jacquelina W; Calci, Kevin R; Marchant-Tambone, Joey G; Burkhardt, William

2016-10-01

Human noroviruses are the leading cause of non-bacterial shellfish associated gastroenteritis. Here we report on the detection and characterization of norovirus (NoV) in shellfish associated outbreaks. Requests were received from state and federal officials for technical assistance in the analysis of shellfish for NoV and male specific coliphage (MSC; an enteric virus surrogate) during the years 2009 thru 2014. In outbreaks where NoV was detected, genogroup II (GII) levels ranged from 2.4 to 82.0 RT-qPCR U/g of digestive diverticula (DD) while NoV genogroup I (GI) levels ranged from 1.5 to 29.8 RT-qPCR U/g of DD. Murine norovirus extraction efficiencies ranged between 50 and 85%. MSC levels ranged from <6 to 80 PFU/100 g. Phylogenetic analysis of the outbreak sequences revealed strains clustering with GI.8, GI.4, GII.3, GII.4, GII.7, and GII.21. There was 100% homology between the shellfish and clinical strains occurring in 2 of 8 outbreaks. Known shellfish consumption data demonstrated probable infectious particles ingested as low as 12. These investigations demonstrate effective detection, quantification, and characterization of NoV in shellfish associated with illness. Published by Elsevier Ltd.

Diagnostic Evasion of Highly-Resistant Microorganisms: A Critical Factor in Nosocomial Outbreaks.

PubMed

Zhou, Xuewei; Friedrich, Alexander W; Bathoorn, Erik

2017-01-01

Highly resistant microorganisms (HRMOs) may evade screening strategies used in routine diagnostics. Bacteria that have evolved to evade diagnostic tests may have a selective advantage in the nosocomial environment. Evasion of resistance detection can result from the following mechanisms: low-level expression of resistance genes not resulting in detectable resistance, slow growing variants, mimicry of wild-type-resistance, and resistance mechanisms that are only detected if induced by antibiotic pressure. We reviewed reports on hospital outbreaks in the Netherlands over the past 5 years. Remarkably, many outbreaks including major nation-wide outbreaks were caused by microorganisms able to evade resistance detection by diagnostic screening tests. We describe various examples of diagnostic evasion by several HRMOs and discuss this in a broad and international perspective. The epidemiology of hospital-associated bacteria may strongly be affected by diagnostic screening strategies. This may result in an increasing reservoir of resistance genes in hospital populations that is unnoticed. The resistance elements may horizontally transfer to hosts with systems for high-level expression, resulting in a clinically significant resistance problem. We advise to communicate the identification of HRMOs that evade diagnostics within national and regional networks. Such signaling networks may prevent inter-hospital outbreaks, and allow collaborative development of adapted diagnostic tests.

Studies on the Immunochemical Techniques for Detection of Selected Fungal and Dinoflagellate Toxins.

DTIC Science & Technology

1985-08-15

to be one of the most potent protein inhibitors. It has been found to be associated with several natural outbreaks of mycotoxicoses in both animals...trichothecene mycotoxins and dinoflagellate phytotoxins and subsequently to develop a radioimmunoassay (RIA) or an enzyme-linked immunosorbent assay...of 7% and variation coeffecient of 8%. The minumal detection for DON was around 20 ppb. The application of this method to limited naturally

Time delays in the response to the Neisseria meningitidis serogroup C outbreak in Nigeria - 2017.

PubMed

Hassan, Assad; Mustapha, G U; Lawal, Bola B; Na'uzo, Aliyu M; Ismail, Raji; Womi-Eteng Oboma, Eteng; Oyebanji, Oyeronke; Agenyi, Jeremiah; Thomas, Chima; Balogun, Muhammad Shakir; Dalhat, Mahmood M; Nguku, Patrick; Ihekweazu, Chikwe

2018-01-01

Nigeria reports high rates of mortality linked with recurring meningococcal meningitis outbreaks within the African meningitis belt. Few studies have thoroughly described the response to these outbreaks to provide strong and actionable public health messages. We describe how time delays affected the response to the 2016/2017 meningococcal meningitis outbreak in Nigeria. Using data from Nigeria Centre for Disease Control (NCDC), National Primary Health Care Development Agency (NPHCDA), World Health Organisation (WHO), and situation reports of rapid response teams, we calculated attack and death rates of reported suspected meningococcal meningitis cases per week in Zamfara, Sokoto and Yobe states respectively, between epidemiological week 49 in 2016 and epidemiological week 25 in 2017. We identified when alert and epidemic thresholds were crossed and determined when the outbreak was detected and notified in each state. We examined response activities to the outbreak. There were 12,535 suspected meningococcal meningitis cases and 877 deaths (CFR: 7.0%) in the three states. It took an average time of three weeks before the outbreaks were detected and notified to NCDC. Four weeks after receiving notification, an integrated response coordinating centre was set up by NCDC and requests for vaccines were sent to International Coordinating Group (ICG) on vaccine provision. While it took ICG one week to approve the requests, it took an average of two weeks for approximately 41% of requested vaccines to arrive. On the average, it took nine weeks from the date the epidemic threshold was crossed to commencement of reactive vaccination in the three states. There were delays in detection and notification of the outbreak, in coordinating response activities, in requesting for vaccines and their arrival from ICG, and in initiating reactive vaccination. Reducing these delays in future outbreaks could help decrease the morbidity and mortality linked with meningococcal meningitis outbreaks.

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks

PubMed Central

Walsh, Aaron M.; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C.; Arthur, Cornelius T.; Claesson, Marcus J.; Scott, Karen P.

2017-01-01

ABSTRACT The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. PMID:28625983

The use of hospital-based nurses for the surveillance of potential disease outbreaks.

PubMed Central

Durrheim, D. N.; Harris, B. N.; Speare, R.; Billinghurst, K.

2001-01-01

OBJECTIVE: To study a novel surveillance system introduced in Mpumalanga Province, a rural area in the north-east of South Africa, in an attempt to address deficiencies in the system of notification for infectious conditions that have the potential for causing outbreaks. METHODS: Hospital-based infection control nurses in all of Mpumalanga's 32 public and private hospitals were trained to recognize, report, and respond to nine clinical syndromes that require immediate action. Sustainability of the system was assured through a schedule of regular training and networking, and by providing feedback to the nurses. The system was evaluated by formal review of hospital records, evidence of the effective containment of a cholera outbreak, and assessment of the speed and appropriateness of responses to other syndromes. FINDINGS: Rapid detection, reporting and response to six imported cholera cases resulted in effective containment, with only 19 proven secondary cholera cases, during the two-year review period. No secondary cases followed detection and prompt response to 14 patients with meningococcal disease. By the end of the first year of implementation, all facilities were providing weekly zero-reports on the nine syndromes before the designated time. Formal hospital record review for cases of acute flaccid paralysis endorsed the value of the system. CONCLUSION: The primary goal of an outbreak surveillance system is to ensure timely recognition of syndromes requiring an immediate response. Infection control nurses in Mpumalanga hospitals have excelled in timely weekly zero-reporting, participation at monthly training and feedback sessions, detection of priority clinical syndromes, and prompt appropriate response. This review provides support for the role of hospital-based nurses as valuable sentinel surveillance agents providing timely data for action. PMID:11217663

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

PubMed Central

2012-01-01

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

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013–2016

PubMed Central

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.; Rollin, Pierre E.

2016-01-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013–2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community’s insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Continued efforts during the outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research. PMID:27070842

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016

DOE PAGES

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.; ...

2016-06-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Finally, continued efforts during themore » outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.« less

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016

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

Spengler, Jessica R.; Ervin, Elizabeth D.; Towner, Jonathan S.

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Finally, continued efforts during themore » outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.« less

Perspectives on West Africa Ebola Virus Disease Outbreak, 2013-2016.

PubMed

Spengler, Jessica R; Ervin, Elizabeth D; Towner, Jonathan S; Rollin, Pierre E; Nichol, Stuart T

2016-06-01

The variety of factors that contributed to the initial undetected spread of Ebola virus disease in West Africa during 2013-2016 and the difficulty controlling the outbreak once the etiology was identified highlight priorities for disease prevention, detection, and response. These factors include occurrence in a region recovering from civil instability and lacking experience with Ebola response; inadequate surveillance, recognition of suspected cases, and Ebola diagnosis; mobile populations and extensive urban transmission; and the community's insufficient general understanding about the disease. The magnitude of the outbreak was not attributable to a substantial change of the virus. Continued efforts during the outbreak and in preparation for future outbreak response should involve identifying the reservoir, improving in-country detection and response capacity, conducting survivor studies and supporting survivors, engaging in culturally appropriate public education and risk communication, building productive interagency relationships, and continuing support for basic research.

Outbreak of Corynebacterium pseudodiphtheriticum Infection in Cystic Fibrosis Patients, France

PubMed Central

Bittar, Fadi; Cassagne, Carole; Bosdure, Emmanuelle; Stremler, Nathalie; Dubus, Jean-Christophe; Sarles, Jacques; Reynaud-Gaubert, Martine; Raoult, Didier

2010-01-01

An increasing body of evidence indicates that nondiphtheria corynebacteria may be responsible for respiratory tract infections. We report an outbreak of Corynebacterium pseudodiphtheriticum infection in children with cystic fibrosis (CF). To identify 18 C. pseudodiphtheriticum strains isolated from 13 French children with CF, we used molecular methods (partial rpoB gene sequencing) and matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry. Clinical symptoms were exhibited by 10 children (76.9%), including cough, rhinitis, and lung exacerbations. The results of MALDI-TOF identification matched perfectly with those obtained from molecular identification. Retrospective analysis of sputum specimens by using specific real-time PCR showed that ≈20% of children with CF were colonized with these bacteria, whereas children who did not have CF had negative test results. Our study reemphasizes the conclusion that correctly identifying bacteria at the species level facilitates detection of an outbreak of new or emerging infections in humans. PMID:20678316

Local amplification of highly pathogenic avian influenza H5N8 viruses in wild birds in the Netherlands, 2016 to 2017

PubMed Central

Poen, Marjolein J.; Bestebroer, Theo M.; Vuong, Oanh; Scheuer, Rachel D.; van der Jeugd, Henk P.; Kleyheeg, Erik; Eggink, Dirk; Lexmond, Pascal; van den Brand, Judith M.A.; Begeman, Lineke; van der Vliet, Stefan; Müskens, Gerhard J.D.M.; Majoor, Frank A.; Koopmans, Marion P.G.; Kuiken, Thijs; Fouchier, Ron A.M.

2018-01-01

Introduction Highly pathogenic avian influenza (HPAI) viruses of subtype H5N8 were re-introduced into the Netherlands by late 2016, after detections in south-east Asia and Russia. This second H5N8 wave resulted in a large number of outbreaks in poultry farms and the deaths of large numbers of wild birds in multiple European countries. Methods: Here we report on the detection of HPAI H5N8 virus in 57 wild birds of 12 species sampled during active (32/5,167) and passive (25/36) surveillance activities, i.e. in healthy and dead animals respectively, in the Netherlands between 8 November 2016 and 31 March 2017. Moreover, we further investigate the experimental approach of wild bird serology as a contributing tool in HPAI outbreak investigations. Results: In contrast to the first H5N8 wave, local virus amplification with associated wild bird mortality has occurred in the Netherlands in 2016/17, with evidence for occasional gene exchange with low pathogenic avian influenza (LPAI) viruses. Discussion: These apparent differences between outbreaks and the continuing detections of HPAI viruses in Europe are a cause of concern. With the current circulation of zoonotic HPAI and LPAI virus strains in Asia, increased understanding of the drivers responsible for the global spread of Asian poultry viruses via wild birds is needed. PMID:29382414

Local amplification of highly pathogenic avian influenza H5N8 viruses in wild birds in the Netherlands, 2016 to 2017.

PubMed

Poen, Marjolein J; Bestebroer, Theo M; Vuong, Oanh; Scheuer, Rachel D; van der Jeugd, Henk P; Kleyheeg, Erik; Eggink, Dirk; Lexmond, Pascal; van den Brand, Judith M A; Begeman, Lineke; van der Vliet, Stefan; Müskens, Gerhard J D M; Majoor, Frank A; Koopmans, Marion P G; Kuiken, Thijs; Fouchier, Ron A M

2018-01-01

IntroductionHighly pathogenic avian influenza (HPAI) viruses of subtype H5N8 were re-introduced into the Netherlands by late 2016, after detections in south-east Asia and Russia. This second H5N8 wave resulted in a large number of outbreaks in poultry farms and the deaths of large numbers of wild birds in multiple European countries. Methods : Here we report on the detection of HPAI H5N8 virus in 57 wild birds of 12 species sampled during active (32/5,167) and passive (25/36) surveillance activities, i.e. in healthy and dead animals respectively, in the Netherlands between 8 November 2016 and 31 March 2017. Moreover, we further investigate the experimental approach of wild bird serology as a contributing tool in HPAI outbreak investigations. Results : In contrast to the first H5N8 wave, local virus amplification with associated wild bird mortality has occurred in the Netherlands in 2016/17, with evidence for occasional gene exchange with low pathogenic avian influenza (LPAI) viruses. Discussion : These apparent differences between outbreaks and the continuing detections of HPAI viruses in Europe are a cause of concern. With the current circulation of zoonotic HPAI and LPAI virus strains in Asia, increased understanding of the drivers responsible for the global spread of Asian poultry viruses via wild birds is needed.

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

PubMed

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

2014-10-01

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

Nosocomial transmission of respiratory syncytial virus in an outpatient cancer center.

PubMed

Chu, Helen Y; Englund, Janet A; Podczervinski, Sara; Kuypers, Jane; Campbell, Angela P; Boeckh, Michael; Pergam, Steven A; Casper, Corey

2014-06-01

Respiratory syncytial virus (RSV) outbreaks in inpatient settings are associated with poor outcomes in cancer patients. The use of molecular epidemiology to document RSV transmission in the outpatient setting has not been well described. We performed a retrospective cohort study of 2 nosocomial outbreaks of RSV at the Seattle Cancer Care Alliance. Subjects included patients seen at the Seattle Cancer Care Alliance with RSV detected in 2 outbreaks in 2007-2008 and 2012 and all employees with respiratory viruses detected in the 2007-2008 outbreak. A subset of samples was sequenced using semi-nested PCR targeting the RSV attachment glycoprotein coding region. Fifty-one cases of RSV were identified in 2007-2008. Clustering of identical viral strains was detected in 10 of 15 patients (67%) with RSV sequenced from 2007 to 2008. As part of a multimodal infection control strategy implemented as a response to the outbreak, symptomatic employees had nasal washes collected. Of 254 employee samples, 91 (34%) tested positive for a respiratory virus, including 14 with RSV. In another RSV outbreak in 2012, 24 cases of RSV were identified; 9 of 10 patients (90%) had the same viral strain, and 1 (10%) had another viral strain. We document spread of clonal strains within an outpatient cancer care setting. Infection control interventions should be implemented in outpatient, as well as inpatient, settings to reduce person-to-person transmission and limit progression of RSV outbreaks. Copyright © 2014 American Society for Blood and Marrow Transplantation. All rights reserved.

Phylogeny of Yellow Fever Virus, Uganda, 2016.

PubMed

Hughes, Holly R; Kayiwa, John; Mossel, Eric C; Lutwama, Julius; Staples, J Erin; Lambert, Amy J

2018-08-17

In April 2016, a yellow fever outbreak was detected in Uganda. Removal of contaminating ribosomal RNA in a clinical sample improved the sensitivity of next-generation sequencing. Molecular analyses determined the Uganda yellow fever outbreak was distinct from the concurrent yellow fever outbreak in Angola, improving our understanding of yellow fever epidemiology.

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

PubMed

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

2016-02-16

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

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

PubMed

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

2018-03-21

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

A single Legionella pneumophila genotype in the freshwater system in a ship experiencing three separate outbreaks of legionellosis in 6 years.

PubMed

Ahlen, Catrine; Aas, Marianne; Krusnell, Jadwiga; Iversen, Ole-Jan

2016-01-01

Recurrent legionella outbreaks at one and the same location are common. We have identified a single Legionella pneumophila genotype associated with recurrent Legionella outbreaks over 6 years. Field emergency surveys following Legionella outbreaks were performed on a vessel in 2008, 2009 and 2013. Water samples from both the distribution and technical parts of the potable water system were analyzed with respect to L. pneumophila [Real-Time PCR, cultivation, serotyping and genotyping (PFGE)] and free-living amoebae, (FLA). Legionella pneumophila serogroup 1 was present in the ship's potable water system during every outbreak. Genotyping of the 2008 survey material showed two separate PFGE genotypes while those in 2009 and 2013 demonstrated the presence of only one of the two genotypes. FLA with intracellular L. pneumophila of the same genotype were also detected. Analyses of the freshwater system on a ship following three separate Legionella outbreaks, for L. pneumophila and FLAs, revealed a single L. pneumophila genotype and FLA (Hartmanella). It is reasonable to assume that the L. pneumophila genotype detected in the freshwater system was the causal agent in the outbreaks onboard. Persistence of an apparently low-pathogenic L. pneumophila genotype and FLA in a potable water system represent a potential risk for recurrent outbreaks.

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.

A likelihood-based approach to identifying contaminated food products using sales data: performance and challenges.

PubMed

Kaufman, James; Lessler, Justin; Harry, April; Edlund, Stefan; Hu, Kun; Douglas, Judith; Thoens, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

2014-07-01

Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and--in the worst cases--death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single "guilty" food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially "guilty" products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to "hard-to-identify" foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for "hard-to-identify" products.

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.

[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.

Development and application of a multiplex PCR assay for detection of the Clostridium perfringens enterotoxin-encoding genes cpe and becAB.

PubMed

Yonogi, Shinya; Kanki, Masashi; Ohnishi, Takahiro; Shiono, Masami; Iida, Tetsuya; Kumeda, Yuko

2016-08-01

Clostridium perfringens causes food-borne gastroenteritis following the consumption of contaminated food by producing C. perfringens enterotoxin (CPE) in the intestines. Recently, we reported a novel enterotoxin, binary enterotoxin of C. perfringens (BEC) in C. perfringens isolates, which caused two disease outbreaks in Japan. Consequently, in the event of food poisoning outbreaks caused by C. perfringens, it is now necessary to screen for both the cpe and becAB genes by diagnostic PCR. Here, we present a simple multiplex PCR method for simultaneous detection of cpe, becAB and a C. perfringens control locus, phospholipase C (plc). Applying this method, we investigated the prevalence of cpe- or becAB-carrying C. perfringens strains in human stool and bovine rectum swab samples. Using a total of 169 isolates, we found that the percentage of becAB-carrying strains was very small (0.59%), one-tenth that of cpe-carrying strains. The simple method presented in this study with high specificity and sensitivity to C. perfringens will be a useful tool to survey the global prevalence of becAB-carrying C. perfringens strains. Copyright © 2016 Elsevier B.V. All rights reserved.

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

EPA Science Inventory

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

Detecting and distinguishing among type 1 and type 2 Shiga toxins in human serum

USDA-ARS?s Scientific Manuscript database

Shiga toxins, also known as verotoxins, are a major virulence factor associated with Shiga toxin producing Escherichia coli (STEC). STEC are the E. coli responsible for many of the serious foodborne outbreaks of disease. We have developed a sensitive and specific mass spectrometry-based method of de...

Multiplex PCR for Diagnosis of Enteric Infections Associated with Diarrheagenic Escherichia coli

PubMed Central

Vidal, Roberto; Vidal, Maricel; Lagos, Rossana; Levine, Myron; Prado, Valeria

2004-01-01

A multiplex PCR for detection of three categories of diarrheagenic Escherichia coli was developed. With this method, enterohemorrhagic E. coli, enteropathogenic E. coli, and enterotoxigenic E. coli were identified in fecal samples from patients with hemorrhagic colitis, watery diarrhea, or hemolytic-uremic syndrome and from food-borne outbreaks. PMID:15071051

Livers provide a reliable matrix for real-time PCR confirmation of avian botulism.

PubMed

Le Maréchal, Caroline; Ballan, Valentine; Rouxel, Sandra; Bayon-Auboyer, Marie-Hélène; Baudouard, Marie-Agnès; Morvan, Hervé; Houard, Emmanuelle; Poëzevara, Typhaine; Souillard, Rozenn; Woudstra, Cédric; Le Bouquin, Sophie; Fach, Patrick; Chemaly, Marianne

2016-04-01

Diagnosis of avian botulism is based on clinical symptoms, which are indicative but not specific. Laboratory investigations are therefore required to confirm clinical suspicions and establish a definitive diagnosis. Real-time PCR methods have recently been developed for the detection of Clostridium botulinum group III producing type C, D, C/D or D/C toxins. However, no study has been conducted to determine which types of matrices should be analyzed for laboratory confirmation using this approach. This study reports on the comparison of different matrices (pooled intestinal contents, livers, spleens and cloacal swabs) for PCR detection of C. botulinum. Between 2013 and 2015, 63 avian botulism suspicions were tested and 37 were confirmed as botulism. Analysis of livers using real-time PCR after enrichment led to the confirmation of 97% of the botulism outbreaks. Using the same method, spleens led to the confirmation of 90% of botulism outbreaks, cloacal swabs of 93% and pooled intestinal contents of 46%. Liver appears to be the most reliable type of matrix for laboratory confirmation using real-time PCR analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Outbreak of acute respiratory disease caused by human adenovirus type 7 in a military training camp in Shaanxi, China.

PubMed

Yu, Pengbo; Ma, Chaofeng; Nawaz, Muhammad; Han, Lei; Zhang, Jianfang; Du, Quanli; Zhang, Lixia; Feng, Qunling; Wang, Jingjun; Xu, Jiru

2013-08-01

Outbreaks of ARD associated with HAdV have been reported in military populations in many countries. Here, we report an ARD outbreak caused by HAdV-7 in a military training camp in Shaanxi Province, China, from February to March of 2012. Epidemic data and samples from the patients were collected, and viral nucleotides from samples and viral isolations were detected and sequenced. IgG and IgA antibodies against HAdV, and the neutralization antibodies against the viral strain isolated in this outbreak, were detected. Epidemiological study showed that all personnel affected were males with an average age of 19.1 years. Two peaks appeared on the epicurve and there was an 8-day interval between peaks. Laboratory results of viral nucleotide detection carried out with clinical specimens were positive for HAdV (83.33%, 15/18). Further study through serum antibody assay, virus isolation and phylogenetic analysis showed that HAdV-7 was the etiological agent responsible for the outbreak. IgA antibody began to appear on the 4th day after the onset and showed 100% positivity on the 8th day. The virus strain in the present outbreak was highly similar to the virus isolated in Hanzhong Shaanxi in 2009. We conclude that HAdV-7 was the pathogen corresponding to the outbreak, and this is the first report of an ARD outbreak caused by HAdV-7 in military persons in China. Vaccine development, as well as enhanced epidemiological and virological surveillance of HAdV infections in China should be emphasized. © 2013 The Societies and Wiley Publishing Asia Pty Ltd.

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

PubMed Central

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

2017-01-01

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

Locus-specific mutational events in a multilocus variable-number tandem repeat analysis of Escherichia coli O157:H7.

PubMed

Noller, Anna C; McEllistrem, M Catherine; Shutt, Kathleen A; Harrison, Lee H

2006-02-01

Multilocus variable-number tandem repeat analysis (MLVA) is a validated molecular subtyping method for detecting and evaluating Escherichia coli O157:H7 outbreaks. In a previous study, five outbreaks with a total of 21 isolates were examined by MLVA. Nearly 20% of the epidemiologically linked strains were single-locus variants (SLV) of their respective predominant outbreak clone. This result prompted an investigation into the mutation rates of the seven MLVA loci (TR1 to TR7). With an outbreak strain that was an SLV at the TR1 locus of the predominant clone, parallel and serial batch culture experiments were performed. In a parallel experiment, none (0/384) of the strains analyzed had mutations at the seven MLVA loci. In contrast, in the two 5-day serial experiments, 4.3% (41/960) of the strains analyzed had a significant variation in at least one of these loci (P < 0.001). The TR2 locus accounted for 85.3% (35/41) of the mutations, with an average mutation rate of 3.5 x 10(-3); the mutations rates for TR1 and TR5 were 10-fold lower. Single additions accounted for 77.1% (27/35) of the mutation events in TR2 and all (6/6) of the additions in TR1 and TR5. The remaining four loci had no slippage events detected. The mutation rates were locus specific and may impact the interpretation of MLVA data for epidemiologic investigations.

Group C rotavirus infection in patients with acute gastroenteritis in outbreaks in western India between 2006 and 2014.

PubMed

Joshi, M S; Jare, V M; Gopalkrishna, V

2017-01-01

Faecal specimens collected from outbreak (n = 253) and sporadic (n = 147) cases of acute gastroenteritis that occurred in western India between 2006 and 2014 were tested for group C rotavirus (GCR) using partial VP6 gene-based RT-PCR. All specimens were tested previously for the presence of other viral and bacterial aetiological agents by conventional methods. The rate of GCR detection was 8·6% and 0·7% in outbreak and sporadic cases, respectively. GCR infections prevailed in outbreaks reported from rural areas (10·9%) compared to urban areas (1·6%). Clinical severity score of the patients with GCR infection (n = 23) indicated severe disease in the majority (70%) of cases. The age distribution analysis indicated 52·1% of GCR infections in children aged <10 years. The male:female ratio in GCR-positive patients was 2·3:1. Of the 23 GCR-positive cases, 17 (73·9%) had a sole GCR infection and six had mixed infections with other viral and/or bacterial agents. Phylogenetic analysis of nucleotide sequences classified GCR strains of the study in to I2 genotype of the VP6 gene. This is the first study to show the occurrence of GCR in gastroenteritis outbreaks in India.

Rapid Whole-Genome Sequencing for Investigation of a Neonatal MRSA Outbreak

PubMed Central

Köser, Claudio U.; Holden, Matthew T.G.; Ellington, Matthew J.; Cartwright, Edward J.P.; Brown, Nicholas M.; Ogilvy-Stuart, Amanda L.; Hsu, Li Yang; Chewapreecha, Claire; Croucher, Nicholas J.; Harris, Simon R.; Sanders, Mandy; Enright, Mark C.; Dougan, Gordon; Bentley, Stephen D.; Parkhill, Julian; Fraser, Louise J.; Betley, Jason R.; Schulz-Trieglaff, Ole B.; Smith, Geoffrey P.; Peacock, Sharon J.

2013-01-01

Background Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks. Methods We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital. Results We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial “resistome” of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a “toxome” consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain. Conclusions Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.) PMID:22693998

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

Epidemiologic, Virologic, and Host Genetic Factors of Norovirus Outbreaks in Long-term Care Facilities

PubMed Central

Costantini, Veronica P.; Cooper, Emilie M.; Hardaker, Hope L.; Lee, Lore E.; Bierhoff, Marieke; Biggs, Christianne; Cieslak, Paul R.; Hall, Aron J.; Vinjé, Jan

2018-01-01

Background In the Unites States, long-term care facilities (LTCFs) are the most common setting for norovirus outbreaks. These outbreaks provide a unique opportunity to better characterize the viral and host characteristics of norovirus disease. Methods We enrolled 43 LTCFs prospectively to study the epidemiology, virology, and genetic host factors of naturally occurring norovirus outbreaks. Acute and convalescent stool, serum, and saliva samples from cases, exposed and nonexposed controls were collected. Norovirus infection was confirmed using quantitative polymerase chain reaction testing of stool samples or 4-fold increase in serum antibody titers. The presence of histo-blood group antigens (secretor, ABO, and Lewis type) was determined in saliva. Results Sixty-two cases, 34 exposed controls, and 18 nonexposed controls from 10 norovirus outbreaks were enrolled. Forty-six percent of acute, 27% of convalescent case, and 11% of control stool samples tested norovirus positive. Outbreak genotypes were GII.4 (Den Haag, n = 3; New Orleans, n = 4; and Sydney, n = 2) and GI.1 (n = 1). Viral load in GII.4 Sydney outbreaks was significantly higher than in outbreaks caused by other genotypes; cases and controls shed similar amounts of virus. Forty-seven percent of cases shed virus for ≥21 days. Symptomatic infections with GII.4 Den Haag and GII.4 New Orleans were detected among nonsecretor individuals. Conclusions Almost half of all symptomatic individuals shed virus for at least 21 days. Viral load was highest in GII.4 viruses that most recently emerged; these viruses also infect the nonsecretor population. These findings will help to guide development of targeted prevention and control measures in the elderly. PMID:26508509

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...

Characterization of an outbreak of Clostridium perfringens food poisoning by quantitative fecal culture and fecal enterotoxin measurement.

PubMed Central

Birkhead, G; Vogt, R L; Heun, E M; Snyder, J T; McClane, B A

1988-01-01

Published criteria for implicating Clostridium perfringens as the cause of food-poisoning outbreaks include finding a median fecal C. perfringens spore count of greater than 10(6)/g among specimens from ill persons. We investigated a food-poisoning outbreak with the epidemiologic characteristics of C. perfringens-related disease in a nursing home in which the median fecal spore count for ill patients (2.5 X 10(7)/g) was similar to that for well patients (4.0 X 10(6)/g), making the etiology of the outbreak uncertain. All ill and well patients tested had eaten turkey, the implicated food item. C. perfringens enterotoxin was detected by reverse passive latex agglutination in fecal specimens from six of six ill and none of four well patients who had eaten turkey (P = 0.005), suggesting that this organism had caused the outbreak. This investigation suggests that detection of fecal C. perfringens enterotoxin is a specific way to identify this organism as the causative agent in food-poisoning outbreaks. PMID:2895776

Cross-Border Cholera Outbreaks in Sub-Saharan Africa, the Mystery behind the Silent Illness: What Needs to Be Done?

PubMed Central

Mwesawina, Maurice; Baluku, Yosia; Kanyanda, Setiala S. E.; Orach, Christopher Garimoi

2016-01-01

Introduction Cross-border cholera outbreaks are a major public health problem in Sub-Saharan Africa contributing to the high annual reported cholera cases and deaths. These outbreaks affect all categories of people and are challenging to prevent and control. This article describes lessons learnt during the cross-border cholera outbreak control in Eastern and Southern Africa sub-regions using the case of Uganda-DRC and Malawi-Mozambique borders and makes recommendations for future outbreak prevention and control. Materials and Methods We reviewed weekly surveillance data, outbreak response reports and documented experiences on the management of the most recent cross-border cholera outbreaks in Eastern and Southern Africa sub-regions, namely in Uganda and Malawi respectively. Uganda-Democratic Republic of Congo and Malawi-Mozambique borders were selected because the countries sharing these borders reported high cholera disease burden to WHO. Results A total of 603 cross-border cholera cases with 5 deaths were recorded in Malawi and Uganda in 2015. Uganda recorded 118 cases with 2 deaths and CFR of 1.7%. The under-fives and school going children were the most affected age groups contributing 24.2% and 36.4% of all patients seen along Malawi-Mozambique and Uganda-DRC borders, respectively. These outbreaks lasted for over 3 months and spread to new areas leading to 60 cases with 3 deaths, CRF of 5%, and 102 cases 0 deaths in Malawi and Uganda, respectively. Factors contributing to these outbreaks were: poor sanitation and hygiene, use of contaminated water, floods and rampant cross-border movements. The outbreak control efforts mainly involved unilateral measures implemented by only one of the affected countries. Conclusions Cross-border cholera outbreaks contribute to the high annual reported cholera burden in Sub-Saharan Africa yet they remain silent, marginalized and poorly identified by cholera actors (governments and international agencies). The under-fives and the school going children were the most affected age groups. To successfully prevent and control these outbreaks, guidelines and strategies should be reviewed to assign clear roles and responsibilities to cholera actors on collaboration, prevention, detection, monitoring and control of these epidemics. PMID:27258124

A Study of Failure Events in Drinking Water Systems As a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse Schemes

PubMed Central

Onyango, Laura A.; Quinn, Chloe; Tng, Keng H.; Wood, James G.; Leslie, Greg

2015-01-01

Potable reuse is implemented in several countries around the world to augment strained water supplies. This article presents a public health perspective on potable reuse by comparing the critical infrastructure and institutional capacity characteristics of two well-established potable reuse schemes with conventional drinking water schemes in developed nations that have experienced waterborne outbreaks. Analysis of failure events in conventional water systems between 2003 and 2013 showed that despite advances in water treatment technologies, drinking water outbreaks caused by microbial contamination were still frequent in developed countries and can be attributed to failures in infrastructure or institutional practices. Numerous institutional failures linked to ineffective treatment protocols, poor operational practices, and negligence were detected. In contrast, potable reuse schemes that use multiple barriers, online instrumentation, and operational measures were found to address the events that have resulted in waterborne outbreaks in conventional systems in the past decade. Syndromic surveillance has emerged as a tool in outbreak detection and was useful in detecting some outbreaks; increases in emergency department visits and GP consultations being the most common data source, suggesting potential for an increasing role in public health surveillance of waterborne outbreaks. These results highlight desirable characteristics of potable reuse schemes from a public health perspective with potential for guiding policy on surveillance activities. PMID:27053920

A Study of Failure Events in Drinking Water Systems As a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse Schemes.

PubMed

Onyango, Laura A; Quinn, Chloe; Tng, Keng H; Wood, James G; Leslie, Greg

2015-01-01

Potable reuse is implemented in several countries around the world to augment strained water supplies. This article presents a public health perspective on potable reuse by comparing the critical infrastructure and institutional capacity characteristics of two well-established potable reuse schemes with conventional drinking water schemes in developed nations that have experienced waterborne outbreaks. Analysis of failure events in conventional water systems between 2003 and 2013 showed that despite advances in water treatment technologies, drinking water outbreaks caused by microbial contamination were still frequent in developed countries and can be attributed to failures in infrastructure or institutional practices. Numerous institutional failures linked to ineffective treatment protocols, poor operational practices, and negligence were detected. In contrast, potable reuse schemes that use multiple barriers, online instrumentation, and operational measures were found to address the events that have resulted in waterborne outbreaks in conventional systems in the past decade. Syndromic surveillance has emerged as a tool in outbreak detection and was useful in detecting some outbreaks; increases in emergency department visits and GP consultations being the most common data source, suggesting potential for an increasing role in public health surveillance of waterborne outbreaks. These results highlight desirable characteristics of potable reuse schemes from a public health perspective with potential for guiding policy on surveillance activities.

Noroviruses associated with acute gastroenteritis in a children's day care facility in Rio de Janeiro, Brazil.

PubMed

Gallimore, C I; Barreiros, M A B; Brown, D W G; Nascimento, J P; Leite, J P G

2004-03-01

Noroviruses (Norwalk-like viruses) are an important cause of gastroenteritis worldwide. They are the most common cause of outbreaks of gastroenteritis in the adult population and occur in nursing homes for the elderly, geriatric wards, medical wards, and in hotel and restaurant settings. Food-borne outbreaks have also occurred following consumption of contaminated oysters. This study describes the application of a reverse transcription-polymerase chain reaction (RT-PCR) assay using random primers (PdN6) and specific Ni and E3 primers, directed at a small region of the RNA-dependent RNA polymerase-coding region of the norovirus genome, and DNA sequencing for the detection and preliminary characterisation of noroviruses in outbreaks of gastroenteritis in children in Brazil. The outbreak samples were collected from children <5 years of age at the Bertha Lutz children's day care facility at Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, that occurred between 1996 and 1998, where no pathogen had been identified. At the Bertha Lutz day care center facility, only Fiocruz's employee children are provided for, and they come from different social, economic and cultural backgrounds. Three distinct genogroup II strains were detected in three outbreaks in 1997/98 and were most closely related to genotypes GII-3 (Mexico virus) and GII-4 (Grimsby virus), both of which have been detected in paediatric and adult outbreaks of gastroenteritis worldwide.

First detection of foot-and-mouth disease virus O/Ind-2001d in Vietnam.

PubMed

Vu, Le T; Long, Ngo T; Brito, Barbara; Stenfeldt, Carolina; Phuong, Nguyen T; Hoang, Bui H; Pauszek, Steven J; Hartwig, Ethan J; Smoliga, George R; Vu, Pham P; Quang, Le T V; Hung, Vo V; Tho, Nguyen D; Dong, Pham V; Minh, Phan Q; Bertram, Miranda; Fish, Ian H; Rodriguez, Luis L; Dung, Do H; Arzt, Jonathan

2017-01-01

In recent years, foot-and-mouth disease virus (FMDV) serotype O, topotype Middle East-South Asia (ME-SA), lineage Ind-2001d has spread from the Indian subcontinent to the Middle East, North Africa, and Southeast Asia. In the current report, we describe the first detection of this lineage in Vietnam in May, 2015 in Đắk Nông province. Three subsequent outbreaks caused by genetically related viruses occurred between May-October, 2015 after which the virus was not detected in clinical outbreaks for at least 15 subsequent months. The observed outbreaks affected (in chronological order): cattle in Đắk Nông province, pigs in Đắk Lắk province and Đắk Nông province, and cattle in Ninh Thuận province. The clinical syndromes associated with these outbreaks were consistent with typical FMD in the affected species. Overall attack rate on affected premises was 0.85 in pigs and 0.93 in cattle over the course of the outbreak. Amongst 378 pigs at risk on affected premises, 85 pigs died during the outbreaks; there were no deaths among cattle. The manner in which FMDV/O/ME-SA/Ind-2001d was introduced into Vietnam remains undetermined; however, movement of live cattle is the suspected route. This incursion has substantial implications for epidemiology and control of FMD in Southeast Asia.

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

Detection of nineteen enteric viruses in raw sewage in Japan.

PubMed

Thongprachum, Aksara; Fujimoto, Tsuguto; Takanashi, Sayaka; Saito, Hiroyuki; Okitsu, Shoko; Shimizu, Hiroyuki; Khamrin, Pattara; Maneekarn, Niwat; Hayakawa, Satoshi; Ushijima, Hiroshi

2018-05-10

One-year surveillance for enteric viruses in raw sewage was conducted in Kansai area, central part of Japan from July 2015 to June 2016. The raw sewage was collected monthly from an inlet polluted pool and was concentrated by polyethylene glycol (PEG) precipitation. Twelve sewage samples were screened for nineteen kinds of enteric viruses by using RT-PCR method and further analyzed by nucleotide sequencing. Twelve enteric viruses were found in the investigative sewage samples. Rotavirus A and norovirus GI and GII with several genotypes were detected all year round. Interestingly, norovirus GII.17 (Kawasaki-like strain) and rotavirus G2 that caused the outbreaks in Japan last epidemic season were also found in sewage. Moreover, adenovirus, astrovirus, sapovirus, bocavirus, human parechovirus, enterovirus, Aichi virus, Saffold virus and salivirus were also detected. Enterovirus D68 was detected only in the same month as those of enterovirus D68 outbreak in Japan. The rotavirus B and C, hepatitis A and E viruses, human cosavirus, bufavirus and rosavirus were not detected in this surveillance. The study provides the information on the enteric viruses contaminated in raw sewage, which is valuable for risk assessment. Our results imply that the viruses detected in sewage may be associated with infections in the Japanese population. Copyright © 2017. Published by Elsevier B.V.

A secure protocol for protecting the identity of providers when disclosing data for disease surveillance

PubMed Central

Hu, Jun; Mercer, Jay; Peyton, Liam; Kantarcioglu, Murat; Malin, Bradley; Buckeridge, David; Samet, Saeed; Earle, Craig

2011-01-01

Background Providers have been reluctant to disclose patient data for public-health purposes. Even if patient privacy is ensured, the desire to protect provider confidentiality has been an important driver of this reluctance. Methods Six requirements for a surveillance protocol were defined that satisfy the confidentiality needs of providers and ensure utility to public health. The authors developed a secure multi-party computation protocol using the Paillier cryptosystem to allow the disclosure of stratified case counts and denominators to meet these requirements. The authors evaluated the protocol in a simulated environment on its computation performance and ability to detect disease outbreak clusters. Results Theoretical and empirical assessments demonstrate that all requirements are met by the protocol. A system implementing the protocol scales linearly in terms of computation time as the number of providers is increased. The absolute time to perform the computations was 12.5 s for data from 3000 practices. This is acceptable performance, given that the reporting would normally be done at 24 h intervals. The accuracy of detection disease outbreak cluster was unchanged compared with a non-secure distributed surveillance protocol, with an F-score higher than 0.92 for outbreaks involving 500 or more cases. Conclusion The protocol and associated software provide a practical method for providers to disclose patient data for sentinel, syndromic or other indicator-based surveillance while protecting patient privacy and the identity of individual providers. PMID:21486880

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

Assessment of the risk posed to Singapore by the 2015 Middle East respiratory syndrome outbreak in the Republic of Korea

PubMed Central

Zhang, Emma Xuxiao; Oh, Olivia Seen Huey; See, Wanhan; Raj, Pream; James, Lyn; Khan, Kamran

2016-01-01

Objective To assess the public health risk to Singapore posed by the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea in 2015. Methods The likelihood of importation of MERS cases and the magnitude of the public health impact in Singapore were assessed to determine overall risk. Literature on the epidemiology and contextual factors associated with MERS coronavirus infection was collected and reviewed. Connectivity between the Republic of Korea and Singapore was analysed. Public health measures implemented by the two countries were reviewed. Results The epidemiology of the 2015 MERS outbreak in the Republic of Korea remained similar to the MERS outbreaks in Saudi Arabia. In addition, strong infection control and response measures were effective in controlling the outbreak. In view of the air traffic between Singapore and MERS-affected areas, importation of MERS cases into Singapore is possible. Nonetheless, the risk of a serious public health impact to Singapore in the event of an imported case of MERS would be mitigated by its strong health-care system and established infection control practices. Discussion The MERS outbreak was sparked by an exported case from the Middle East, which remains a concern as the reservoir of infection (thought to be camels) continues to exist in the Middle East, and sporadic cases in the community and outbreaks in health-care settings continue to occur there. This risk assessment highlights the need for Singapore to stay vigilant and to continue enhancing core public health capacities to detect and respond to MERS coronavirus. PMID:27508087

Multicenter Outbreak of Infections by Saprochaete clavata, an Unrecognized Opportunistic Fungal Pathogen

PubMed Central

Vaux, Sophie; Criscuolo, Alexis; Desnos-Ollivier, Marie; Diancourt, Laure; Tarnaud, Chloé; Vandenbogaert, Matthias; Brisse, Sylvain; Coignard, Bruno; Garcia-Hermoso, Dea; Blanc, Catherine; Hoinard, Damien; Lortholary, Olivier; Bretagne, Stéphane; Thiolet, Jean-Michel; de Valk, Henriette; Courbil, Rémi; Chabanel, Anne; Simonet, Marion; Maire, Francoise; Jbilou, Saadia; Tiberghien, Pierre; Blanchard, Hervé; Venier, Anne-Gaëlle; Bernet, Claude; Simon, Loïc; Sénéchal, Hélène; Pouchol, Elodie; Angot, Christiane; Ribaud, Patricia; Socié, G.; Flèche, M.; Brieu, Nathalie; Lagier, Evelyne; Chartier, Vanessa; Allegre, Thierry; Maulin, Laurence; Lanic, Hélène; Tilly, Hervé; Bouchara, Jean-Philippe; Pihet, Marc; Schmidt, Aline; Kouatchet, Achille; Vandamme, Yves-Marie; Ifrah, Norbert; Mercat, Alain; Accoceberry, Isabelle; Albert, Olivier; Leguay, Thibaut; Rogues, Anne-Marie; Bonhomme, Julie; Reman, Oumédaly; Lesteven, Claire; Poirier, Philippe; Chabrot, Cécile Molucon; Calvet, Laure; Baud, Olivier; Cambon, Monique; Farkas, Jean Chistophe; Lafon, Bruno; Dalle, Frédéric; Caillot, Denis; Lazzarotti, Aline; Aho, Serge; Combret, Sandrine; Facon, Thierry; Sendid, Boualem; Loridant, Séverine; Louis, Terriou; Cazin, Bruno; Grandbastien, Bruno; Bourgeois, Nathalie; Lotthé, Anne; Cartron, Guillaume; Ravel, Christophe; Colson, Pascal; Gaudard, Philippe; Bonmati, Caroline; Simon, Loic; Rabaud, Christian; Machouart, Marie; Poisson, Didier; Carp, Diana; Meunier, Jérôme; Gaschet, Anne; Miquel, Chantal; Sanhes, Laurence; Ferreyra, Milagros; Leibinger, Franck; Geudet, Philippe; Toubas, Dominique; Himberlin, Chantal; Bureau-Chalot, Florence; Delmer, Alain; Favennec, Loïc; Gargala, Gilles; Michot, Jean-Baptiste; Girault, Christophe; David, Marion; Leprêtre, Stéphane; Jardin, Fabrice; Honderlick, Pierre; Caille, Vincent; Cerf, Charles; Cassaing, Sophie; Recher, Christian; Picard, Muriel; Protin, Caroline; Huguet, Françoise; Huynh, Anne; Ruiz, Jean; Riu-Poulenc, Béatrice; Letocart, Philippe; Marchou, Bruno; Verdeil, Xavier; Cavalié, Laurent; Chauvin, Pamela; Iriart, Xavier; Valentin, Alexis; Bouvet, Emmanuelle; Delmas-Marsalet, Béatrice; Jeblaoui, Asma; Kassis-Chikhani, Najiby; Mühlethaler, Konrad; Zimmerli, Stefan; Zalar, Polona; Sánchez-Reus, Ferran; Gurgui, Merce

2014-01-01

ABSTRACT Rapidly fatal cases of invasive fungal infections due to a fungus later identified as Saprochaete clavata were reported in France in May 2012. The objectives of this study were to determine the clonal relatedness of the isolates and to investigate possible sources of contamination. A nationwide alert was launched to collect cases. Molecular identification methods, whole-genome sequencing (WGS), and clone-specific genotyping were used to analyze recent and historical isolates, and a case-case study was performed. Isolates from thirty cases (26 fungemias, 22 associated deaths at day 30) were collected between September 2011 and October 2012. Eighteen cases occurred within 8 weeks (outbreak) in 10 health care facilities, suggesting a common source of contamination, with potential secondary cases. Phylogenetic analysis identified one clade (clade A), which accounted for 16/18 outbreak cases. Results of microbiological investigations of environmental, drug, or food sources were negative. Analysis of exposures pointed to a medical device used for storage and infusion of blood products, but no fungal contamination was detected in the unused devices. Molecular identification of isolates from previous studies demonstrated that S. clavata can be found in dairy products and has already been involved in monocentric outbreaks in hematology wards. The possibility that S. clavata may transmit through contaminated medical devices or can be associated with dairy products as seen in previous European outbreaks is highly relevant for the management of future outbreaks due to this newly recognized pathogen. This report also underlines further the potential of WGS for investigation of outbreaks due to uncommon fungal pathogens. PMID:25516620

Multicenter outbreak of infections by Saprochaete clavata, an unrecognized opportunistic fungal pathogen.

PubMed

Vaux, Sophie; Criscuolo, Alexis; Desnos-Ollivier, Marie; Diancourt, Laure; Tarnaud, Chloé; Vandenbogaert, Matthias; Brisse, Sylvain; Coignard, Bruno; Dromer, Françoise

2014-12-16

Rapidly fatal cases of invasive fungal infections due to a fungus later identified as Saprochaete clavata were reported in France in May 2012. The objectives of this study were to determine the clonal relatedness of the isolates and to investigate possible sources of contamination. A nationwide alert was launched to collect cases. Molecular identification methods, whole-genome sequencing (WGS), and clone-specific genotyping were used to analyze recent and historical isolates, and a case-case study was performed. Isolates from thirty cases (26 fungemias, 22 associated deaths at day 30) were collected between September 2011 and October 2012. Eighteen cases occurred within 8 weeks (outbreak) in 10 health care facilities, suggesting a common source of contamination, with potential secondary cases. Phylogenetic analysis identified one clade (clade A), which accounted for 16/18 outbreak cases. Results of microbiological investigations of environmental, drug, or food sources were negative. Analysis of exposures pointed to a medical device used for storage and infusion of blood products, but no fungal contamination was detected in the unused devices. Molecular identification of isolates from previous studies demonstrated that S. clavata can be found in dairy products and has already been involved in monocentric outbreaks in hematology wards. The possibility that S. clavata may transmit through contaminated medical devices or can be associated with dairy products as seen in previous European outbreaks is highly relevant for the management of future outbreaks due to this newly recognized pathogen. This report also underlines further the potential of WGS for investigation of outbreaks due to uncommon fungal pathogens. Several cases of rapidly fatal infections due to the fungus Saprochaete clavata were reported in France within a short period of time in three health care facilities, suggesting a common source of contamination. A nationwide alert collected 30 cases over 1 year, including an outbreak of 18 cases over 8 weeks. Whole-genome sequencing (WGS) was used to analyze recent and historical isolates and to design a clade-specific genotyping method that uncovered a clone associated with the outbreak, thus allowing a case-case study to analyze the risk factors associated with infection by the clone. The possibility that S. clavata may transmit through contaminated medical devices or can be associated with dairy products as seen in previous European outbreaks is highly relevant for the management of future outbreaks due to this newly recognized pathogen. Copyright © 2014 Vaux et al.

Zika virus outbreak: a review of neurological complications, diagnosis, and treatment options.

PubMed

Koppolu, Veerendra; Shantha Raju, T

2018-06-01

Zika virus (ZIKV) is an arbovirus transmitted mainly by mosquitos of Aedes species. The virus has emerged in recent years and spread throughout North and South Americas. The recent outbreak of ZIKV started in Brazil (2015) has resulted in infections surpassing a million mark. Contrary to the previous beliefs that Zika causes mildly symptomatic infections fever, headache, rash, arthralgia, and conjunctivitis, the recent outbreak associated ZIKV to serious neurological complications such as microcephaly, Guillain-Barré syndrome, and eye infections. The recent outbreak has resulted in an astonishing number of microcephaly cases in fetus and infants. Consequently, numerous studies were conducted using in vitro cell and in vivo animal models. These studies showed clear links between ZIKV infections and neurological abnormalities. Diagnosis methods based on nucleic acid and serological detection facilitated rapid and accurate identification of ZIKV infections. New transmission modalities such as sexual and transplacental transmission were uncovered. Given the seriousness of ZIKV infections, WHO declared the development of safe and effective vaccines and new antiviral drugs as an urgent global health priority. Rapid work in this direction has led to the identification of several vaccine and antiviral drug candidates. Here, we review the remarkable progress made in understanding the molecular links between ZIKV infections and neurological irregularities, new diagnosis methods, potential targets for antiviral drugs, and the current state of vaccine development.

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.

[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.

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.

Presence and Persistence of Salmonella in Water: The Impact on Microbial Quality of Water and Food Safety.

PubMed

Liu, Huanli; Whitehouse, Chris A; Li, Baoguang

2018-01-01

Salmonella ranks high among the pathogens causing foodborne disease outbreaks. According to the Centers for Disease Control and Prevention, Salmonella contributed to about 53.4% of all foodborne disease outbreaks from 2006 to 2017, and approximately 32.7% of these foodborne Salmonella outbreaks were associated with consumption of produce. Trace-back investigations have suggested that irrigation water may be a source of Salmonella contamination of produce and a vehicle for transmission. Presence and persistence of Salmonella have been reported in surface waters such as rivers, lakes, and ponds, while ground water in general offers better microbial quality for irrigation. To date, culture methods are still the gold standard for detection, isolation and identification of Salmonella in foods and water. In addition to culture, other methods for the detection of Salmonella in water include most probable number, immunoassay, and PCR. The U.S. Food and Drug Administration (FDA) issued the Produce Safety Rule (PSR) in January 2013 based on the Food Safety Modernization Act (FSMA), which calls for more efforts toward enhancing and improving approaches for the prevention of foodborne outbreaks. In the PSR, agricultural water is defined as water used for in a way that is intended to, or likely to, contact covered produce, such as spray, wash, or irrigation. In summary, Salmonella is frequently present in surface water, an important source of water for irrigation. An increasing evidence indicates irrigation water as a source (or a vehicle) for transmission of Salmonella . This pathogen can survive in aquatic environments by a number of mechanisms, including entry into the viable but nonculturable (VBNC) state and/or residing within free-living protozoa. As such, assurance of microbial quality of irrigation water is critical to curtail the produce-related foodborne outbreaks and thus enhance the food safety. In this review, we will discuss the presence and persistence of Salmonella in water and the mechanisms Salmonella uses to persist in the aquatic environment, particularly irrigation water, to better understand the impact on the microbial quality of water and food safety due to the presence of Salmonella in the water environment.

Presence and Persistence of Salmonella in Water: The Impact on Microbial Quality of Water and Food Safety

PubMed Central

Liu, Huanli; Whitehouse, Chris A.; Li, Baoguang

2018-01-01

Salmonella ranks high among the pathogens causing foodborne disease outbreaks. According to the Centers for Disease Control and Prevention, Salmonella contributed to about 53.4% of all foodborne disease outbreaks from 2006 to 2017, and approximately 32.7% of these foodborne Salmonella outbreaks were associated with consumption of produce. Trace-back investigations have suggested that irrigation water may be a source of Salmonella contamination of produce and a vehicle for transmission. Presence and persistence of Salmonella have been reported in surface waters such as rivers, lakes, and ponds, while ground water in general offers better microbial quality for irrigation. To date, culture methods are still the gold standard for detection, isolation and identification of Salmonella in foods and water. In addition to culture, other methods for the detection of Salmonella in water include most probable number, immunoassay, and PCR. The U.S. Food and Drug Administration (FDA) issued the Produce Safety Rule (PSR) in January 2013 based on the Food Safety Modernization Act (FSMA), which calls for more efforts toward enhancing and improving approaches for the prevention of foodborne outbreaks. In the PSR, agricultural water is defined as water used for in a way that is intended to, or likely to, contact covered produce, such as spray, wash, or irrigation. In summary, Salmonella is frequently present in surface water, an important source of water for irrigation. An increasing evidence indicates irrigation water as a source (or a vehicle) for transmission of Salmonella. This pathogen can survive in aquatic environments by a number of mechanisms, including entry into the viable but nonculturable (VBNC) state and/or residing within free-living protozoa. As such, assurance of microbial quality of irrigation water is critical to curtail the produce-related foodborne outbreaks and thus enhance the food safety. In this review, we will discuss the presence and persistence of Salmonella in water and the mechanisms Salmonella uses to persist in the aquatic environment, particularly irrigation water, to better understand the impact on the microbial quality of water and food safety due to the presence of Salmonella in the water environment. PMID:29900166

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

PubMed

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

2013-10-01

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

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 ...

Big Data and the Global Public Health Intelligence Network (GPHIN)

PubMed Central

Dion, M; AbdelMalik, P; Mawudeku, A

2015-01-01

Background Globalization and the potential for rapid spread of emerging infectious diseases have heightened the need for ongoing surveillance and early detection. The Global Public Health Intelligence Network (GPHIN) was established to increase situational awareness and capacity for the early detection of emerging public health events. Objective To describe how the GPHIN has used Big Data as an effective early detection technique for infectious disease outbreaks worldwide and to identify potential future directions for the GPHIN. Findings Every day the GPHIN analyzes over more than 20,000 online news reports (over 30,000 sources) in nine languages worldwide. A web-based program aggregates data based on an algorithm that provides potential signals of emerging public health events which are then reviewed by a multilingual, multidisciplinary team. An alert is sent out if a potential risk is identified. This process proved useful during the Severe Acute Respiratory Syndrome (SARS) outbreak and was adopted shortly after by a number of countries to meet new International Health Regulations that require each country to have the capacity for early detection and reporting. The GPHIN identified the early SARS outbreak in China, was credited with the first alert on MERS-CoV and has played a significant role in the monitoring of the Ebola outbreak in West Africa. Future developments are being considered to advance the GPHIN’s capacity in light of other Big Data sources such as social media and its analytical capacity in terms of algorithm development. Conclusion The GPHIN’s early adoption of Big Data has increased global capacity to detect international infectious disease outbreaks and other public health events. Integration of additional Big Data sources and advances in analytical capacity could further strengthen the GPHIN’s capability for timely detection and early warning. PMID:29769954

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.

Utility of a stressed-SNP real-time PCR assay for the rapid identification of measles vaccine strain in patient samples.

PubMed

Tran, Thomas; Kostecki, Renata; Catton, Michael; Druce, Julian

2018-05-09

Rapid differentiation of wild-type measles virus from measles vaccine strains is crucial during a measles outbreak and in a measles elimination setting. A real-time RT-PCR for the rapid detection of measles vaccine strains was developed with high specificity and greater sensitivity than when compared to traditional measles genotyping methods. The "stressed" minor grove binder TaqMan probe design approach achieves specificity to vaccine strains only, without compromising sensitivity. This assay has proven to be extremely useful in outbreak settings, without requiring sequence genotyping, for over 4 years at the Regional Measles Reference Laboratory for the Western Pacific Region. Copyright © 2018 Tran et al.

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...

Measles Cases during Ebola Outbreak, West Africa, 2013-2106.

PubMed

Colavita, Francesca; Biava, Mirella; Castilletti, Concetta; Quartu, Serena; Vairo, Francesco; Caglioti, Claudia; Agrati, Chiara; Lalle, Eleonora; Bordi, Licia; Lanini, Simone; Guanti, Michela Delli; Miccio, Rossella; Ippolito, Giuseppe; Capobianchi, Maria R; Di Caro, Antonino

2017-06-01

The recent Ebola outbreak in West Africa caused breakdowns in public health systems, which might have caused outbreaks of vaccine-preventable diseases. We tested 80 patients admitted to an Ebola treatment center in Freetown, Sierra Leone, for measles. These patients were negative for Ebola virus. Measles virus IgM was detected in 13 (16%) of the patients.

Evaluating a New Online Course in the Epidemiology of Infectious Diseases by Studying Student Learning Styles

ERIC Educational Resources Information Center

Rogers, James W.; Cox, James R.

2008-01-01

At RMIT University, students may now elect to study infectious diseases through a course called Outbreak--The Detection and Control of Infectious Disease. Outbreak was designed to simulate in an online class the effective teamwork required to bring resolution to outbreak crises and enable frameworks for future prevention. The appropriateness of…

Ultra-Deep Sequencing Analysis of the Hepatitis A Virus 5'-Untranslated Region among Cases of the Same Outbreak from a Single Source

PubMed Central

Wu, Shuang; Nakamoto, Shingo; Kanda, Tatsuo; Jiang, Xia; Nakamura, Masato; Miyamura, Tatsuo; Shirasawa, Hiroshi; Sugiura, Nobuyuki; Takahashi-Nakaguchi, Azusa; Gonoi, Tohru; Yokosuka, Osamu

2014-01-01

Hepatitis A virus (HAV) is a causative agent of acute viral hepatitis for which an effective vaccine has been developed. Here we describe ultra-deep pyrosequences (UDPSs) of HAV 5'-untranslated region (5'UTR) among cases of the same outbreak, which arose from a single source, associated with a revolving sushi bar. We determined the reference sequence from HAV-derived clone from an attendant by the Sanger method. Sixteen UDPSs from this outbreak and one from another sporadic case were compared with this reference. Nucleotide errors yielded a UDPS error rate of < 1%. This study confirmed that nucleotide substitutions of this region are transition mutations in outbreak cases, that insertion was observed only in non-severe cases, and that these nucleotide substitutions were different from those of the sporadic case. Analysis of UDPSs detected low-prevalence HAV variations in 5'UTR, but no specific mutations associated with severity in these outbreak cases. To our surprise, HAV strains in this outbreak conserved HAV IRES sequence even if we performed analysis of UDPSs. UDPS analysis of HAV 5'UTR gave us no association between the disease severity of hepatitis A and HAV 5'UTR substitutions. It might be more interesting to perform ultra-deep sequencing of full length HAV genome in order to reveal possible unknown genomic determinants associated with disease severity. Further studies will be needed. PMID:24396287

Outbreaks of infectious intestinal disease associated with person to person spread in hotels and restaurants.

PubMed

McDonnell, R J; Wall, P G; Adak, G K; Evans, H S; Cowden, J M; Caul, E O

1995-09-15

Twenty-eight outbreaks of infectious intestinal disease, reported as being transmitted mainly by the person to person route, were identified in association with retail catering premises, such as hotels, restaurants, and public houses, in England and Wales between 1992 and 1994. Five thousand and forty-eight people were at risk in these outbreaks and 1234 were affected. Most of the outbreaks (over 90%) occurred in hotels. Small round structured viruses were the most commonly detected pathogens. Diarrhoea and vomiting were common symptoms and most of the outbreaks occurred in the summer months. Control measures to contain infectious individuals and improved hygiene measures are necessary to contain such outbreaks.

Communitywide cryptosporidiosis outbreak associated with a surface water-supplied municipal water system--Baker City, Oregon, 2013.

PubMed

DeSilva, M B; Schafer, S; Kendall Scott, M; Robinson, B; Hills, A; Buser, G L; Salis, K; Gargano, J; Yoder, J; Hill, V; Xiao, L; Roellig, D; Hedberg, K

2016-01-01

Cryptosporidium, a parasite known to cause large drinking and recreational water outbreaks, is tolerant of chlorine concentrations used for drinking water treatment. Human laboratory-based surveillance for enteric pathogens detected a cryptosporidiosis outbreak in Baker City, Oregon during July 2013 associated with municipal drinking water. Objectives of the investigation were to confirm the outbreak source and assess outbreak extent. The watershed was inspected and city water was tested for contamination. To determine the community attack rate, a standardized questionnaire was administered to randomly sampled households. Weighted attack rates and confidence intervals (CIs) were calculated. Water samples tested positive for Cryptosporidium species; a Cryptosporidium parvum subtype common in cattle was detected in human stool specimens. Cattle were observed grazing along watershed borders; cattle faeces were observed within watershed barriers. The city water treatment facility chlorinated, but did not filter, water. The community attack rate was 28·3% (95% CI 22·1-33·6), sickening an estimated 2780 persons. Watershed contamination by cattle probably caused this outbreak; water treatments effective against Cryptosporidium were not in place. This outbreak highlights vulnerability of drinking water systems to pathogen contamination and underscores the need for communities to invest in system improvements to maintain multiple barriers to drinking water contamination.

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

PubMed

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

2016-01-01

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

Investigation of a type C/D botulism outbreak in free-range laying hens in France.

PubMed

Souillard, R; Le Maréchal, C; Ballan, V; Rouxel, S; Léon, D; Balaine, L; Poëzevara, T; Houard, E; Robineau, B; Robinault, C; Chemaly, M; Le Bouquin, S

2017-04-01

In 2014, a botulism outbreak in a flock of laying hens was investigated in France. In the flock of 5020 hens, clinical signs of botulism occurred at 46 weeks of age. A type C/D botulism outbreak was confirmed using the mouse lethality assay for detection of botulinum toxin in serum and a real-time PCR test to detect Clostridium botulinum in intestinal contents. The disease lasted one week with a mortality rate of 2.6% without recurrence. Botulism in laying hens has rarely been reported. Five monthly visits were made to the farm between December 2014 and May 2015 for a longitudinal study of the persistence of C. botulinum in the poultry house after the outbreak, and to assess egg contamination by C. botulinum. Several samples were collected on each visit: in the house (from the ventilation circuit, the egg circuit, water and feed, droppings) and the surrounding area. Thirty clean and 30 dirty eggs were also swabbed at each visit. In addition, 12 dirty and 12 clean eggs were collected to analyse eggshell and egg content. The samples were analysed using real-time PCR to detect type C/D C. botulinum. The bacterium was still detected in the house more than 5 months after the outbreak, mostly on the walls and in the egg circuit. Regarding egg contamination, the bacteria were detected only on the shell but not in the content of the eggs. Control measures should therefore be implemented throughout the egg production period to avoid dissemination of the bacteria, particularly during egg collection.

Comparison of the Sensitivity of Laboratory Diagnostic Methods from a Well-Characterized Outbreak of Mumps in New York City in 2009

PubMed Central

Rosen, Jennifer B.; Doll, Margaret K.; McNall, Rebecca J.; McGrew, Marcia; Williams, Nobia; Lopareva, Elena N.; Barskey, Albert E.; Punsalang, Amado; Rota, Paul A.; Oleszko, William R.; Hickman, Carole J.; Zimmerman, Christopher M.; Bellini, William J.

2013-01-01

A mumps outbreak in upstate New York in 2009 at a summer camp for Orthodox Jewish boys spread into Orthodox Jewish communities in the Northeast, including New York City. The availability of epidemiologic information, including vaccination records and parotitis onset dates, allowed an enhanced analysis of laboratory methods for mumps testing. Serum and buccal swab samples were collected from 296 confirmed cases with onsets from September through December 2009. All samples were tested using the Centers for Disease Control and Prevention (CDC) capture IgM enzyme immunoassay (EIA) and a real-time reverse transcription-PCR (rRT-PCR) that targets the short hydrophobic gene. A subset of the samples (n = 205) was used to evaluate 3 commercial mumps IgM assays and to assess the sensitivity of using an alternative target gene (nucleoprotein) in the rRT-PCR protocol. Among 115 cases of mumps with 2 documented doses of measles, mumps, and rubella (MMR) vaccine, the CDC capture IgM EIA detected IgM in 51% of serum samples compared to 9% to 24% using three commercial IgM assays. The rRT-PCR that targeted the nucleoprotein gene increased RNA detection by 14% compared to that obtained with the original protocol. The ability to detect IgM improved when serum was collected 3 days or more after symptom onset, whereas sensitivity of RNA detection by rRT-PCR declined when buccal swabs were collected later than 2 days after onset. Selection of testing methods and timing of sample collection are important factors in the ability to confirm infection among vaccinated persons. These results reinforce the need to use virus detection assays in addition to serologic tests. PMID:23324519

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

Molecular Analysis of an Outbreak of Lethal Postpartum Sepsis Caused by Streptococcus pyogenes

PubMed Central

Turner, Claire E.; Dryden, Matthew; Holden, Matthew T. G.; Davies, Frances J.; Lawrenson, Richard A.; Farzaneh, Leili; Bentley, Stephen D.; Efstratiou, Androulla

2013-01-01

Sepsis is now the leading direct cause of maternal death in the United Kingdom, and Streptococcus pyogenes is the leading pathogen. We combined conventional and genomic analyses to define the duration and scale of a lethal outbreak. Two postpartum deaths caused by S. pyogenes occurred within 24 h; one was characterized by bacteremia and shock and the other by hemorrhagic pneumonia. The women gave birth within minutes of each other in the same maternity unit 2 days earlier. Seven additional infections in health care and household contacts were subsequently detected and treated. All cluster-associated S. pyogenes isolates were genotype emm1 and were initially indistinguishable from other United Kingdom emm1 isolates. Sequencing of the virulence gene sic revealed that all outbreak isolates had the same unique sic type. Genome sequencing confirmed that the cluster was caused by a unique S. pyogenes clone. Transmission between patients occurred on a single day and was associated with casual contact only. A single isolate from one patient demonstrated a sequence change in sic consistent with longer infection duration. Transmission to health care workers was traced to single clinical contacts with index cases. The last case was detected 18 days after the first case. Following enhanced surveillance, the outbreak isolate was not detected again. Mutations in bacterial regulatory genes played no detectable role in this outbreak, illustrating the intrinsic ability of emm1 S. pyogenes to spread while retaining virulence. This fast-moving outbreak highlights the potential of S. pyogenes to cause a range of diseases in the puerperium with rapid transmission, underlining the importance of immediate recognition and response by clinical infection and occupational health teams. PMID:23616448

Canine Circovirus 1 (CaCV-1) and Canine Parvovirus 2 (CPV-2): Recurrent Dual Infections in a Papillon Breeding Colony.

PubMed

Thaiwong, T; Wise, A G; Maes, R K; Mullaney, T; Kiupel, M

2016-11-01

Recurrent outbreaks of sudden death and bloody diarrhea were reported in March 2013 and February 2014 in a breeding colony of Papillon dogs. During the first outbreak, 1 adult dog and 2 eight-month-old puppies died. During the second outbreak, 2 ten-week-old puppies died. One puppy from the first outbreak and 2 puppies from the second outbreak were examined at necropsy. Histologically, all 3 puppies had severe segmental crypt necrosis of the small intestine and marked lymphoid follicle depletion in the spleen and Peyer's patches. Real-time (RT) polymerase chain reaction (PCR) demonstrated abundant canine parvovirus (CPV-2) DNA (Ct<15) in the affected small intestine, and immunohistochemistry detected large amounts of CPV-2 antigen in intestinal crypt epithelium and Kupffer cells but few positive macrophages in lymphoid organs. All puppies had marked sinusoidal histiocytosis and multifocal granulomatous inflammation in mesenteric lymph nodes and spleen, prompting additional RT-PCR testing for canine circovirus 1 (CaCV-1). Very high levels of CaCV-1 DNA (Ct<13) were detected in small intestine, lymph nodes, and spleen. In situ hybridization for CaCV-1 detected rare positive nuclei of regenerating crypt epithelium but abundant amounts of CaCV-1 nucleic acid in the cytoplasm and nuclei of histiocytes in all lymphoid tissues, including granulomatous inflammatory foci and hepatic Kupffer cells. Significant levels of CaCV-1 DNA were detected in blood and serum (Ct as low as 13) but not feces from 3 surviving dogs at 2 months or 1 year after the outbreak, respectively. We hypothesize that CPV-2 infection predisposed dogs to CaCV-1 infection and ultimately resulted in more severe clinical disease. © The Author(s) 2016.

Noroviruses associated with outbreaks of acute gastroenteritis in the State of Rio Grande do Sul, Brazil, 2004-2011.

PubMed

de Andrade, Juliana da Silva Ribeiro; Rocha, Monica Simões; Carvalho-Costa, Felipe Aníbal; Fioretti, Julia Monassa; Xavier, Maria da Penha Trindade Pinheiro; Nunes, Zenaida Maria Alves; Cardoso, Jeanice; Fialho, Alexandre Madi; Leite, José Paulo Gagliardi; Miagostovich, Marize Pereira

2014-11-01

Acute gastroenteritis norovirus (NoV) in a country of continental dimensions like Brazil has resulted in under-reporting of the number of outbreaks, as well as the genotypes associated. To demonstrate the role of NoV in outbreaks occurring in the State of Rio Grande do Sul, Southern Brazil, we determined its prevalence, as well as the genotypes associated, and evaluated clinical and epidemiological aspects. NoV investigation was carried out in rotavirus group A negative stool samples from 2265 patients from 741 outbreaks that occurred in the State of Rio Grande do Sul, Brazil, during a period of eight years (2004-2011). NoV detection and nucleotide sequencing for genotype characterization was carried by using sets of primers targeting a conservative Rd-Rp polymerase genome region and the viral capsid gene, respectively. NoVs were detected in 817 stool samples (36.1%) and associated with 327 outbreaks (44.1%). NoV GII.2, GII.3, GII.4, GII.6, GII.12, GII.13, GII.14, GII.15, GII.17, GII.21; and GI.1 and GI.3 were characterized. GII.4 was the most frequently detected (72.3%), with five variants identified (Asia_2003, Hunter_2004, Yerseke_2006a, Den_Haag_2006b, New Orleans_2009). This study describes the first detection of GI.1 and GII.13 and GII.15 in Brazil and demonstrates NoV winter-spring seasonality in this region of the country. NoVs were responsible for almost 50% of outbreaks, with about 70% of them resulting from genotype GII.4 and its variants. The seasonality observed could help health authorities to establish a system of active surveillance in order to reduce NoV impact especially in congregate settings. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2007-01-01

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

A Likelihood-Based Approach to Identifying Contaminated Food Products Using Sales Data: Performance and Challenges

PubMed Central

Kaufman, James; Lessler, Justin; Harry, April; Edlund, Stefan; Hu, Kun; Douglas, Judith; Thoens, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

2014-01-01

Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and—in the worst cases—death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single “guilty” food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially “guilty” products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to “hard-to-identify” foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for “hard-to-identify” products. PMID:24992565

Incidence and Tracking of Escherichia coli O157:H7 in a Major Produce Production Region in California

PubMed Central

Cooley, Michael; Carychao, Diana; Crawford-Miksza, Leta; Jay, Michele T.; Myers, Carol; Rose, Christopher; Keys, Christine; Farrar, Jeff; Mandrell, Robert E.

2007-01-01

Fresh vegetables have become associated with outbreaks caused by Escherichia coli O157:H7 (EcO157). Between 1995–2006, 22 produce outbreaks were documented in the United States, with nearly half traced to lettuce or spinach grown in California. Outbreaks between 2002 and 2006 induced investigations of possible sources of pre-harvest contamination on implicated farms in the Salinas and San Juan valleys of California, and a survey of the Salinas watershed. EcO157 was isolated at least once from 15 of 22 different watershed sites over a 19 month period. The incidence of EcO157 increased significantly when heavy rain caused an increased flow rate in the rivers. Approximately 1000 EcO157 isolates obtained from cultures of>100 individual samples were typed using Multi-Locus Variable-number-tandem-repeat Analysis (MLVA) to assist in identifying potential fate and transport of EcO157 in this region. A subset of these environmental isolates were typed by Pulse Field Gel Electrophoresis (PFGE) in order to make comparisons with human clinical isolates associated with outbreak and sporadic illness. Recurrence of identical and closely related EcO157 strains from specific locations in the Salinas and San Juan valleys suggests that transport of the pathogen is usually restricted. In a preliminary study, EcO157 was detected in water at multiple locations in a low-flow creek only within 135 meters of a point source. However, possible transport up to 32 km was detected during periods of higher water flow associated with flooding. During the 2006 baby spinach outbreak investigation, transport was also detected where water was unlikely to be involved. These results indicate that contamination of the environment is a dynamic process involving multiple sources and methods of transport. Intensive studies of the sources, incidence, fate and transport of EcO157 near produce production are required to determine the mechanisms of pre-harvest contamination and potential risks for human illness. PMID:18174909

Detection of Mycoplasma pneumoniae by real-time PCR.

PubMed

Winchell, Jonas M; Mitchell, Stephanie L

2013-01-01

Mycoplasma pneumoniae is a significant cause of respiratory disease, accounting for approximately 20% of cases of community-acquired pneumonia. Although several diagnostic methods exist to detect M. pneumoniae in respiratory specimens, real-time PCR has emerged as a significant improvement for the rapid diagnosis of this pathogen. The method described herein details the procedure for the detection of M. pneumoniae by real-time PCR (qPCR). The qPCR assay described can be performed with three targets specific for M. pneumoniae (Mp181, Mp3, and Mp7) and one marker for the detection of the RNaseP gene found in human nucleic acid as an internal control reaction. Recent studies have demonstrated the ability of this procedure to reliably identify this agent and facilitate the timely recognition of an outbreak.

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.

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.

Mapping and detecting bark beetle-caused tree mortality in the western United States

NASA Astrophysics Data System (ADS)

Meddens, Arjan J. H.

Recently, insect outbreaks across North America have dramatically increased and the forest area affected by bark beetles is similar to that affected by fire. Remote sensing offers the potential to detect insect outbreaks with high accuracy. Chapter one involved detection of insect-caused tree mortality on the tree level for a 90km2 area in northcentral Colorado. Classes of interest included green trees, multiple stages of post-insect attack tree mortality including dead trees with red needles ("red-attack") and dead trees without needles ("gray-attack"), and non-forest. The results illustrated that classification of an image with a spatial resolution similar to the area of a tree crown outperformed that from finer and coarser resolution imagery for mapping tree mortality and non-forest classes. I also demonstrated that multispectral imagery could be used to separate multiple postoutbreak attack stages (i.e., red-attack and gray-attack) from other classes in the image. In Chapter 2, I compared and improved methods for detecting bark beetle-caused tree mortality using medium-resolution satellite data. I found that overall classification accuracy was similar between single-date and multi-date classification methods. I developed regression models to predict percent red attack within a 30-m grid cell and these models explained >75% of the variance using three Landsat spectral explanatory variables. Results of the final product showed that approximately 24% of the forest within the Landsat scene was comprised of tree mortality caused by bark beetles. In Chapter 3, I developed a gridded data set with 1-km2 resolution using aerial survey data and improved estimates of tree mortality across the western US and British Columbia. In the US, I also produced an upper estimate by forcing the mortality area to match that from high-resolution imagery in Idaho, Colorado, and New Mexico. Cumulative mortality area from all bark beetles was 5.46 Mha in British Columbia in 2001-2010 and 0.47-5.37 Mha (lower and upper estimate) in the western conterminous US during 1997-2010. Improved methods for detection and mapping of insect outbreak areas will lead to improved assessments of the effects of these forest disturbances on the economy, carbon cycle (and feedback to climate change), fuel loads, hydrology and forest ecology.

Multiplex PCR detection of waterborne intestinal protozoa: microsporidia, Cyclospora, and Cryptosporidium.

PubMed

Lee, Seung-Hyun; Joung, Migyo; Yoon, Sejoung; Choi, Kyoungjin; Park, Woo-Yoon; Yu, Jae-Ran

2010-12-01

Recently, emerging waterborne protozoa, such as microsporidia, Cyclospora, and Cryptosporidium, have become a challenge to human health worldwide. Rapid, simple, and economical detection methods for these major waterborne protozoa in environmental and clinical samples are necessary to control infection and improve public health. In the present study, we developed a multiplex PCR test that is able to detect all these 3 major waterborne protozoa at the same time. Detection limits of the multiplex PCR method ranged from 10(1) to 10(2) oocysts or spores. The primers for microsporidia or Cryptosporidium used in this study can detect both Enterocytozoon bieneusi and Encephalitozoon intestinalis, or both Cryptosporidium hominis and Cryptosporidium parvum, respectively. Restriction enzyme digestion of PCR products with BsaBI or BsiEI makes it possible to distinguish the 2 species of microsporidia or Cryptosporidium, respectively. This simple, rapid, and cost-effective multiplex PCR method will be useful for detecting outbreaks or sporadic cases of waterborne protozoa infections.

[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.

Nosocomial outbreak of neonatal gastroenteritis caused by a new serotype 4, subtype 4B human rotavirus.

PubMed

Gerna, G; Forster, J; Parea, M; Sarasini, A; Di Matteo, A; Baldanti, F; Langosch, B; Schmidt, S; Battaglia, M

1990-07-01

A nosocomial outbreak of rotavirus gastroenteritis involving 52 newborns occurred between June and September 1988 at the University Children's Hospital of Freiburg, Federal Republic of Germany. Stools from 27 representative patients were examined for rotavirus serotypes, using a monoclonal antibody-based enzyme-linked immunosorbent assay. The electropherotype was also examined by polyacrylamide gel electrophoresis of genomic RNA. As many as 18 patients were found to be infected by serotype 4, subtype 4B strain, and in all of them the same electropherotype was detected. Although rotavirus from the remaining nine patients could not be typed, the electropherotype in four was identical to that of the serotype 4, subtype 4B strain. Thus, most of the patients in the outbreak were infected by the same rotavirus strain. Retrospective epidemiological studies showed that the 4B strain began to circulate at the hospital in January 1988, whereas only rotavirus serotypes 1, 3, and 4A were detected in 1985-1987. The primary case of the outbreak was presumably a newborn with acute gastroenteritis, admitted to the hospital from a small maternity unit in the same urban area. During the outbreak, 12 of 44 healthy newborns in the nurseries of the Children's Hospital and other maternity hospitals were found to be asymptomatic rotavirus carriers, and in three of the newborns the same 4B strain was detected. This is the first reported outbreak caused by a serotype 4, subtype 4B strain.

Field study of pneumonia in vaccinated cattle associated with incorrect vaccination and Pasteurella multocida infection.

PubMed

Crawshaw, W M; Caldow, G L

2015-04-25

This field study used data on the vaccine courses against bovine respiratory disease sold by one pharmaceutical company in conjunction with pharmacovigilance data to explore reported suspected lack of expected efficacy and the reasons for this. The study ran from May 1, 2007, to April 30, 2010, and covered vaccines sold in Scotland and part of Northumberland. In total, 83 groups of cattle reported suspected lack of expected efficacy, representing 1.6 per cent of the 804,618 vaccine courses sold. It was possible to investigate 45 of these outbreaks in depth using a standard questionnaire and diagnostic protocol. Vaccine usage outwith the specific product characteristics (SPC) occurred in 47 per cent of cases (21/45). The proportion of vaccination courses used where a pathogen contained in the vaccine was detected in the diseased cattle and vaccine use was consistent with the SPC was estimated at 0.12 per cent of the courses sold. Pasteurella multocida was the most common pathogen detected and was found in 21 of the outbreaks. For outbreaks where a pathogen contained in the vaccine was detected, P. multocida was found at a significantly greater frequency (P=0.03) where vaccine use was compliant with the SPC (five of six outbreaks) compared with outbreaks where vaccine use had not been compliant with the SPC (one of seven outbreaks). The limitations of the study, including the diagnostic tests employed and definition of vaccination outwith the SPC, are discussed. British Veterinary Association.

Enhanced Reverse Transcription-PCR Assay for Detection of Norovirus Genogroup I

PubMed Central

Dreier, Jens; Störmer, Melanie; Mäde, Dietrich; Burkhardt, Sabine; Kleesiek, Knut

2006-01-01

We have developed a one-tube reverse transcription (RT)-PCR method using the real-time TaqMan PCR system for the detection of norovirus genogroup I (NV GGI). By introduction of a novel probe based on locked nucleic acid technology, we enhanced the sensitivity of the assay compared to those of conventional TaqMan probes. The sensitivity of the NV GGI RT-PCR was determined by probit analysis with defined RNA standards and quantified norovirus isolates to 711 copies/ml (95% detection limit). In order to detect PCR inhibition, we included a heterologous internal control (IC) system based on phage MS2. This internally controlled RT-PCR was tested on different real-time PCR platforms, LightCycler, Rotorgene, Mastercycler EP realplex, and ABI Prism. Compared to the assay without an IC, the duplex RT-PCR exhibited no reduction in sensitivity in clinical samples. In combination with an established NV GGII real-time RT-PCR, we used the novel assay in a routine assay for diagnosis of clinical and food-borne norovirus infection. We applied this novel assay to analyze outbreaks of nonbacterial acute gastroenteritis. Norovirus of GGI was detected in these outbreaks. Sequence and similarity plot analysis of open reading frame 1 (ORF1) and ORF2 showed two genotypes, GGI/2 and GGI/4, in semiclosed communities. PMID:16891482

Detection and genotyping of Entamoeba histolytica, Entamoeba dispar, Giardia lamblia, and Cryptosporidium parvum by oligonucleotide microarray.

PubMed

Wang, Zheng; Vora, Gary J; Stenger, David A

2004-07-01

Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum are the most frequently identified protozoan parasites causing waterborne disease outbreaks. The morbidity and mortality associated with these intestinal parasitic infections warrant the development of rapid and accurate detection and genotyping methods to aid public health efforts aimed at preventing and controlling outbreaks. In this study, we describe the development of an oligonucleotide microarray capable of detecting and discriminating between E. histolytica, Entamoeba dispar, G. lamblia assemblages A and B, and C. parvum types 1 and 2 in a single assay. Unique hybridization patterns for each selected protozoan were generated by amplifying six to eight diagnostic sequences/organism by multiplex PCR; fluorescent labeling of the amplicons via primer extension; and subsequent hybridization to a set of genus-, species-, and subtype-specific covalently immobilized oligonucleotide probes. The profile-based specificity of this methodology not only permitted for the unequivocal identification of the six targeted species and subtypes, but also demonstrated its potential in identifying related species such as Cryptosporidium meleagridis and Cryptosporidium muris. In addition, sensitivity assays demonstrated lower detection limits of five trophozoites of G. lamblia. Taken together, the specificity and sensitivity of the microarray-based approach suggest that this methodology may provide a promising tool to detect and genotype protozoa from clinical and environmental samples.

Mapping Health Data: Improved Privacy Protection With Donut Method Geomasking

PubMed Central

Hampton, Kristen H.; Fitch, Molly K.; Allshouse, William B.; Doherty, Irene A.; Gesink, Dionne C.; Leone, Peter A.; Serre, Marc L.; Miller, William C.

2010-01-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest. PMID:20817785

Mapping health data: improved privacy protection with donut method geomasking.

PubMed

Hampton, Kristen H; Fitch, Molly K; Allshouse, William B; Doherty, Irene A; Gesink, Dionne C; Leone, Peter A; Serre, Marc L; Miller, William C

2010-11-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.

[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.

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.

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Risk exposures for human ornithosis in a poultry processing plant modified by use of personal protective equipment: an analytical outbreak study.

PubMed

Williams, C J; Sillis, M; Fearne, V; Pezzoli, L; Beasley, G; Bracebridge, S; Reacher, M; Nair, P

2013-09-01

Ornithosis outbreaks in poultry processing plants are well-described, but evidence for preventive measures is currently lacking. This study describes a case-control study into an outbreak of ornithosis at a poultry processing plant in the East of England, identified following three employees being admitted to hospital. Workers at the affected plant were recruited via their employer, with exposures assessed using a self-completed questionnaire. Cases were ascertained using serological methods or direct antigen detection in sputum. 63/225 (28%) staff participated, with 10% of participants showing evidence of recent infection. Exposure to the killing/defeathering and automated evisceration areas, and contact with viscera or blood were the main risk factors for infection. Personal protective equipment (goggles and FFP3 masks) reduced the effect of exposure to risk areas and to self-contamination with potentially infectious material. Our study provides some evidence of effectiveness for respiratory protective equipment in poultry processing plants where there is a known and current risk of ornithosis. Further studies are required to confirm this tentative finding, but in the meantime respiratory protective equipment is recommended as a precautionary measure in plants where outbreaks of ornithosis occur.

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.

Evidence for the presence of African swine fever virus in an endemic region of Western Kenya in the absence of any reported outbreak.

PubMed

Thomas, Lian F; Bishop, Richard P; Onzere, Cynthia; Mcintosh, Michael T; Lemire, Karissa A; de Glanville, William A; Cook, E Anne J; Fèvre, Eric M

2016-09-08

African swine fever (ASF), caused by African swine fever virus (ASFV), is a severe haemorrhagic disease of pigs, outbreaks of which can have a devastating impact upon commercial and small-holder pig production. Pig production in western Kenya is characterised by low-input, free-range systems practised by poor farmers keeping between two and ten pigs. These farmers are particularly vulnerable to the catastrophic loss of livestock assets experienced in an ASF outbreak. This study wished to expand our understanding of ASFV epidemiology during a period when no outbreaks were reported. Two hundred and seventy six whole blood samples were analysed using two independent conventional and real time PCR assays to detect ASFV. Despite no recorded outbreak of clinical ASF during this time, virus was detected in 90/277 samples analysed by conventional PCR and 142/209 samples analysed by qPCR. Genotyping of a sub-set of these samples indicated that the viruses associated with the positive samples were classified within genotype IX and that these strains were therefore genetically similar to the virus associated with the 2006/2007 ASF outbreaks in Kenya. The detection of ASFV viral DNA in a relatively high number of pigs delivered for slaughter during a period with no reported outbreaks provides support for two hypotheses, which are not mutually exclusive: (1) that virus prevalence may be over-estimated by slaughter-slab sampling, relative to that prevailing in the wider pig population; (2) that sub-clinical, chronically infected or recovered pigs may be responsible for persistence of the virus in endemic areas.

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.

The use of a geographic information system to identify a dairy goat farm as the most likely source of an urban Q-fever outbreak.

PubMed

Schimmer, Barbara; Ter Schegget, Ronald; Wegdam, Marjolijn; Züchner, Lothar; de Bruin, Arnout; Schneeberger, Peter M; Veenstra, Thijs; Vellema, Piet; van der Hoek, Wim

2010-03-16

A Q-fever outbreak occurred in an urban area in the south of the Netherlands in May 2008. The distribution and timing of cases suggested a common source. We studied the spatial relationship between the residence locations of human cases and nearby small ruminant farms, of which one dairy goat farm had experienced abortions due to Q-fever since mid April 2008. A generic geographic information system (GIS) was used to develop a method for source detection in the still evolving major epidemic of Q-fever in the Netherlands. All notified Q-fever cases in the area were interviewed. Postal codes of cases and of small ruminant farms (size >40 animals) located within 5 kilometres of the cluster area were geo-referenced as point locations in a GIS-model. For each farm, attack rates and relative risks were calculated for 5 concentric zones adding 1 kilometre at a time, using the 5-10 kilometres zone as reference. These data were linked to the results of veterinary investigations. Persons living within 2 kilometres of an affected dairy goat farm (>400 animals) had a much higher risk for Q-fever than those living more than 5 kilometres away (Relative risk 31.1 [95% CI 16.4-59.1]). The study supported the hypothesis that a single dairy goat farm was the source of the human outbreak. GIS-based attack rate analysis is a promising tool for source detection in outbreaks of human Q-fever.

Epidemiology and detection as options for control of viral and parasitic foodborne disease.

PubMed Central

Jaykus, L. A.

1997-01-01

Human enteric viruses and protozoal parasites are important causes of emerging food and waterborne disease. Epidemiologic investigation and detection of the agents in clinical, food, and water specimens, which are traditionally used to establish the cause of disease outbreaks, are either cumbersome, expensive, and frequently unavailable or unattempted for the important food and waterborne enteric viruses and protozoa. However, the recent introduction of regulatory testing mandates, alternative testing strategies, and increased epidemiologic surveillance for food and waterborne disease should significantly improve the ability to detect and control these agents. We discuss new methods of investigating foodborne viral and parasitic disease and the future of these methods in recognizing, identifying, and controlling disease agents. PMID:9366607

Statistical monitoring of the hand, foot and mouth disease in China.

PubMed

Zhang, Jingnan; Kang, Yicheng; Yang, Yang; Qiu, Peihua

2015-09-01

In a period starting around 2007, the Hand, Foot, and Mouth Disease (HFMD) became wide-spreading in China, and the Chinese public health was seriously threatened. To prevent the outbreak of infectious diseases like HFMD, effective disease surveillance systems would be especially helpful to give signals of disease outbreaks as early as possible. Statistical process control (SPC) charts provide a major statistical tool in industrial quality control for detecting product defectives in a timely manner. In recent years, SPC charts have been used for disease surveillance. However, disease surveillance data often have much more complicated structures, compared to the data collected from industrial production lines. Major challenges, including lack of in-control data, complex seasonal effects, and spatio-temporal correlations, make the surveillance data difficult to handle. In this article, we propose a three-step procedure for analyzing disease surveillance data, and our procedure is demonstrated using the HFMD data collected during 2008-2009 in China. Our method uses nonparametric longitudinal data and time series analysis methods to eliminate the possible impact of seasonality and temporal correlation before the disease incidence data are sequentially monitored by a SPC chart. At both national and provincial levels, our proposed method can effectively detect the increasing trend of disease incidence rate before the disease becomes wide-spreading. © 2015, The International Biometric Society.

Spatio-temporal scan statistics for the detection of outbreaks involving common molecular subtypes: using human cases of Escherichia coli O157:H7 provincial PFGE pattern 8 (National Designation ECXAI.0001) in Alberta as an example.

PubMed

So, H C; Pearl, D L; von Königslöw, T; Louie, M; Chui, L; Svenson, L W

2013-08-01

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed-field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space-time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space-time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space-time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space-time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern. © 2012 Blackwell Verlag GmbH.

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

PubMed

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

2009-11-01

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

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

PubMed

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

2016-12-30

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

Legionnaires' disease from a cooling tower in a community outbreak in Lidköping, Sweden- epidemiological, environmental and microbiological investigation supported by meteorological modelling.

PubMed

Ulleryd, Peter; Hugosson, Anna; Allestam, Görel; Bernander, Sverker; Claesson, Berndt E B; Eilertz, Ingrid; Hagaeus, Anne-Christine; Hjorth, Martin; Johansson, Agneta; de Jong, Birgitta; Lindqvist, Anna; Nolskog, Peter; Svensson, Nils

2012-11-21

An outbreak of Legionnaires' Disease took place in the Swedish town Lidköping on Lake Vänern in August 2004 and the number of pneumonia cases at the local hospital increased markedly. As soon as the first patients were diagnosed, health care providers were informed and an outbreak investigation was launched. Classical epidemiological investigation, diagnostic tests, environmental analyses, epidemiological typing and meteorological methods. Thirty-two cases were found. The median age was 62 years (range 36 - 88) and 22 (69%) were males. No common indoor exposure was found. Legionella pneumophila serogroup 1 was found at two industries, each with two cooling towers. In one cooling tower exceptionally high concentrations, 1.2 × 109 cfu/L, were found. Smaller amounts were also found in the other tower of the first industry and in one tower of the second plant. Sero- and genotyping of isolated L. pneumophila serogroup 1 from three patients and epidemiologically suspected environmental strains supported the cooling tower with the high concentration as the source. In all, two L. pneumophila strains were isolated from three culture confirmed cases and both these strains were detected in the cooling tower, but one strain in another cooling tower as well. Meteorological modelling demonstrated probable spread from the most suspected cooling tower towards the town centre and the precise location of four cases that were stray visitors to Lidköping. Classical epidemiological, environmental and microbiological investigation of an LD outbreak can be supported by meteorological modelling methods.The broad competence and cooperation capabilities in the investigation team from different authorities were of paramount importance in stopping this outbreak.

Extraction of Trypanosoma cruzi DNA from food: a contribution to the elucidation of acute Chagas disease outbreaks.

PubMed

Ferreira, Renata Trotta Barroso; Melandre, Aline Martins; Cabral, Maria Luiza; Branquinho, Maria Regina; Cardarelli-Leite, Paola

2016-04-01

Before 2004, the occurrence of acute Chagas disease (ACD) by oral transmission associated with food was scarcely known or investigated. Originally sporadic and circumstantial, ACD occurrences have now become frequent in the Amazon region, with recently related outbreaks spreading to several Brazilian states. These cases are associated with the consumption of açai juice by waste reservoir animals or insect vectors infected with Trypanosoma cruzi in endemic areas. Although guidelines for processing the fruit to minimize contamination through microorganisms and parasites exist, açai-based products must be assessed for quality, for which the demand for appropriate methodologies must be met. Dilutions ranging from 5 to 1,000 T. cruzi CL Brener cells were mixed with 2mL of acai juice. Four Extraction of T. cruzi DNA methods were used on the fruit, and the cetyltrimethyl ammonium bromide (CTAB) method was selected according to JRC, 2005. DNA extraction by the CTAB method yielded satisfactory results with regard to purity and concentration for use in PCR. Overall, the methods employed proved that not only extraction efficiency but also high sensitivity in amplification was important. The method for T. cruzi detection in food is a powerful tool in the epidemiological investigation of outbreaks as it turns epidemiological evidence into supporting data that serve to confirm T. cruzi infection in the foods. It also facilitates food quality control and assessment of good manufacturing practices involving acai-based products.

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

Community-wide outbreak of haemolytic uraemic syndrome associated with Shiga toxin 2-producing Escherichia coli O26:H11 in southern Italy, summer 2013

PubMed Central

Germinario, Cinzia; Caprioli, Alfredo; Giordano, Mario; Chironna, Maria; Gallone, Maria Serena; Tafuri, Silvio; Minelli, Fabio; Maugliani, Antonella; Michelacci, Valeria; Santangelo, Luisa; Mongelli, Onofrio; Montagna, Cosimo; Scavia, Gaia

2016-01-01

In summer 2013, an excess of paediatric cases of haemolytic uraemic syndrome (HUS) in a southern region of Italy prompted the investigation of a community-wide outbreak of Shiga toxin 2-producing Escherichia coli (STEC) O26:H11 infections. Case finding was based on testing patients with HUS or bloody diarrhoea for STEC infection by microbiological and serological methods. A case–control study was conducted to identify the source of the outbreak. STEC O26 infection was identified in 20 children (median age 17 months) with HUS, two of whom reported severe neurological sequelae. No cases in adults were detected. Molecular typing showed that two distinct STEC O26:H11 strains were involved. The case–control study showed an association between STEC O26 infection and consumption of dairy products from two local plants, but not with specific ready-to-eat products. E.coli O26:H11 strains lacking the stx genes were isolated from bulk milk and curd samples, but their PFGE profiles did not match those of the outbreak isolates. This outbreak supports the view that infections with Stx2-producing E. coli O26 in children have a high probability of progressing to HUS and represent an emerging public health problem in Europe. PMID:27684204

Community-wide outbreak of haemolytic uraemic syndrome associated with Shiga toxin 2-producing Escherichia coli O26:H11 in southern Italy, summer 2013.

PubMed

Germinario, Cinzia; Caprioli, Alfredo; Giordano, Mario; Chironna, Maria; Gallone, Maria Serena; Tafuri, Silvio; Minelli, Fabio; Maugliani, Antonella; Michelacci, Valeria; Santangelo, Luisa; Mongelli, Onofrio; Montagna, Cosimo; Scavia, Gaia

2016-09-22

In summer 2013, an excess of paediatric cases of haemolytic uraemic syndrome (HUS) in a southern region of Italy prompted the investigation of a community-wide outbreak of Shiga toxin 2-producing Escherichia coli (STEC) O26:H11 infections. Case finding was based on testing patients with HUS or bloody diarrhoea for STEC infection by microbiological and serological methods. A case-control study was conducted to identify the source of the outbreak. STEC O26 infection was identified in 20 children (median age 17 months) with HUS, two of whom reported severe neurological sequelae. No cases in adults were detected. Molecular typing showed that two distinct STEC O26:H11 strains were involved. The case-control study showed an association between STEC O26 infection and consumption of dairy products from two local plants, but not with specific ready-to-eat products. E.coli O26:H11 strains lacking the stx genes were isolated from bulk milk and curd samples, but their PFGE profiles did not match those of the outbreak isolates. This outbreak supports the view that infections with Stx2-producing E. coli O26 in children have a high probability of progressing to HUS and represent an emerging public health problem in Europe. This article is copyright of The Authors, 2016.

An outbreak of endophthalmitis after extracapsular cataract surgery probably caused by endotoxin contaminated distilled water used to dissolve acetylcholine

PubMed Central

Boks, T; van Dissel, J T; Teterissa, N; Ros, F; Mahmut, M H; Utama, E D; Rol, M; van Asdonk, P; Airiani, S; van Meurs, J C

2006-01-01

Aim To study possible causes of an outbreak of severe endophthalmitis after planned extracapsular cataract surgery in Medan, Indonesia. Methods In a 3 week period in November 2001, 17 of 43 patients developed signs of endophthalmitis after planned extracapsular cataract surgery. A search for possible causes was undertaken 4 months later. Results In autoclaved stored distilled water used to dissolve acetylcholine (used in 16 of 17 patients with endophthalmitis) a high amount of endotoxin was detected in a human blood essay, as well as a small number of non‐typeable Pseudomonas spp. Conclusions These findings suggest that distilled water used as solvent for acetylcholine was responsible for this outbreak of endophthalmitis. As a consequence, we now rely on solvents that are regularly checked for impurities such as an intravenous infusion fluid, rather than on vials with distilled water that is presumed to be sterile and kept for some time. PMID:16687451

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

[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.

Accuracy of Diagnostic Methods and Surveillance Sensitivity for Human Enterovirus, South Korea, 1999–2011

PubMed Central

Hyeon, Ji-Yeon; Hwang, Seoyeon; Kim, Hyejin; Song, Jaehyoung; Ahn, Jeongbae; Kang, Byunghak; Kim, Kisoon; Choi, Wooyoung; Chung, Jae Keun; Kim, Cheon-Hyun; Cho, Kyungsoon; Jee, Youngmee; Kim, Jonghyun; Kim, Kisang; Kim, Sun-Hee; Kim, Min-Ji

2013-01-01

The epidemiology of enteroviral infection in South Korea during 1999–2011 chronicles nationwide outbreaks and changing detection and subtyping methods used over the 13-year period. Of 14,657 patients whose samples were tested, 4,762 (32.5%) samples were positive for human enterovirus (human EV); as diagnostic methods improved, the rate of positive results increased. A seasonal trend of outbreaks was documented. Genotypes enterovirus 71, echovirus 30, coxsackievirus B5, enterovirus 6, and coxsackievirus B2 were the most common genotypes identified. Accurate test results correlated clinical syndromes to enterovirus genotypes: aseptic meningitis to echovirus 30, enterovirus 6, and coxsackievirus B5; hand, foot and mouth disease to coxsackievirus A16; and hand, foot and mouth disease with neurologic complications to enterovirus 71. There are currently no treatments specific to human EV infections; surveillance of enterovirus infections such as this study provides may assist with evaluating the need to research and develop treatments for infections caused by virulent human EV genotypes. PMID:23876671

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.

Evaluation of a multiplex real-time PCR method for detecting Shiga toxin-producing Escherichia coli in beef and comparison to the FSIS microbiology laboratory guidebook method

USDA-ARS?s Scientific Manuscript database

The “top-six” non-O157 STEC (O26, O45, O103, O111, O121, and O145) most frequently associated with outbreaks and cases of food-borne illnesses have been declared as adulterants in beef by the USDA Food Safety and Inspection Service (FSIS), and regulatory testing for these serogroups in beef began in...

An improved method to simultaneously detect Salmonella enteritidis, Escherichia coli O157 and Listeria monocytogenes in ground black pepper using multiplex real-time PCR

USDA-ARS?s Scientific Manuscript database

Introduction: The three common foodborne pathogens implicated in foodborne outbreaks are Salmonella spp., Escherichia coli O157:H7 and Listeria monocytogenes. Hence, it is important to identify these pathogens in contaminated foods so that they can be eliminated from the marketplace. At present, the...

Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery

Treesearch

Arjan J. H. Meddens; Jeffrey A. Hicke; Lee A. Vierling; Andrew T. Hudak

2013-01-01

Bark beetles cause significant tree mortality in coniferous forests across North America. Mapping beetle-caused tree mortality is therefore important for gauging impacts to forest ecosystems and assessing trends. Remote sensing offers the potential for accurate, repeatable estimates of tree mortality in outbreak areas. With the advancement of multi-temporal disturbance...

Method selection and adaptation for distributed monitoring of infectious diseases for syndromic surveillance.

PubMed

Xing, Jian; Burkom, Howard; Tokars, Jerome

2011-12-01

Automated surveillance systems require statistical methods to recognize increases in visit counts that might indicate an outbreak. In prior work we presented methods to enhance the sensitivity of C2, a commonly used time series method. In this study, we compared the enhanced C2 method with five regression models. We used emergency department chief complaint data from US CDC BioSense surveillance system, aggregated by city (total of 206 hospitals, 16 cities) during 5/2008-4/2009. Data for six syndromes (asthma, gastrointestinal, nausea and vomiting, rash, respiratory, and influenza-like illness) was used and was stratified by mean count (1-19, 20-49, ≥50 per day) into 14 syndrome-count categories. We compared the sensitivity for detecting single-day artificially-added increases in syndrome counts. Four modifications of the C2 time series method, and five regression models (two linear and three Poisson), were tested. A constant alert rate of 1% was used for all methods. Among the regression models tested, we found that a Poisson model controlling for the logarithm of total visits (i.e., visits both meeting and not meeting a syndrome definition), day of week, and 14-day time period was best. Among 14 syndrome-count categories, time series and regression methods produced approximately the same sensitivity (<5% difference) in 6; in six categories, the regression method had higher sensitivity (range 6-14% improvement), and in two categories the time series method had higher sensitivity. When automated data are aggregated to the city level, a Poisson regression model that controls for total visits produces the best overall sensitivity for detecting artificially added visit counts. This improvement was achieved without increasing the alert rate, which was held constant at 1% for all methods. These findings will improve our ability to detect outbreaks in automated surveillance system data. Published by Elsevier Inc.

Interagency Coordination in the Case of an Intentional Agroterrorist Incident

DTIC Science & Technology

2009-05-11

and working groups; development of a National Veterinary Stockpile of vaccines needed to respond to animal diseases; and funding of research...outbreak or an intentional incident. They include lack of personnel able to recognize a foreign animal disease outbreak, difficulty with vaccination and... vaccination stockpiling, and difficulty detecting a covert attack and differentiating it from a natural outbreak with the current surveillance and

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

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.

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

PubMed

Heymann, D L; Rodier, G R

2001-12-01

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

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

PubMed

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

2009-12-01

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

Assessment of air sampling methods and size distribution of virus-laden aerosols in outbreaks in swine and poultry farms.

PubMed

Alonso, Carmen; Raynor, Peter C; Goyal, Sagar; Olson, Bernard A; Alba, Anna; Davies, Peter R; Torremorell, Montserrat

2017-05-01

Swine and poultry viruses, such as porcine reproductive and respiratory syndrome virus (PRRSV), porcine epidemic diarrhea virus (PEDV), and highly pathogenic avian influenza virus (HPAIV), are economically important pathogens that can spread via aerosols. The reliability of methods for quantifying particle-associated viruses as well as the size distribution of aerosolized particles bearing these viruses under field conditions are not well documented. We compared the performance of 2 size-differentiating air samplers in disease outbreaks that occurred in swine and poultry facilities. Both air samplers allowed quantification of particles by size, and measured concentrations of PRRSV, PEDV, and HPAIV stratified by particle size both within and outside swine and poultry facilities. All 3 viruses were detectable in association with aerosolized particles. Proportions of positive sampling events were 69% for PEDV, 61% for HPAIV, and 8% for PRRSV. The highest virus concentrations were found with PEDV, followed by HPAIV and PRRSV. Both air collectors performed equally for the detection of total virus concentration. For all 3 viruses, higher numbers of RNA copies were associated with larger particles; however, a bimodal distribution of particles was observed in the case of PEDV and HPAIV.

A local outbreak of dengue caused by an imported case in Dongguan China

PubMed Central

2012-01-01

Background Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions around the world. Since the first occurrence of dengue was confirmed in Guangdong, China in 1978, dengue outbreaks have been reported sequentially in different provinces in South China transmitted by.peridomestic Ae. albopictus mosquitoes, diplaying Ae. aegypti, a fully domestic vector that transmits dengue worldwide. Rapid and uncontrolled urbanization is a characteristic change in developing countries, which impacts greatly on vector habitat, human lifestyle and transmission dynamics on dengue epidemics. In September 2010, an outbreak of dengue was detected in Dongguan, a city in Guangdong province characterized by its fast urbanization. An investigation was initiated to identify the cause, to describe the epidemical characteristics of the outbreak, and to implement control measures to stop the outbreak. This is the first report of dengue outbreak in Dongguan, even though dengue cases were documented before in this city. Methods Epidemiological data were obtained from local Center of Disease Control and prevention (CDC). Laboratory tests such as real-time Reverse Transcription Polymerase Chain Reaction (RT-PCR), the virus cDNA sequencing, and Enzyme-Linked immunosorbent assay (ELISA) were employed to identify the virus infection and molecular phylogenetic analysis was performed with MEGA5. The febrile cases were reported every day by the fever surveillance system. Vector control measures including insecticidal fogging and elimination of habitats of Ae. albopictus were used to control the dengue outbreak. Results The epidemiological studies results showed that this dengue outbreak was initiated by an imported case from Southeast Asia. The outbreak was characterized by 31 cases reported with an attack rate of 50.63 out of a population of 100,000. Ae. albopictus was the only vector species responsible for the outbreak. The virus cDNA sequencing analysis showed that the virus responsible for the outbreak was Dengue Virus serotype-1 (DENV-1). Conclusions Several characterized points of urbanization contributed to this outbreak of dengue in Dongguan: the residents are highly concentrated; the residents' life habits helped to form the habitats of Ae. albopictus and contributed to the high Breteau Index; the self-constructed houses lacks of mosquito prevention facilities. This report has reaffirmed the importance of a surveillance system for infectious diseases control and aroused the awareness of an imported case causing the epidemic of an infectious disease in urbanized region. PMID:22276682

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.

PubMed

Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R

2013-01-01

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

An evaluation of asymptomatic Dengue infections among blood donors during the 2014 Dengue outbreak in Guangzhou, China.

PubMed

Liao, Qiao; Shan, Zhengang; Wang, Min; Huang, Jieting; Xu, Ru; Huang, Ke; Tang, Xi; Zhang, Weiyun; Nelson, Kenrad; Li, Chengyao; Fu, Yongshui; Rong, Xia

2017-11-01

In 2014, an outbreak of dengue virus (DENV) infection led to 45 171 clinical cases diagnosed in Guangdong province, Southern China. However, the potential risk of blood donors asymptomatically infected with DENV has not been evaluated . In the current study we detected anti-DENV IgG antibody and RNA in volunteer Chinese blood donors. We found that anti-DENV IgG antibody was positively detected in 3.4% (51/1500) and two donors were detected as being DENV RNA positive out of 3000 blood samples. We concluded that the presence of potential DENV in blood donors might be potential risk for blood safety. Therefore, screening for DENV infection should be considered in blood donations during a period of dengue outbreak in high epidemic area of China. © 2017 Wiley Periodicals, Inc.

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

Molecular Subtyping to Detect Human Listeriosis Clusters

PubMed Central

Sauders, Brian D.; Fortes, Esther D.; Morse, Dale L.; Dumas, Nellie; Kiehlbauch, Julia A.; Schukken, Ynte; Hibbs, Jonathan R.

2003-01-01

We analyzed the diversity (Simpson’s Index, D) and distribution of Listeria monocytogenes in human listeriosis cases in New York State (excluding New York City) from November 1996 to June 2000 by using automated ribotyping and pulsed-field gel electrophoresis (PFGE). We applied a scan statistic (p<0.05) to detect listeriosis clusters caused by a specific Listeria monocytogenes subtype. Of 131 human isolates, 34 (D=0.923) ribotypes and 74 (D=0.975) PFGE types were found. Nine (31% of cases) clusters were identified by ribotype or PFGE; five (18% of cases) clusters were identified by using both methods. Two of the nine clusters (13% of cases) identified corresponded with investigated multistate listeriosis outbreaks. While most human listeriosis cases are considered sporadic, highly discriminatory molecular subtyping approaches thus indicated that 13% to 31% of cases reported in New York State may represent single-source clusters. Listeriosis control and reduction efforts should include broad-based subtyping of human isolates and consider that a large number of cases may represent outbreaks. PMID:12781006

Multinational outbreak of Salmonella Enteritidis infection during an international youth ice hockey competition in Riga, Latvia, preliminary report, March and April 2015.

PubMed

Pesola, A K; Parn, T; Huusko, S; Perevosčikovs, J; Ollgren, J; Salmenlinna, S; Lienemann, T; Gossner, C; Danielsson, N; Rimhanen-Finne, R

2015-05-21

A multinational outbreak of salmonellosis linked to the Riga Cup 2015 junior ice-hockey competition was detected by the Finnish health authorities in mid-April and immediately notified at the European Union level. This prompted an international outbreak investigation supported by the European Centre for Disease Prevention and Control. As of 8 May 2015, seven countries have reported 214 confirmed and suspected cases, among which 122 from Finland. The search for the source of the outbreak is ongoing.

Enabling analytical and Modeling Tools for Enhanced Disease Surveillance

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

Dawn K. Manley

2003-04-01

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

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

PubMed

Walsh, Aaron M; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C; Arthur, Cornelius T; Claesson, Marcus J; Scott, Karen P; Cotter, Paul D

2017-08-15

The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. Copyright © 2017 American Society for Microbiology.

Characterization of Viral Load, Viability and Persistence of Influenza A Virus in Air and on Surfaces of Swine Production Facilities.

PubMed

Neira, Victor; Rabinowitz, Peter; Rendahl, Aaron; Paccha, Blanca; Gibbs, Shawn G; Torremorell, Montserrat

2016-01-01

Indirect transmission of influenza A virus (IAV) in swine is poorly understood and information is lacking on levels of environmental exposure encountered by swine and people during outbreaks of IAV in swine barns. We characterized viral load, viability and persistence of IAV in air and on surfaces during outbreaks in swine barns. IAV was detected in pigs, air and surfaces from five confirmed outbreaks with 48% (47/98) of oral fluid, 38% (32/84) of pen railing and 43% (35/82) of indoor air samples testing positive by IAV RT-PCR. IAV was isolated from air and oral fluids yielding a mixture of subtypes (H1N1, H1N2 and H3N2). Detection of IAV RNA from air was sustained during the outbreaks with maximum levels estimated between 7 and 11 days from reported onset. Our results indicate that during outbreaks of IAV in swine, aerosols and surfaces in barns contain significant levels of IAV potentially representing an exposure hazard to both swine and people.

Imported dengue from 2013 Angola outbreak: Not just serotype 1 was detected.

PubMed

Abreu, Cândida; Silva-Pinto, André; Lazzara, Daniela; Sobrinho-Simões, Joana; Guimarães, João Tiago; Sarmento, António

2016-06-01

All the reports from Angola's 2013 dengue outbreak revealed serotype 1. However, previously dengue serotypes 1-4 have been reported in Africa and in 2014 serotype 4 was reported in Angola. To report dengue serotypes in patients returning from Angola during 2013 outbreak. Retrospective, cross-sectional study. We serotyped the dengue by an in house Polymerase Chain Reaction technique in randomly selected cases. From the 2013 Angola's dengue outbreak we treated 47 adult patients. None had history of past dengue. A combo kit test for dengue revealed positive NS1 antigen in 39 and IgM antibodies in 8. From 17 randomly patients tested by RNA Real Time-PCR, 11 were positive: 7 for DENV-1, 2 for DENV-2, 1 for DENV-3 (co-infected with DENV-1) and 1 for DENV-4. None had a complicated or fatal evolution. Unlike previous reports the 4 serotypes were detected, and this resulted in a different epidemiological situation, raising the risk of future outbreaks of severe dengue. Copyright © 2016 Elsevier B.V. All rights reserved.

Echovirus 30 meningitis epidemic followed by an outbreak-specific RT-qPCR.

PubMed

Österback, Riikka; Kalliokoski, Teemu; Lähdesmäki, Tuire; Peltola, Ville; Ruuskanen, Olli; Waris, Matti

2015-08-01

An outbreak of enteroviral aseptic meningitis emerged in Southwestern Finland in August 2009. The same enterovirus reappeared with increasing incidence of meningitis in other parts of Finland in 2010. To identify the incidence and molecular epidemiology of enteroviral meningitis outbreak. The causative agent was identified as echovirus 30 (E-30) by sequencing partial viral protein 1 capsid genome, and a virus type-specific RT-qPCR was set up for sensitive detection of the virus in cerebrospinal fluid specimens. Enterovirus positive CSF specimens were subjected to the E-30-specific assay to investigate this unusual occurrence of aseptic meningitis and facilitate case confirmation during the outbreaks between August 2009 and September 2010. E-30 was detected in 106 (72%) enterovirus positive cerebrospinal fluid specimens. All the meningitis cases in 2009 and most of them in 2010 were among adolescents and several were members of sport teams. Between August 2009 and September 2010, E-30 caused an extensive outbreak with two peaks in Finland. Type-specific RT-PCR allowed rapid diagnostic follow-up of the epidemic. Copyright © 2015 Elsevier B.V. All rights reserved.

Mild Illness during Outbreak of Shiga Toxin-Producing Escherichia coli O157 Infections Associated with Agricultural Show, Australia.

PubMed

Vasant, Bhakti R; Stafford, Russell J; Jennison, Amy V; Bennett, Sonya M; Bell, Robert J; Doyle, Christine J; Young, Jeannette R; Vlack, Susan A; Titmus, Paul; El Saadi, Debra; Jarvinen, Kari A J; Coward, Patricia; Barrett, Janine; Staples, Megan; Graham, Rikki M A; Smith, Helen V; Lambert, Stephen B

2017-10-01

During a large outbreak of Shiga toxin-producing Escherichia coli illness associated with an agricultural show in Australia, we used whole-genome sequencing to detect an IS1203v insertion in the Shiga toxin 2c subunit A gene of Shiga toxin-producing E. coli. Our study showed that clinical illness was mild, and hemolytic uremic syndrome was not detected.

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...

Subtyping of Canadian isolates of Salmonella Enteritidis using Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) alone and in combination with Pulsed-Field Gel Electrophoresis (PFGE) and phage typing.

PubMed

Ziebell, Kim; Chui, Linda; King, Robin; Johnson, Suzanne; Boerlin, Patrick; Johnson, Roger P

2017-08-01

Salmonella enterica subspecies enterica serovar Enteritidis (SE) is one of the most common causes of human salmonellosis and in Canada currently accounts for over 40% of human cases. Reliable subtyping of isolates is required for outbreak detection and source attribution. However, Pulsed-Field Gel Electrophoresis (PFGE), the current standard subtyping method for Salmonella spp., is compromised by the high genetic homogeneity of SE. Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) was introduced to supplement PFGE, although there is a lack of data on the ability of MLVA to subtype Canadian isolates of SE. Three subtyping methods, PFGE, MLVA and phage typing were compared for their discriminatory power when applied to three panels of Canadian SE isolates: Panel 1: 70 isolates representing the diversity of phage types (PTs) and PFGE subtypes within these PTs; Panel 2: 214 apparently unrelated SE isolates of the most common PTs; and Panel 3: 27 isolates from 10 groups of epidemiologically related strains. For Panel 2 isolates, four MLVA subtypes were shared among 74% of unrelated isolates and in Panel 3 isolates, one MLVA subtype accounted for 62% of the isolates. For all panels, combining results from PFGE, MLVA and PT gave the best discrimination, except in Panel 1, where the combination of PT and PFGE was equally as high, due to the selection criteria for this panel. However, none of these methods is sufficiently discriminatory alone for reliable outbreak detection or source attribution, and must be applied together to achieve sufficient discrimination for practical purposes. Even then, some large clusters were not differentiated adequately. More discriminatory methods are required for reliable subtyping of this genetically highly homogeneous serovar. This need will likely be met by whole genome sequence analysis given the recent promising reports and as more laboratories implement this tool for outbreak response and surveillance. Copyright © 2017 Elsevier B.V. All rights reserved.

Protective effect of inactivated hepatitis A vaccine against the outbreak of hepatitis A in an open rural community

PubMed Central

Shen, Yue-Gen; Gu, Xie-Jun; Zhou, Jian-Hong

2008-01-01

AIM: To evaluate the protective effect of inactivated hepatitis A vaccine (Healive®) against hepatitis A outbreak in an emergency vaccination campaign. METHODS: During an outbreak of hepatitis A in Honghe Town, Xiuzhou District, Jiaxing City, Zhejiang Province, two nonrandomized controlled trials were conducted in September 2006. The first trial was to vaccinate 108 anti-HAV negative individuals with close contacts of the patients from September with 1 dose of an inactivated hepatitis A vaccine, Healive®. The control group comprised of 115 individuals with close contacts of the patients before September. The second trial was to vaccinate 3365 primary and secondary school students who volunteered to receive a dose of Healive® and 2572 students who did not receive Healive® serving as its controls. An epidemiological survey was conducted to evaluate the protective efficacy of the vaccine. RESULTS: A total of 136 hepatitis A cases were reported during an outbreak that started in June, peaked in August and September, and ended after December of 2006. After a massive vaccination of school children in September, the number of cases declined significantly. No hepatitis A was detected in the 108 vaccinated individuals with close contacts of patients, whereas 4 cases of hepatitis A were found in the controls. The infection rate of hepatitis A was not significantly different in the individuals with close contacts of patients whether or not they received the vaccine (P = 0.122). No hepatitis A was detected in the 3365 students who received the vaccine, four cases of hepatitis A were found in the controls. The infection rate of students with or without vaccination was significantly different in the students who received the vaccine (0/3365 vs 4/2572, P = 0.035). The protective efficacy of the vaccine was 100%. CONCLUSION: Inactivated hepatitis A vaccine demonstrates a good protective effect against an outbreak of hepatitis A. PMID:18461664

Utilizing qualitative methods in survey design: examining Texas cattle producers' intent to participate in foot-and-mouth disease detection and control.

PubMed

Delgado, Amy H; Norby, Bo; Dean, Wesley R; McIntosh, W Alex; Scott, H Morgan

2012-02-01

The effective control of an outbreak of a highly contagious disease such as foot-and-mouth disease (FMD) in the United States will require a strong partnership between the animal agriculture industry and the government. However, because of the diverse number of economic, social, and psychological influences affecting livestock producers, their complete cooperation during an outbreak may not be assured. We conducted interviews with 40 individuals involved in the Texas cattle industry in order to identify specific behaviors where producer participation or compliance may be reduced. Through qualitative analysis of these interviews, we identified specific factors which the participants suggested would influence producer behavior in regard to FMD detection and control. Using the Theory of Planned Behavior (TPB) as an initial guide, we developed an expanded theoretical framework in order to allow for the development of a questionnaire and further evaluation of the relative importance of the relationships indicated in the framework. A 2-day stakeholder workshop was used to develop and critique the final survey instruments. The behaviors which we identified where producer compliance may be reduced included requesting veterinary examination of cattle with clinical signs of FMD either before or during an outbreak of FMD, gathering and holding cattle at the date and time requested by veterinary authorities, and maintaining cattle in their current location during an outbreak of FMD. In addition, we identified additional factors which may influence producers' behavior including risk perception, trust in other producers and regulatory agencies, and moral norms. The theoretical frameworks presented in this paper can be used during an outbreak to assess barriers to and social pressures for producer compliance, prioritize the results in terms of their effects on behavior, and improve and better target risk communication strategies. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of an Improved U.S. Food and Drug Administration Method for the Detection of Cyclospora cayetanensis in Produce Using Real-Time PCR.

PubMed

Murphy, Helen R; Lee, Seulgi; da Silva, Alexandre J

2017-07-01

Cyclospora cayetanensis is a protozoan parasite that causes human diarrheal disease associated with the consumption of fresh produce or water contaminated with C. cayetanensis oocysts. In the United States, foodborne outbreaks of cyclosporiasis have been linked to various types of imported fresh produce, including cilantro and raspberries. An improved method was developed for identification of C. cayetanensis in produce at the U.S. Food and Drug Administration. The method relies on a 0.1% Alconox produce wash solution for efficient recovery of oocysts, a commercial kit for DNA template preparation, and an optimized TaqMan real-time PCR assay with an internal amplification control for molecular detection of the parasite. A single laboratory validation study was performed to assess the method's performance and compare the optimized TaqMan real-time PCR assay and a reference nested PCR assay by examining 128 samples. The samples consisted of 25 g of cilantro or 50 g of raspberries seeded with 0, 5, 10, or 200 C. cayetanensis oocysts. Detection rates for cilantro seeded with 5 and 10 oocysts were 50.0 and 87.5%, respectively, with the real-time PCR assay and 43.7 and 94.8%, respectively, with the nested PCR assay. Detection rates for raspberries seeded with 5 and 10 oocysts were 25.0 and 75.0%, respectively, with the real-time PCR assay and 18.8 and 68.8%, respectively, with the nested PCR assay. All unseeded samples were negative, and all samples seeded with 200 oocysts were positive. Detection rates using the two PCR methods were statistically similar, but the real-time PCR assay is less laborious and less prone to amplicon contamination and allows monitoring of amplification and analysis of results, making it more attractive to diagnostic testing laboratories. The improved sample preparation steps and the TaqMan real-time PCR assay provide a robust, streamlined, and rapid analytical procedure for surveillance, outbreak response, and regulatory testing of foods for detection of C. cayetanensis.

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

PubMed

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

2016-06-23

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

Chromosomal Rearrangements in Salmonella enterica Serotype Typhi Affecting Molecular Typing in Outbreak Investigations

PubMed Central

Echeita, M. A.; Usera, M. A.

1998-01-01

Salmonella enterica serotype Typhi strains belonging to eight different outbreaks of typhoid fever that occurred in Spain between 1989 and 1994 were analyzed by ribotyping and pulsed-field gel electrophoresis. For three outbreaks, two different patterns were detected for each outbreak. The partial digestion analysis by the intron-encoded endonuclease I-CeuI of the two different strains from each outbreak provided an excellent tool for examining the organization of the genomes of epidemiologically related strains. S. enterica serotype Typhi seems to be more susceptible than other serotypes to genetic rearrangements produced by homologous recombinations between rrn operons; these rearrangements do not substantially alter the stability or survival of the bacterium. We conclude that genetic rearrangements can occur during the emergence of an outbreak. PMID:9650981

Pseudo-Outbreak of Actinomyces graevenitzii Associated with Bronchoscopy

PubMed Central

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

2014-01-01

Outbreaks and pseudo-outbreaks of infection related to bronchoscopy typically involve Gram-negative bacteria, Mycobacterium species or Legionella species. We report an unusual bronchoscopy-related pseudo-outbreak due to Actinomyces graevenitzii. Extensive epidemiological and microbiological investigation failed to identify a common source. Strain typing revealed that the cluster was comprised of heterogeneous strains of A. graevenitzii. A change in laboratory procedures for Actinomyces cultures was coincident with the emergence of the pseudo-outbreak, and we determined that A. graevenitzii isolates more readily adopted a white, dry, molar tooth appearance on anaerobic colistin nalidixic acid (CNA) agar which likely facilitated its detection and identification in bronchoscopic specimens. This unusual pseudo-outbreak was related to frequent requests of bronchoscopists for Actinomyces cultures combined with a change in microbiology laboratory practices. PMID:25355767

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.

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.

Control Measures Used during Lymphogranuloma Venereum Outbreak, Europe

PubMed Central

Hulscher, Marlies E.J.L.; Vos, Dieuwke; van de Laar, Marita J.W.; Fenton, Kevin A.; van Steenbergen, Jim E.; van der Meer, Jos W.M.; Grol, Richard P.T.M.

2008-01-01

To assess the response to the reemergence of lymphogranuloma venereum, we conducted a cross-sectional survey by administering a structured questionnaire to representatives from 26 European countries. Responses were received from 18 countries. The ability to respond quickly and the measures used for outbreak detection and control varied. Evidence-based criteria were not consistently used to develop recommendations. We did not develop criteria to determine the effectiveness of the recommendations. The degree of preparedness for an unexpected outbreak, as well as the ability of countries to respond quickly to alerts, varied, which indicates weaknesses in the ability to control an outbreak. More guidance is needed to implement and evaluate control measures used during international outbreaks. PMID:18394274

Yellow Fever outbreak in Darfur, Sudan in October 2012; the initial outbreak investigation report.

PubMed

Soghaier, Mohammed A; Hagar, Ahmed; Abbas, Mohammed A; Elmangory, Mutasim M; Eltahir, Khalid M; Sall, Amadou A

2013-10-01

Sudan is subject to repeated outbreaks, including Viral Hemorrhagic Fever (VHF), which is considered to be a very serious illness. Yellow Fever (YF) outbreaks in Sudan have been reported from the 1940s through 2005. In 2012, a new outbreak of YF occurred in the Darfur region. To identify the potential for an outbreak, to diagnose the disease and to be able to recognize its cause among the initial reported cases. >This is a descriptive and investigative field study that applies standard communicable disease outbreak investigation steps. The study involved clinical, serological, entomological and environmental surveys. The field investigation confirmed the outbreak and identified its cause to be YF. National surveillance systems should be strong enough to detect VHFs in a timely manner. Local health facilities should be prepared to promptly treat the initial cases because the case fatality ratios (CFRs) are usually very high among the index cases. Copyright © 2013 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Two outbreaks of classical swine fever in wild boar in France.

PubMed

Pol, F; Rossi, S; Mesplède, A; Kuntz-Simon, G; Le Potier, M-F

2008-06-21

In 2002 and 2003, two successive outbreaks of classical swine fever were declared in wild boar in northern France. The first was in Moselle, near the town of Thionville and the border with Luxembourg, and the second was in the northern Vosges area, near the German border. The outbreaks were investigated by serological and virological diagnosis of dead or shot animals. Hunting restrictions were applied to limit the spread of the outbreaks. The virus was detected eight times between April and July 2002 in the Thionville area, an area well delimited by natural or artificial barriers such as rivers or highways. Cooperation between the authorities concerned was good, and hunting restrictions were applied for one year. No virus was detected after July 2002 and the Thionville outbreak was officially considered over in March 2005. In the northern Vosges the situation was different, with no barriers to animal movements, continuous forest, difficulties in establishing hunting restrictions in this huge area, and the circulation of the virus in Germany close to the frontier. Virus of a different strain from that isolated in the Thionville outbreak was still being isolated in the northern Vosges in 2004, and owing to the failure of the hunting restrictions, the French health authorities decided to vaccinate wild boar.

An outbreak of food poisoning due to egg yolk reaction-negative Staphylococcus aureus.

PubMed

Miwa, N; Kawamura, A; Masuda, T; Akiyama, M

2001-03-20

An outbreak of staphylococcal food poisoning due to an egg yolk (EY) reaction-negative strain occurred in Japan. Twenty-one of 53 dam construction workers who ate boxed lunches prepared at their company cafeteria became ill, and eight required hospital treatment. The outbreak showed a typical incubation time (1.5-4 h with a median time of 2.7 h) and symptoms (vomiting and diarrhea) of staphylococcal food poisoning. Staphylococcus aureus, which produces staphylococcal enterotoxin (SE) A, was isolated from four fecal specimens of eight patients tested. Scrambled egg in the boxed lunches contained 20-40 ng/g of SEA, and 3.0 x 10(9)/g of viable S. aureus cells that produced this toxin. All isolates from patients and the food were EY reaction-negative, coagulase type II, and showed the same restriction fragment length polymorphism (RFLP) pattern. We concluded that the outbreak was caused by scrambled egg contaminated with EY reaction-negative S. aureus. In Japan, outbreaks of staphylococcal food poisoning are mainly caused by EY reaction-positive S. aureus, and EY reaction-negative colonies grown on agar plates containing EY are usually not analyzed further for detection of S. aureus. The present outbreak suggested that EY reaction-negative isolates should be subjected to further analysis to detect the causative agents of staphylococcal food poisoning.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

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.

Biosensors for rapid and sensitive detection of Staphylococcus aureus in food.

PubMed

Rubab, Momna; Shahbaz, Hafiz Muhammad; Olaimat, Amin N; Oh, Deog-Hwan

2018-05-15

Foodborne illness outbreaks caused by the consumption of food contaminated with harmful bacteria has drastically increased in the past decades. Therefore, detection of harmful bacteria in the food has become an important factor for the recognition and prevention of problems associated with food safety and public health. Staphylococcus aureus is one of the most commonly isolated foodborne pathogen and it is considered as a major cause of foodborne illnesses worldwide. A number of different methods have been developed for the detection and identification of S. aureus in food samples. However, some of these methods are laborious and time-consuming and are not suitable for on-site applications. Therefore, it is highly important to develop rapid and more approachable detection methods. In the last decade, biosensors have gained popularity as an attractive alternative method and now considered as one of most rapid and on-site applicable methods. An overview of the biosensor based methods used for the detection of S. aureus is presented herein. This review focuses on the state-of-the-art biosensor methods towards the detection and quantification of S. aureus, and discusses the most commonly used biosensor methods based on the transducing mode, such as electrochemical, optical, and mass-based biosensors. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection of Salmonella enteritidis Using a Miniature Optical Surface Plasmon Resonance Biosensor

NASA Astrophysics Data System (ADS)

Son, J. R.; Kim, G.; Kothapalli, A.; Morgan, M. T.; Ess, D.

2007-04-01

The frequent outbreaks of foodborne illness demand rapid detection of foodborne pathogens. Unfortunately, conventional methods for pathogen detection and identification are labor-intensive and take days to complete. Biosensors have shown great potential for the rapid detection of foodborne pathogens. Surface plasmon resonance (SPR) sensors have been widely adapted as an analysis tool for the study of various biological binding reactions. SPR biosensors could detect antibody-antigen bindings on the sensor surface by measuring either a resonance angle or refractive index value. In this study, the feasibility of a miniature SPR sensor (Spreeta, TI, USA) for detection of Salmonella enteritidis has been evaluated. Anti-Salmonella antibodies were immobilized on the gold sensor surface by using neutravidin. Salmonella could be detected by the Spreeta biosensor at concentrations down to 105 cfu/ml.

Evaluation of DNA extraction methods for PCR-based detection of Listeria monocytogenes from vegetables.

PubMed

Vojkovska, H; Kubikova, I; Kralik, P

2015-03-01

Epidemiological data indicate that raw vegetables are associated with outbreaks of Listeria monocytogenes. Therefore, there is a demand for the availability of rapid and sensitive methods, such as PCR assays, for the detection and accurate discrimination of L. monocytogenes. However, the efficiency of PCR methods can be negatively affected by inhibitory compounds commonly found in vegetable matrices that may cause false-negative results. Therefore, the sample processing and DNA isolation steps must be carefully evaluated prior to the introduction of such methods into routine practice. In this study, we compared the ability of three column-based and four magnetic bead-based commercial DNA isolation kits to extract DNA of the model micro-organism L. monocytogenes from raw vegetables. The DNA isolation efficiency of all isolation kits was determined using a triplex real-time qPCR assay designed to specifically detect L. monocytogenes. The kit with best performance, the PowerSoil(™) Microbial DNA Isolation Kit, is suitable for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. Coupled with the triplex real-time qPCR assay, this DNA isolation kit is applicable to the samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. Several recent outbreaks of Listeria monocytogenes have been associated with the consumption of fruits and vegetables. Real-time PCR assays allow fast detection and accurate quantification of microbes. However, the success of real-time PCR is dependent on the success with which template DNA can be extracted. The results of this study suggest that the PowerSoil(™) Microbial DNA Isolation Kit can be used for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. This method is applicable to samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. © 2014 The Society for Applied Microbiology.

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

PubMed

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

2017-02-13

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

Environmental Survey of Drinking Water Sources in Kampala, Uganda, during a Typhoid Fever Outbreak

PubMed Central

Kahler, A. M.; Nansubuga, I.; Nanyunja, E. M.; Kaplan, B.; Jothikumar, N.; Routh, J.; Gómez, G. A.; Mintz, E. D.; Hill, V. R.

2017-01-01

ABSTRACT In 2015, a typhoid fever outbreak began in downtown Kampala, Uganda, and spread into adjacent districts. In response, an environmental survey of drinking water source types was conducted in areas of the city with high case numbers. A total of 122 samples was collected from 12 source types and tested for Escherichia coli, free chlorine, and conductivity. An additional 37 grab samples from seven source types and 16 paired large volume (20 liter) samples from wells and springs were also collected and tested for the presence of Salmonella enterica serovar Typhi. Escherichia coli was detected in 60% of kaveras (drinking water sold in plastic bags) and 80% of refilled water bottles; free chlorine was not detected in either source type. Most jerry cans (68%) contained E. coli and had free chlorine residuals below the WHO-recommended level of 0.5 mg/liter during outbreaks. Elevated conductivity readings for kaveras, refilled water bottles, and jerry cans (compared to treated surface water supplied by the water utility) suggested that they likely contained untreated groundwater. All unprotected springs and wells and more than 60% of protected springs contained E. coli. Water samples collected from the water utility were found to have acceptable free chlorine levels and no detectable E. coli. While S. Typhi was not detected in water samples, Salmonella spp. were detected in samples from two unprotected springs, one protected spring, and one refilled water bottle. These data provided clear evidence that unregulated vended water and groundwater represented a risk for typhoid transmission. IMPORTANCE Despite the high incidence of typhoid fever globally, relatively few outbreak investigations incorporate drinking water testing. During waterborne disease outbreaks, measurement of physical-chemical parameters, such as free chlorine residual and electrical conductivity, and of microbiological parameters, such as the presence of E. coli or the implicated etiologic agent, in drinking water samples can identify contaminated sources. This investigation indicated that unregulated vended water and groundwater sources were contaminated and were therefore a risk to consumers during the 2015 typhoid fever outbreak in Kampala. Identification of contaminated drinking water sources and sources that do not contain adequate disinfectant levels can lead to rapid targeted interventions. PMID:28970225

Search for Hepatitis A Viruses by New Methods

DTIC Science & Technology

1981-09-01

VII. Detection of HAV and Rotavirus In a Community Water Supply Following an Outbreak of Gastroenteritls and Infectious Hepatitis . . . 1* VUL...22). An "aliquot of each concentrate was further concentrated by ultracentrifugation to assay for HAV antigen and rotavirus . Samples were assayed for... rotavirus using an Indirect "immunofluorescence test (23) and for HAV antigen using a radloirmunoassay (24, 25). Ř. Table 9 shows the concentrations

Molecular and serological detection of Trypanosoma cruzi in dogs (Canis lupus familiaris) suggests potential transmission risk in areas of recent acute Chagas disease outbreaks in Colombia.

PubMed

Jaimes-Dueñez, Jeiczon; Triana-Chávez, Omar; Cantillo-Barraza, Omar; Hernández, Carolina; Ramírez, Juan David; Góngora-Orjuela, Agustín

2017-06-01

Chagas disease is a zoonotic infection widely distributed in tropical and subtropical regions of America, including more than 50% of the Colombian territory. In the last years, an increase of outbreaks of acute Chagas disease has been observed in the east of the country due to environmental changes and mammal movements toward human settlements. Given the importance of dogs (Canis lupus familiaris) as reservoir hosts and sentinels of Trypanosoma cruzi infection across different regions of America, in this study we reported a serological and molecular detection of T. cruzi infection in 242 dogs from an endemic area of Meta department (East of Colombia), with recent emergence of acute Chagas disease outbreaks. The distribution of T. cruzi infection in dogs was not homogeneous, ranging from 0-41.4% and 0-5.1% in different sampling sectors, through serological (ELISA/IFAT) and molecular methods (conventional and real time PCR), respectively. Statistical analysis indicated that dog infection was associated with specific sampling sectors. Our results show a moderate seroprevalence of infection and active circulation of T. cruzi in dogs from this zone, which suggest areas with potential risk of infection to human that must be taken into consideration when Chagas disease control programs need to be implemented. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

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

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.

1978-01-01

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Rapid detection of Listeria monocytogenes in raw milk and soft cheese by a redox potential measurement based method combined with real-time PCR.

PubMed

Erdősi, Orsolya; Szakmár, Katalin; Reichart, Olivér; Szili, Zsuzsanna; László, Noémi; Székely Körmöczy, Péter; Laczay, Péter

2014-09-01

The incidence of outbreaks of foodborne listeriosis has indicated the need for a reliable and rapid detection of the microbe in different foodstuffs. A method combining redox potential measurement and real-time polymerase chain reaction (PCR) was developed to detect Listeria monocytogenes in artificially contaminated raw milk and soft cheese. Food samples of 25 g or 25 ml were homogenised in 225 ml of Listeria Enrichment Broth (LEB) with Oxford supplement, and the redox potential measurement technique was applied. For Listeria species the measuring time was maximum 34 h. The absence of L. monocytogenes could reliably be proven by the redox potential measurement method, but Listeria innocua and Bacillus subtilis could not be differentiated from L. monocytogenes on the basis of the redox curves. The presence of L. monocytogenes had to be confirmed by real-time PCR. The combination of these two methods proved to detect < 10 cfu/g of L. monocytogenes in a cost- and time-effective manner. This method can potentially be used as an alternative to the standard nutrient method for the rapid detection of L. monocytogenes in food.

Cost of dengue outbreaks: literature review and country case studies

PubMed Central

2013-01-01

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

Investigation of Swedish cases reveals an outbreak of cryptosporidiosis at a Norwegian hotel with possible links to in-house water systems

PubMed Central

Hajdu, Agnes; Vold, Line; Østmo, Torild A; Helleve, Anna; Helgebostad, Sigrid R; Krogh, Truls; Robertson, Lucy; de Jong, Birgitta; Nygård, Karin

2008-01-01

Background In March 2007, the Norwegian Institute of Public Health was notified of Swedish individuals diagnosed with cryptosporidiosis after staying at a Norwegian hotel. In Norway, cryptosporidiosis is not reportable, and human infections are rarely diagnosed. Methods A questionnaire on illness and exposure history was e-mailed to seven organised groups who had visited the hotel in March. Cases were defined as persons with diarrhoea for more than two days or laboratory-confirmed cryptosporidiosis during or within two weeks of the hotel visit. The risk factor analysis was restricted to two groups with the highest attack rates (AR) and same hotel stay period. Local food safety authorities conducted environmental investigations. Results In total, 25 diarrhoeal cases (10 laboratory-confirmed) were identified among 89 respondents. Although environmental samples were negative, epidemiological data suggest an association with in-house water consumption. In one group, the AR was higher amongst consumers of water from hotel dispenser (relative risk [RR] = 3.0; 95% confidence interval [CI]: 0.9–9.8), tap water (RR = 2.3; CI: 0.9–5.8), and lower amongst commercial bottled water drinkers (RR = 0.6; CI: 0.4–1.0). Consumption of ice cubes was a risk-factor (RR = 7.1; CI: 1.1–45.7) in the two groups combined. Conclusion This outbreak would probably have remained undetected without the alert from Swedish health authorities, illustrating the difficulties in outbreak detection due to low health care seeking behaviour for diarrhoea and limited parasite diagnostics in Norway. Awareness of cryptosporidiosis should be raised amongst Norwegian medical personnel to improve case and outbreak detection, and possible risks related to in-house water systems should be assessed. PMID:18976495

Increased information on waterborne outbreaks through efficient notification system enforces actions towards safe drinking water.

PubMed

Zacheus, Outi; Miettinen, Ilkka T

2011-12-01

In 1997, a compulsory notification system for waterborne outbreaks was introduced in Finland. The main aim of this notification is to obtain immediate information on suspected waterborne outbreaks in order to restrict and manage the outbreak promptly. During the past ten years, there have been 67 waterborne outbreaks in Finland, mainly associated with small groundwater supplies or private wells. The number of reported waterborne outbreaks has increased since the launch of the notification system indicating that the threshold limit of outbreak detection has most probably decreased. The number of cases of illness has fulfilled the national health target, which is below 0.01% of the population, but more action is still needed to ensure the production of safe drinking water under all circumstances. Ten years accumulation of knowledge on outbreaks has revealed that a compulsory notification system is an effective tool to gather information on waterborne outbreaks. The system has also increased awareness of possible problems related to the quality of drinking water. This article summarises management and legislative actions and policy measures taken so far in Finland to reduce the number of outbreaks and cases of illness related to them.

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

PubMed

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

2017-09-01

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

Follow-Up of Norovirus Contamination in an Oyster Production Area Linked to Repeated Outbreaks.

PubMed

Le Mennec, Cécile; Parnaudeau, Sylvain; Rumebe, Myriam; Le Saux, Jean-Claude; Piquet, Jean-Côme; Le Guyader, S Françoise

2017-03-01

A production area repeatedly implicated in oyster-related gastroenteritis in France was studied for several months over 2 years. Outbreaks and field samples were analyzed by undertaking triplicate extractions, followed by norovirus (NoV) detection using triplicate wells for genomic amplification. This approach allowed us to demonstrate that some variabilities can be observed for samples with a low level of contamination, but most samples analyzed gave reproducible results. At the first outbreak, implicated oysters were collected at the beginning of the contamination event, which was reflected by the higher NoV levels during the first month of the study. During the second year, NoV concentrations in samples implicated in outbreaks and collected from the production area were similar, confirming the failure of the shellfish depuration process. Contamination was detected mainly during winter-spring months, and a high prevalence of NoV GI contamination was observed. A half-life of 18 days was calculated from NoV concentrations detected in oysters during this study, showing a very slow decrease of the contamination in the production area. Preventing the contamination of coastal waters should be a priority.

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

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.

Importance of molecular typing in confirmation of the source of a national hepatitis A virus outbreak in Norway and the detection of a related cluster in Germany.

PubMed

Guzman-Herrador, Bernardo R; Panning, Marcus; Stene-Johansen, Kathrine; Borgen, Katrine; Einöder-Moreno, Margot; Huzly, Daniela; Jensvoll, Laila; Lange, Heidi; Maassen, Sigrid; Myking, Solveig; Myrmel, Mette; Neumann-Haefelin, Christoph; Nygård, Karin; Wenzel, Jürgen J; Øye, Ann Kristin; Vold, Line

2015-11-01

In March 2014, after an increase of notifications of domestically acquired hepatitis A virus infections, an outbreak investigation was launched in Norway. Sequenced-based typing results showed that these cases were associated with a strain that was identical to one causing an ongoing multinational outbreak in Europe linked to frozen mixed berries. Thirty-three confirmed cases with the outbreak strain were notified in Norway from November 2013 to June 2014. Epidemiological evidence and trace-back investigations linked the outbreak to the consumption of a berry mix cake. Identification of the hepatitis A virus outbreak strain in berries from one of the implicated cakes confirmed the cake to be the source. Subsequently, a cluster in Germany linked to the cake was also identified.

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

PubMed

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

2016-10-10

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

Optofluidic analysis system for amplification-free, direct detection of Ebola infection

NASA Astrophysics Data System (ADS)

Cai, H.; Parks, J. W.; Wall, T. A.; Stott, M. A.; Stambaugh, A.; Alfson, K.; Griffiths, A.; Mathies, R. A.; Carrion, R.; Patterson, J. L.; Hawkins, A. R.; Schmidt, H.

2015-09-01

The massive outbreak of highly lethal Ebola hemorrhagic fever in West Africa illustrates the urgent need for diagnostic instruments that can identify and quantify infections rapidly, accurately, and with low complexity. Here, we report on-chip sample preparation, amplification-free detection and quantification of Ebola virus on clinical samples using hybrid optofluidic integration. Sample preparation and target preconcentration are implemented on a PDMS-based microfluidic chip (automaton), followed by single nucleic acid fluorescence detection in liquid-core optical waveguides on a silicon chip in under ten minutes. We demonstrate excellent specificity, a limit of detection of 0.2 pfu/mL and a dynamic range of thirteen orders of magnitude, far outperforming other amplification-free methods. This chip-scale approach and reduced complexity compared to gold standard RT-PCR methods is ideal for portable instruments that can provide immediate diagnosis and continued monitoring of infectious diseases at the point-of-care.

The Impact of Multilocus Variable-Number Tandem-Repeat Analysis on PulseNet Canada Escherichia coli O157:H7 Laboratory Surveillance and Outbreak Support, 2008-2012.

PubMed

Rumore, Jillian Leigh; Tschetter, Lorelee; Nadon, Celine

2016-05-01

The lack of pattern diversity among pulsed-field gel electrophoresis (PFGE) profiles for Escherichia coli O157:H7 in Canada does not consistently provide optimal discrimination, and therefore, differentiating temporally and/or geographically associated sporadic cases from potential outbreak cases can at times impede investigations. To address this limitation, DNA sequence-based methods such as multilocus variable-number tandem-repeat analysis (MLVA) have been explored. To assess the performance of MLVA as a supplemental method to PFGE from the Canadian perspective, a retrospective analysis of all E. coli O157:H7 isolated in Canada from January 2008 to December 2012 (inclusive) was conducted. A total of 2285 E. coli O157:H7 isolates and 63 clusters of cases (by PFGE) were selected for the study. Based on the qualitative analysis, the addition of MLVA improved the categorization of cases for 60% of clusters and no change was observed for ∼40% of clusters investigated. In such situations, MLVA serves to confirm PFGE results, but may not add further information per se. The findings of this study demonstrate that MLVA data, when used in combination with PFGE-based analyses, provide additional resolution to the detection of clusters lacking PFGE diversity as well as demonstrate good epidemiological concordance. In addition, MLVA is able to identify cluster-associated isolates with variant PFGE pattern combinations that may have been previously missed by PFGE alone. Optimal laboratory surveillance in Canada is achieved with the application of PFGE and MLVA in tandem for routine surveillance, cluster detection, and outbreak response.

Genetic characterization of measles virus in the Philippines, 2008-2011.

PubMed

Centeno, Rex; Fuji, Naoko; Okamoto, Michiko; Dapat, Clyde; Saito, Mariko; Tandoc, Amado; Lupisan, Socorro; Oshitani, Hitoshi

2015-06-03

Large outbreaks of measles occurred in the Philippines in 2010 and 2011. Genetic analysis was performed to identify the genotype of measles virus (MeV) that was responsible for the large outbreaks. A total of 114 representative MeVs that were detected in the Philippines from 2008 to 2011 were analyzed by sequencing the C-terminal region of nucleocapsid (N) gene and partial hemagglutinin (H) gene and by inferring the phylogenetic trees. Genetic analysis showed that genotype D9 was the predominant circulating strain during the 4-year study period. Genotype D9 was detected in 23 samples (92%) by N gene sequencing and 93 samples (94%) by H gene analysis. Sporadic cases of genotype G3 MeV were identified in 2 samples (8%) by N gene sequencing and 6 samples (6%) by H gene analysis. Genotype G3 MeV was detected mainly in Panay Island in 2009 and 2010. Molecular clock analysis of N gene showed that the recent genotype D9 viruses that caused the big outbreaks in 2010 and 2011 diverged from a common ancestor in 2005 in one of the neighboring Southeast Asian countries, where D9 was endemic. These big outbreaks of measles resulted in a spillover and were associated with genotype D9 MeV importation to Japan and the USA. Genotype D9 MeV became endemic and caused two big outbreaks in the Philippines in 2010 and 2011. Genotype G3 MeV was detected sporadically with limited geographic distribution. This study highlights the importance of genetic analysis not only in helping with the assessment of measles elimination program in the country but also in elucidating the transmission dynamics of measles virus.

Identification of Shiga-Toxigenic Escherichia coli outbreak isolates by a novel data analysis tool after matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Christner, Martin; Dressler, Dirk; Andrian, Mark; Reule, Claudia; Petrini, Orlando

2017-01-01

The fast and reliable characterization of bacterial and fungal pathogens plays an important role in infectious disease control and tracking of outbreak agents. DNA based methods are the gold standard for epidemiological investigations, but they are still comparatively expensive and time-consuming. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a fast, reliable and cost-effective technique now routinely used to identify clinically relevant human pathogens. It has been used for subspecies differentiation and typing, but its use for epidemiological tasks, e. g. for outbreak investigations, is often hampered by the complexity of data analysis. We have analysed publicly available MALDI-TOF mass spectra from a large outbreak of Shiga-Toxigenic Escherichia coli in northern Germany using a general purpose software tool for the analysis of complex biological data. The software was challenged with depauperate spectra and reduced learning group sizes to mimic poor spectrum quality and scarcity of reference spectra at the onset of an outbreak. With high quality formic acid extraction spectra, the software's built in classifier accurately identified outbreak related strains using as few as 10 reference spectra (99.8% sensitivity, 98.0% specificity). Selective variation of processing parameters showed impaired marker peak detection and reduced classification accuracy in samples with high background noise or artificially reduced peak counts. However, the software consistently identified mass signals suitable for a highly reliable marker peak based classification approach (100% sensitivity, 99.5% specificity) even from low quality direct deposition spectra. The study demonstrates that general purpose data analysis tools can effectively be used for the analysis of bacterial mass spectra.

Multilocus sequence typing scheme versus pulsed-field gel electrophoresis for typing Mycobacterium abscessus isolates.

PubMed

Machado, Gabriel Esquitini; Matsumoto, Cristianne Kayoko; Chimara, Erica; Duarte, Rafael da Silva; de Freitas, Denise; Palaci, Moises; Hadad, David Jamil; Lima, Karla Valéria Batista; Lopes, Maria Luiza; Ramos, Jesus Pais; Campos, Carlos Eduardo; Caldas, Paulo César; Heym, Beate; Leão, Sylvia Cardoso

2014-08-01

Outbreaks of infections by rapidly growing mycobacteria following invasive procedures, such as ophthalmological, laparoscopic, arthroscopic, plastic, and cardiac surgeries, mesotherapy, and vaccination, have been detected in Brazil since 1998. Members of the Mycobacterium chelonae-Mycobacterium abscessus group have caused most of these outbreaks. As part of an epidemiological investigation, the isolates were typed by pulsed-field gel electrophoresis (PFGE). In this project, we performed a large-scale comparison of PFGE profiles with the results of a recently developed multilocus sequence typing (MLST) scheme for M. abscessus. Ninety-three isolates were analyzed, with 40 M. abscessus subsp. abscessus isolates, 47 M. abscessus subsp. bolletii isolates, and six isolates with no assigned subspecies. Forty-five isolates were obtained during five outbreaks, and 48 were sporadic isolates that were not associated with outbreaks. For MLST, seven housekeeping genes (argH, cya, glpK, gnd, murC, pta, and purH) were sequenced, and each isolate was assigned a sequence type (ST) from the combination of obtained alleles. The PFGE patterns of DraI-digested DNA were compared with the MLST results. All isolates were analyzable by both methods. Isolates from monoclonal outbreaks showed unique STs and indistinguishable or very similar PFGE patterns. Thirty-three STs and 49 unique PFGE patterns were identified among the 93 isolates. The Simpson's index of diversity values for MLST and PFGE were 0.69 and 0.93, respectively, for M. abscessus subsp. abscessus and 0.96 and 0.97, respectively, for M. abscessus subsp. bolletii. In conclusion, the MLST scheme showed 100% typeability and grouped monoclonal outbreak isolates in agreement with PFGE, but it was less discriminative than PFGE for M. abscessus. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Outbreaks of Invasive Kingella kingae Infections in Closed Communities.

PubMed

Yagupsky, Pablo; Ben-Ami, Yael; Trefler, Ronit; Porat, Nurith

2016-02-01

To describe the results of the epidemiologic investigation of outbreaks of invasive Kingella kingae infections among attendees at daycare facilities located in 4 closed communities in Israel. The preschool-aged population of communities with clusters of Kingella cases had oropharyngeal cultures performed. K kingae isolates from infected patients and healthy contacts were genotyped by pulsed field gel electrophoresis to determine the spread of outbreak strains. The affected closed communities (3 military bases and 1 "kibbutz" commune) were characterized by tight social and family networks and intensive mingling. The outbreaks affected 9 of 51 attendees (attack rate: 17.6%) age 8-19 months (median: 12 months), within a 21-day period. Cases included skeletal system infections (n = 8) and bacteremia (n = 1); K kingae isolates were confirmed by the use of blood culture vials and selective media. Clinical presentation was mild and acute-phase reactants were usually normal or only moderately elevated. Thirty out of 55 (54.5%) asymptomatic children carried the outbreak strains. Analysis of the 3 clusters in which the entire preschool-aged population was cultured revealed that 31 of 71 (43.7%) children younger than 24 months of age were colonized with K kingae organisms compared with 8 of 105 (7.6%) older children (P < .001). Clusters of invasive K kingae infections characterized by sudden onset, high attack rate, and wide dissemination of the outbreak strain can occur in daycare facilities and closed communities. Because the mild clinical presentation of invasive K kingae infections and the fastidious nature of the organism, a high index of suspicion and use of sensitive detection methods are recommended. Copyright © 2016 Elsevier Inc. All rights reserved.

Serratia marcescens outbreak in a neonatal intensive care unit (NICU): new insights from next-generation sequencing applications.

PubMed

Martineau, Christine; Li, Xuejing; Lalancette, Cindy; Perreault, Thérèse; Fournier, Eric; Tremblay, Julien; Gonzales, Milagros; Yergeau, Étienne; Quach, Caroline

2018-06-13

Serratia marcescens is an environmental bacterium commonly associated with outbreaks in neonatal intensive care units (NICU). Investigation of S. marcescens outbreaks requires efficient recovery and typing of clinical and environmental isolates. In this study, we described how the use of next-generation sequencing applications, such as bacterial whole-genome sequencing (WGS) and bacterial community profiling, could improve S. marcescens outbreak investigation. Phylogenomic links and potential antibiotic resistance genes and plasmids in S. marcescens isolates were investigated using WGS, while bacterial communities and relative abundances of Serratia in environmental samples were assessed using sequencing of bacterial phylogenetic marker genes (16S rRNA and gyrB genes). Typing results obtained using WGS for the ten S. marcescens isolates recovered during a NICU outbreak investigation were highly consistent with those from pulse-field gel electrophoresis (PFGE), the current gold standard typing method for this bacterium. WGS also allowed for the identification of genes associated with antibiotic resistance in all isolates, while no plasmid was detected. Sequencing of the 16S rRNA and gyrB genes both showed higher relative abundances of Serratia in environmental sampling sites that were in close contact with infected babies. Much lower relative abundances of Serratia were observed following disinfection of a room, indicating that the protocol used was efficient. Variations in the bacterial community composition and structure following room disinfection and between sampling sites were also identified through 16S rRNA gene sequencing. Globally, results from this study highlight the potential for next-generation sequencing tools to improve and facilitate outbreak investigation. Copyright © 2018 American Society for Microbiology.

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.

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.

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.

Identification and molecular epidemiology of nosocomial outbreaks due to Burkholderia cepacia in cystic fibrosis patients of Masih Daneshvary Hospital, Iran.

PubMed

Dallal, M M Soltan; Telefian, C F; Hajia, M; Kalantar, E; Dehkharghani, A R Dolatyar; Forushani, A Rahimi; Khanbabaei, Q; Mobarhan, M; Farzami, M R

2014-03-01

B. cepacia complex have emerged as an important opportunistic pathogen in hospitalized and immunocompromised patients. Small hospital outbreaks are frequent and are usually due to a single contaminated environmental source. In this study we were going to investigate the role of B.cepacia complex in those patients suspected to involve with cystic fibrosis and evaluate responsible types in Masih Daneshvary Hospital. One hundred specimens were collected from all admitted patients who were suspected to cystic fibrosis to Masih Daneshvary hospital during one year April 2011 till end of March 2012. All were culture and identified standard procedure. All samples were checked by API system (API20NE) and by specific PCR method for genus Bulkhorderia and Bcc as well. Identified strains were finally tested by PFGE system to identifying specific involving pulse-types. . Isolation and identification methods revealed 5 specimens were B.cepasia, The frequency of the cystic fibrosis detected at this study was lower than other similar study previously reported. All these isolates showed similar pattern by PFGE standard protocol that may have spread from a single source and could not be attributed to cross infections from patient to patients. Application of PFGE and identification of pulse-type is a potential tool to enhance the investigation of apparent nosocomial outbreaks of B.cepacia. However it needs to be adjusted with environmental findings. Implementation of educational programs and adherence to infection control policies are obviously the main element for complete elimination of an outbreak.

Reported waterborne outbreaks of gastrointestinal disease in Australia are predominantly associated with recreational exposure.

PubMed

Dale, Katie; Kirk, Martyn; Sinclair, Martha; Hall, Robert; Leder, Karin

2010-10-01

To examine the frequency and circumstances of reported waterborne outbreaks of gastroenteritis in Australia. Examination of data reported to OzFoodNet between 2001 and 2007. During these seven years, 6,515 gastroenteritis outbreaks were reported to OzFoodNet, most of which were classified as being transmitted person-to-person or from an unknown source. Fifty-four (0.83%) outbreaks were classified as either 'waterborne' or 'suspected waterborne', of which 78% (42/54) were attributed to recreational water and 19% (10/54) to drinking water. Of the drinking water outbreaks, implicated pathogens were found on all but one occasion and included Salmonella sp. (five outbreaks), Campylobacter jejuni (three outbreaks) and Giardia (one outbreak). There have been few waterborne outbreaks detected in Australia, and most of those reported have been associated with recreational exposure. However, there are difficulties in identifying and categorising gastroenteritis outbreaks, as well as in obtaining microbiological and epidemiological evidence, which can result in misclassification or underestimation of water-associated events. Gastroenteritis surveillance data show that, among reported water-associated gastroenteritis outbreaks in Australia, recreational exposure is currently more common than a drinking water source. However, ongoing surveillance for waterborne outbreaks is important, especially as drought conditions may necessitate replacement of conventional drinking water supplies with alternative water sources, which could incur potential for new health risks. © 2010 The Authors. Journal Compilation © 2010 Public Health Association of Australia.

Modification of a Pollen Trap Design To Capture Airborne Conidia of Entomophaga maimaiga and Detection of Conidia by Quantitative PCR.

PubMed

Bittner, Tonya D; Hajek, Ann E; Liebhold, Andrew M; Thistle, Harold

2017-09-01

The goal of this study was to develop effective and practical field sampling methods for quantification of aerial deposition of airborne conidia of Entomophaga maimaiga over space and time. This important fungal pathogen is a major cause of larval death in invasive gypsy moth ( Lymantria dispar ) populations in the United States. Airborne conidia of this pathogen are relatively large (similar in size to pollen), with unusual characteristics, and require specialized methods for collection and quantification. Initially, dry sampling (settling of spores from the air onto a dry surface) was used to confirm the detectability of E. maimaiga at field sites with L. dispar deaths caused by E. maimaiga , using quantitative PCR (qPCR) methods. We then measured the signal degradation of conidial DNA on dry surfaces under field conditions, ultimately rejecting dry sampling as a reliable method due to rapid DNA degradation. We modified a chamber-style trap commonly used in palynology to capture settling spores in buffer. We tested this wet-trapping method in a large-scale (137-km) spore-trapping survey across gypsy moth outbreak regions in Pennsylvania undergoing epizootics, in the summer of 2016. Using 4-day collection periods during the period of late instar and pupal development, we detected variable amounts of target DNA settling from the air. The amounts declined over the season and with distance from the nearest defoliated area, indicating airborne spore dispersal from outbreak areas. IMPORTANCE We report on a method for trapping and quantifying airborne spores of Entomophaga maimaiga , an important fungal pathogen affecting gypsy moth ( Lymantria dispar ) populations. This method can be used to track dispersal of E. maimaiga from epizootic areas and ultimately to provide critical understanding of the spatial dynamics of gypsy moth-pathogen interactions. Copyright © 2017 American Society for Microbiology.

Epidemiology and estimated costs of a large waterborne outbreak of norovirus infection in Sweden.

PubMed

Larsson, C; Andersson, Y; Allestam, G; Lindqvist, A; Nenonen, N; Bergstedt, O

2014-03-01

A large outbreak of norovirus (NoV) gastroenteritis caused by contaminated municipal drinking water occurred in Lilla Edet, Sweden, 2008. Epidemiological investigations performed using a questionnaire survey showed an association between consumption of municipal drinking water and illness (odds ratio 4·73, 95% confidence interval 3·53-6·32), and a strong correlation between the risk of being sick and the number of glasses of municipal water consumed. Diverse NoV strains were detected in stool samples from patients, NoV genotype I strains predominating. Although NoVs were not detected in water samples, coliphages were identified as a marker of viral contamination. About 2400 (18·5%) of the 13,000 inhabitants in Lilla Edet became ill. Costs associated with the outbreak were collected via a questionnaire survey given to organizations and municipalities involved in or affected by the outbreak. Total costs including sick leave, were estimated to be ∼8,700,000 Swedish kronor (∼€0·87 million).

Outbreak of viral gastroenteritis due to drinking water contaminated by Norwalk-like viruses.

PubMed

Kukkula, M; Maunula, L; Silvennoinen, E; von Bonsdorff, C H

1999-12-01

Heinävesi, a Finnish municipality with a population of 4860 inhabitants, had an outbreak of gastroenteritis in March 1998. On the basis of an epidemiologic survey, an estimated 1700-3000 cases of acute gastroenteritis occurred during the outbreak. Municipal water consumption was found to be associated with illness (risk ratio [RR]=3.5, 95% confidence interval, 3.11>RR>3.96). Norwalk-like virus (NLV) genogroup II (GGII) was identified in untreated water, treated water, and 4 tap water samples by use of reverse transcription-polymerase chain reaction. This was the first time NLVs had been detected in municipal tap water. Fifteen of 27 patient stool samples had NLV GGII, with an identical amplification product to that found in the water samples, indicating that the outbreak was caused by this virus. In some patients, NLV genogroup I was also encountered. This virus, however, could not be detected in the water samples. Inadequate chlorination contributed to the survival of the virus in the water.

Highly Pathogenic Avian Influenza Virus (H5N1) in Frozen Duck Carcasses, Germany, 2007

PubMed Central

Harder, Timm C.; Teuffert, Jürgen; Starick, Elke; Gethmann, Jörn; Grund, Christian; Fereidouni, Sasan; Durban, Markus; Bogner, Karl-Heinz; Neubauer-Juric, Antonie; Repper, Reinhard; Hlinak, Andreas; Engelhardt, Andreas; Nöckler, Axel; Smietanka, Krzysztof; Minta, Zenon; Kramer, Matthias; Globig, Anja; Mettenleiter, Thomas C.; Conraths, Franz J.

2009-01-01

We conducted phylogenetic and epidemiologic analyses to determine sources of outbreaks of highly pathogenic avian influenza virus (HPAIV), subtype H5N1, in poultry holdings in 2007 in Germany, and a suspected incursion of HPAIV into the food chain through contaminated deep-frozen duck carcasses. In summer 2007, HPAIV (H5N1) outbreaks in 3 poultry holdings in Germany were temporally, spatially, and phylogenetically linked to outbreaks in wild aquatic birds. Detection of HPAIV (H5N1) in frozen duck carcass samples of retained slaughter batches of 1 farm indicated that silent infection had occurred for some time before the incidental detection. Phylogenetic analysis established a direct epidemiologic link between HPAIV isolated from duck meat and strains isolated from 3 further outbreaks in December 2007 in backyard chickens that had access to uncooked offal from commercial deep-frozen duck carcasses. Measures that will prevent such undetected introduction of HPAIV (H5N1) into the food chain are urgently required. PMID:19193272

Data-driven approach for creating synthetic electronic medical records.

PubMed

Buczak, Anna L; Babin, Steven; Moniz, Linda

2010-10-14

New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed. This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population. We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified. A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.

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.

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.

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.

Larval outbreaks in West Greenland: Instant and subsequent effects on tundra ecosystem productivity and CO2 exchange.

PubMed

Lund, Magnus; Raundrup, Katrine; Westergaard-Nielsen, Andreas; López-Blanco, Efrén; Nymand, Josephine; Aastrup, Peter

2017-02-01

Insect outbreaks can have important consequences for tundra ecosystems. In this study, we synthesise available information on outbreaks of larvae of the noctuid moth Eurois occulta in Greenland. Based on an extensive dataset from a monitoring programme in Kobbefjord, West Greenland, we demonstrate effects of a larval outbreak in 2011 on vegetation productivity and CO 2 exchange. We estimate a decreased carbon (C) sink strength in the order of 118-143 g C m -2 , corresponding to 1210-1470 tonnes C at the Kobbefjord catchment scale. The decreased C sink was, however, counteracted the following years by increased primary production, probably facilitated by the larval outbreak increasing nutrient turnover rates. Furthermore, we demonstrate for the first time in tundra ecosystems, the potential for using remote sensing to detect and map insect outbreak events.

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

Case-based surveillance enhanced with measles virus detection/genotyping is essential to maintain measles elimination in Aichi Prefecture, Japan.

PubMed

Minagawa, Hiroko; Yasui, Yoshihiro; Adachi, Hirokazu; Ito, Miyabi; Hirose, Emi; Nakamura, Noriko; Hata, Mami; Kobayashi, Shinichi; Yamashita, Teruo

2015-11-09

Japan was verified as having achieved measles elimination by the Measles Regional Verification Commission in the Western Pacific Region in March 2015. Verification of measles elimination implies the absence of continuous endemic transmission. After the last epidemic in 2007 with an estimated 18,000 cases, Japan introduced nationwide case-based measles surveillance in January 2008. Laboratory diagnosis for all suspected measles cases is essentially required by law, and virus detection tests are mostly performed by municipal public health institutes. Despite relatively high vaccination coverage and vigorous response to every case by the local health center staff, outbreak of measles is repeatedly observed in Aichi Prefecture, Japan. Measles virus N and H gene detection by nested double RT-PCR was performed with all specimens collected from suspected cases and transferred to our institute. Genotyping and further molecular epidemiological analyses were performed with the direct nucleotide sequence data of appropriate PCR products. Between 2010 and 2014, specimens from 389 patients suspected for measles were tested in our institute. Genotypes D9, D8, H1 and B3 were detected. Further molecular epidemiological analyses were helpful to establish links between patients, and sometimes useful to discriminate one outbreak from another. All virus-positive cases, including 49 cases involved in three outbreaks without any obvious epidemiological link with importation, were considered as import-related based on the nucleotide sequence information. Chain of transmission in the latest outbreak in 2014 terminated after the third generations, much earlier than the 2010-11 outbreak (6th generations). Since 2010, almost all measles cases reported in Aichi Prefecture are either import or import-related, based primarily on genotypes and nucleotide sequences of measles virus detected. In addition, genotyping and molecular epidemiological analyses are indispensable to prove the interruption of endemic transmission when the importations of measles are repeatedly observed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection of Toxoplasma gondii oocysts in water: proposition of a strategy and evaluation in Champagne-Ardenne Region, France.

PubMed

Aubert, D; Villena, I

2009-03-01

Water is a vehicle for disseminating human and veterinary toxoplasmosis due to oocyst contamination. Several outbreaks of toxoplasmosis throughout the world have been related to contaminated drinking water. We have developed a method for the detection of Toxoplasma gondii oocysts in water and we propose a strategy for the detection of multiple waterborne parasites, including Cryptosporidium spp. and Giardia. Water samples were filtered to recover Toxoplasma oocysts and, after the detection of Cryptosporidium oocysts and Giardia cysts by immunofluorescence, as recommended by French norm procedure NF T 90-455, the samples were purified on a sucrose density gradient. Detection of Toxoplasma was based on PCR amplification and mouse inoculation to determine the presence and infectivity of recovered oocysts. After experimental seeding assays, we determined that the PCR assay was more sensitive than the bioassay. This strategy was then applied to 482 environmental water samples collected since 2001. We detected Toxoplasma DNA in 37 environmental samples (7.7%), including public drinking water; however, none of them were positive by bioassay. This strategy efficiently detects Toxoplasma oocysts in water and may be suitable as a public health sentinel method. Alternative methods can be used in conjunction with this one to determine the infectivity of parasites that were detected by molecular methods.

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, and the key role of good control strategies in the processing environment.

Comparison of advanced whole genome sequence-based methods to distinguish strains of Salmonella enterica serovar Heidelberg involved in foodborne outbreaks in Québec.

PubMed

Vincent, Caroline; Usongo, Valentine; Berry, Chrystal; Tremblay, Denise M; Moineau, Sylvain; Yousfi, Khadidja; Doualla-Bell, Florence; Fournier, Eric; Nadon, Céline; Goodridge, Lawrence; Bekal, Sadjia

2018-08-01

Salmonella enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. This serovar ranks second and third among serovars that cause human infections in Québec and Canada, respectively, and has been associated with severe infections. Traditional typing methods such as PFGE do not display adequate discrimination required to resolve outbreak investigations due to the low level of genetic diversity of isolates belonging to this serovar. This study evaluates the ability of four whole genome sequence (WGS)-based typing methods to differentiate among 145 S. Heidelberg strains involved in four distinct outbreak events and sporadic cases of salmonellosis that occurred in Québec between 2007 and 2016. Isolates from all outbreaks were indistinguishable by PFGE. The core genome single nucleotide variant (SNV), core genome multilocus sequence typing (MLST) and whole genome MLST approaches were highly discriminatory and separated outbreak strains into four distinct phylogenetic clusters that were concordant with the epidemiological data. The clustered regularly interspaced short palindromic repeats (CRISPR) typing method was less discriminatory. However, CRISPR typing may be used as a secondary method to differentiate isolates of S. Heidelberg that are genetically similar but epidemiologically unrelated to outbreak events. WGS-based typing methods provide a highly discriminatory alternative to PFGE for the laboratory investigation of foodborne outbreaks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Governance and One Health: Exploring the Impact of Federalism and Bureaucracy on Zoonotic Disease Detection and Reporting.

PubMed

Allen, Heather A

2015-05-13

The merits of One Health have been thoroughly described in the literature, but how One Health operates in the United States federal system of government is rarely discussed or analyzed. Through a comparative case-study approach, this research explores how federalism, bureaucratic behavior, and institutional design in the United States may influence zoonotic disease outbreak detection and reporting, a key One Health activity. Using theoretical and empirical literature, as well as a survey/interview instrument for individuals directly involved in a past zoonotic disease outbreak, the impacts of governance are discussed. As predicted in the theoretical literature, empirical findings suggest that federalism, institutional design, and bureaucracy may play a role in facilitating or impeding zoonotic disease outbreak detection and reporting. Regulatory differences across states as well as compartmentalization of information within agencies may impede disease detection. However, the impact may not always be negative: bureaucracies can also be adaptive; federalism allows states important opportunities for innovation. While acknowledging there are many other factors that also matter in zoonotic disease detection and reporting, this research is one of the first attempts to raise awareness in the literature and stimulate discussion on the intersection of governance and One Health.

Joint USGS/USEPA Pathogens in Soils Geographic ...

EPA Pesticide Factsheets

Online interactive maps In order to protect the environment from current and potential threats posed by uncontrolled intentional releases of hazardous substances, pollutants, and contaminants, the biothreat research community recognizes the needs to be able to detect threats in the appropriate matrices and also consider whether a detected constituent is naturally occurring or a contaminant associated with an accidental or purposeful release. Therefore, sensitive and specific methods for processing and analyzing environmental samples as well as methods to determine the existing risk to the public from endemic microorganisms are needed. Background data is also an important variable for assessing and managing the risks posed by a contaminated site. The EPA has collaborated with the USGS to analyze over 4800 soil samples collected during the USGS North American Soil Geochemical Landscapes Project for the presence of Bacillus anthracis and a subset of those samples for the presence of Yersinia pestis, and Francisella tularensis. EPA and USGS scientists correlated occurrences with geochemical constituents (> 40 major and trace elements), historical outbreak data, and climate data by creating online interactive maps using a Geographic Information Systems (GIS) platform. This on-going nationwide survey can be used as an investigative tool by animal and public health scientists and emergency responders determine the potential for disease outbreaks and persistenc

Low West Nile virus circulation in wild birds in an area of recurring outbreaks in Southern France.

PubMed

Balança, Gilles; Gaidet, Nicolas; Savini, Giovanni; Vollot, Benjamin; Foucart, Antoine; Reiter, Paul; Boutonnier, Alain; Lelli, Rossella; Monicat, François

2009-12-01

West Nile virus (WNV) has a history of irregular but recurrent epizootics in countries of Mediterranean and of Central and Eastern Europe. We have investigated the temporal enzootic activity of WNV in free-ranging birds over a 3-year period in an area with sporadic occurrences of WNV outbreaks in Southern France. We conducted an intensive serologic survey on several wild bird populations (>4000 serum samples collected from 3300 birds) selected as potential indicators of the WNV circulation. WNV antibodies were detected by seroneutralization and/or plaque reduction neutralization in house sparrows, black-billed magpies, and scops owls, but these species appeared to be insufficient indicators of WNV circulation. Overall seroprevalence was low (<1%), including in birds that had been potentially exposed to the virus during recent outbreaks. However, the detection of a seroconversion in one bird, as well as the detection of seropositive birds in all years of our monitoring, including juveniles, indicate a constant annual circulation of WNV at a low level, including in years without any detectable emergence of WN fever in horses or humans.

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 ...

Whole genome sequencing in the prevention and control of Staphylococcus aureus infection.

PubMed

Price, J R; Didelot, X; Crook, D W; Llewelyn, M J; Paul, J

2013-01-01

Staphylococcus aureus remains a leading cause of hospital-acquired infection but weaknesses inherent in currently available typing methods impede effective infection prevention and control. The high resolution offered by whole genome sequencing has the potential to revolutionise our understanding and management of S. aureus infection. To outline the practicalities of whole genome sequencing and discuss how it might shape future infection control practice. We review conventional typing methods and compare these with the potential offered by whole genome sequencing. In contrast with conventional methods, whole genome sequencing discriminates down to single nucleotide differences and allows accurate characterisation of transmission events and outbreaks and additionally provides information about the genetic basis of phenotypic characteristics, including antibiotic susceptibility and virulence. However, translating its potential into routine practice will depend on affordability, acceptable turnaround times and on creating a reliable standardised bioinformatic infrastructure. Whole genome sequencing has the potential to provide a universal test that facilitates outbreak investigation, enables the detection of emerging strains and predicts their clinical importance. Copyright © 2012 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Western Spruce Budworm Outbreaks Did Not Increase Fire Risk over the Last Three Centuries: A Dendrochronological Analysis of Inter-Disturbance Synergism

PubMed Central

Flower, Aquila; G. Gavin, Daniel; Heyerdahl, Emily K.; Parsons, Russell A.; Cohn, Gregory M.

2014-01-01

Insect outbreaks are often assumed to increase the severity or probability of fire occurrence through increased fuel availability, while fires may in turn alter susceptibility of forests to subsequent insect outbreaks through changes in the spatial distribution of suitable host trees. However, little is actually known about the potential synergisms between these natural disturbances. Assessing inter-disturbance synergism is challenging due to the short length of historical records and the confounding influences of land use and climate changes on natural disturbance dynamics. We used dendrochronological methods to reconstruct defoliator outbreaks and fire occurrence at ten sites along a longitudinal transect running from central Oregon to western Montana. We assessed synergism between disturbance types, analyzed long-term changes in disturbance dynamics, and compared these disturbance histories with dendroclimatological moisture availability records to quantify the influence of moisture availability on disturbances. After approximately 1890, fires were largely absent and defoliator outbreaks became longer-lasting, more frequent, and more synchronous at our sites. Fires were more likely to occur during warm-dry years, while outbreaks were most likely to begin near the end of warm-dry periods. Our results show no discernible impact of defoliation events on subsequent fire risk. Any effect from the addition of fuels during defoliation events appears to be too small to detect given the overriding influence of climatic variability. We therefore propose that if there is any relationship between the two disturbances, it is a subtle synergistic relationship wherein climate determines the probability of occurrence of each disturbance type, and each disturbance type damps the severity, but does not alter the probability of occurrence, of the other disturbance type over long time scales. Although both disturbance types may increase in frequency or extent in response to future warming, our records show no precedent that western spruce budworm outbreaks will increase future fire risk. PMID:25526633

Western spruce budworm outbreaks did not increase fire risk over the last three centuries: a dendrochronological analysis of inter-disturbance synergism.

PubMed

Flower, Aquila; Gavin, Daniel G; Heyerdahl, Emily K; Parsons, Russell A; Cohn, Gregory M

2014-01-01

Insect outbreaks are often assumed to increase the severity or probability of fire occurrence through increased fuel availability, while fires may in turn alter susceptibility of forests to subsequent insect outbreaks through changes in the spatial distribution of suitable host trees. However, little is actually known about the potential synergisms between these natural disturbances. Assessing inter-disturbance synergism is challenging due to the short length of historical records and the confounding influences of land use and climate changes on natural disturbance dynamics. We used dendrochronological methods to reconstruct defoliator outbreaks and fire occurrence at ten sites along a longitudinal transect running from central Oregon to western Montana. We assessed synergism between disturbance types, analyzed long-term changes in disturbance dynamics, and compared these disturbance histories with dendroclimatological moisture availability records to quantify the influence of moisture availability on disturbances. After approximately 1890, fires were largely absent and defoliator outbreaks became longer-lasting, more frequent, and more synchronous at our sites. Fires were more likely to occur during warm-dry years, while outbreaks were most likely to begin near the end of warm-dry periods. Our results show no discernible impact of defoliation events on subsequent fire risk. Any effect from the addition of fuels during defoliation events appears to be too small to detect given the overriding influence of climatic variability. We therefore propose that if there is any relationship between the two disturbances, it is a subtle synergistic relationship wherein climate determines the probability of occurrence of each disturbance type, and each disturbance type damps the severity, but does not alter the probability of occurrence, of the other disturbance type over long time scales. Although both disturbance types may increase in frequency or extent in response to future warming, our records show no precedent that western spruce budworm outbreaks will increase future fire risk.

'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.

Response to a Large Polio Outbreak in a Setting of Conflict - Middle East, 2013-2015.

PubMed

Mbaeyi, Chukwuma; Ryan, Michael J; Smith, Philip; Mahamud, Abdirahman; Farag, Noha; Haithami, Salah; Sharaf, Magdi; Jorba, Jaume C; Ehrhardt, Derek

2017-03-03

As the world advances toward the eradication of polio, outbreaks of wild poliovirus (WPV) in polio-free regions pose a substantial risk to the timeline for global eradication. Countries and regions experiencing active conflict, chronic insecurity, and large-scale displacement of persons are particularly vulnerable to outbreaks because of the disruption of health care and immunization services (1). A polio outbreak occurred in the Middle East, beginning in Syria in 2013 with subsequent spread to Iraq (2). The outbreak occurred 2 years after the onset of the Syrian civil war, resulted in 38 cases, and was the first time WPV was detected in Syria in approximately a decade (3,4). The national governments of eight countries designated the outbreak a public health emergency and collaborated with partners in the Global Polio Eradication Initiative (GPEI) to develop a multiphase outbreak response plan focused on improving the quality of acute flaccid paralysis (AFP) surveillance* and administering polio vaccines to >27 million children during multiple rounds of supplementary immunization activities (SIAs). † Successful implementation of the response plan led to containment and interruption of the outbreak within 6 months of its identification. The concerted approach adopted in response to this outbreak could serve as a model for responding to polio outbreaks in settings of conflict and political instability.

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.

Cholera Outbreaks in Nigeria Are Associated with Multidrug Resistant Atypical El Tor and Non-O1/Non-O139 Vibrio cholerae

PubMed Central

Marin, Michel A.; Thompson, Cristiane C.; Freitas, Fernanda S.; Fonseca, Erica L.; Aboderin, A. Oladipo; Zailani, Sambo B.; Quartey, Naa Kwarley E.; Okeke, Iruka N.; Vicente, Ana Carolina P.

2013-01-01

Background The current millennium has seen a steep rise in the number, size and case-fatalities of cholera outbreaks in many African countries. Over 40,000 cases of cholera were reported from Nigeria in 2010. Variants of Vibrio cholerae O1 El Tor biotype have emerged but very little is known about strains causing cholera outbreaks in West Africa, which is crucial for the implementation of interventions to control epidemic cholera. Methodology/Principal Findings V. cholerae isolates from outbreaks of acute watery diarrhea in Nigeria from December, 2009 to October, 2010 were identified by standard culture methods. Fifteen O1 and five non-O1/non-O139 strains were analyzed; PCR and sequencing targeted regions associated with virulence, resistance and biotype were performed. We also studied genetic interrelatedness among the strains by multilocus sequence analysis and pulsed-field gel electrophoresis. The antibiotic susceptibility was tested by the disk diffusion method and E-test. We found that multidrug resistant atypical El Tor strains, with reduced susceptibility to ciprofloxacin and chloramphenicol, characterized by the presence of the SXT element, and gyrA Ser83Ile/parC Ser85Leu alleles as well CTX phage and TCP cluster characterized by rstR ElTor, ctxB-7 and tcpA CIRS alleles, respectively, were largely responsible for cholera outbreaks in 2009 and 2010. We also identified and characterized a V. cholerae non-O1/non-O139 lineage from cholera-like diarrhea cases in Nigeria. Conclusions/Significance The recent Nigeria outbreaks have been determined by multidrug resistant atypical El Tor and non-O1/non-O139 V. cholerae strains, and it seems that the typical El Tor, from the beginning of seventh cholera pandemic, is no longer epidemic/endemic in this country. This scenario is similar to the East Africa, Asia and Caribbean countries. The detection of a highly virulent, antimicrobial resistant lineage in Nigeria is worrisome and points to a need for vaccine-based control of the disease. This study has also revealed the putative importance of non-O1/non-O139 V. cholerae in diarrheal disease in Nigeria. PMID:23459673

Understanding outbreaks of waterborne infectious disease: quantitative microbial risk assessment vs. epidemiology

USDA-ARS?s Scientific Manuscript database

Drinking water contaminated with microbial pathogens can cause outbreaks of infectious disease, and these outbreaks are traditionally studied using epidemiologic methods. Quantitative microbial risk assessment (QMRA) can predict – and therefore help prevent – such outbreaks, but it has never been r...

Contagious equine metritis: artificial reproduction changes the epidemiologic paradigm.

PubMed

Schulman, Martin Lance; May, Catherine Edith; Keys, Bronwyn; Guthrie, Alan John

2013-11-29

Recent CEM outbreak reports reflect a novel epidemiologic manifestation with a markedly different risk association for transmission via artificial reproduction and subsequent to inadvertent importation of unapparent carrier stallions. Artificial breeding has an increased association with horizontal or fomite-associated transmission. Reported risk factors include inadequate biosecurity protocols at centralised breeding facilities associated with stallion management and methods of semen collection, processing and transport. Detection of carriers is based on traditional bacteriology from genital swabs and despite limitations inherent to Taylorella equigenitalis is currently the gold standard applied in all international trade and movement protocols. These limitations are reported to be overcome by PCR assays improving diagnostic sensitivity and specificity, practicality, turn-around times, through-put and cost efficacy. Molecular methods have increased understanding of the Taylorelleae, facilitate epidemiologic surveillance and outbreak control strategies. Validation and international regulatory acceptance of a robust PCR-based assay and the undefined risks in association with cryopreserved semen and embryos are future areas warranting further investigation. Copyright © 2013 Elsevier B.V. All rights reserved.

Typhoid fever outbreak associated with frozen mamey pulp imported from Guatemala to the western United States, 2010.

PubMed

Loharikar, Anagha; Newton, Anna; Rowley, Patricia; Wheeler, Charlotte; Bruno, Tami; Barillas, Haroldo; Pruckler, James; Theobald, Lisa; Lance, Susan; Brown, Jeffrey M; Barzilay, Ezra J; Arvelo, Wences; Mintz, Eric; Fagan, Ryan

2012-07-01

Fifty-four outbreaks of domestically acquired typhoid fever were reported between 1960 and 1999. In 2010, the Southern Nevada Health District detected an outbreak of typhoid fever among persons who had not recently travelled abroad. We conducted a case-control study to examine the relationship between illness and exposures. A case was defined as illness with the outbreak strain of Salmonella serotype Typhi, as determined by pulsed-field gel electrophoresis (PFGE), with onset during 2010. Controls were matched by neighborhood, age, and sex. Bivariate and multivariate statistical analyses were completed using logistic regression. Traceback investigation was completed. We identified 12 cases in 3 states with onset from 15 April 2010 to 4 September 2010. The median age of case patients was 18 years (range, 4-48 years), 8 (67%) were female, and 11 (92%) were Hispanic. Nine (82%) were hospitalized; none died. Consumption of frozen mamey pulp in a fruit shake was reported by 6 of 8 case patients (75%) and none of the 33 controls (matched odds ratio, 33.9; 95% confidence interval, 4.9). Traceback investigations implicated 2 brands of frozen mamey pulp from a single manufacturer in Guatemala, which was also implicated in a 1998-1999 outbreak of typhoid fever in Florida. Reporting of individual cases of typhoid fever and subtyping of isolates by PFGE resulted in rapid detection of an outbreak associated with a ready-to-eat frozen food imported from a typhoid-endemic region. Improvements in food manufacturing practices and monitoring will prevent additional outbreaks.

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.

Detection of Zika virus using reverse-transcription LAMP coupled with reverse dot blot analysis in saliva

PubMed Central

Yasmin, Rubina; Barber, Cheryl A.; Castro, Talita; Malamud, Daniel; Kim, Beum Jun; Zhu, Hui; Montagna, Richard A.; Abrams, William R.

2018-01-01

In recent years, there have been increasing numbers of infectious disease outbreaks that spread rapidly to population centers resulting from global travel, population vulnerabilities, environmental factors, and ecological disasters such as floods and earthquakes. Some examples of the recent outbreaks are the Ebola epidemic in West Africa, Middle East respiratory syndrome coronavirus (MERS-Co) in the Middle East, and the Zika outbreak through the Americas. We have created a generic protocol for detection of pathogen RNA and/or DNA using loop-mediated isothermal amplification (LAMP) and reverse dot-blot for detection (RDB) and processed automatically in a microfluidic device. In particular, we describe how a microfluidic assay to detect HIV viral RNA was converted to detect Zika virus (ZIKV) RNA. We first optimized the RT-LAMP assay to detect ZIKV RNA using a benchtop isothermal amplification device. Then we implemented the assay in a microfluidic device that will allow analyzing 24 samples simultaneously and automatically from sample introduction to detection by RDB technique. Preliminary data using saliva samples spiked with ZIKV showed that our diagnostic system detects ZIKV RNA in saliva. These results will be validated in further experiments with well-characterized ZIKV human specimens of saliva. The described strategy and methodology to convert the HIV diagnostic assay and platform to a ZIKV RNA detection assay provides a model that can be readily utilized for detection of the next emerging or re-emerging infectious disease. PMID:29401479

Detection of Zika virus using reverse-transcription LAMP coupled with reverse dot blot analysis in saliva.

PubMed

Sabalza, Maite; Yasmin, Rubina; Barber, Cheryl A; Castro, Talita; Malamud, Daniel; Kim, Beum Jun; Zhu, Hui; Montagna, Richard A; Abrams, William R

2018-01-01

In recent years, there have been increasing numbers of infectious disease outbreaks that spread rapidly to population centers resulting from global travel, population vulnerabilities, environmental factors, and ecological disasters such as floods and earthquakes. Some examples of the recent outbreaks are the Ebola epidemic in West Africa, Middle East respiratory syndrome coronavirus (MERS-Co) in the Middle East, and the Zika outbreak through the Americas. We have created a generic protocol for detection of pathogen RNA and/or DNA using loop-mediated isothermal amplification (LAMP) and reverse dot-blot for detection (RDB) and processed automatically in a microfluidic device. In particular, we describe how a microfluidic assay to detect HIV viral RNA was converted to detect Zika virus (ZIKV) RNA. We first optimized the RT-LAMP assay to detect ZIKV RNA using a benchtop isothermal amplification device. Then we implemented the assay in a microfluidic device that will allow analyzing 24 samples simultaneously and automatically from sample introduction to detection by RDB technique. Preliminary data using saliva samples spiked with ZIKV showed that our diagnostic system detects ZIKV RNA in saliva. These results will be validated in further experiments with well-characterized ZIKV human specimens of saliva. The described strategy and methodology to convert the HIV diagnostic assay and platform to a ZIKV RNA detection assay provides a model that can be readily utilized for detection of the next emerging or re-emerging infectious disease.

Detection of Salmonella typhimurium in retail chicken meat and chicken giblets

PubMed Central

El-Aziz, Doaa M Abd

2013-01-01

Objective To detect Salmonella typhimurium (S. typhimurium), one of the most frequently isolated serovars from food borne outbreaks throughout the world, in retail raw chicken meat and giblets. Methods One hundred samples of retail raw chicken meat and giblets (Liver, heart and gizzard) which were collected from Assiut city markets for detection of the organism and by using Duplex PCR amplification of DNA using rfbJ and fliC genes. Results S. typhimurium was detected at rate of 44%, 40% and 48% in chicken meat, liver and heart, respectively, but not detected in gizzard. Conclusions The results showed high incidence of S. typhimurium in the examined samples and greater emphasis should be applied on prevention and control of contamination during processing for reducing food-borne risks to consumers. PMID:23998006

Clinical investigation of an outbreak of alveolitis and asthma in a car engine manufacturing plant

PubMed Central

Robertson, W; Robertson, A S; Burge, C B S G; Moore, V C; Jaakkola, M S; Dawkins, P A; Burd, M; Rawbone, R; Gardner, I; Kinoulty, M; Crook, B; Evans, G S; Harris‐Roberts, J; Rice, S; Burge, P S

2007-01-01

Background Exposure to metal working fluid (MWF) has been associated with outbreaks of extrinsic allergic alveolitis (EAA) in the USA, with bacterial contamination of MWF being a possible cause, but is uncommon in the UK. Twelve workers developed EAA in a car engine manufacturing plant in the UK, presenting clinically between December 2003 and May 2004. This paper reports the subsequent epidemiological investigation of the whole workforce. The study had three aims: (1) to measure the extent of the outbreak by identifying other workers who may have developed EAA or other work‐related respiratory diseases; (2) to provide case detection so that those affected could be treated; and (3) to provide epidemiological data to identify the cause of the outbreak. Methods The outbreak was investigated in a three‐phase cross‐sectional survey of the workforce. In phase I a respiratory screening questionnaire was completed by 808/836 workers (96.7%) in May 2004. In phase II 481 employees with at least one respiratory symptom on screening and 50 asymptomatic controls were invited for investigation at the factory in June 2004. This included a questionnaire, spirometry and clinical opinion. 454/481 (94.4%) responded and 48/50 (96%) controls. Workers were identified who needed further investigation and serial measurements of peak expiratory flow (PEF). In phase III 162 employees were seen at the Birmingham Occupational Lung Disease clinic. 198 employees returned PEF records, including 141 of the 162 who attended for clinical investigation. Case definitions for diagnoses were agreed. Results 87 workers (10.4% of the workforce) met case definitions for occupational lung disease, comprising EAA (n = 19), occupational asthma (n = 74) and humidifier fever (n = 7). 12 workers had more than one diagnosis. The peak onset of work‐related breathlessness was Spring 2003. The proportion of workers affected was higher for those using MWF from a large sump (27.3%) than for those working all over the manufacturing area (7.9%) (OR = 4.39, p<0.001). Two workers had positive specific provocation tests to the used but not the unused MWF solution. Conclusions Extensive investigation of the outbreak of EAA detected a large number of affected workers, not only with EAA but also occupational asthma. This is the largest reported outbreak in Europe. Mist from used MWF is the likely cause. In workplaces using MWF there is a need to carry out risk assessments, to monitor and maintain fluid quality, to control mist and to carry out respiratory health surveillance. PMID:17504818

Visual detection of Ebola virus using reverse transcription loop-mediated isothermal amplification combined with nucleic acid strip detection.

PubMed

Xu, Changping; Wang, Hualei; Jin, Hongli; Feng, Na; Zheng, Xuexing; Cao, Zengguo; Li, Ling; Wang, Jianzhong; Yan, Feihu; Wang, Lina; Chi, Hang; Gai, Weiwei; Wang, Chong; Zhao, Yongkun; Feng, Yan; Wang, Tiecheng; Gao, Yuwei; Lu, Yiyu; Yang, Songtao; Xia, Xianzhu

2016-05-01

Ebola virus (species Zaire ebolavirus) (EBOV) is highly virulent in humans. The largest recorded outbreak of Ebola hemorrhagic fever in West Africa to date was caused by EBOV. Therefore, it is necessary to develop a detection method for this virus that can be easily distributed and implemented. In the current study, we developed a visual assay that can detect EBOV-associated nucleic acids. This assay combines reverse transcription loop-mediated isothermal amplification and nucleic acid strip detection (RT-LAMP-NAD). Nucleic acid amplification can be achieved in a one-step process at a constant temperature (58 °C, 35 min), and the amplified products can be visualized within 2-5 min using a nucleic acid strip detection device. The assay is capable of detecting 30 copies of artificial EBOV glycoprotein (GP) RNA and RNA encoding EBOV GP from 10(2) TCID50 recombinant viral particles per ml with high specificity. Overall, the RT-LAMP-NAD method is simple and has high sensitivity and specificity; therefore, it is especially suitable for the rapid detection of EBOV in African regions.

Specificity of coliphages in evaluating marker efficacy: a new insight for water quality indicators.

PubMed

Mookerjee, Subham; Batabyal, Prasenjit; Halder, Madhumanti; Palit, Anup

2014-11-01

Conventional procedures for qualitative assessment of coliphage are time consuming multiple step approach for achieving results. A modified and rapid technique has been introduced for determination of coliphage contamination among potable water sources during water borne outbreaks. During December 2013, 40 water samples from different potable water sources, were received for water quality analyses, from a jaundice affected Municipality of West Bengal, India. Altogether, 30% water samples were contaminated with coliform (1-20 cfu/ml) and 5% with E. coli (2-5 cfu/ml). Among post-outbreak samples, preponderance of coliform has decreased (1-4 cfu/ml) with total absence of E. coli. While standard technique has detected 55% outbreak samples with coliphage contamination, modified technique revealed that 80%, double than that of bacteriological identification rate, were contaminated with coliphages (4-20 pfu/10 ml). However, post-outbreak samples were detected with 1-5 pfu/10 ml coliphages among 20% samples. Coliphage detection rate through modified technique was nearly double (50%) than that of standard technique (27.5%). In few samples (with coliform load of 10-100 cfu/ml), while modified technique could detect coliphages among six samples (10-20 pfu/10 ml), standard protocol failed to detect coliphage in any of them. An easy, rapid and accurate modified technique has thereby been implemented for coliphage assessment from water samples. Coliform free water does not always signify pathogen free potable water and it is demonstrated that coliphage is a more reliable 'biomarker' to ascertain contamination level in potable water. Copyright © 2014 Elsevier B.V. All rights reserved.

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

Increased norovirus activity was associated with a novel norovirus GII.17 variant in Beijing, China during winter 2014-2015.

PubMed

Gao, Zhiyong; Liu, Baiwei; Huo, Da; Yan, Hanqiu; Jia, Lei; Du, Yiwei; Qian, Haikun; Yang, Yang; Wang, Xiaoli; Li, Jie; Wang, Quanyi

2015-12-18

Norovirus (NoV) is a leading cause of sporadic cases and outbreaks of acute gastroenteritis (AGE). Increased NoV activity was observed in Beijing, China during winter 2014-2015; therefore, we examined the epidemiological patterns and genetic characteristics of NoV in the sporadic cases and outbreaks. The weekly number of infectious diarrhea cases reported by all hospitals in Beijing was analyzed through the China information system for disease control and prevention. Fecal specimens were collected from the outbreaks and outpatients with AGE, and GI and GII NoVs were detected using real time reverse transcription polymerase chain reaction. The partial capsid genes and RNA-dependent RNA polymerase (RdRp) genes of NoV were both amplified and sequenced, and genotyping and phylogenetic analyses were performed. Between December 2014 and March 2015, the number of infectious diarrhea cases in Beijing (10,626 cases) increased by 35.6% over that of the previous year (7835 cases), and the detection rate of NoV (29.8%, 191/640) among outpatients with AGE was significantly higher than in the previous year (12.9%, 79/613) (χ(2) = 53.252, P < 0.001). Between November 2014 and March 2015, 35 outbreaks of AGE were reported in Beijing, and NoVs were detected in 33 outbreaks, all of which belonged to the GII genogroup. NoVs were sequenced and genotyped in 22 outbreaks, among which 20 were caused by a novel GII.17 strain. Among outpatients with AGE, this novel GII.17 strain was first detected in an outpatient in August 2014, and it replaced GII.4 Sydney_2012 as the predominant variant between December 2014 and March 2015. A phylogenetic analysis of the capsid genes and RdRp genes revealed that this novel GII.17 strain was distinct from previously identified GII variants, and it was recently designated as GII.P17_GII.17. This variant was further clustered into two sub-groups, named GII.17_2012 and GII.17_2014. During winter 2014-2015, GII.17_2014 caused the majority of AGE outbreaks in China and Japan. During winter 2014-2015, a novel NoV GII.17 variant replaced the GII.4 variant Sydney 2012 as the predominant strain in Beijing, China and caused increased NoV activity.

Networks and tuberculosis: an undetected community outbreak involving public places.

PubMed

Klovdahl, A S; Graviss, E A; Yaganehdoost, A; Ross, M W; Wanger, A; Adams, G J; Musser, J M

2001-03-01

After decades of decline in developed countries, there was a resurgence of tuberculosis in the mid-1980s accompanied by increased recognition that this infectious disease has long remained a major public health problem at the global level. New methods from molecular biology, in particular DNA 'fingerprinting' (of Mycobacterium tuberculosis), made it clear that current transmission and recent infection (in contrast to reactivation of earlier, latent infection) were much more significant than previously believed. Studies of tuberculosis outbreaks using these new tools pointed to complex networks through which infection was spreading and highlighted the need for new approaches to outbreak investigation and disease control. In the study reported here a new approach--combining methods from molecular biology, epidemiology and network analysis--was used to examine an outbreak of tuberculosis in Houston, Texas. Initial investigation using conventional strategies revealed few contacts among 37 patients with identical (six-band) DNA (IS6110-based) fingerprints but subsequent research uncovered over 40 places (including many gay bars) to which patients in this outbreak could be linked. Network methods were used to reconstruct an outbreak network and to quantify the relative importance (here, 'betweenness' centrality) of different actors (persons and places) playing a role in the outbreak. The multidisciplinary work provides the basis for a new approach to outbreak investigation and disease control.

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.

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

PubMed

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

2014-05-12

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

Comparative Recovery of Two Human Norovirus Surrogates, Feline Calicivirus and Murine Norovirus, with a Wet Vacuum System, Macrofoam-Tipped Swab, and Bottle Extraction Method from Carpets.

PubMed

Buckley, David; Fraser, Angela; Pettigrew, Charles; Anderson, Jeffery; Jiang, Xiuping

2018-05-10

Human noroviruses (HuNoV) are the leading cause of known foodborne illness in the United States, but direct detection during outbreak investigations is challenging. On the other hand, sampling both hard and soft environmental surfaces can be used to improve outbreak investigations. Currently, we lack virus recovery methods for soft surfaces, such as carpet, despite evidence suggesting that carpets contribute to HuNoV outbreaks. Our aim was to compare two recovery methods, wet vacuum and swabbing, for routine carpet sampling of HuNoV against a laboratory reference method known as bottle extraction (BE). Specifically, we compared the microbial vacuum (MVAC), macrofoam-tipped swab (MS), and BE by using HuNoV surrogates, feline calicivirus (FCV) and murine norovirus (MNV), inoculated on wool and nylon carpet carriers. The highest recovery of infectious FCV from wool was 5.51, 3.76, and 5.16 log PFU, whereas on nylon, recovery was 5.03, 3.62, and 4.75 log PFU by using BE, MS, and MVAC, respectively. On the other hand, the highest recovery of infectious MNV from wool was 6.10, 4.50, and 5.99 log PFU, while recovery on nylon was 6.07, 4.58, and 6.13 log PFU by using BE, MS, and MVAC, respectively. Significantly more PFU and genomic copies were recovered by using BE and MVAC compared with MS, while buffer type played a significant role in recovery of infectious FCV.

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.

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.

Natural vertical transmission of dengue viruses by Aedes aegypti in Bolivia

PubMed Central

Le Goff, G.; Revollo, J.; Guerra, M.; Cruz, M.; Barja Simon, Z.; Roca, Y.; Vargas Florès, J.; Hervé, J.P.

2011-01-01

The natural transmission of dengue virus from an infected female mosquito to its progeny, namely the vertical transmission, was researched in wild caught Aedes aegypti during an important outbreak in the town of Santa Cruz de la Sierra, Bolivia. Mosquitoes were collected at the preimaginal stages (eggs, larvae and pupae) then reared up to adult stage for viral detection using molecular methods. Dengue virus serotypes 1 and 3 were found to be co-circulating with significant higher prevalence in male than in female mosquitoes. Of the 97 pools of Ae. aegypti (n = 635 male and 748 female specimens) screened, 14 pools, collected in February-May in 2007, were found positive for dengue virus infection: five DEN-1 and nine DEN-3. The average true infection rate (TIR) and minimum infection rate (MIR) were respectively 1.08% and 1.01%. These observations suggest that vertical transmission of dengue virus may be detected in vectors at the peak of an outbreak as well as several months before an epidemic occurs in human population. PMID:21894270

Whole-Genome Sequencing of Recent Listeria monocytogenes Isolates from Germany Reveals Population Structure and Disease Clusters.

PubMed

Halbedel, Sven; Prager, Rita; Fuchs, Stephan; Trost, Eva; Werner, Guido; Flieger, Antje

2018-06-01

Listeria monocytogenes causes foodborne outbreaks with high mortality. For improvement of outbreak cluster detection, the German consiliary laboratory for listeriosis implemented whole-genome sequencing (WGS) in 2015. A total of 424 human L. monocytogenes isolates collected in 2007 to 2017 were subjected to WGS and core-genome multilocus sequence typing (cgMLST). cgMLST grouped the isolates into 38 complexes, reflecting 4 known and 34 unknown disease clusters. Most of these complexes were confirmed by single nucleotide polymorphism (SNP) calling, but some were further differentiated. Interestingly, several cgMLST cluster types were further subtyped by pulsed-field gel electrophoresis, partly due to phage insertions in the accessory genome. Our results highlight the usefulness of cgMLST for routine cluster detection but also show that cgMLST complexes require validation by methods providing higher typing resolution. Twelve cgMLST clusters included recent cases, suggesting activity of the source. Therefore, the cgMLST nomenclature data presented here may support future public health actions. Copyright © 2018 American Society for Microbiology.