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

PubMed Central

Le Strat, Yann

2017-01-01

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

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.

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.

'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.

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

PubMed

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

2011-06-01

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

Building test data from real outbreaks for evaluating detection algorithms.

PubMed

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

2017-01-01

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

Building test data from real outbreaks for evaluating detection algorithms

PubMed Central

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

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method—ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals. PMID:28863159

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

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.

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

Detection of disease outbreaks by the use of oral manifestations.

PubMed

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

2009-01-01

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

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 Cough-Based Algorithm for Automatic Diagnosis of Pertussis.

PubMed

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control.

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

PubMed Central

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. PMID:27583523

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2013-01-01

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

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.

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.

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

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

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.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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).

Developing a disease outbreak event corpus.

PubMed

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

2010-09-28

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

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.

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.

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

PubMed

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

2014-11-18

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

Dose-response algorithms for water-borne Pseudomonas aeruginosa folliculitis.

PubMed

Roser, D J; Van Den Akker, B; Boase, S; Haas, C N; Ashbolt, N J; Rice, S A

2015-05-01

We developed two dose-response algorithms for P. aeruginosa pool folliculitis using bacterial and lesion density estimates, associated with undetectable, significant, and almost certain folliculitis. Literature data were fitted to Furumoto & Mickey's equations, developed for plant epidermis-invading pathogens: N l = A ln(1 + BC) (log-linear model); P inf = 1-e(-r c C) (exponential model), where A and B are 2.51644 × 107 lesions/m2 and 2.28011 × 10-11 c.f.u./ml P. aeruginosa, respectively; C = pathogen density (c.f.u./ml), N l = folliculitis lesions/m2, P inf = probability of infection, and r C = 4·3 × 10-7 c.f.u./ml P. aeruginosa. Outbreak data indicates these algorithms apply to exposure durations of 41 ± 25 min. Typical water quality benchmarks (≈10-2 c.f.u./ml) appear conservative but still useful as the literature indicated repeated detection likely implies unstable control barriers and bacterial bloom potential. In future, culture-based outbreak testing should be supplemented with quantitative polymerase chain reaction and organic carbon assays, and quantification of folliculitis aetiology to better understand P. aeruginosa risks.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

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.

Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System.

PubMed Central

Tsui, Fu-Chiang; Espino, Jeremy U.; Wagner, Michael M.; Gesteland, Per; Ivanov, Oleg; Olszewski, Robert T.; Liu, Zhen; Zeng, Xiaoming; Chapman, Wendy; Wong, Weng Keen; Moore, Andrew

2002-01-01

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system. PMID:12463938

Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System.

PubMed

Tsui, Fu-Chiang; Espino, Jeremy U; Wagner, Michael M; Gesteland, Per; Ivanov, Oleg; Olszewski, Robert T; Liu, Zhen; Zeng, Xiaoming; Chapman, Wendy; Wong, Weng Keen; Moore, Andrew

2002-01-01

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system.

Towards cross-lingual alerting for bursty epidemic events.

PubMed

Collier, Nigel

2011-10-06

Online news reports are increasingly becoming a source for event-based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challanges as opportunities due to the patterns of reporting complex spatio-temporal events. In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup.

Technical description of RODS: a real-time public health surveillance system.

PubMed

Tsui, Fu-Chiang; Espino, Jeremy U; Dato, Virginia M; Gesteland, Per H; Hutman, Judith; Wagner, Michael M

2003-01-01

This report describes the design and implementation of the Real-time Outbreak and Disease Surveillance (RODS) system, a computer-based public health surveillance system for early detection of disease outbreaks. Hospitals send RODS data from clinical encounters over virtual private networks and leased lines using the Health Level 7 (HL7) message protocol. The data are sent in real time. RODS automatically classifies the registration chief complaint from the visit into one of seven syndrome categories using Bayesian classifiers. It stores the data in a relational database, aggregates the data for analysis using data warehousing techniques, applies univariate and multivariate statistical detection algorithms to the data, and alerts users of when the algorithms identify anomalous patterns in the syndrome counts. RODS also has a Web-based user interface that supports temporal and spatial analyses. RODS processes sales of over-the-counter health care products in a similar manner but receives such data in batch mode on a daily basis. RODS was used during the 2002 Winter Olympics and currently operates in two states-Pennsylvania and Utah. It has been and continues to be a resource for implementing, evaluating, and applying new methods of public health surveillance.

A multi-data source surveillance system to detect a bioterrorism attack during the G8 Summit in Scotland.

PubMed

Meyer, N; McMenamin, J; Robertson, C; Donaghy, M; Allardice, G; Cooper, D

2008-07-01

In 18 weeks, Health Protection Scotland (HPS) deployed a syndromic surveillance system to early-detect natural or intentional disease outbreaks during the G8 Summit 2005 at Gleneagles, Scotland. The system integrated clinical and non-clinical datasets. Clinical datasets included Accident & Emergency (A&E) syndromes, and General Practice (GPs) codes grouped into syndromes. Non-clinical data included telephone calls to a nurse helpline, laboratory test orders, and hotel staff absenteeism. A cumulative sum-based detection algorithm and a log-linear regression model identified signals in the data. The system had a fax-based track for real-time identification of unusual presentations. Ninety-five signals were triggered by the detection algorithms and four forms were faxed to HPS. Thirteen signals were investigated. The system successfully complemented a traditional surveillance system in identifying a small cluster of gastroenteritis among the police force and triggered interventions to prevent further cases.

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

PubMed Central

Burkom, Howard; Xing, Jian; English, Roseanne; Bloom, Steven; Cox, Kenneth; Pavlin, Julie A.

2009-01-01

BioSense is a US national system that uses data from health information systems for automated disease surveillance. We studied 4 time-series algorithm modifications designed to improve sensitivity for detecting artificially added data. To test these modified algorithms, we used reports of daily syndrome visits from 308 Department of Defense (DoD) facilities and 340 hospital emergency departments (EDs). At a constant alert rate of 1%, sensitivity was improved for both datasets by using a minimum standard deviation (SD) of 1.0, a 14–28 day baseline duration for calculating mean and SD, and an adjustment for total clinic visits as a surrogate denominator. Stratifying baseline days into weekdays versus weekends to account for day-of-week effects increased sensitivity for the DoD data but not for the ED data. These enhanced methods may increase sensitivity without increasing the alert rate and may improve the ability to detect outbreaks by using automated surveillance system data. PMID:19331728

Dengue Contingency Planning: From Research to Policy and Practice.

PubMed

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

2016-09-01

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

Development and evaluation of a data-adaptive alerting algorithm for univariate temporal biosurveillance data.

PubMed

Elbert, Yevgeniy; Burkom, Howard S

2009-11-20

This paper discusses further advances in making robust predictions with the Holt-Winters forecasts for a variety of syndromic time series behaviors and introduces a control-chart detection approach based on these forecasts. Using three collections of time series data, we compare biosurveillance alerting methods with quantified measures of forecast agreement, signal sensitivity, and time-to-detect. The study presents practical rules for initialization and parameterization of biosurveillance time series. Several outbreak scenarios are used for detection comparison. We derive an alerting algorithm from forecasts using Holt-Winters-generalized smoothing for prospective application to daily syndromic time series. The derived algorithm is compared with simple control-chart adaptations and to more computationally intensive regression modeling methods. The comparisons are conducted on background data from both authentic and simulated data streams. Both types of background data include time series that vary widely by both mean value and cyclic or seasonal behavior. Plausible, simulated signals are added to the background data for detection performance testing at signal strengths calculated to be neither too easy nor too hard to separate the compared methods. Results show that both the sensitivity and the timeliness of the Holt-Winters-based algorithm proved to be comparable or superior to that of the more traditional prediction methods used for syndromic surveillance.

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.

Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group.

PubMed

Buehler, James W; Hopkins, Richard S; Overhage, J Marc; Sosin, Daniel M; Tong, Van

2004-05-07

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health surveillance systems for early detection of outbreaks. State and local health departments are enhancing existing surveillance systems and developing new systems to better detect outbreaks through public health surveillance. However, information is limited about the usefulness of surveillance systems for outbreak detection or the best ways to support this function. This report supplements previous guidelines for evaluating public health surveillance systems. Use of this framework is intended to improve decision-making regarding the implementation of surveillance for outbreak detection. Use of a standardized evaluation methodology, including description of system design and operation, also will enhance the exchange of information regarding methods to improve early detection of outbreaks. The framework directs particular attention to the measurement of timeliness and validity for outbreak detection. The evaluation framework is designed to support assessment and description of all surveillance approaches to early detection, whether through traditional disease reporting, specialized analytic routines for aberration detection, or surveillance using early indicators of disease outbreaks, such as syndromic surveillance.

in silico Surveillance: evaluating outbreak detection with simulation models

PubMed Central

2013-01-01

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

Dengue Contingency Planning: From Research to Policy and Practice

PubMed Central

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

2016-01-01

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

DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response.

PubMed

Thapen, Nicholas; Simmie, Donal; Hankin, Chris; Gillard, Joseph

2016-01-01

In recent years social and news media have increasingly been used to explain patterns in disease activity and progression. Social media data, principally from the Twitter network, has been shown to correlate well with official disease case counts. This fact has been exploited to provide advance warning of outbreak detection, forecasting of disease levels and the ability to predict the likelihood of individuals developing symptoms. In this paper we introduce DEFENDER, a software system that integrates data from social and news media and incorporates algorithms for outbreak detection, situational awareness and forecasting. As part of this system we have developed a technique for creating a location network for any country or region based purely on Twitter data. We also present a disease nowcasting (forecasting the current but still unknown level) approach which leverages counts from multiple symptoms, which was found to improve the nowcasting accuracy by 37 percent over a model that used only previous case data. Finally we attempt to forecast future levels of symptom activity based on observed user movement on Twitter, finding a moderate gain of 5 percent over a time series forecasting model.

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.

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

PubMed

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

2017-11-24

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

Adapting MODIS Dust Mask Algorithm to Suomi NPP VIIRS for Air Quality Applications

NASA Astrophysics Data System (ADS)

Ciren, P.; Liu, H.; Kondragunta, S.; Laszlo, I.

2012-12-01

Despite pollution reduction control strategies enforced by the Environmental Protection Agency (EPA), large regions of the United States are often under exceptional events such as biomass burning and dust outbreaks that lead to non-attainment of particulate matter standards. This has warranted the National Weather Service (NWS) to provide smoke and dust forecast guidance to the general public. The monitoring and forecasting of dust outbreaks relies on satellite data. Currently, Aqua/MODIS (MODerate resolution Imaging Spectrometer) and Terra/MODIS provide measurements needed to derive dust mask and Aerosol Optical Thickness (AOT) products. The newly launched Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument has a Suspended Matter (SM) product that indicates the presence of dust, smoke, volcanic ash, sea salt, and unknown aerosol types in a given pixel. The algorithm to identify dust is different over land and ocean but for both, the information comes from AOT retrieval algorithm. Over land, the selection of dust aerosol model in the AOT retrieval algorithm indicates the presence of dust and over ocean a fine mode fraction smaller than 20% indicates dust. Preliminary comparisons of VIIRS SM to CALIPSO Vertical Feature Mask (VFM) aerosol type product indicate that the Probability of Detection (POD) is at ~10% and the product is not mature for operational use. As an alternate approach, NESDIS dust mask algorithm developed for NWS dust forecast verification that uses MODIS deep blue, visible, and mid-IR channels using spectral differencing techniques and spatial variability tests was applied to VIIRS radiances. This algorithm relies on the spectral contrast of dust absorption at 412 and 440 nm and an increase in reflectivity at 2.13 μm when dust is present in the atmosphere compared to a clear sky. To avoid detecting bright desert surface as airborne dust, the algorithm uses the reflectances at 1.24 μm and 2.25 μm to flag bright pixels. The algorithm flags pixels that fall into the glint region so sun glint is not picked up as dust. The algorithm also has a spatial variability test that uses reflectances at 0.86 μm to screen for clouds over water. Analysis of one granule for a known dust event on May 2, 2012 shows that the agreement between VIIRS and MODIS is 82% and VIIRS and CALIPSO is 71%. The probability of detection for VIIRS when compared to MODIS and CALIPSO is 53% and 45% respectively whereas the false alarm ratio for VIIRS when compared to MODIS and CALIPSO is 20% and 37% respectively. The algorithm details, results from the test cases, and the use of the dust flag product in NWS applications will be presented.

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

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.

Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.

PubMed

Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jansen, Ruud; Den Boer, Jeroen W

2012-01-01

Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

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

PubMed

Wang, Jiao; Deng, Zhiqiang

2012-09-01

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

DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response

PubMed Central

Simmie, Donal; Hankin, Chris; Gillard, Joseph

2016-01-01

In recent years social and news media have increasingly been used to explain patterns in disease activity and progression. Social media data, principally from the Twitter network, has been shown to correlate well with official disease case counts. This fact has been exploited to provide advance warning of outbreak detection, forecasting of disease levels and the ability to predict the likelihood of individuals developing symptoms. In this paper we introduce DEFENDER, a software system that integrates data from social and news media and incorporates algorithms for outbreak detection, situational awareness and forecasting. As part of this system we have developed a technique for creating a location network for any country or region based purely on Twitter data. We also present a disease nowcasting (forecasting the current but still unknown level) approach which leverages counts from multiple symptoms, which was found to improve the nowcasting accuracy by 37 percent over a model that used only previous case data. Finally we attempt to forecast future levels of symptom activity based on observed user movement on Twitter, finding a moderate gain of 5 percent over a time series forecasting model. PMID:27192059

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

Control fast or control smart: When should invading pathogens be controlled?

PubMed

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

2018-02-01

The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.

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.

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

PubMed

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

2017-04-01

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

Molecular diagnosis of Legionella infections--Clinical utility of front-line screening as part of a pneumonia diagnostic algorithm.

PubMed

Gadsby, Naomi J; Helgason, Kristjan O; Dickson, Elizabeth M; Mills, Jonathan M; Lindsay, Diane S J; Edwards, Giles F; Hanson, Mary F; Templeton, Kate E

2016-02-01

Urinary antigen testing for Legionella pneumophila serogroup 1 is the leading rapid diagnostic test for Legionnaires' Disease (LD); however other Legionella species and serogroups can also cause LD. The aim was to determine the utility of front-line L. pneumophila and Legionella species PCR in a severe respiratory infection algorithm. L. pneumophila and Legionella species duplex real-time PCR was carried out on 1944 specimens from hospitalised patients over a 4 year period in Edinburgh, UK. L. pneumophila was detected by PCR in 49 (2.7%) specimens from 36 patients. During a LD outbreak, combined L. pneumophila respiratory PCR and urinary antigen testing had optimal sensitivity and specificity (92.6% and 98.3% respectively) for the detection of confirmed cases. Legionella species was detected by PCR in 16 (0.9%) specimens from 10 patients. The 5 confirmed and 1 probable cases of Legionella longbeachae LD were both PCR and antibody positive. Front-line L. pneumophila and Legionella species PCR is a valuable addition to urinary antigen testing as part of a well-defined algorithm. Cases of LD due to L. longbeachae might be considered laboratory-confirmed when there is a positive Legionella species PCR result and detection of L. longbeachae specific antibody response. Copyright © 2015 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2006-06-01

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

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.

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication

PubMed Central

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

2016-01-01

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

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication.

PubMed

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

2016-03-01

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

Characterizing recent and projecting future potential patterns of mountain pine beetle outbreaks in the Southern Rocky Mountains

USGS Publications Warehouse

Liang, Lu; Hawbaker, Todd J.; Chen, Yanlei; Zhu, Zhi-Liang; Gong, Peng

2014-01-01

The recent widespread mountain pine beetle (MPB) outbreak in the Southern Rocky Mountains presents an opportunity to investigate the relative influence of anthropogenic, biologic, and physical drivers that have shaped the spatiotemporal patterns of the outbreak. The aim of this study was to quantify the landscape-level drivers that explained the dynamic patterns of MPB mortality, and simulate areas with future potential MPB mortality under projected climate-change scenarios in Grand County, Colorado, USA. The outbreak patterns of MPB were characterized by analysis of a decade-long Landsat time-series stack, aided by automatic attribution of change detected by the Landsat-based Detection of Trends in Disturbance and Recovery algorithm (LandTrendr). The annual area of new MPB mortality was then related to a suite of anthropogenic, biologic, and physical predictor variables under a general linear model (GLM) framework. Data from years 2001–2005 were used to train the model and data from years 2006–2011 were retained for validation. After stepwise removal of non-significant predictors, the remaining predictors in the GLM indicated that neighborhood mortality, winter mean temperature anomaly, and residential housing density were positively associated with MPB mortality, whereas summer precipitation was negatively related. The final model had an average area under the curve (AUC) of a receiver operating characteristic plot value of 0.72 in predicting the annual area of new mortality for the independent validation years, and the mean deviation from the base maps in the MPB mortality areal estimates was around 5%. The extent of MPB mortality will likely expand under two climate-change scenarios (RCP 4.5 and 8.5) in Grand County, which implies that the impacts of MPB outbreaks on vegetation composition and structure, and ecosystem functioning are likely to increase in the future.

Emergency Department Chief Complaint and Diagnosis Data to Detect Influenza-Like Illness with an Electronic Medical Record

PubMed Central

May, Larissa S.; Griffin, Beth Ann; Bauers, Nicole Maier; Jain, Arvind; Mitchum, Marsha; Sikka, Neal; Carim, Marianne; Stoto, Michael A.

2010-01-01

Background: The purpose of syndromic surveillance is early detection of a disease outbreak. Such systems rely on the earliest data, usually chief complaint. The growing use of electronic medical records (EMR) raises the possibility that other data, such as emergency department (ED) diagnosis, may provide more specific information without significant delay, and might be more effective in detecting outbreaks if mechanisms are in place to monitor and report these data. Objective: The purpose of this study is to characterize the added value of the primary ICD-9 diagnosis assigned at the time of ED disposition compared to the chief complaint for patients with influenza-like illness (ILI). Methods: The study was a retrospective analysis of the EMR of a single urban, academic ED with an annual census of over 60, 000 patients per year from June 2005 through May 2006. We evaluate the objective in two ways. First, we characterize the proportion of patients whose ED diagnosis is inconsistent with their chief complaint and the variation by complaint. Second, by comparing time series and applying syndromic detection algorithms, we determine which complaints and diagnoses are the best indicators for the start of the influenza season when compared to the Centers for Disease Control regional data for Influenza-Like Illness for the 2005 to 2006 influenza season using three syndromic surveillance algorithms: univariate cumulative sum (CUSUM), exponentially weighted CUSUM, and multivariate CUSUM. Results: In the first analysis, 29% of patients had a different diagnosis at the time of disposition than suggested by their chief complaint. In the second analysis, complaints and diagnoses consistent with pneumonia, viral illness and upper respiratory infection were together found to be good indicators of the start of the influenza season based on temporal comparison with regional data. In all examples, the diagnosis data outperformed the chief-complaint data. Conclusion: Both analyses suggest the ED diagnosis contains useful information for detection of ILI. Where an EMR is available, the short time lag between complaint and diagnosis may be a price worth paying for additional information despite the brief potential delay in detection, especially considering that detection usually occurs over days rather than hours. PMID:20411066

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.

Fever detection from free-text clinical records for biosurveillance.

PubMed

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

2004-04-01

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

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.

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

PubMed

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

2018-05-30

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

Usefulness of syndromic data sources for investigating morbidity resulting from a severe weather event.

PubMed

Baer, Atar; Elbert, Yevgeniy; Burkom, Howard S; Holtry, Rekha; Lombardo, Joseph S; Duchin, Jeffrey S

2011-03-01

We evaluated emergency department (ED) data, emergency medical services (EMS) data, and public utilities data for describing an outbreak of carbon monoxide (CO) poisoning following a windstorm. Syndromic ED data were matched against previously collected chart abstraction data. We ran detection algorithms on selected time series derived from all 3 data sources to identify health events associated with the CO poisoning outbreak. We used spatial and spatiotemporal scan statistics to identify geographic areas that were most heavily affected by the CO poisoning event. Of the 241 CO cases confirmed by chart review, 190 (78.8%) were identified in the syndromic surveillance data as exact matches. Records from the ED and EMS data detected an increase in CO-consistent syndromes after the storm. The ED data identified significant clusters of CO-consistent syndromes, including zip codes that had widespread power outages. Weak temporal gastrointestinal (GI) signals, possibly resulting from ingestion of food spoiled by lack of refrigeration, were detected in the ED data but not in the EMS data. Spatial clustering of GI-based groupings in the ED data was not detected. Data from this evaluation support the value of ED data for surveillance after natural disasters. Enhanced EMS data may be useful for monitoring a CO poisoning event, if these data are available to the health department promptly. ©2011 American Medical Association. All rights reserved.

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

PubMed

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

2015-02-01

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

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

PubMed Central

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

2014-01-01

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

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.

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.

Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection.

PubMed

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

2013-01-01

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

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.

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

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.

Solving the patient zero inverse problem by using generalized simulated annealing

NASA Astrophysics Data System (ADS)

Menin, Olavo H.; Bauch, Chris T.

2018-01-01

Identifying patient zero - the initially infected source of a given outbreak - is an important step in epidemiological investigations of both existing and emerging infectious diseases. Here, the use of the Generalized Simulated Annealing algorithm (GSA) to solve the inverse problem of finding the source of an outbreak is studied. The classical disease natural histories susceptible-infected (SI), susceptible-infected-susceptible (SIS), susceptible-infected-recovered (SIR) and susceptible-infected-recovered-susceptible (SIRS) in a regular lattice are addressed. Both the position of patient zero and its time of infection are considered unknown. The algorithm performance with respect to the generalization parameter q˜v and the fraction ρ of infected nodes for whom infection was ascertained is assessed. Numerical experiments show the algorithm is able to retrieve the epidemic source with good accuracy, even when ρ is small, but present no evidence to support that GSA performs better than its classical version. Our results suggest that simulated annealing could be a helpful tool for identifying patient zero in an outbreak where not all cases can be ascertained.

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.

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.

Mining the key predictors for event outbreaks in social networks

NASA Astrophysics Data System (ADS)

Yi, Chengqi; Bao, Yuanyuan; Xue, Yibo

2016-04-01

It will be beneficial to devise a method to predict a so-called event outbreak. Existing works mainly focus on exploring effective methods for improving the accuracy of predictions, while ignoring the underlying causes: What makes event go viral? What factors that significantly influence the prediction of an event outbreak in social networks? In this paper, we proposed a novel definition for an event outbreak, taking into account the structural changes to a network during the propagation of content. In addition, we investigated features that were sensitive to predicting an event outbreak. In order to investigate the universality of these features at different stages of an event, we split the entire lifecycle of an event into 20 equal segments according to the proportion of the propagation time. We extracted 44 features, including features related to content, users, structure, and time, from each segment of the event. Based on these features, we proposed a prediction method using supervised classification algorithms to predict event outbreaks. Experimental results indicate that, as time goes by, our method is highly accurate, with a precision rate ranging from 79% to 97% and a recall rate ranging from 74% to 97%. In addition, after applying a feature-selection algorithm, the top five selected features can considerably improve the accuracy of the prediction. Data-driven experimental results show that the entropy of the eigenvector centrality, the entropy of the PageRank, the standard deviation of the betweenness centrality, the proportion of re-shares without content, and the average path length are the key predictors for an event outbreak. Our findings are especially useful for further exploring the intrinsic characteristics of outbreak prediction.

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.

Multiplex PCR Tests for Detection of Pathogens Associated with Gastroenteritis

PubMed Central

Zhang, Hongwei; Morrison, Scott; Tang, Yi-Wei

2016-01-01

Synopsis A wide range of enteric pathogens can cause infectious gastroenteritis. Conventional diagnostic algorithms including culture, biochemical identification, immunoassay and microscopic examination are time consuming and often lack sensitivity and specificity. Advances in molecular technology have as allowed its use as clinical diagnostic tools. Multiplex PCR based testing has made its way to gastroenterology diagnostic arena in recent years. In this article we present a review of recent laboratory developed multiplex PCR tests and current commercial multiplex gastrointestinal pathogen tests. We will focus on two FDA cleared commercial syndromic multiplex tests: Luminex xTAG GPP and Biofire FimArray GI test. These multiplex tests can detect and identify multiple enteric pathogens in one test and provide results within hours. Multiplex PCR tests have shown superior sensitivity to conventional methods for detection of most pathogens. The high negative predictive value of these multiplex tests has led to the suggestion that they be used as screening tools especially in outbreaks. Although the clinical utility and benefit of multiplex PCR test are to be further investigated, implementing these multiplex PCR tests in gastroenterology diagnostic algorithm has the potential to improve diagnosis of infectious gastroenteritis. PMID:26004652

Recursive least squares background prediction of univariate syndromic surveillance data

PubMed Central

2009-01-01

Background Surveillance of univariate syndromic data as a means of potential indicator of developing public health conditions has been used extensively. This paper aims to improve the performance of detecting outbreaks by using a background forecasting algorithm based on the adaptive recursive least squares method combined with a novel treatment of the Day of the Week effect. Methods Previous work by the first author has suggested that univariate recursive least squares analysis of syndromic data can be used to characterize the background upon which a prediction and detection component of a biosurvellance system may be built. An adaptive implementation is used to deal with data non-stationarity. In this paper we develop and implement the RLS method for background estimation of univariate data. The distinctly dissimilar distribution of data for different days of the week, however, can affect filter implementations adversely, and so a novel procedure based on linear transformations of the sorted values of the daily counts is introduced. Seven-days ahead daily predicted counts are used as background estimates. A signal injection procedure is used to examine the integrated algorithm's ability to detect synthetic anomalies in real syndromic time series. We compare the method to a baseline CDC forecasting algorithm known as the W2 method. Results We present detection results in the form of Receiver Operating Characteristic curve values for four different injected signal to noise ratios using 16 sets of syndromic data. We find improvements in the false alarm probabilities when compared to the baseline W2 background forecasts. Conclusion The current paper introduces a prediction approach for city-level biosurveillance data streams such as time series of outpatient clinic visits and sales of over-the-counter remedies. This approach uses RLS filters modified by a correction for the weekly patterns often seen in these data series, and a threshold detection algorithm from the residuals of the RLS forecasts. We compare the detection performance of this algorithm to the W2 method recently implemented at CDC. The modified RLS method gives consistently better sensitivity at multiple background alert rates, and we recommend that it should be considered for routine application in bio-surveillance systems. PMID:19149886

Recursive least squares background prediction of univariate syndromic surveillance data.

PubMed

Najmi, Amir-Homayoon; Burkom, Howard

2009-01-16

Surveillance of univariate syndromic data as a means of potential indicator of developing public health conditions has been used extensively. This paper aims to improve the performance of detecting outbreaks by using a background forecasting algorithm based on the adaptive recursive least squares method combined with a novel treatment of the Day of the Week effect. Previous work by the first author has suggested that univariate recursive least squares analysis of syndromic data can be used to characterize the background upon which a prediction and detection component of a biosurvellance system may be built. An adaptive implementation is used to deal with data non-stationarity. In this paper we develop and implement the RLS method for background estimation of univariate data. The distinctly dissimilar distribution of data for different days of the week, however, can affect filter implementations adversely, and so a novel procedure based on linear transformations of the sorted values of the daily counts is introduced. Seven-days ahead daily predicted counts are used as background estimates. A signal injection procedure is used to examine the integrated algorithm's ability to detect synthetic anomalies in real syndromic time series. We compare the method to a baseline CDC forecasting algorithm known as the W2 method. We present detection results in the form of Receiver Operating Characteristic curve values for four different injected signal to noise ratios using 16 sets of syndromic data. We find improvements in the false alarm probabilities when compared to the baseline W2 background forecasts. The current paper introduces a prediction approach for city-level biosurveillance data streams such as time series of outpatient clinic visits and sales of over-the-counter remedies. This approach uses RLS filters modified by a correction for the weekly patterns often seen in these data series, and a threshold detection algorithm from the residuals of the RLS forecasts. We compare the detection performance of this algorithm to the W2 method recently implemented at CDC. The modified RLS method gives consistently better sensitivity at multiple background alert rates, and we recommend that it should be considered for routine application in bio-surveillance systems.

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

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.

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

PubMed

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

2007-04-15

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

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.

Strengthening the diagnostic capacity to detect Bio Safety Level 3 organisms in unusual respiratory viral outbreaks.

PubMed

van Asten, Liselotte; van der Lubben, Mariken; van den Wijngaard, Cees; van Pelt, Wilfrid; Verheij, Robert; Jacobi, Andre; Overduin, Pieter; Meijer, Adam; Luijt, Dirk; Claas, Eric; Hermans, Mirjam; Melchers, Willem; Rossen, John; Schuurman, Rob; Wolffs, Petra; Boucher, Charles; Bouchier, Charles; Schirm, Jurjen; Kroes, Louis; Leenders, Sander; Galama, Joep; Peeters, Marcel; van Loon, Anton; Stobberingh, Ellen; Schutten, Martin; Koopmans, Marion

2009-07-01

Experience with a highly pathogenic avian influenza outbreak in the Netherlands (2003) illustrated that the diagnostic demand for respiratory viruses at different biosafety levels (including BSL3), can increase unexpectedly and dramatically. We describe the measures taken since, aimed at strengthening national laboratory surge capacity and improving preparedness for dealing with diagnostic demand during outbreaks of (emerging) respiratory virus infections, including pandemic influenza virus. Academic and peripheral medical-microbiological laboratories collaborated to determine minimal laboratory requirements for the identification of viruses in the early stages of a pandemic or a large outbreak of avian influenza virus. Next, an enhanced collaborative national network of outbreak assistance laboratories (OAL) was set up. An inventory was made of the maximum diagnostic throughput that this network can deliver in a period of intensified demand. For an estimate of the potential magnitude of this surge demand, historical counts were calculated from hospital- and physician-based registries of patients presenting with respiratory symptoms. Number of respiratory physician-visits ranged from 140,000 to 615,000 per month and hospitalizations ranged from 3000 to 11,500 per month. The established OAL-network provides rapid diagnostic response with agreed quality requirements and a maximum throughput capacity of 1275 samples/day (38,000 per month), assuming other routine diagnostic work needs to be maintained. Thus surge demand for diagnostics for hospitalized cases (if not distinguishable from other respiratory illness) could be handled by the OAL network. Assessing etiology of community acquired acute respiratory infection however, may rapidly exceed the capacity of the network. Therefore algorithms are needed for triaging for laboratory diagnostics; currently this is not addressed in pandemic preparedness plans.

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

Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

NASA Astrophysics Data System (ADS)

Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

2014-12-01

A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

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.

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.

Hot Spot Detection System Using Landsat 8/OLI Data

NASA Astrophysics Data System (ADS)

Kato, S.; Nakamura, R.; Oda, A.; Iijima, A.; Kouyama, T.; Iwata, T.

2015-12-01

We developed a simple algorithm and a Web-based visualizing system to detect hot spots using Landsat 8 OLI multispectral data as one of the applications of the real-time processing of Landsat 8 data. An empirical equation and radiometric and reflective thresholds were derived to detect hot spots using the OLI data at band 5 (0.865 μm) and band 7 (2.200 μm) based on the increase in spectral radiance at shortwave infrared (SWIR) region due to the emission from objects with high surface temperature. We surveyed typical patterns of surface spectra using the ASTER spectral library to delineate a threshold to distinguish hot spots from background surfaces. To adjust the empirical coefficients of our detection algorithm, we visually inspected the detected hot spots using 6593 Landsat 8 scenes, which cover eastern part of East Asia, taken from January 1, 2014 to December 31, 2014, displayed on a dedicated Web GIS system. Eventually we determined threshold equations which can theoretically detect hot spots at temperatures above 230 °C over isothermal pixels and hot spots as small as 1 m2 at temperatures of 1000 °C as the lowest temperature and the smallest subpixel coverage, respectively, for daytime scenes. The algorithm detected hot spots including wildfires, volcanos, open burnings and factories. 30-m spatial resolution of Landsat 8 enabled to detect wild fires and open burnings accompanied by clearer shapes of fire front lines than MODIS and VIIRS fire products. Although the 16-day revisit cycle of Landsat 8 is too long to effectively find unexpected wildfire or outbreak of eruption, the revisit cycle is enough to monitor temporally stable heat sources, such as continually erupting volcanos and factories. False detection was found over building rooftops, which have relatively smooth surfaces at longer wavelengths, when specular reflection occurred at the satellite overpass.

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

Establishing Ebola Virus Disease (EVD) diagnostics using GeneXpert technology at a mobile laboratory in Liberia: Impact on outbreak response, case management and laboratory systems strengthening

PubMed Central

Condell, Orla; Wasunna, Christine; Kpaka, Jonathan; Zwizwai, Ruth; Nuha, Mahmood; Fallah, Mosoka; Freeman, Maxwell; Harris, Victoria; Miller, Mark; Baller, April; Massaquoi, Moses; Katawera, Victoria; Saindon, John; Bemah, Philip; Hamblion, Esther; Castle, Evelyn; Williams, Desmond; Gasasira, Alex; Nyenswah, Tolbert

2018-01-01

The 2014–16 Ebola Virus Disease (EVD) outbreak in West Africa highlighted the necessity for readily available, accurate and rapid diagnostics. The magnitude of the outbreak and the re-emergence of clusters of EVD cases following the declaration of interrupted transmission in Liberia, reinforced the need for sustained diagnostics to support surveillance and emergency preparedness. We describe implementation of the Xpert Ebola Assay, a rapid molecular diagnostic test run on the GeneXpert platform, at a mobile laboratory in Liberia and the subsequent impact on EVD outbreak response, case management and laboratory system strengthening. During the period of operation, site coordination, management and operational capacity was supported through a successful collaboration between Ministry of Health (MoH), World Health Organization (WHO) and international partners. A team of Liberian laboratory technicians were trained to conduct EVD diagnostics and the laboratory had capacity to test 64–100 blood specimens per day. Establishment of the laboratory significantly increased the daily testing capacity for EVD in Liberia, from 180 to 250 specimens at a time when the effectiveness of the surveillance system was threatened by insufficient diagnostic capacity. During the 18 months of operation, the laboratory tested a total of 9,063 blood specimens, including 21 EVD positives from six confirmed cases during two outbreaks. Following clearance of the significant backlog of untested EVD specimens in November 2015, a new cluster of EVD cases was detected at the laboratory. Collaboration between surveillance and laboratory coordination teams during this and a later outbreak in March 2016, facilitated timely and targeted response interventions. Specimens taken from cases during both outbreaks were analysed at the laboratory with results informing clinical management of patients and discharge decisions. The GeneXpert platform is easy to use, has relatively low running costs and can be integrated into other national diagnostic algorithms. The technology has on average a 2-hour sample-to-result time and allows for single specimen testing to overcome potential delays of batching. This model of a mobile laboratory equipped with Xpert Ebola test, staffed by local laboratory technicians, could serve to strengthen outbreak preparedness and response for future outbreaks of EVD in Liberia and the region. PMID:29304039

Establishing Ebola Virus Disease (EVD) diagnostics using GeneXpert technology at a mobile laboratory in Liberia: Impact on outbreak response, case management and laboratory systems strengthening.

PubMed

Raftery, Philomena; Condell, Orla; Wasunna, Christine; Kpaka, Jonathan; Zwizwai, Ruth; Nuha, Mahmood; Fallah, Mosoka; Freeman, Maxwell; Harris, Victoria; Miller, Mark; Baller, April; Massaquoi, Moses; Katawera, Victoria; Saindon, John; Bemah, Philip; Hamblion, Esther; Castle, Evelyn; Williams, Desmond; Gasasira, Alex; Nyenswah, Tolbert

2018-01-01

The 2014-16 Ebola Virus Disease (EVD) outbreak in West Africa highlighted the necessity for readily available, accurate and rapid diagnostics. The magnitude of the outbreak and the re-emergence of clusters of EVD cases following the declaration of interrupted transmission in Liberia, reinforced the need for sustained diagnostics to support surveillance and emergency preparedness. We describe implementation of the Xpert Ebola Assay, a rapid molecular diagnostic test run on the GeneXpert platform, at a mobile laboratory in Liberia and the subsequent impact on EVD outbreak response, case management and laboratory system strengthening. During the period of operation, site coordination, management and operational capacity was supported through a successful collaboration between Ministry of Health (MoH), World Health Organization (WHO) and international partners. A team of Liberian laboratory technicians were trained to conduct EVD diagnostics and the laboratory had capacity to test 64-100 blood specimens per day. Establishment of the laboratory significantly increased the daily testing capacity for EVD in Liberia, from 180 to 250 specimens at a time when the effectiveness of the surveillance system was threatened by insufficient diagnostic capacity. During the 18 months of operation, the laboratory tested a total of 9,063 blood specimens, including 21 EVD positives from six confirmed cases during two outbreaks. Following clearance of the significant backlog of untested EVD specimens in November 2015, a new cluster of EVD cases was detected at the laboratory. Collaboration between surveillance and laboratory coordination teams during this and a later outbreak in March 2016, facilitated timely and targeted response interventions. Specimens taken from cases during both outbreaks were analysed at the laboratory with results informing clinical management of patients and discharge decisions. The GeneXpert platform is easy to use, has relatively low running costs and can be integrated into other national diagnostic algorithms. The technology has on average a 2-hour sample-to-result time and allows for single specimen testing to overcome potential delays of batching. This model of a mobile laboratory equipped with Xpert Ebola test, staffed by local laboratory technicians, could serve to strengthen outbreak preparedness and response for future outbreaks of EVD in Liberia and the region.

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

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.

Performance of the OraQuick HCV rapid antibody test for screening exposed patients in a hepatitis C outbreak investigation.

PubMed

Gao, Fengxiang; Talbot, Elizabeth A; Loring, Carol H; Power, Jill J; Dionne-Odom, Jodie; Alroy-Preis, Sharon; Jackson, Patricia; Bean, Christine L

2014-07-01

During a nosocomial hepatitis C outbreak, emergency public clinics employed the OraQuick HCV rapid antibody test on site, and all results were verified by a standard enzyme immunoassay (EIA). Of 1,157 persons, 1,149 (99.3%) exhibited concordant results between the two tests (16 positive, 1,133 negative). The sensitivity, specificity, positive predictive value, and negative predictive value were 94.1%, 99.5%, 72.7%, and 99.9%, respectively. OraQuick performed well as a screening test during an outbreak investigation and could be integrated into future hepatitis C virus (HCV) outbreak testing algorithms. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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

PubMed

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

2015-10-01

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

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.

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.

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

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.

Devising a method towards development of early warning tool for detection of malaria outbreak.

PubMed

Verma, Preeti; Sarkar, Soma; Singh, Poonam; Dhiman, Ramesh C

2017-11-01

Uncertainty often arises in differentiating seasonal variation from outbreaks of malaria. The present study was aimed to generalize the theoretical structure of sine curve for detecting an outbreak so that a tool for early warning of malaria may be developed. A 'case/mean-ratio scale' system was devised for labelling the outbreak in respect of two diverse districts of Assam and Rajasthan. A curve-based method of analysis was developed for determining outbreak and using the properties of sine curve. It could be used as an early warning tool for Plasmodium falciparum malaria outbreaks. In the present method of analysis, the critical C max (peak value of sine curve) value of seasonally adjusted curve for P. falciparum malaria outbreak was 2.3 for Karbi Anglong and 2.2 for Jaisalmer districts. On case/mean-ratio scale, the C max value of malaria curve between C max and 3.5, the outbreak could be labelled as minor while >3.5 may be labelled as major. In epidemic years, with mean of case/mean ratio of ≥1.00 and root mean square (RMS) ≥1.504 of case/mean ratio, outbreaks can be predicted 1-2 months in advance. The present study showed that in P. falciparum cases in Karbi Anglong (Assam) and Jaisalmer (Rajasthan) districts, the rise in C max value of curve was always followed by rise in average/RMS or both and hence could be used as an early warning tool. The present method provides better detection of outbreaks than the conventional method of mean plus two standard deviation (mean+2 SD). The identified tools are simple and may be adopted for preparedness of malaria outbreaks.

Critical dynamics in population vaccinating behavior.

PubMed

Pananos, A Demetri; Bury, Thomas M; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P; Nyhan, Brendan; Salathé, Marcel; Bauch, Chris T

2017-12-26

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena-special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles-mumps-rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014-2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior-disease systems, the population responds to the outbreak by moving away from the tipping point, causing "critical speeding up" whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. Copyright © 2017 the Author(s). Published by PNAS.

Critical dynamics in population vaccinating behavior

PubMed Central

Pananos, A. Demetri; Bury, Thomas M.; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P.; Nyhan, Brendan; Bauch, Chris T.

2017-01-01

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena—special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles–mumps–rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014–2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior–disease systems, the population responds to the outbreak by moving away from the tipping point, causing “critical speeding up” whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. PMID:29229821

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

Biochemical Phenotypes to Discriminate Microbial Subpopulations and Improve Outbreak Detection

PubMed Central

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

2013-01-01

Background Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Methodology/Principal Findings Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis. Results: 4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as “nuisance” biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms. Conclusions The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events. PMID:24391936

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

PubMed

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

2013-06-20

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

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

PubMed

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

2007-04-01

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

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

Outbreak investigation for toxigenic Corynebacterium diphtheriae wound infections in refugees from Northeast Africa and Syria in Switzerland and Germany by whole genome sequencing.

PubMed

Meinel, D M; Kuehl, R; Zbinden, R; Boskova, V; Garzoni, C; Fadini, D; Dolina, M; Blümel, B; Weibel, T; Tschudin-Sutter, S; Widmer, A F; Bielicki, J A; Dierig, A; Heininger, U; Konrad, R; Berger, A; Hinic, V; Goldenberger, D; Blaich, A; Stadler, T; Battegay, M; Sing, A; Egli, A

2016-12-01

Toxigenic Corynebacterium diphtheriae is an important and potentially fatal threat to patients and public health. During the current dramatic influx of refugees into Europe, our objective was to use whole genome sequencing for the characterization of a suspected outbreak of C. diphtheriae wound infections among refugees. After conventional culture, we identified C. diphtheriae using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and investigated toxigenicity by PCR. Whole genome sequencing was performed on a MiSeq Illumina with >70×coverage, 2×250 bp read length, and mapping against a reference genome. Twenty cases of cutaneous C. diphtheriae in refugees from East African countries and Syria identified between April and August 2015 were included. Patients presented with wound infections shortly after arrival in Switzerland and Germany. Toxin production was detected in 9/20 (45%) isolates. Whole genome sequencing-based typing revealed relatedness between isolates using neighbour-joining algorithms. We detected three separate clusters among epidemiologically related refugees. Although the isolates within a cluster showed strong relatedness, isolates differed by >50 nucleotide polymorphisms. Toxigenic C. diphtheriae associated wound infections are currently observed more frequently in Europe, due to refugees travelling under poor hygienic conditions. Close genetic relatedness of C. diphtheriae isolates from 20 refugees with wound infections indicates likely transmission between patients. However, the diversity within each cluster and phylogenetic time-tree analysis suggest that transmissions happened several months ago, most likely outside Europe. Whole genome sequencing offers the potential to describe outbreaks at very high resolution and is a helpful tool in infection tracking and identification of transmission routes. Copyright © 2016. Published by Elsevier Ltd.

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

Contrasting environments associated with storm prediction center tornado outbreak forecasts using synoptic-scale composite analysis

NASA Astrophysics Data System (ADS)

Bates, Alyssa Victoria

Tornado outbreaks have significant human impact, so it is imperative forecasts of these phenomena are accurate. As a synoptic setup lays the foundation for a forecast, synoptic-scale aspects of Storm Prediction Center (SPC) outbreak forecasts of varying accuracy were assessed. The percentages of the number of tornado outbreaks within SPC 10% tornado probability polygons were calculated. False alarm events were separately considered. The outbreaks were separated into quartiles using a point-in-polygon algorithm. Statistical composite fields were created to represent the synoptic conditions of these groups and facilitate comparison. Overall, temperature advection had the greatest differences between the groups. Additionally, there were significant differences in the jet streak strengths and amounts of vertical wind shear. The events forecasted with low accuracy consisted of the weakest synoptic-scale setups. These results suggest it is possible that events with weak synoptic setups should be regarded as areas of concern by tornado outbreak forecasters.

PREDICT: A next generation platform for near real-time prediction of cholera

NASA Astrophysics Data System (ADS)

Jutla, A.; Aziz, S.; Akanda, A. S.; Alam, M.; Ahsan, G. U.; Huq, A.; Colwell, R. R.

2017-12-01

Data on disease prevalence and infectious pathogens is sparingly collected/available in region(s) where climatic variability and extreme natural events intersect with population vulnerability (such as lack of access to water and sanitation infrastructure). Therefore, traditional time series modeling approach of calibration and validation of a model is inadequate. Hence, prediction of diarrheal infections (such as cholera, Shigella etc) remain a challenge even though disease causing pathogens are strongly associated with modalities of regional climate and weather system. Here we present an algorithm that integrates satellite derived data on several hydroclimatic and ecological processes into a framework that can determine high resolution cholera risk on global scales. Cholera outbreaks can be classified in three forms- epidemic (sudden or seasonal outbreaks), endemic (recurrence and persistence of the disease for several consecutive years) and mixed-mode endemic (combination of certain epidemic and endemic conditions) with significant spatial and temporal heterogeneity. Using data from multiple satellites (AVHRR, TRMM, GPM, MODIS, VIIRS, GRACE), we will show examples from Haiti, Yemen, Nepal and several other regions where our algorithm has been successful in capturing risk of outbreak of infection in human population. A spatial model validation algorithm will also be presented that has capabilities to self-calibrate as new hydroclimatic and disease data become available.

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.

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.

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

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2014-11-01

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

METHODS FOR DETECTION OF CRYPTOSPORIDIUM SP. AND GIARDIA SP.

EPA Science Inventory

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

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.

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.

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data.

PubMed

Vial, Flavie; Wei, Wei; Held, Leonhard

2016-12-20

In an era of ubiquitous electronic collection of animal health data, multivariate surveillance systems (which concurrently monitor several data streams) should have a greater probability of detecting disease events than univariate systems. However, despite their limitations, univariate aberration detection algorithms are used in most active syndromic surveillance (SyS) systems because of their ease of application and interpretation. On the other hand, a stochastic modelling-based approach to multivariate surveillance offers more flexibility, allowing for the retention of historical outbreaks, for overdispersion and for non-stationarity. While such methods are not new, they are yet to be applied to animal health surveillance data. We applied an example of such stochastic model, Held and colleagues' two-component model, to two multivariate animal health datasets from Switzerland. In our first application, multivariate time series of the number of laboratories test requests were derived from Swiss animal diagnostic laboratories. We compare the performance of the two-component model to parallel monitoring using an improved Farrington algorithm and found both methods yield a satisfactorily low false alarm rate. However, the calibration test of the two-component model on the one-step ahead predictions proved satisfactory, making such an approach suitable for outbreak prediction. In our second application, the two-component model was applied to the multivariate time series of the number of cattle abortions and the number of test requests for bovine viral diarrhea (a disease that often results in abortions). We found that there is a two days lagged effect from the number of abortions to the number of test requests. We further compared the joint modelling and univariate modelling of the number of laboratory test requests time series. The joint modelling approach showed evidence of superiority in terms of forecasting abilities. Stochastic modelling approaches offer the potential to address more realistic surveillance scenarios through, for example, the inclusion of times series specific parameters, or of covariates known to have an impact on syndrome counts. Nevertheless, many methodological challenges to multivariate surveillance of animal SyS data still remain. Deciding on the amount of corroboration among data streams that is required to escalate into an alert is not a trivial task given the sparse data on the events under consideration (e.g. disease outbreaks).

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...

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.

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.

TESTING METHODS FOR DETECTION OF CRYPTOSPORIDIUM SPP. IN WATER SAMPLES

EPA Science Inventory

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

Description of two waterborne disease outbreaks in France: a comparative study with data from cohort studies and from health administrative databases.

PubMed

Mouly, D; Van Cauteren, D; Vincent, N; Vaissiere, E; Beaudeau, P; Ducrot, C; Gallay, A

2016-02-01

Waterborne disease outbreaks (WBDO) of acute gastrointestinal illness (AGI) are a public health concern in France. Their occurrence is probably underestimated due to the lack of a specific surveillance system. The French health insurance database provides an interesting opportunity to improve the detection of these events. A specific algorithm to identify AGI cases from drug payment reimbursement data in the health insurance database has been previously developed. The purpose of our comparative study was to retrospectively assess the ability of the health insurance data to describe WBDO. Data from the health insurance database was compared with the data from cohort studies conducted in two WBDO in 2010 and 2012. The temporal distribution of cases, the day of the peak and the duration of the epidemic, as measured using the health insurance data, were similar to the data from one of the two cohort studies. However, health insurance data accounted for 54 cases compared to the estimated 252 cases accounted for in the cohort study. The accuracy of using health insurance data to describe WBDO depends on the medical consultation rate in the impacted population. As this is never the case, data analysis underestimates the total number of AGI cases. However this data source can be considered for the development of a detection system of a WBDO in France, given its ability to describe an epidemic signal.

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

Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees

PubMed Central

Kenah, Eben; Britton, Tom; Halloran, M. Elizabeth; Longini, Ira M.

2016-01-01

Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology. PMID:27070316

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.

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

PubMed

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

2016-03-01

Worldwide diarrhea outbreaks in cattle herds are more frequently detected in calves being that diarrhea outbreaks in adult cattle are not common. Winter dysentery (WD) is a bovine coronavirus (BCoV) enteric infection that is more reported in Northern hemisphere. Seasonal outbreaks of WD in adult cattle occur mainly in dairy cows. WD has not been described in beef cattle herds of tropical countries. This study describes the molecular detection of BCoV in a diarrhea outbreak in beef cattle steers (Nellore) raised on pasture in Parana, southern Brazil. During the outbreak, the farm had about 600 fattening steers. Watery and bloody diarrhea unresponsive to systemic broad-spectrum antibiotic therapy reveals a morbidity rate of approximately 15 %. The BCoV N gene was identified in 42.9 % (6/14) of the diarrheic fecal samples evaluated by semi-nested polymerase chain reaction (SN-PCR) technique. Other enteric microorganisms occasionally identified in adult cattle and evaluated in this study such as bovine groups A, B, and C rotavirus, bovine viral diarrhea virus, bovine torovirus, aichivirus B, and Eimeria sp. were not identified in the fecal samples. To the best knowledge of the authors, this is the first description of the BCoV diagnosis in fecal samples collected in a diarrhea outbreak in adult beef cattle grazing in the grass in a tropical country.

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

PubMed Central

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

2017-01-01

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

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.

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

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

Integrating Remote Sensing and Disease Surveillance to Forecast Malaria Epidemics

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

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

2014-12-01

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

[Meningitis outbreak caused by Echovirus serotype 30 in the Valencian Community].

PubMed

Juliá, M Lirios; Colomina, Javier; Domínguez, Victoria; Orta, Nieves; Guerrero, Antonio

2009-05-01

Aseptic meningitis can be caused by several agents, and in many cases the etiology remains unknown. The aim of this study to analyze the clinical and epidemiological characteristics of a meningitis outbreak detected in Health Department 11 of the Valencian Community (Spain). The study was performed in children hospitalized between November and December 2006 with meningitis symptoms, CSF pleocytosis, and negative CSF bacteriological culture. An epidemiological survey was conducted among cases and family members. Virus detection and phylogenetic analysis were performed with molecular biology techniques. The outbreak affected at least 44 children, with a mean age (standard deviation) of 5.5 years (2.9). The average hospital stay was 3.1 days and outcome was favorable in all cases. In 24 patients the CSF specimen sufficed for viral detection by PCR; enteroviruses ultimately serotyped as echovirus 30 were detected in 12 of them (50%). This serotype has been recently found in other parts of our country. Detection of echovirus 30 in CSF and the epidemiological presentation of cases enabled determination of the etiology of the outbreak. This finding coincided in time with other outbreaks of echovirus 30 in Spain, a fact that may explain the epidemic situation in the Valencian Community during 2006. Establishment of a national surveillance network for monitoring systemic enterovirus infection would provide data on the circulation patterns and identify new emerging serotypes.

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.

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

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.

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

USDA-ARS?s Scientific Manuscript database

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

Plasmodium falciparum Malaria, Southern Algeria, 2007

PubMed Central

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

2010-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

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.

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

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

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

PubMed

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

2016-10-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2018-01-01

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

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.

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

PubMed

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

2014-06-01

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

Nosocomial Transmission of Respiratory Syncytial Virus in an Outpatient Cancer Center

PubMed Central

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

2014-01-01

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

Phylogeny of Yellow Fever Virus, Uganda, 2016.

PubMed

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

2018-08-17

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

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.

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.

Measles surveillance in Victoria, Australia.

PubMed Central

Wang, Yung-Hsuan J.; Andrews, Ross M.; Lambert, Stephen B.

2006-01-01

OBJECTIVE: Many countries are implementing measles elimination strategies. In Australia, the State of Victoria has conducted enhanced measles surveillance since 1997 using case interviews and home-based specimen collection for laboratory confirmation. We attempted to identify features of notified cases that would better target surveillance resources. METHODS: We retrospectively classified notifications received from 1998 to 2003 as having been received in an epidemic (one or more laboratory-confirmed cases) or an interepidemic period (no laboratory-confirmed cases). We labelled the first case notified in any epidemic period that was not laboratory-confirmed at the time of notification as a "sentinel case". To maximize detection of sentinel cases while minimizing the follow-up of eventually discarded notifications, we generated algorithms using sentinel cases and interepidemic notifications. FINDINGS: We identified 10 sentinel cases with 422 interepidemic notifications from 1281 Victorian notifications. Sentinel cases were more likely to report fever at rash onset (odds ratio (OR) 15.7, 95% confidence interval (CI) CI: 2.1-688.9), cough (OR 10.4, 95% CI: 1.4-456.7), conjunctivitis (OR 7.9, 95% CI: 1.8-39.1), or year of birth between 1968 and 1981 (OR 31.8, 95% CI: 6.7-162.3). Prospective application of an algorithm consisting of fever at rash onset or born between 1968 and 1981 in the review period would have detected all sentinel cases and avoided the need for enhanced follow-up of 162 of the 422 eventually discarded notifications. CONCLUSION: Elimination strategies should be refined to suit regional and local priorities. The prospective application of an algorithm in Victoria is likely to reduce enhanced measles surveillance resource use in interepidemic periods, while still detecting early cases during measles outbreaks. PMID:16501727

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.

Inspection of fecal contamination on strawberries using fluorescence imaging

NASA Astrophysics Data System (ADS)

Chuang, Yung-Kun; Yang, Chun-Chieh; Kim, Moon S.; Delwiche, Stephen R.; Lo, Y. Martin; Chen, Suming; Chan, Diane E.

2013-05-01

Fecal contamination of produce is a food safety issue associated with pathogens such as Escherichia coli that can easily pollute agricultural products via animal and human fecal matters. Outbreaks of foodborne illnesses associated with consuming raw fruits and vegetables have occurred more frequently in recent years in the United States. Among fruits, strawberry is one high-potential vector of fecal contamination and foodborne illnesses since the fruit is often consumed raw and with minimal processing. In the present study, line-scan LED-induced fluorescence imaging techniques were applied for inspection of fecal material on strawberries, and the spectral characteristics and specific wavebands of strawberries were determined by detection algorithms. The results would improve the safety and quality of produce consumed by the public.

Molecular Typing of Clinical Adenovirus Specimens by an Algorithm which Permits Detection of Adenovirus Coinfections and Intermediate Adenovirus Strains

PubMed Central

McCarthy, Troy; Lebeck, Mark G.; Capuano, Ana W.; Schnurr, David P.; Gray, Gregory C.

2009-01-01

Background Epidemiological data suggest that clinical outcomes of human adenovirus (HAdV) infection may be influenced by virus serotype, coinfection with multiple strains, or infection with novel intermediate strains. In this report, we propose a clinical algorithm for detecting HAdV coinfection and intermediate strains. Study Design We PCR amplified and sequenced subregions of the hexon and fiber genes of 342 HAdV positive clinical specimens obtained from 14 surveillance laboratories. Sequences were then compared with those from 52 HAdV prototypic strains. HAdV positive specimens that showed nucleotide sequence identity with a corresponding prototype strain were designated as being of that strain. When hexon and fiber gene sequences disagreed, or sequence identity was low, the specimens were further characterized by viral culture, plaque purification, repeat PCR with sequencing, and genome restriction enzyme digest analysis. Results Of the 342 HAdV-positive clinical specimens, 328 (95.9%) were single HAdV strain infections, 12 (3.5%) were coinfections, and 2 (0.6%) had intermediate strains. Coinfected specimens and intermediate HAdV strains considered together were more likely to be associated with severe illness compared to other HAdv-positive specimens (OR=3.8; 95% CI = 1.2–11.9). Conclusions The majority of severe cases of HAdV illness cases occurred among immunocompromised patients. The analytic algorithm we describe here can be used to screen clinical specimens for evidence of HAdV coinfection and novel intermediate HAdV strains. This algorithm may be especially useful in investigating HAdV outbreaks and clusters of unusually severe HAdV disease. PMID:19577957

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

PubMed

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

2016-08-01

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Effects of gypsy moth outbreaks on North American woodpeckers

Treesearch

Walter D. Koenig; Eric L. Walters; Andrew M. Liebhold

2011-01-01

We examined the effects of the introduced gypsy moth (Lymantria dispar) on seven species of North American woodpeckers by matching spatially explicit data on gypsy moth outbreaks with data on breeding and wintering populations. In general, we detected modest effects during outbreaks: during the breeding season one species, the Red-headed Woodpecker...

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed Central

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

1988-01-01

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

Privacy protection versus cluster detection in spatial epidemiology.

PubMed

Olson, Karen L; Grannis, Shaun J; Mandl, Kenneth D

2006-11-01

Patient data that includes precise locations can reveal patients' identities, whereas data aggregated into administrative regions may preserve privacy and confidentiality. We investigated the effect of varying degrees of address precision (exact latitude and longitude vs the center points of zip code or census tracts) on detection of spatial clusters of cases. We simulated disease outbreaks by adding supplementary spatially clustered emergency department visits to authentic hospital emergency department syndromic surveillance data. We identified clusters with a spatial scan statistic and evaluated detection rate and accuracy. More clusters were identified, and clusters were more accurately detected, when exact locations were used. That is, these clusters contained at least half of the simulated points and involved few additional emergency department visits. These results were especially apparent when the synthetic clustered points crossed administrative boundaries and fell into multiple zip code or census tracts. The spatial cluster detection algorithm performed better when addresses were analyzed as exact locations than when they were analyzed as center points of zip code or census tracts, particularly when the clustered points crossed administrative boundaries. Use of precise addresses offers improved performance, but this practice must be weighed against privacy concerns in the establishment of public health data exchange policies.

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Characteristics of Clusters of Salmonella and Escherichia coli O157 Detected by Pulsed-Field Gel Electrophoresis that Predict Identification of Outbreaks.

PubMed

Jones, Timothy F; Sashti, Nupur; Ingram, Amanda; Phan, Quyen; Booth, Hillary; Rounds, Joshua; Nicholson, Cyndy S; Cosgrove, Shaun; Crocker, Kia; Gould, L Hannah

2016-12-01

Molecular subtyping of pathogens is critical for foodborne disease outbreak detection and investigation. Many clusters initially identified by pulsed-field gel electrophoresis (PFGE) are not confirmed as point-source outbreaks. We evaluated characteristics of clusters that can help prioritize investigations to maximize effective use of limited resources. A multiagency collaboration (FoodNet) collected data on Salmonella and Escherichia coli O157 clusters for 3 years. Cluster size, timing, extent, and nature of epidemiologic investigations were analyzed to determine associations with whether the cluster was identified as a confirmed outbreak. During the 3-year study period, 948 PFGE clusters were identified; 849 (90%) were Salmonella and 99 (10%) were E. coli O157. Of those, 192 (20%) were ultimately identified as outbreaks (154 [18%] of Salmonella and 38 [38%] of E. coli O157 clusters). Successful investigation was significantly associated with larger cluster size, more rapid submission of isolates (e.g., for Salmonella, 6 days for outbreaks vs. 8 days for nonoutbreaks) and PFGE result reporting to investigators (16 days vs. 29 days, respectively), and performance of analytic studies (completed in 33% of Salmonella outbreaks vs. 1% of nonoutbreaks) and environmental investigations (40% and 1%, respectively). Intervals between first and second cases in a cluster did not differ significantly between outbreaks and nonoutbreaks. Molecular subtyping of pathogens is a rapidly advancing technology, and successfully identifying outbreaks will vary by pathogen and methods used. Understanding criteria for successfully investigating outbreaks is critical for efficiently using limited resources.

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

Selection tool for foodborne norovirus outbreaks.

PubMed

Verhoef, Linda P B; Kroneman, Annelies; van Duynhoven, Yvonne; Boshuizen, Hendriek; van Pelt, Wilfrid; Koopmans, Marion

2009-01-01

Detection of pathogens in the food chain is limited mainly to bacteria, and the globalization of the food industry enables international viral foodborne outbreaks to occur. Outbreaks from 2002 through 2006 recorded in a European norovirus surveillance database were investigated for virologic and epidemiologic indicators of food relatedness. The resulting validated multivariate logistic regression model comparing foodborne (n = 224) and person-to-person (n = 654) outbreaks was used to create a practical web-based tool that can be limited to epidemiologic parameters for nongenotyping countries. Non-genogroup-II.4 outbreaks, higher numbers of cases, and outbreaks in restaurants or households characterized (sensitivity = 0.80, specificity = 0.86) foodborne outbreaks and reduced the percentage of outbreaks requiring source-tracing to 31%. The selection tool enabled prospectively focused follow-up. Use of this tool is likely to improve data quality and strain typing in current surveillance systems, which is necessary for identification of potential international foodborne outbreaks.

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

PubMed

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

2018-03-01

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

Coccidioidomycosis Outbreaks, United States and Worldwide, 1940–2015

PubMed Central

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

2018-01-01

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

[Outbreaks of acute gastroenteritis caused by small round structured viruses in Tokyo].

PubMed

Sekine, S; Hayashi, Y; Ando, T; Ohta, K; Miki, T; Okada, S

1992-07-01

Of 34 non-bacterial gastroenteritis outbreaks which occurred at day-care centers, kindergartens, elementary and secondary schools in Tokyo during the period from February 1985 to June 1991, 28 outbreaks from which small round structured viruses (SRSV) were detected in the patients' stool specimens by electron microscopy were subjected to an epidemiological investigation. The outbreaks tended to occur frequently in the cold season; twenty-two (79%) of these outbreaks from November through April. Though detailed epidemiological informations was not obtained from all outbreaks, the common source of infection were presumed to be present in many of the outbreaks, judged from the incidence as to time course of patients. Food doubted to be incriminated as transmission vehicles in these outbreaks was served at schools, kindergartens, and lodgings. In some outbreaks, SRSV was detected from stool specimens of food handlers, or they were seroconverted to SRSV, suggesting that food was incriminated as a transmission vehicle. The symptoms of patients differ slightly from age to age: in the age range of 0 to 6 years, vomiting 90%, fever 41% and diarrhea 32%; in the 6 to 12 year-olds, nausea 61%, vomiting 48%, abdominal pain 65%, diarrhea 20% and fever 29%; and in the 12 to 15 year-olds, nausea 69%, vomiting 42%, abdominal pain 60%, diarrhea 30% and fever 34%. The lower the age of patient vomiting was more frequently observed. In these lower age groups, the frequency of nausea and vomiting tended to exceed that of diarrhea.

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

PubMed Central

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

2008-01-01

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

Using demographic characteristics of populations to detect spatial fragmentation following suspected ebola outbreaks in great apes.

PubMed

Genton, Céline; Cristescu, Romane; Gatti, Sylvain; Levréro, Florence; Bigot, Elodie; Motsch, Peggy; Le Gouar, Pascaline; Pierre, Jean-Sébastien; Ménard, Nelly

2017-09-01

Demographic crashes due to emerging diseases can contribute to population fragmentation and increase extinction risk of small populations. Ebola outbreaks in 2002-2004 are suspected to have caused a decline of more than 80% in some Western lowland gorilla (Gorilla gorilla gorilla) populations. We investigated whether demographic indicators of this event allowed for the detection of spatial fragmentation in gorilla populations. We collected demographic data from two neighbouring populations: the Lokoué population, suspected to have been affected by an Ebola outbreak (followed from 2001 to 2014), and the Romani population, of unknown demographic status before Ebola outbreaks (followed from 2005 to 2014). Ten years after the outbreak, the Lokoué population is slowly recovering and the short-term demographic indicators of a population crash were no longer detectable. The Lokoué population has not experienced any additional demographic perturbation over the past decade. The Romani population did not show any of the demographic indicators of a population crash over the past decade. Its demographic structure remained similar to that of unaffected populations. Our results highlighted that the Ebola disease could contribute to fragmentation of gorilla populations due to the spatially heterogeneous impact of its outbreaks. The demographic structure of populations (i.e., age-sex and group structure) can be useful indicators of a possible occurrence of recent Ebola outbreaks in populations without known history, and may be more broadly used in other emerging disease/species systems. Longitudinal data are critical to our understanding of the impact of emerging diseases on wild populations and their conservation. © 2017 Wiley Periodicals, Inc.

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 ...

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.

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…

[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.

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.

Modeling the geographic distribution of Bacillus anthracis, the causative agent of anthrax disease, for the contiguous United States using predictive ecological [corrected] niche modeling.

PubMed

Blackburn, Jason K; McNyset, Kristina M; Curtis, Andrew; Hugh-Jones, Martin E

2007-12-01

The ecology and distribution of Bacillus anthracis is poorly understood despite continued anthrax outbreaks in wildlife and livestock throughout the United States. Little work is available to define the potential environments that may lead to prolonged spore survival and subsequent outbreaks. This study used the genetic algorithm for rule-set prediction modeling system to model the ecological niche for B. anthracis in the contiguous United States using wildlife and livestock outbreaks and several environmental variables. The modeled niche is defined by a narrow range of normalized difference vegetation index, precipitation, and elevation, with the geographic distribution heavily concentrated in a narrow corridor from southwest Texas northward into the Dakotas and Minnesota. Because disease control programs rely on vaccination and carcass disposal, and vaccination in wildlife remains untenable, understanding the distribution of B. anthracis plays an important role in efforts to prevent/eradicate the disease. Likewise, these results potentially aid in differentiating endemic/natural outbreaks from industrial-contamination related outbreaks or bioterrorist attacks.

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.

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system

PubMed Central

Lall, Ramona; Levin-Rector, Alison; Sell, Jessica; Paladini, Marc; Konty, Kevin J.; Olson, Don; Weiss, Don

2017-01-01

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method’s implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System’s C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis. PMID:28886112

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system.

PubMed

Mathes, Robert W; Lall, Ramona; Levin-Rector, Alison; Sell, Jessica; Paladini, Marc; Konty, Kevin J; Olson, Don; Weiss, Don

2017-01-01

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method's implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System's C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis.

Toxin Detection in Patients' Sera by Mass Spectrometry during Two Outbreaks of Type A Botulism in France

PubMed Central

Mazuet, Christelle; Ezan, Eric; Volland, Hervé; Becher, François

2012-01-01

In two outbreaks of food-borne botulism in France, Clostridium botulinum type A was isolated and characterized from incriminated foods. Botulinum neurotoxin type A was detected in the patients' sera by mouse bioassay and in vitro endopeptidase assay with an immunocapture step and identification of the cleavage products by mass spectrometry. PMID:22993181

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

PubMed Central

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

2014-01-01

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

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

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.

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.

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.

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.

Validation of Metagenomic Next-Generation Sequencing Tests for Universal Pathogen Detection.

PubMed

Schlaberg, Robert; Chiu, Charles Y; Miller, Steve; Procop, Gary W; Weinstock, George

2017-06-01

- Metagenomic sequencing can be used for detection of any pathogens using unbiased, shotgun next-generation sequencing (NGS), without the need for sequence-specific amplification. Proof-of-concept has been demonstrated in infectious disease outbreaks of unknown causes and in patients with suspected infections but negative results for conventional tests. Metagenomic NGS tests hold great promise to improve infectious disease diagnostics, especially in immunocompromised and critically ill patients. - To discuss challenges and provide example solutions for validating metagenomic pathogen detection tests in clinical laboratories. A summary of current regulatory requirements, largely based on prior guidance for NGS testing in constitutional genetics and oncology, is provided. - Examples from 2 separate validation studies are provided for steps from assay design, and validation of wet bench and bioinformatics protocols, to quality control and assurance. - Although laboratory and data analysis workflows are still complex, metagenomic NGS tests for infectious diseases are increasingly being validated in clinical laboratories. Many parallels exist to NGS tests in other fields. Nevertheless, specimen preparation, rapidly evolving data analysis algorithms, and incomplete reference sequence databases are idiosyncratic to the field of microbiology and often overlooked.

[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.

[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.

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 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

Genetic Analysis of Hepatitis A Virus Strains That Induced Epidemics in Korea during 2007–2009

PubMed Central

Lee, Hyeokjin; Jeong, Hyesook; Yun, Heasun; Kim, Kisang; Kim, Jong-Hyun; Yang, Jai Myung

2012-01-01

Hepatitis A virus is one of the most prominent causes of fecally transmitted acute hepatitis worldwide. In order to characterize the viral agents causing an outbreak in Korea (comprising North and South Korea) from June 2007 to May 2009, we collected specimens and performed genotyping of the VP1/P2A and VP3/VP1 regions of hepatitis A virus. We then used a multiple-alignment algorithm to compare the nucleotide sequences of the 2 regions with those of reference strains. Hepatitis A virus antibodies were detected in 64 patients from 5 reported outbreaks (North Korea, June 2007 [n = 11]; Jeonnam, April 2008 [n = 15]; Daegu, May 2008 [n = 13]; Seoul, May 2009 [n = 22]; and Incheon, May 2009 [n = 3]). We found 100% homology between strains isolated from the Kaesong Industrial Region and Jeonnam. While those strains were classified as genotype IA strains, strains from Seoul and Incheon were identified as genotype IIIA strains and showed 98.9 to 100% homology. Genotype IIIA was also dominant in Daegu, where strains were 95.7 to 100% homologous. All hepatitis A virus strains isolated from the Kaesong Industrial Region, Jeonnam, Seoul, and Incheon belonged to a single cluster. However, strains from Daegu could be classified into 2 clusters, suggesting that the outbreak had multiple sources. This study indicates that hepatitis A virus strains of 2 different genotypes are currently cocirculating in Korea. Moreover, it documents an increasing prevalence of genotype IIIA strains in the country. PMID:22238447

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.

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.

[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.

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.

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

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.

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...

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.

African Swine Fever in Uganda: Qualitative Evaluation of Three Surveillance Methods with Implications for Other Resource-Poor Settings.

PubMed

Chenais, Erika; Sternberg-Lewerin, Susanna; Boqvist, Sofia; Emanuelson, Ulf; Aliro, Tonny; Tejler, Emma; Cocca, Giampaolo; Masembe, Charles; Ståhl, Karl

2015-01-01

Animal diseases impact negatively on households and on national economies. In low-income countries, this pertains especially to socio-economic effects on household level. To control animal diseases and mitigate their impact, it is necessary to understand the epidemiology of the disease in its local context. Such understanding, gained through disease surveillance, is often lacking in resource-poor settings. Alternative surveillance methods have been developed to overcome some of the hurdles obstructing surveillance. The objective of this study was to evaluate and qualitatively compare three methods for surveillance of acute infectious diseases using African swine fever in northern Uganda as an example. Report-driven outbreak investigations, participatory rural appraisals (PRAs), and a household survey using a smartphone application were evaluated. All three methods had good disease-detecting capacity, and each of them detected many more outbreaks compared to those reported to the World Organization for Animal Health during the same time period. Apparent mortality rates were similar for the three methods although highest for the report-driven outbreak investigations, followed by the PRAs, and then the household survey. The three methods have different characteristics and the method of choice will depend on the surveillance objective. The optimal situation might be achieved by a combination of the methods: outbreak detection via smartphone-based real-time surveillance, outbreak investigation for collection of biological samples, and a PRA for a better understanding of the epidemiology of the specific outbreak. All three methods require initial investments and continuous efforts. The sustainability of the surveillance system should, therefore, be carefully evaluated before making such investments.

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.

A smartphone-based diagnostic platform for rapid detection of Zika, chikungunya, and dengue viruses

PubMed Central

Priye, Aashish; Bird, Sara W.; Light, Yooli K.; Ball, Cameron S.; Negrete, Oscar A.; Meagher, Robert J.

2017-01-01

Current multiplexed diagnostics for Zika, dengue, and chikungunya viruses are situated outside the intersection of affordability, high performance, and suitability for use at the point-of-care in resource-limited settings. Consequently, insufficient diagnostic capabilities are a key limitation facing current Zika outbreak management strategies. Here we demonstrate highly sensitive and specific detection of Zika, chikungunya, and dengue viruses by coupling reverse-transcription loop-mediated isothermal amplification (RT-LAMP) with our recently developed quenching of unincorporated amplification signal reporters (QUASR) technique. We conduct reactions in a simple, inexpensive and portable “LAMP box” supplemented with a consumer class smartphone. The entire assembly can be powered by a 5 V USB source such as a USB power bank or solar panel. Our smartphone employs a novel algorithm utilizing chromaticity to analyze fluorescence signals, which improves the discrimination of positive/negative signals by 5-fold when compared to detection with traditional RGB intensity sensors or the naked eye. The ability to detect ZIKV directly from crude human sample matrices (blood, urine, and saliva) demonstrates our device’s utility for widespread clinical deployment. Together, these advances enable our system to host the key components necessary to expand the use of nucleic acid amplification-based detection assays towards point-of-care settings where they are needed most. PMID:28317856

Privacy Protection Versus Cluster Detection in Spatial Epidemiology

PubMed Central

Olson, Karen L.; Grannis, Shaun J.; Mandl, Kenneth D.

2006-01-01

Objectives. Patient data that includes precise locations can reveal patients’ identities, whereas data aggregated into administrative regions may preserve privacy and confidentiality. We investigated the effect of varying degrees of address precision (exact latitude and longitude vs the center points of zip code or census tracts) on detection of spatial clusters of cases. Methods. We simulated disease outbreaks by adding supplementary spatially clustered emergency department visits to authentic hospital emergency department syndromic surveillance data. We identified clusters with a spatial scan statistic and evaluated detection rate and accuracy. Results. More clusters were identified, and clusters were more accurately detected, when exact locations were used. That is, these clusters contained at least half of the simulated points and involved few additional emergency department visits. These results were especially apparent when the synthetic clustered points crossed administrative boundaries and fell into multiple zip code or census tracts. Conclusions. The spatial cluster detection algorithm performed better when addresses were analyzed as exact locations than when they were analyzed as center points of zip code or census tracts, particularly when the clustered points crossed administrative boundaries. Use of precise addresses offers improved performance, but this practice must be weighed against privacy concerns in the establishment of public health data exchange policies. PMID:17018828

An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

NASA Technical Reports Server (NTRS)

Rudasill-Neigh, Christopher S.; Bolton, Douglas K.; Diabate, Mouhamad; Williams, Jennifer J.; Carvalhais, Nuno

2014-01-01

Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 2007, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometer (AVHRR). To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1) multiple disturbance index thresholds to capture clear-cut harvest; and (2) a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer's and user's accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2). Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories, future observations must be temporally dense to distinguish between type and frequency in heterogeneous landscapes.

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

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.

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.

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

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.

[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.

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.

Legionnaires' disease case-finding algorithm, attack rates, and risk factors during a residential outbreak among older adults: an environmental and cohort study.

PubMed

Silk, Benjamin J; Foltz, Jennifer L; Ngamsnga, Kompan; Brown, Ellen; Muñoz, Mary Grace; Hampton, Lee M; Jacobs-Slifka, Kara; Kozak, Natalia A; Underwood, J Michael; Krick, John; Travis, Tatiana; Farrow, Olivia; Fields, Barry S; Blythe, David; Hicks, Lauri A

2013-06-27

During a Legionnaires' disease (LD) outbreak, combined epidemiological and environmental investigations were conducted to identify prevention recommendations for facilities where elderly residents live independently but have an increased risk of legionellosis. Survey responses (n = 143) were used to calculate attack rates and describe transmission routes by estimating relative risk (RR) and 95% confidence intervals (95% CI). Potable water collected from five apartments of LD patients and three randomly-selected apartments of residents without LD (n = 103 samples) was cultured for Legionella. Eight confirmed LD cases occurred among 171 residents (attack rate = 4.7%); two visitors also developed LD. One case was fatal. The average age of patients was 70 years (range: 62-77). LD risk was lower among residents who reported tub bathing instead of showering (RR = 0.13, 95% CI: 0.02-1.09, P = 0.03). Two respiratory cultures were characterized as L. pneumophila serogroup 1, monoclonal antibody type Knoxville (1,2,3), sequence type 222. An indistinguishable strain was detected in 31 (74%) of 42 potable water samples. Managers of elderly-housing facilities and local public health officials should consider developing a Legionella prevention plan. When Legionella colonization of potable water is detected in these facilities, remediation is indicated to protect residents at higher risk. If LD occurs among residents, exposure reduction, heightened awareness, and clinical surveillance activities should be coordinated among stakeholders. For prompt diagnosis and effective treatment, clinicians should recognize the increased risk and atypical presentation of LD in older adults.

Genomic Infectious Disease Epidemiology in Partially Sampled and Ongoing Outbreaks

PubMed Central

Didelot, Xavier; Fraser, Christophe; Gardy, Jennifer; Colijn, Caroline

2017-01-01

Abstract Genomic data are increasingly being used to understand infectious disease epidemiology. Isolates from a given outbreak are sequenced, and the patterns of shared variation are used to infer which isolates within the outbreak are most closely related to each other. Unfortunately, the phylogenetic trees typically used to represent this variation are not directly informative about who infected whom—a phylogenetic tree is not a transmission tree. However, a transmission tree can be inferred from a phylogeny while accounting for within-host genetic diversity by coloring the branches of a phylogeny according to which host those branches were in. Here we extend this approach and show that it can be applied to partially sampled and ongoing outbreaks. This requires computing the correct probability of an observed transmission tree and we herein demonstrate how to do this for a large class of epidemiological models. We also demonstrate how the branch coloring approach can incorporate a variable number of unique colors to represent unsampled intermediates in transmission chains. The resulting algorithm is a reversible jump Monte–Carlo Markov Chain, which we apply to both simulated data and real data from an outbreak of tuberculosis. By accounting for unsampled cases and an outbreak which may not have reached its end, our method is uniquely suited to use in a public health environment during real-time outbreak investigations. We implemented this transmission tree inference methodology in an R package called TransPhylo, which is freely available from https://github.com/xavierdidelot/TransPhylo. PMID:28100788

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

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

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.

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

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.

Differential Single Nucleotide Polymorphism-Based Analysis of an Outbreak Caused by Salmonella enterica Serovar Manhattan Reveals Epidemiological Details Missed by Standard Pulsed-Field Gel Electrophoresis

PubMed Central

Scaltriti, Erika; Sassera, Davide; Comandatore, Francesco; Morganti, Marina; Mandalari, Carmen; Gaiarsa, Stefano; Bandi, Claudio; Zehender, Gianguglielmo; Bolzoni, Luca; Casadei, Gabriele

2015-01-01

We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n = 15) and food, feed, animal, and environmental sources (n = 24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system. PMID:25653407

Differential single nucleotide polymorphism-based analysis of an outbreak caused by Salmonella enterica serovar Manhattan reveals epidemiological details missed by standard pulsed-field gel electrophoresis.

PubMed

Scaltriti, Erika; Sassera, Davide; Comandatore, Francesco; Morganti, Marina; Mandalari, Carmen; Gaiarsa, Stefano; Bandi, Claudio; Zehender, Gianguglielmo; Bolzoni, Luca; Casadei, Gabriele; Pongolini, Stefano

2015-04-01

We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n=15) and food, feed, animal, and environmental sources (n=24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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 ...

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-06-24

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

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.

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.

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.

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.

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

Syndromic surveillance system based on near real-time cattle mortality monitoring.

PubMed

Torres, G; Ciaravino, V; Ascaso, S; Flores, V; Romero, L; Simón, F

2015-05-01

Early detection of an infectious disease incursion will minimize the impact of outbreaks in livestock. Syndromic surveillance based on the analysis of readily available data can enhance traditional surveillance systems and allow veterinary authorities to react in a timely manner. This study was based on monitoring the number of cattle carcasses sent for rendering in the veterinary unit of Talavera de la Reina (Spain). The aim was to develop a system to detect deviations from expected values which would signal unexpected health events. Historical weekly collected dead cattle (WCDC) time series stabilized by the Box-Cox transformation and adjusted by the minimum least squares method were used to build the univariate cycling regression model based on a Fourier transformation. Three different models, according to type of production system, were built to estimate the baseline expected number of WCDC. Two types of risk signals were generated: point risk signals when the observed value was greater than the upper 95% confidence interval of the expected baseline, and cumulative risk signals, generated by a modified cumulative sum algorithm, when the cumulative sums of reported deaths were above the cumulative sum of expected deaths. Data from 2011 were used to prospectively validate the model generating seven risk signals. None of them were correlated to infectious disease events but some coincided, in time, with very high climatic temperatures recorded in the region. The harvest effect was also observed during the first week of the study year. Establishing appropriate risk signal thresholds is a limiting factor of predictive models; it needs to be adjusted based on experience gained during the use of the models. To increase the sensitivity and specificity of the predictions epidemiological interpretation of non-specific risk signals should be complemented by other sources of information. The methodology developed in this study can enhance other existing early detection surveillance systems. Syndromic surveillance based on mortality monitoring can reduce the detection time for certain disease outbreaks associated with mild mortality only detected at regional level. The methodology can be adapted to monitor other parameters routinely collected at farm level which can be influenced by communicable diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

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

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

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.

Zika Virus Outbreak in Rio de Janeiro, Brazil: Clinical Characterization, Epidemiological and Virological Aspects

PubMed Central

Calvet, Guilherme Amaral; Siqueira, André Machado; Wakimoto, Mayumi; de Sequeira, Patrícia Carvalho; Nobre, Aline; Quintana, Marcel de Souza Borges; de Mendonça, Marco Cesar Lima; Lupi, Otilia; de Souza, Rogerio Valls; Romero, Carolina; Zogbi, Heruza; Bressan, Clarisse da Silveira; Alves, Simone Sampaio; Lourenço-de-Oliveira, Ricardo; Nogueira, Rita Maria Ribeiro; Carvalho, Marilia Sá

2016-01-01

Background In 2015, Brazil was faced with the cocirculation of three arboviruses of major public health importance. The emergence of Zika virus (ZIKV) presents new challenges to both clinicians and public health authorities. Overlapping clinical features between diseases caused by ZIKV, Dengue (DENV) and Chikungunya (CHIKV) and the lack of validated serological assays for ZIKV make accurate diagnosis difficult. Methodology / Principal Findings The outpatient service for acute febrile illnesses in Fiocruz initiated a syndromic clinical observational study in 2007 to capture unusual presentations of DENV infections. In January 2015, an increase of cases with exanthematic disease was observed. Trained physicians evaluated the patients using a detailed case report form that included clinical assessment and laboratory investigations. The laboratory diagnostic algorithm included assays for detection of ZIKV, CHIKV and DENV. 364 suspected cases of Zika virus disease were identified based on clinical criteria between January and July 2015. Of these, 262 (71.9%) were tested and 119 (45.4%) were confirmed by the detection of ZIKV RNA. All of the samples with sequence information available clustered within the Asian genotype. Conclusions / Significance This is the first report of a ZIKV outbreak in the state of Rio de Janeiro, based on a large number of suspected (n = 364) and laboratory confirmed cases (n = 119). We were able to demonstrate that ZIKV was circulating in Rio de Janeiro as early as January 2015. The peak of the outbreak was documented in May/June 2015. More than half of the patients reported headache, arthralgia, myalgia, non-purulent conjunctivitis, and lower back pain, consistent with the case definition of suspected ZIKV disease issued by the Pan American Health Organization (PAHO). However, fever, when present, was low-intensity and short-termed. In our opinion, pruritus, the second most common clinical sign presented by the confirmed cases, should be added to the PAHO case definition, while fever could be given less emphasis. The emergence of ZIKV as a new pathogen for Brazil in 2015 underscores the need for clinical vigilance and strong epidemiological and laboratory surveillance. PMID:27070912

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.

Sexual networks, surveillance, and geographical space during syphilis outbreaks in rural North Carolina.

PubMed

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

2012-11-01

Sexually transmitted infections (STIs) spread along sexual networks whose structural characteristics promote transmission that routine surveillance may not capture. Cases who have partners from multiple localities may operate as spatial network bridges, thereby facilitating geographical dissemination. We investigated how surveillance, sexual networks, and spatial bridges relate to each other for syphilis outbreaks in rural counties of North Carolina. We selected from the state health department's surveillance database cases diagnosed with primary, secondary, or early latent syphilis during October 1998 to December 2002 and who resided in central and southeastern North Carolina, along with their sex partners and their social contacts irrespective of infection status. We applied matching algorithms to eliminate duplicate names and create a unique roster of partnerships from which networks were compiled and graphed. Network members were differentiated by disease status and county of residence. In the county most affected by the outbreak, densely connected networks indicative of STI outbreaks were consistent with increased incidence and a large case load. In other counties, the case loads were low with fluctuating incidence, but network structures suggested the presence of outbreaks. In a county with stable, low incidence and a high number of cases, the networks were sparse and dendritic, indicative of endemic spread. Outbreak counties exhibited densely connected networks within well-defined geographic boundaries and low connectivity between counties; spatial bridges did not seem to facilitate transmission. Simple visualization of sexual networks can provide key information to identify communities most in need of resources for outbreak investigation and disease control.

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.

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

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.

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.

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.

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 ...

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.

Ocean observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1998-01-01

Significant accomplishments made during the present reporting period: (1) We expanded our "spectral-matching" algorithm (SMA), for identifying the presence of absorbing aerosols and simultaneously performing atmospheric correction and derivation of the ocean's bio-optical parameters, to the point where it could be added as a subroutine to the MODIS water-leaving radiance algorithm; (2) A modification to the SMA that does not require detailed aerosol models has been developed. This is important as the requirement for realistic aerosol models has been a weakness of the SMA; and (3) We successfully acquired micro pulse lidar data in a Saharan dust outbreak during ACE-2 in the Canary Islands.

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.

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

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.

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.

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.

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.

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.

Doppler weather radar detects emigratory flights of noctuids during a major pest outbreak

USDA-ARS?s Scientific Manuscript database

An outbreak of beet armyworm (Spodoptera exigua (Hübner)), cabbage looper, (Trichoplusia ni (Hübner)), and other lepidopteran pests devastated cotton production in the Lower Rio Grande Valley TX, in 1995. Major infestations occurred later in the year several hundred kilometers away in other cotton ...

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...

Economic costs of outbreaks of acute viral gastroenteritis due to norovirus in Catalonia (Spain), 2010-2011.

PubMed

Navas, Encarna; Torner, Nuria; Broner, Sonia; Godoy, Pere; Martínez, Ana; Bartolomé, Rosa; Domínguez, Angela

2015-10-01

To determine the direct and indirect costs of outbreaks of acute viral gastroenteritis (AVG) due to norovirus in closed institutions (hospitals, social health centers or nursing homes) and the community in Catalonia in 2010-11. Information on outbreaks were gathered from the reports made by epidemiological surveillance units. Direct costs (medical visits, hospital stays, drug treatment, sample processing, transport, diagnostic tests, monitoring and control of the outbreaks investigated) and indirect costs (lost productivity due to work absenteeism, caregivers time and working hours lost due to medical visits) were calculated. Twenty-seven outbreaks affecting 816 people in closed institutions and 74 outbreaks affecting 1,940 people in the community were detected. The direct and indirect costs of outbreaks were € 131,997.36 (€ 4,888.79 per outbreak) in closed institutions and € 260,557.16 (€ 3,521.04 per outbreak) in community outbreaks. The cost per case was € 161.76 in outbreaks in closed institutions and € 134.31 in community outbreaks. The main costs were surveillance unit monitoring (€ 116,652.93), laboratory diagnoses (€ 119,950.95), transport of samples (€ 69,970.90), medical visits (€ 25,250.50) and hospitalization (€ 13,400.00). The cost of outbreaks of acute viral gastroenteritis due to norovirus obtained in this study was influenced by the number of people affected and the severity of the outbreak, which determined hospitalizations and work absenteeism. Urgent reporting of outbreaks would allow the implementation of control measures that could reduce the numbers affected and the duration of the illness and thus the costs derived from them.

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

PubMed

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

2017-04-26

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

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

PubMed

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

1999-12-01

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

Modelling the time at which overcrowding and feed interruption emerge on the swine premises under movement restrictions during a classical swine fever outbreak.

PubMed

Weng, H Y; Yadav, S; Olynk Widmar, N J; Croney, C; Ash, M; Cooper, M

2017-03-01

A stochastic risk model was developed to estimate the time elapsed before overcrowding (TOC) or feed interruption (TFI) emerged on the swine premises under movement restrictions during a classical swine fever (CSF) outbreak in Indiana, USA. Nursery (19 to 65 days of age) and grow-to-finish (40 to 165 days of age) pork production operations were modelled separately. Overcrowding was defined as the total weight of pigs on premises exceeding 100% to 115% of the maximum capacity of the premises, which was computed as the total weight of the pigs at harvest/transition age. Algorithms were developed to estimate age-specific weight of the pigs on premises and to compare the daily total weight of the pigs with the threshold weight defining overcrowding to flag the time when the total weight exceeded the threshold (i.e. when overcrowding occurred). To estimate TFI, an algorithm was constructed to model a swine producer's decision to discontinue feed supply by incorporating the assumptions that a longer estimated epidemic duration, a longer time interval between the age of pigs at the onset of the outbreak and the harvest/transition age, or a longer progression of an ongoing outbreak would increase the probability of a producer's decision to discontinue the feed supply. Adverse animal welfare conditions were modelled to emerge shortly after an interruption of feed supply. Simulations were run with 100 000 iterations each for a 365-day period. Overcrowding occurred in all simulated iterations, and feed interruption occurred in 30% of the iterations. The median (5th and 95th percentiles) TOC was 24 days (10, 43) in nursery operations and 78 days (26, 134) in grow-to-finish operations. Most feed interruptions, if they emerged, occurred within 15 days of an outbreak. The median (5th and 95th percentiles) time at which either overcrowding or feed interruption emerged was 19 days (4, 42) in nursery and 57 days (4, 130) in grow-to-finish operations. The study findings suggest that overcrowding and feed interruption could emerge early during a CSF outbreak among swine premises under movement restrictions. The outputs derived from the risk model could be used to estimate and evaluate associated mitigation strategies for alleviating adverse animal welfare conditions resulting from movement restrictions.

A smartphone-based diagnostic platform for rapid detection of Zika, chikungunya, and dengue viruses

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

Priye, Aashish; Bird, Sara W.; Light, Yooli K.

Current multiplexed diagnostics for Zika, dengue, and chikungunya viruses are situated outside the intersection of affordability, high performance, and suitability for use at the point-of-care in resource-limited settings. Consequently, insufficient diagnostic capabilities are a key limitation facing current Zika outbreak management strategies. We demonstrate highly sensitive and specific detection of Zika, chikungunya, and dengue viruses by coupling reverse-transcription loop-mediated isothermal amplification (RT-LAMP) with our recently developed quenching of unincorporated amplification signal reporters (QUASR) technique. We conduct reactions in a simple, inexpensive and portable “LAMP box” supplemented with a consumer class smartphone. The entire assembly can be powered by a 5more » V USB source such as a USB power bank or solar panel. The smartphone employs a novel algorithm utilizing chromaticity to analyze fluorescence signals, which improves the discrimination of positive/negative signals by 5-fold when compared to detection with traditional RGB intensity sensors or the naked eye. The ability to detect ZIKV directly from crude human sample matrices (blood, urine, and saliva) demonstrates our device’s utility for widespread clinical deployment. Altogether, these advances enable our system to host the key components necessary to expand the use of nucleic acid amplification-based detection assays towards point-of-care settings where they are needed most.« less

A smartphone-based diagnostic platform for rapid detection of Zika, chikungunya, and dengue viruses

DOE PAGES

Priye, Aashish; Bird, Sara W.; Light, Yooli K.; ...

2017-03-20

Current multiplexed diagnostics for Zika, dengue, and chikungunya viruses are situated outside the intersection of affordability, high performance, and suitability for use at the point-of-care in resource-limited settings. Consequently, insufficient diagnostic capabilities are a key limitation facing current Zika outbreak management strategies. We demonstrate highly sensitive and specific detection of Zika, chikungunya, and dengue viruses by coupling reverse-transcription loop-mediated isothermal amplification (RT-LAMP) with our recently developed quenching of unincorporated amplification signal reporters (QUASR) technique. We conduct reactions in a simple, inexpensive and portable “LAMP box” supplemented with a consumer class smartphone. The entire assembly can be powered by a 5more » V USB source such as a USB power bank or solar panel. The smartphone employs a novel algorithm utilizing chromaticity to analyze fluorescence signals, which improves the discrimination of positive/negative signals by 5-fold when compared to detection with traditional RGB intensity sensors or the naked eye. The ability to detect ZIKV directly from crude human sample matrices (blood, urine, and saliva) demonstrates our device’s utility for widespread clinical deployment. Altogether, these advances enable our system to host the key components necessary to expand the use of nucleic acid amplification-based detection assays towards point-of-care settings where they are needed most.« less

Development of a Sensitive and Specific Serological Assay Based on Luminex Technology for Detection of Antibodies to Zaire Ebola Virus

PubMed Central

Touré, Abdoulaye; Butel, Christelle; Keita, Alpha Kabinet; Binetruy, Florian; Sow, Mamadou S.; Foulongne, Vincent; Delaporte, Eric; Peeters, Martine

2016-01-01

ABSTRACT The recent Zaire Ebola virus (EBOV) outbreak in West Africa illustrates clearly the need for additional studies with humans and animals to elucidate the ecology of Ebola viruses (EBVs). In this study, we developed a serological assay based on the Luminex technology. Nine recombinant proteins representing different viral regions (nucleoprotein [NP], 40-kDa viral protein [VP40], and glycoprotein [GP]) from four of the five EBV lineages were used. Samples from 94 survivors of the EBOV outbreak in Guinea and negative samples from 108 patients in France were used to calculate test performance for EBOV detection and cross-reaction with other Ebola virus lineages. For EBOV antibody detection, sensitivities of 95.7%, 96.8%, and 92.5% and specificities of 94.4%, 95.4%, and 96.3% for NP, GP, and VP40, respectively, were observed. All EBOV-negative samples that presented a reaction, except for one, interacted with a single antigen, whereas almost all samples from EBOV survivors were simultaneously reactive with NP and GP (90/94) or with NP, GP, and VP40 (87/94). Considering as positive for past EBOV infection only samples that reacted with EBOV NP and GP, sensitivity was 95.7% and specificity increased to 99.1%. Comparing results with commercial EBOV NP and GP enzyme-linked immunosorbent assays (ELISAs; Alpha Diagnostic, San Antonio, TX), lower sensitivity (92.5%) and high specificity (100%) were observed with the same positivity criteria. Samples from EBOV survivors cross-reacted with GP from Sudan Ebola virus (GP-SUDV) (81.9%), GP from Bundibugyo Ebola virus (GP-BDBV) (51.1%), GP from Reston Ebola virus (GP-RESTV) (9.6%), VP40-SUDV (76.6%), and VP40-BDBV (38.3%). Overall, we developed a sensitive and specific high-throughput serological assay, and defined an algorithm, for epidemiological surveys with humans. PMID:27795350

Development of a Sensitive and Specific Serological Assay Based on Luminex Technology for Detection of Antibodies to Zaire Ebola Virus.

PubMed

Ayouba, Ahidjo; Touré, Abdoulaye; Butel, Christelle; Keita, Alpha Kabinet; Binetruy, Florian; Sow, Mamadou S; Foulongne, Vincent; Delaporte, Eric; Peeters, Martine

2017-01-01

The recent Zaire Ebola virus (EBOV) outbreak in West Africa illustrates clearly the need for additional studies with humans and animals to elucidate the ecology of Ebola viruses (EBVs). In this study, we developed a serological assay based on the Luminex technology. Nine recombinant proteins representing different viral regions (nucleoprotein [NP], 40-kDa viral protein [VP40], and glycoprotein [GP]) from four of the five EBV lineages were used. Samples from 94 survivors of the EBOV outbreak in Guinea and negative samples from 108 patients in France were used to calculate test performance for EBOV detection and cross-reaction with other Ebola virus lineages. For EBOV antibody detection, sensitivities of 95.7%, 96.8%, and 92.5% and specificities of 94.4%, 95.4%, and 96.3% for NP, GP, and VP40, respectively, were observed. All EBOV-negative samples that presented a reaction, except for one, interacted with a single antigen, whereas almost all samples from EBOV survivors were simultaneously reactive with NP and GP (90/94) or with NP, GP, and VP40 (87/94). Considering as positive for past EBOV infection only samples that reacted with EBOV NP and GP, sensitivity was 95.7% and specificity increased to 99.1%. Comparing results with commercial EBOV NP and GP enzyme-linked immunosorbent assays (ELISAs; Alpha Diagnostic, San Antonio, TX), lower sensitivity (92.5%) and high specificity (100%) were observed with the same positivity criteria. Samples from EBOV survivors cross-reacted with GP from Sudan Ebola virus (GP-SUDV) (81.9%), GP from Bundibugyo Ebola virus (GP-BDBV) (51.1%), GP from Reston Ebola virus (GP-RESTV) (9.6%), VP40-SUDV (76.6%), and VP40-BDBV (38.3%). Overall, we developed a sensitive and specific high-throughput serological assay, and defined an algorithm, for epidemiological surveys with humans. Copyright © 2016 American Society for Microbiology.

Legionnaires’ disease case-finding algorithm, attack rates, and risk factors during a residential outbreak among older adults: an environmental and cohort study

PubMed Central

2013-01-01

Background During a Legionnaires’ disease (LD) outbreak, combined epidemiological and environmental investigations were conducted to identify prevention recommendations for facilities where elderly residents live independently but have an increased risk of legionellosis. Methods Survey responses (n = 143) were used to calculate attack rates and describe transmission routes by estimating relative risk (RR) and 95% confidence intervals (95% CI). Potable water collected from five apartments of LD patients and three randomly-selected apartments of residents without LD (n = 103 samples) was cultured for Legionella. Results Eight confirmed LD cases occurred among 171 residents (attack rate = 4.7%); two visitors also developed LD. One case was fatal. The average age of patients was 70 years (range: 62–77). LD risk was lower among residents who reported tub bathing instead of showering (RR = 0.13, 95% CI: 0.02–1.09, P = 0.03). Two respiratory cultures were characterized as L. pneumophila serogroup 1, monoclonal antibody type Knoxville (1,2,3), sequence type 222. An indistinguishable strain was detected in 31 (74%) of 42 potable water samples. Conclusions Managers of elderly-housing facilities and local public health officials should consider developing a Legionella prevention plan. When Legionella colonization of potable water is detected in these facilities, remediation is indicated to protect residents at higher risk. If LD occurs among residents, exposure reduction, heightened awareness, and clinical surveillance activities should be coordinated among stakeholders. For prompt diagnosis and effective treatment, clinicians should recognize the increased risk and atypical presentation of LD in older adults. PMID:23806063

Environmental Survey of Drinking Water Sources in Kampala, Uganda, during a Typhoid Fever Outbreak.

PubMed

Murphy, J L; Kahler, A M; Nansubuga, I; Nanyunja, E M; Kaplan, B; Jothikumar, N; Routh, J; Gómez, G A; Mintz, E D; Hill, V R

2017-12-01

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. Copyright © 2017 American Society for Microbiology.

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

PubMed

Rastawicki, Waldemar; Kałużewski, Stanisław

2015-01-01

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

A large outbreak of typhoid fever associated with a high rate of intestinal perforation in Kasese District, Uganda, 2008-2009.

PubMed

Neil, Karen P; Sodha, Samir V; Lukwago, Luswa; O-Tipo, Shikanga; Mikoleit, Matthew; Simington, Sherricka D; Mukobi, Peter; Balinandi, Stephen; Majalija, Samuel; Ayers, Joseph; Kagirita, Atek; Wefula, Edward; Asiimwe, Frank; Kweyamba, Vianney; Talkington, Deborah; Shieh, Wun-Ju; Adem, Patricia; Batten, Brigid C; Zaki, Sherif R; Mintz, Eric

2012-04-01

Salmonella enterica serovar Typhi (Salmonella Typhi) causes an estimated 22 million typhoid fever cases and 216 000 deaths annually worldwide. In Africa, the lack of laboratory diagnostic capacity limits the ability to recognize endemic typhoid fever and to detect outbreaks. We report a large laboratory-confirmed outbreak of typhoid fever in Uganda with a high proportion of intestinal perforations (IPs). A suspected case of typhoid fever was defined as fever and abdominal pain in a person with either vomiting, diarrhea, constipation, headache, weakness, arthralgia, poor response to antimalarial medications, or IP. From March 4, 2009 to April 17, 2009, specimens for blood and stool cultures and serology were collected from suspected cases. Antimicrobial susceptibility testing and pulsed-field gel electrophoresis (PFGE) were performed on Salmonella Typhi isolates. Surgical specimens from patients with IP were examined. A community survey was conducted to characterize the extent of the outbreak. From December 27, 2007 to July 30, 2009, 577 cases, 289 hospitalizations, 249 IPs, and 47 deaths from typhoid fever occurred; Salmonella Typhi was isolated from 27 (33%) of 81 patients. Isolates demonstrated multiple PFGE patterns and uniform susceptibility to ciprofloxacin. Surgical specimens from 30 patients were consistent with typhoid fever. Estimated typhoid fever incidence in the community survey was 8092 cases per 100 000 persons. This typhoid fever outbreak was detected because of an elevated number of IPs. Underreporting of milder illnesses and delayed and inadequate antimicrobial treatment contributed to the high perforation rate. Enhancing laboratory capacity for detection is critical to improving typhoid fever control.

Silent Circulation of St. Louis Encephalitis Virus Prior to an Encephalitis Outbreak in Cordoba, Argentina (2005)

PubMed Central

Díaz, Luis Adrian; Albrieu Llinás, Guillermo; Vázquez, Ana; Tenorio, Antonio; Contigiani, Marta Silvia

2012-01-01

St. Louis encephalitis virus is a complex zoonoses. In 2005, 47 laboratory-confirmed and probable clinical cases of SLEV infection were reported in Córdoba, Argentina. Although the causes of 2005 outbreak remain unknown, they might be related not only to virological factors, but also to ecological and environmental conditions. We hypothesized that one of the factors for SLE reemergence in Córdoba, Argentina, was the introduction of a new SLEV genotype (SLEV genotype III), with no previous activity in the area. In order to evaluate this hypothesis we carried out a molecular characterization of SLEV detections from mosquitoes collected between 2001 and 2004 in Córdoba city. A total of 315 mosquito pools (11,002 individuals) including 12 mosquitoes species were analyzed. Overall, 20 pools (8 mosquitoes species) were positive for SLEV. During this study, genotypes II, V and VII were detected. No mosquito pool infected with genotype III was detected before the 2005 outbreak. Genotype V was found every year and in the 8 sampled sites. Genotypes II and VII showed limited temporal and spatial activities. We cannot dismiss the association of genotype II and V as etiological agents during the outbreak. However, the silent circulation of other SLEV strains in Córdoba city before the 2005 outbreak suggests that the introduction of genotype III was an important factor associated to this event. Not mutually exclusive, other factors such as changes in avian hosts and mosquitoes vectors communities, driven by climatic and environmental modifications, should also be taken into consideration in further studies. PMID:22303490

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

PubMed Central

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

2016-01-01

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

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.

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.

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

Outbreak of scarlet fever associated with emm12 type group A Streptococcus in 2011 in Shanghai, China.

PubMed

Chen, Mingliang; Yao, Weilei; Wang, Xiaohong; Li, Yuefang; Chen, Min; Wang, Gangyi; Zhang, Xi; Pan, Hao; Hu, Jiayu; Zeng, Mei

2012-09-01

An unprecedented, large outbreak of childhood scarlet fever occurred in Shanghai between April and July 2011. Investigation of the epidemiology could enhance our understanding of the factors related to the outbreak. We retrospectively analyzed the demographic and seasonal characteristics of children with scarlet fever and the outcome. During the peak month of the 2011 outbreak, 45 GAS isolates recovered from pediatric patients and 13 (43.3%) GAS isolates recovered from 30 asymptomatic student contacts were characterized by emm typing, superantigen profiles, pulsed-field gel electrophoresis genotypes, mutilocus sequence typing and antimicrobial susceptibility. The 2011 outbreak of scarlet fever started in April and peaked in May and June. Boys outnumbered girls (65.1% versus 34.9%). Preschool and primary school children accounted for 96% of cases. No severe outcome was found. emm1, emm12 and emm75 were identified among 58 GAS isolates, and 53 (91.4%) isolates belonged to emm12, st36. Ten pulsed-field gel electrophoresis genotypes were identified among emm12 GAS isolates, 43 (81.1%) shared SPYS16.001 genotype and the remaining 7 genotypes detected were related to SPYS16.001 closely or possibly. No streptococcal pyrogenic exotoxin A and streptococcal pyrogenic exotoxin M were detected in 58 isolates. All emm12 GAS isolates were resistant to azithromycin and clindamycin. emm12 GAS strain caused the large 2011 outbreak of scarlet fever in Shanghai. Antibiotic resistance to macrolides and clindamycin in GAS is prevalent in Shanghai.

Post-Outbreak Investigation of Pseudomonas aeruginosa Faucet Contamination by Quantitative Polymerase Chain Reaction and Environmental Factors Affecting Positivity.

PubMed

Bédard, Emilie; Laferrière, Céline; Charron, Dominique; Lalancette, Cindy; Renaud, Christian; Desmarais, Nadia; Déziel, Eric; Prévost, Michèle

2015-11-01

To perform a post-outbreak prospective study of the Pseudomonas aeruginosa contamination at the faucets (water, aerator and drain) by culture and quantitative polymerase chain reaction (qPCR) and to assess environmental factors influencing occurrence A 450-bed pediatric university hospital in Montreal, Canada Water, aerator swab, and drain swab samples were collected from faucets and analyzed by culture and qPCR for the post-outbreak investigation. Water microbial and physicochemical parameters were measured, and a detailed characterization of the sink environmental and design parameters was performed. The outbreak genotyping investigation identified drains and aerators as the source of infection. The implementation of corrective measures was effective, but post-outbreak sampling using qPCR revealed 50% positivity for P. aeruginosa remaining in the water compared with 7% by culture. P. aeruginosa was recovered in the water, the aerator, and the drain in 21% of sinks. Drain alignment vs the faucet and water microbial quality were significant factors associated with water positivity, whereas P. aeruginosa load in the water was an average of 2 log higher for faucets with a positive aerator. P. aeruginosa contamination in various components of sink environments was still detected several years after the resolution of an outbreak in a pediatric university hospital. Although contamination is often not detectable in water samples by culture, P. aeruginosa is present and can recover its culturability under favorable conditions. The importance of having clear maintenance protocols for water systems, including the drainage components, is highlighted.

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.

A Waterborne Gastroenteritis Outbreak Caused by Norovirus GII.17 in a Hotel, Hebei, China, December 2014.

PubMed

Qin, Meng; Dong, Xiao-Gen; Jing, Yan-Yan; Wei, Xiu-Xia; Wang, Zhao-E; Feng, Hui-Ru; Yu, Hong; Li, Jin-Song; Li, Jie

2016-09-01

Norovirus (NoV) is responsible for an estimated 90 % of all epidemic nonbacterial outbreaks of gastroenteritis worldwide. Waterborne outbreaks of NoV are commonly reported. A novel GII.17 NoV strain emerged as a major cause of gastroenteritis outbreaks in China during the winter of 2014/2015. During this time, an outbreak of gastroenteritis occurred at a hotel in a ski park in Hebei Province, China. Epidemiological investigations indicated that one water well, which had only recently been in use, was the probable source. GII.17 NoV was detected by real-time reverse-transcription polymerase chain reaction from samples taken from cases, from concentrated water samples from water well, and from the nearby sewage settling tank. Nucleotide sequences of NoV extracted from clinical and water specimens were genetically identical and had 99 % homology with Beijing/CHN/2015. All epidemiological data indicated that GII.17 NoV was responsible for this outbreak. This is the first reported laboratory-confirmed waterborne outbreak caused by GII.17 NoV genotype in China. Strengthening management of well drinking water and systematica monitoring of NoV is essential for preventing future outbreaks.

Internet and free press are associated with reduced lags in global outbreak reporting.

PubMed

McAlarnen, Lindsey; Smith, Katherine; Brownstein, John S; Jerde, Christopher

2014-10-30

Global outbreak detection and reporting have generally improved for a variety of infectious diseases and geographic regions in recent decades. Nevertheless, lags in outbreak reporting remain a threat to the global human health and economy. In the time between first occurrence of a novel disease incident and public notification of an outbreak, infected individuals have a greater possibility of traveling and spreading the pathogen to other nations. Shortening outbreak reporting lags has the potential to improve global health by preventing local outbreaks from escalating into global epidemics. Reporting lags between the first record and the first public report of an event were calculated for 318 outbreaks occurring 1996-2009. The influence of freedom of the press, Internet usage, per capita health expenditure, and cell phone subscriptions, on the timeliness of outbreak reporting was evaluated. Freer presses and increasing Internet usage correlate with reduced time between the first record of an outbreak and the public report. Increasing Internet usage reduced the expected reporting lag from more than one month in nations without Internet users to one day in those where 75 of 100 people use the Internet. Advances in technology and the emergence of more open and free governments are associated with to improved global infectious disease surveillance.

Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli.

PubMed

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

2014-01-01

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. 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. 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. 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.

Outbreaks of human metapneumovirus in two skilled nursing facilities -West Virginia and Idaho, 2011-2012.

PubMed

2013-11-22

During January and February 2012, state and local public health agencies in West Virginia and Idaho, with assistance from facility staff members and CDC, investigated outbreaks of unexplained respiratory illness characterized by high proportions of lower respiratory tract infections (LRTIs) at two skilled nursing facilities (SNFs). Investigations were conducted to determine the extent and etiology of each outbreak and make recommendations to prevent further spread. During both outbreaks, influenza was initially suspected; however, human metapneumovirus (hMPV) was identified as the etiologic agent. Among 57 cases of respiratory illness from both facilities, 45 (79%) patients had evidence of LRTI, of whom 25 (56%) had radiologically confirmed pneumonia; five (9%) had evidence of upper respiratory tract infection (URTI), and seven (12%) could not be classified. Six patients (11%) died. These outbreaks demonstrate that hMPV, a recently described pathogen that would not have been detected without the use of molecular diagnostics in these outbreaks, is associated with severe LRTI and should be considered as a possible etiology of respiratory outbreaks in SNFs.

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.

Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

NASA Astrophysics Data System (ADS)

Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

2014-05-01

The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

Polio and Measles Down the Drain: Environmental Enterovirus Surveillance in the Netherlands, 2005 to 2015.

PubMed

Benschop, Kimberley S M; van der Avoort, Harrie G; Jusic, Edin; Vennema, Harry; van Binnendijk, Rob; Duizer, Erwin

2017-07-01

Polioviruses (PVs) are members of the genus Enterovirus In the Netherlands, the exclusion of PV circulation is based on clinical enterovirus (EV) surveillance (CEVS) of EV-positive cases and routine environmental EV surveillance (EEVS) conducted on sewage samples collected in the region of the Netherlands where vaccination coverage is low due to religious reasons. We compared the EEVS data to those of the CEVS to gain insight into the relevance of EEVS for poliovirus and nonpolio enterovirus surveillance. Following the polio outbreak in Syria, EEVS was performed at the primary refugee center in Ter Apel in the Netherlands, and data were compared to those of CEVS and EEVS. Furthermore, we assessed the feasibility of poliovirus detection by EEVS using measles virus detection in sewage during a measles outbreak as a proxy. Two Sabin-like PVs were found in routine EEVS, 11 Sabin-like PVs were detected in the CEVS, and one Sabin-like PV was found in the Ter Apel sewage. We observed significant differences between the three programs regarding which EVs were found. In 6 sewage samples collected during the measles outbreak in 2013, measles virus RNA was detected in regions where measles cases were identified. In conclusion, we detected PVs, nonpolio EVs, and measles virus in sewage and showed that environmental surveillance is useful for poliovirus detection in the Netherlands, where live oral poliovirus vaccine is not used and communities with lower vaccination coverage exist. EEVS led to the detection of EV types not seen in the CEVS, showing that EEVS is complementary to CEVS. IMPORTANCE We show that environmental enterovirus surveillance complements clinical enterovirus surveillance for poliovirus detection, or exclusion, and for nonpolio enterovirus surveillance. Even in the presence of adequate surveillance, only a very limited number of Sabin-like poliovirus strains were detected in a 10-year period, and no signs of transmission of oral polio vaccine (OPV) strains were found in a country using exclusively inactivated polio vaccine (IPV). Measles viruses can be detected during an outbreak in sewage samples collected and concentrated following procedures used for environmental enterovirus surveillance. Copyright © 2017 American Society for Microbiology.

Polio and Measles Down the Drain: Environmental Enterovirus Surveillance in the Netherlands, 2005 to 2015

PubMed Central

Benschop, Kimberley S. M.; van der Avoort, Harrie G.; Jusic, Edin; Vennema, Harry; van Binnendijk, Rob

2017-01-01

ABSTRACT Polioviruses (PVs) are members of the genus Enterovirus. In the Netherlands, the exclusion of PV circulation is based on clinical enterovirus (EV) surveillance (CEVS) of EV-positive cases and routine environmental EV surveillance (EEVS) conducted on sewage samples collected in the region of the Netherlands where vaccination coverage is low due to religious reasons. We compared the EEVS data to those of the CEVS to gain insight into the relevance of EEVS for poliovirus and nonpolio enterovirus surveillance. Following the polio outbreak in Syria, EEVS was performed at the primary refugee center in Ter Apel in the Netherlands, and data were compared to those of CEVS and EEVS. Furthermore, we assessed the feasibility of poliovirus detection by EEVS using measles virus detection in sewage during a measles outbreak as a proxy. Two Sabin-like PVs were found in routine EEVS, 11 Sabin-like PVs were detected in the CEVS, and one Sabin-like PV was found in the Ter Apel sewage. We observed significant differences between the three programs regarding which EVs were found. In 6 sewage samples collected during the measles outbreak in 2013, measles virus RNA was detected in regions where measles cases were identified. In conclusion, we detected PVs, nonpolio EVs, and measles virus in sewage and showed that environmental surveillance is useful for poliovirus detection in the Netherlands, where live oral poliovirus vaccine is not used and communities with lower vaccination coverage exist. EEVS led to the detection of EV types not seen in the CEVS, showing that EEVS is complementary to CEVS. IMPORTANCE We show that environmental enterovirus surveillance complements clinical enterovirus surveillance for poliovirus detection, or exclusion, and for nonpolio enterovirus surveillance. Even in the presence of adequate surveillance, only a very limited number of Sabin-like poliovirus strains were detected in a 10-year period, and no signs of transmission of oral polio vaccine (OPV) strains were found in a country using exclusively inactivated polio vaccine (IPV). Measles viruses can be detected during an outbreak in sewage samples collected and concentrated following procedures used for environmental enterovirus surveillance. PMID:28432101

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

PubMed

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

2007-12-01

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

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

PubMed Central

Kamadjeu, Raoul; Gathenji, Caroline

2017-01-01

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

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

PubMed

Kamadjeu, Raoul; Gathenji, Caroline

2017-01-01

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

Dead or alive: animal sampling during Ebola hemorrhagic fever outbreaks in humans

PubMed Central

Olson, Sarah H.; Reed, Patricia; Cameron, Kenneth N.; Ssebide, Benard J.; Johnson, Christine K.; Morse, Stephen S.; Karesh, William B.; Mazet, Jonna A. K.; Joly, Damien O.

2012-01-01

There are currently no widely accepted animal surveillance guidelines for human Ebola hemorrhagic fever (EHF) outbreak investigations to identify potential sources of Ebolavirus (EBOV) spillover into humans and other animals. Animal field surveillance during and following an outbreak has several purposes, from helping identify the specific animal source of a human case to guiding control activities by describing the spatial and temporal distribution of wild circulating EBOV, informing public health efforts, and contributing to broader EHF research questions. Since 1976, researchers have sampled over 10,000 individual vertebrates from areas associated with human EHF outbreaks and tested for EBOV or antibodies. Using field surveillance data associated with EHF outbreaks, this review provides guidance on animal sampling for resource-limited outbreak situations, target species, and in some cases which diagnostics should be prioritized to rapidly assess the presence of EBOV in animal reservoirs. In brief, EBOV detection was 32.7% (18/55) for carcasses (animals found dead) and 0.2% (13/5309) for live captured animals. Our review indicates that for the purposes of identifying potential sources of transmission from animals to humans and isolating suspected virus in an animal in outbreak situations, (1) surveillance of free-ranging non-human primate mortality and morbidity should be a priority, (2) any wildlife morbidity or mortality events should be investigated and may hold the most promise for locating virus or viral genome sequences, (3) surveillance of some bat species is worthwhile to isolate and detect evidence of exposure, and (4) morbidity, mortality, and serology studies of domestic animals should prioritize dogs and pigs and include testing for virus and previous exposure. PMID:22558004

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

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

PubMed

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

2015-09-15

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. A rise in Campylobacter gastroenteritis in an isolated population was investigated using whole-genome sequencing (WGS), an epidemiological study, and environmental investigations. 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. 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. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

Health of whitebark pine forests after mountain pine beetle outbreaks

Treesearch

Sandra Kegley; John Schwandt; Ken Gibson; Dana Perkins

2011-01-01

Whitebark pine (Pinus albicaulis), a keystone high-elevation species, is currently at risk due to a combination of white pine blister rust (WPBR) (Cronartium ribicola), forest succession, and outbreaks of mountain pine beetle (MPB) (Dendroctonus ponderosae). While recent mortality is often quantified by aerial detection surveys (ADS) or ground surveys, little...

Molecular typing of Salmonella enterica serovar typhi.

PubMed Central

Navarro, F; Llovet, T; Echeita, M A; Coll, P; Aladueña, A; Usera, M A; Prats, G

1996-01-01

The efficiencies of different tests for epidemiological markers--phage typing, ribotyping, IS200 typing, and pulsed-field gel electrophoresis (PFGE)--were evaluated for strains from sporadic cases of typhoid fever and a well-defined outbreak. Ribotyping and PFGE proved to be the most discriminating. Both detected two different patterns among outbreak-associated strains. PMID:8897193

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

Treesearch

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

2017-01-01

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

Landscape-scale genetic variation in a forest outbreak species, the mountain pine beetle (Dendroctonus ponderosae)

Treesearch

K. E. Mock; B. J. Bentz; E. M. O' Neill; J. P. Chong; J. Orwin; M. E. Pfrender

2007-01-01

The mountain pine beetle Dendroctonus ponderosae is a native species currently experiencing large-scale outbreaks in western North American pine forests. We sought to describe the pattern of genetic variation across the range of this species, to determine whether there were detectable genetic differences between D. ponderosae...

Outbreak of sorghum/sugarcane aphid on sorghum: First detections, distribution, and notes on management

USDA-ARS?s Scientific Manuscript database

An outbreak of an invasive aphid was discovered damaging grain sorghum in Texas and neighboring states in 2013. It may be a new variant of sugarcane aphid, Melanaphis sacchari, that has a high preference for sorghum, or a very closely related species (M. sorghi). We designate it sorghum/sugarcane ...

Evaluation of Strategies to Control a Potential Outbreak of Foot-and-Mouth Disease in Sweden.

PubMed

Dórea, Fernanda C; Nöremark, Maria; Widgren, Stefan; Frössling, Jenny; Boklund, Anette; Halasa, Tariq; Ståhl, Karl

2017-01-01

To minimize the potential consequences of an introduction of foot-and-mouth disease (FMD) in Europe, European Union (EU) member states are required to present a contingency plan. This study used a simulation model to study potential outbreak scenarios in Sweden and evaluate the best control strategies. The model was informed by the Swedish livestock structure using herd information from cattle, pig, and small ruminant holdings in the country. The contact structure was based on animal movement data and studies investigating the movements between farms of veterinarians, service trucks, and other farm visitors. All scenarios of outbreak control included depopulation of detected herds, 3 km protection and 10 km surveillance zones, movement tracing, and 3 days national standstill. The effect of availability of surveillance resources, i.e., number of field veterinarians per day, and timeliness of enforcement of interventions, was assessed. With the estimated currently available resources, an FMD outbreak in Sweden is expected to be controlled (i.e., last infected herd detected) within 3 weeks of detection in any evaluated scenario. The density of farms in the area where the epidemic started would have little impact on the time to control the outbreak, but spread in high density areas would require more surveillance resources, compared to areas of lower farm density. The use of vaccination did not result in a reduction in the expected number of infected herds. Preemptive depopulation was able to reduce the number of infected herds in extreme scenarios designed to test a combination of worst-case conditions of virus introduction and spread, but at the cost of doubling the number of herds culled. This likely resulted from a combination of the small outbreaks predicted by the spread model, and the high efficacy of the basic control measures evaluated, under the conditions of the Swedish livestock industry, and considering the assumed control resources available. The results indicate that the duration and extent of FMD outbreaks could be kept limited in Sweden using the EU standard control strategy and a 3 days national standstill.

Evaluation of Strategies to Control a Potential Outbreak of Foot-and-Mouth Disease in Sweden

PubMed Central

Dórea, Fernanda C.; Nöremark, Maria; Widgren, Stefan; Frössling, Jenny; Boklund, Anette; Halasa, Tariq; Ståhl, Karl

2017-01-01

To minimize the potential consequences of an introduction of foot-and-mouth disease (FMD) in Europe, European Union (EU) member states are required to present a contingency plan. This study used a simulation model to study potential outbreak scenarios in Sweden and evaluate the best control strategies. The model was informed by the Swedish livestock structure using herd information from cattle, pig, and small ruminant holdings in the country. The contact structure was based on animal movement data and studies investigating the movements between farms of veterinarians, service trucks, and other farm visitors. All scenarios of outbreak control included depopulation of detected herds, 3 km protection and 10 km surveillance zones, movement tracing, and 3 days national standstill. The effect of availability of surveillance resources, i.e., number of field veterinarians per day, and timeliness of enforcement of interventions, was assessed. With the estimated currently available resources, an FMD outbreak in Sweden is expected to be controlled (i.e., last infected herd detected) within 3 weeks of detection in any evaluated scenario. The density of farms in the area where the epidemic started would have little impact on the time to control the outbreak, but spread in high density areas would require more surveillance resources, compared to areas of lower farm density. The use of vaccination did not result in a reduction in the expected number of infected herds. Preemptive depopulation was able to reduce the number of infected herds in extreme scenarios designed to test a combination of worst-case conditions of virus introduction and spread, but at the cost of doubling the number of herds culled. This likely resulted from a combination of the small outbreaks predicted by the spread model, and the high efficacy of the basic control measures evaluated, under the conditions of the Swedish livestock industry, and considering the assumed control resources available. The results indicate that the duration and extent of FMD outbreaks could be kept limited in Sweden using the EU standard control strategy and a 3 days national standstill. PMID:28791298

Molecular identification of the first local dengue fever outbreak in Shenzhen city, China: a potential imported vertical transmission from Southeast Asia?

PubMed

Yang, F; Guo, G Z; Chen, J Q; Ma, H W; Liu, T; Huang, D N; Yao, C H; Zhang, R L; Xue, C F; Zhang, L

2014-02-01

A suspected dengue fever outbreak occurred in 2010 at a solitary construction site in Shenzhen city, China. To investigate this epidemic, we used serological, molecular biological, and bioinformatics techniques. Of nine serum samples from suspected patients, we detected seven positive for dengue virus (DENV) antibodies, eight for DENV-1 RNA, and three containing live viruses. The isolated virus, SZ1029 strain, was sequenced and confirmed as DENV-1, showing the highest E-gene homology to D1/Malaysia/36000/05 and SG(EHI)DED142808 strains recently reported in Southeast Asia. Further phylogenetic tree analysis confirmed their close relationship. At the epidemic site, we also detected 14 asymptomatic co-workers (out of 291) positive for DENV antibody, and DENV-1-positive mosquitoes. Thus, we concluded that DENV-1 caused the first local dengue fever outbreak in Shenzhen. Because no imported case was identified, the molecular fingerprints of the SZ1029 strain suggest this outbreak may be due to vertical transmission imported from Southeast Asia.

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

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

PubMed

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

2002-08-01

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

Epidemiological and molecular analysis of a waterborne outbreak of norovirus GII.4.

PubMed

Zhou, X; Li, H; Sun, L; Mo, Y; Chen, S; Wu, X; Liang, J; Zheng, H; Ke, C; Varma, J K; Klena, J D; Chen, Q; Zou, L; Yang, X

2012-12-01

Contaminated water is one of the main sources of norovirus (NoV) gastroenteritis outbreaks globally. Waterborne NoV outbreaks are infrequently attributed to GII.4 NoV. In September 2009, a NoV outbreak affected a small school in Guangdong Province, China. Epidemiological investigations indicated that household use water, supplied by a well, was the probable source (relative risk 1·9). NoV nucleic acid material in concentrated well-water samples was detected using real-time RT-PCR. Nucleotide sequences of NoV extracted from diarrhoea and well-water specimens were identical and had the greatest sequence identity to corresponding sequences from the epidemic strain GII.4-2006b. Our report documents the first laboratory-confirmed waterborne outbreak caused by GII.4 NoV genotype in China. Our investigations indicate that well water, intended exclusively for household use but not for consumption, caused this outbreak. The results of this report serve as a reminder that private well water intended for household use should be tested for NoV.

Detection of Multiple Parallel Transmission Outbreak of Streptococcus suis Human Infection by Use of Genome Epidemiology, China, 2005

PubMed Central

Du, Pengcheng; Zheng, Han; Zhou, Jieping; Lan, Ruiting; Ye, Changyun; Jing, Huaiqi; Jin, Dong; Cui, Zhigang; Bai, Xuemei; Liang, Jianming; Liu, Jiantao; Xu, Lei; Zhang, Wen; Chen, Chen

2017-01-01

Streptococcus suis sequence type 7 emerged and caused 2 of the largest human infection outbreaks in China in 1998 and 2005. To determine the major risk factors and source of the infections, we analyzed whole genomes of 95 outbreak-associated isolates, identified 160 single nucleotide polymorphisms, and classified them into 6 clades. Molecular clock analysis revealed that clade 1 (responsible for the 1998 outbreak) emerged in October 1997. Clades 2–6 (responsible for the 2005 outbreak) emerged separately during February 2002–August 2004. A total of 41 lineages of S. suis emerged by the end of 2004 and rapidly expanded to 68 genome types through single base mutations when the outbreak occurred in June 2005. We identified 32 identical isolates and classified them into 8 groups, which were distributed in a large geographic area with no transmission link. These findings suggest that persons were infected in parallel in respective geographic sites. PMID:27997331

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

PubMed

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

2012-05-01

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

Serratia marcescens outbreak due to contaminated 2% aqueous chlorhexidine.

PubMed

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

2017-12-01

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

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

Epidemiological situation of measles in Romania, Italy, and Hungary: On what threats should we focus nowadays?

PubMed

Orosz, László; Gáspár, Gábor; Rózsa, Ágnes; Rákos, Nóra; Sziveri, Szilárd; Bosnyákovits, Tünde

2018-02-28

Although the prevalence of wild-type measles virus infection has decreased by >90% in Europe, the disease is still not eliminated and has even reemerged with recurrent outbreaks in different countries, including Romania and Italy. Minor outbreaks of Romanian origin were reported from Hungary as well. In Romania, an outbreak has been ongoing since February 2016. As of October 2017, 9,670 measles cases and 35 deaths were registered in the country. The three most affected counties are located next to the Hungarian border. In Italy, until the end of August 2017, 4,477 cases were reported to the surveillance system. The outbreak affected most of the Italian administrative regions. Until October 2017, three minor measles outbreaks were also detected in Hungary. All of these outbreaks were derived from Romanian cases. Although in these countries, there are vaccination programs running, the spread of the disease raises the possibility of secondary vaccine failure.

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.

Governance and One Health: Exploring the Impact of Federalism and Bureaucracy on Zoonotic Disease Detection and Reporting

PubMed Central

Allen, Heather A.

2015-01-01

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. PMID:29061932

Characteristics of a dengue outbreak in a remote pacific island chain--Republic of The Marshall Islands, 2011-2012.

PubMed

Sharp, Tyler M; Mackay, Andrew J; Santiago, Gilberto A; Hunsperger, Elizabeth; Nilles, Eric J; Perez-Padilla, Janice; Tikomaidraubuta, Kinisalote S; Colon, Candimar; Amador, Manuel; Chen, Tai-Ho; Lalita, Paul; Muñoz-Jordán, Jorge L; Barrera, Roberto; Langidrik, Justina; Tomashek, Kay M

2014-01-01

Dengue is a potentially fatal acute febrile illness caused by four mosquito-transmitted dengue viruses (DENV-1-4). Although dengue outbreaks regularly occur in many regions of the Pacific, little is known about dengue in the Republic of the Marshall Islands (RMI). To better understand dengue in RMI, we investigated an explosive outbreak that began in October 2011. Suspected cases were reported to the Ministry of Health, serum specimens were tested with a dengue rapid diagnostic test (RDT), and confirmatory testing was performed using RT-PCR and IgM ELISA. Laboratory-positive cases were defined by detection of DENV nonstructural protein 1 by RDT, DENV nucleic acid by RT-PCR, or anti-DENV IgM antibody by RDT or ELISA. Secondary infection was defined by detection of anti-DENV IgG antibody by ELISA in a laboratory-positive acute specimen. During the four months of the outbreak, 1,603 suspected dengue cases (3% of the RMI population) were reported. Of 867 (54%) laboratory-positive cases, 209 (24%) had dengue with warning signs, six (0.7%) had severe dengue, and none died. Dengue incidence was highest in residents of Majuro and individuals aged 10-29 years, and ∼95% of dengue cases were experiencing secondary infection. Only DENV-4 was detected by RT-PCR, which phylogenetic analysis demonstrated was most closely related to a virus previously identified in Southeast Asia. Cases of vertical DENV transmission, and DENV/Salmonella Typhi and DENV/Mycobacterium leprae co-infection were identified. Entomological surveys implicated water storage containers and discarded tires as the most important development sites for Aedes aegypti and Ae. albopictus, respectively. Although this is the first documented dengue outbreak in RMI, the age groups of cases and high prevalence of secondary infection demonstrate prior DENV circulation. Dengue surveillance should continue to be strengthened in RMI and throughout the Pacific to identify and rapidly respond to future outbreaks.

Characteristics of a Dengue Outbreak in a Remote Pacific Island Chain – Republic of the Marshall Islands, 2011–2012

PubMed Central

Sharp, Tyler M.; Mackay, Andrew J.; Santiago, Gilberto A.; Hunsperger, Elizabeth; Nilles, Eric J.; Perez-Padilla, Janice; Tikomaidraubuta, Kinisalote S.; Colon, Candimar; Amador, Manuel; Chen, Tai-Ho; Lalita, Paul; Muñoz-Jordán, Jorge L.; Barrera, Roberto; Langidrik, Justina; Tomashek, Kay M.

2014-01-01

Dengue is a potentially fatal acute febrile illness caused by four mosquito-transmitted dengue viruses (DENV-1–4). Although dengue outbreaks regularly occur in many regions of the Pacific, little is known about dengue in the Republic of the Marshall Islands (RMI). To better understand dengue in RMI, we investigated an explosive outbreak that began in October 2011. Suspected cases were reported to the Ministry of Health, serum specimens were tested with a dengue rapid diagnostic test (RDT), and confirmatory testing was performed using RT-PCR and IgM ELISA. Laboratory-positive cases were defined by detection of DENV nonstructural protein 1 by RDT, DENV nucleic acid by RT-PCR, or anti-DENV IgM antibody by RDT or ELISA. Secondary infection was defined by detection of anti-DENV IgG antibody by ELISA in a laboratory-positive acute specimen. During the four months of the outbreak, 1,603 suspected dengue cases (3% of the RMI population) were reported. Of 867 (54%) laboratory-positive cases, 209 (24%) had dengue with warning signs, six (0.7%) had severe dengue, and none died. Dengue incidence was highest in residents of Majuro and individuals aged 10–29 years, and ∼95% of dengue cases were experiencing secondary infection. Only DENV-4 was detected by RT-PCR, which phylogenetic analysis demonstrated was most closely related to a virus previously identified in Southeast Asia. Cases of vertical DENV transmission, and DENV/Salmonella Typhi and DENV/Mycobacterium leprae co-infection were identified. Entomological surveys implicated water storage containers and discarded tires as the most important development sites for Aedes aegypti and Ae. albopictus, respectively. Although this is the first documented dengue outbreak in RMI, the age groups of cases and high prevalence of secondary infection demonstrate prior DENV circulation. Dengue surveillance should continue to be strengthened in RMI and throughout the Pacific to identify and rapidly respond to future outbreaks. PMID:25268134

Using Combined Diagnostic Test Results to Hindcast Trends of Infection from Cross-Sectional Data

PubMed Central

Rydevik, Gustaf; Innocent, Giles T.; Marion, Glenn; White, Piran C. L.; Billinis, Charalambos; Barrow, Paul; Mertens, Peter P. C.; Gavier-Widén, Dolores; Hutchings, Michael R.

2016-01-01

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time. PMID:27384712

Nosocomial outbreak of extensively drug-resistant Pseudomonas aeruginosa associated with aromatherapy.

PubMed

Mayr, Astrid; Hinterberger, Guido; Lorenz, Ingo H; Kreidl, Peter; Mutschlechner, Wolfgang; Lass-Flörl, Cornelia

2017-04-01

An increase of extensively drug-resistant Pseudomonas aeruginosa (XDR-PA) in various clinical specimens among intensive care unit patients (n = 7) initiated an outbreak investigation consisting of patient data analyses, control of adherence to infection control guidelines, microbiologic surveys, and molecular-based studies. XDR-PA was detected in a jointly used aroma-oil nursing bottle for aromatherapy. We implemented the restriction of oil sharing among patients. Hence, the outbreak was controlled successfully. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2016-06-01

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

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

PubMed

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

2015-06-01

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

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

PubMed Central

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

2015-01-01

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

Usefulness of molecular markers in the diagnosis of occupational and recreational histoplasmosis outbreaks.

PubMed

Frías-De-León, María Guadalupe; Ramírez-Bárcenas, José Antonio; Rodríguez-Arellanes, Gabriela; Velasco-Castrejón, Oscar; Taylor, Maria Lucia; Reyes-Montes, María Del Rocío

2017-03-01

Histoplasmosis is considered the most important systemic mycosis in Mexico, and its diagnosis requires fast and reliable methodologies. The present study evaluated the usefulness of PCR using Hcp100 and 1281-1283 (220) molecular markers in detecting Histoplasma capsulatum in occupational and recreational outbreaks. Seven clinical serum samples of infected individuals from three different histoplasmosis outbreaks were processed by enzyme-linked immunosorbent assay (ELISA) to titre anti-H. capsulatum antibodies and to extract DNA. Fourteen environmental samples were also processed for H. capsulatum isolation and DNA extraction. Both clinical and environmental DNA samples were analysed by PCR with Hcp100 and 1281-1283 (220) markers. Antibodies to H. capsulatum were detected by ELISA in all serum samples using specific antigens, and in six of these samples, the PCR products of both molecular markers were amplified. Four environmental samples amplified one of the two markers, but only one sample amplified both markers and an isolate of H. capsulatum was cultured from this sample. All PCR products were sequenced, and the sequences for each marker were analysed using the Basic Local Alignment Search Tool (BLASTn), which revealed 95-98 and 98-100 % similarities with the reference sequences deposited in the GenBank for Hcp100 and 1281-1283 (220) , respectively. Both molecular markers proved to be useful in studying histoplasmosis outbreaks because they are matched for pathogen detection in either clinical or environmental samples.

Transmission and molecular characterisation of wild measles virus in Romania, 2008 to 2012.

PubMed

Necula, G; Lazar, M; Stanescu, A; Pistol, A; Santibanez, S; Mankertz, A; Lupulescu, E

2013-12-12

Molecular characterisation of measles virus is a powerful tool for tracing transmission. Genotyping may prove the absence of endemic circulation of measles virus, i.e. transmission for more than 12 months, which is one of the criteria for verifying elimination of the disease. We have genetically characterised measles viruses detected in Romania from 2008 to 2012, focusing on the recent outbreaks from 2010 to 2012 that affected mainly groups with limited access to healthcare and schools. The findings emphasise the importance of genotyping during the different phases of an outbreak. A total of 8,170 cases were notified, and 5,093 (62%) of the 7,559 possible cases were serologically confirmed. RT-PCR was performed for 104 samples: from the 101 positive samples obtained from sporadic measles cases or clusters from different counties, 73 were genotyped. Sporadic measles cases associated with D4 and D5 viruses were observed from2008 to 2009. Genotype D4-Manchester was predominant in 2011 and 2012. In addition, the related variant D4-Maramures and MVs/Limoges.FRA/17.10[D4] and a few D4-Hamburg strains were detected. The detection of several distinct MV-D4 genotypes suggests multiple virus importations to Romania. The outbreak associated with D4 genotype is the second largest outbreak in Romania in less than 10 years.

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.

European Surveillance for West Nile Virus in Mosquito Populations

PubMed Central

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

2013-01-01

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

Tactics and strategies for managing Ebola outbreaks and the salience of immunization.

PubMed

Getz, Wayne M; Gonzalez, Jean-Paul; Salter, Richard; Bangura, James; Carlson, Colin; Coomber, Moinya; Dougherty, Eric; Kargbo, David; Wolfe, Nathan D; Wauquier, Nadia

2015-01-01

We present a stochastic transmission chain simulation model for Ebola viral disease (EVD) in West Africa, with the salutary result that the virus may be more controllable than previously suspected. The ongoing tactics to detect cases as rapidly as possible and isolate individuals as safely as practicable is essential to saving lives in the current outbreaks in Guinea, Liberia, and Sierra Leone. Equally important are educational campaigns that reduce contact rates between susceptible and infectious individuals in the community once an outbreak occurs. However, due to the relatively low R 0 of Ebola (around 1.5 to 2.5 next generation cases are produced per current generation case in naïve populations), rapid isolation of infectious individuals proves to be highly efficacious in containing outbreaks in new areas, while vaccination programs, even with low efficacy vaccines, can be decisive in curbing future outbreaks in areas where the Ebola virus is maintained in reservoir populations.

Seven Salmonella Typhimurium Outbreaks in Australia Linked by Trace-Back and Whole Genome Sequencing.

PubMed

Ford, Laura; Wang, Qinning; Stafford, Russell; Ressler, Kelly-Anne; Norton, Sophie; Shadbolt, Craig; Hope, Kirsty; Franklin, Neil; Krsteski, Radomir; Carswell, Adrienne; Carter, Glen P; Seemann, Torsten; Howard, Peter; Valcanis, Mary; Castillo, Cristina Fabiola Sotomayor; Bates, John; Glass, Kathryn; Williamson, Deborah A; Sintchenko, Vitali; Howden, Benjamin P; Kirk, Martyn D

2018-05-01

Salmonella Typhimurium is a common cause of foodborne illness in Australia. We report on seven outbreaks of Salmonella Typhimurium multilocus variable-number tandem-repeat analysis (MLVA) 03-26-13-08-523 (European convention 2-24-12-7-0212) in three Australian states and territories investigated between November 2015 and March 2016. We identified a common egg grading facility in five of the outbreaks. While no Salmonella Typhimurium was detected at the grading facility and eggs could not be traced back to a particular farm, whole genome sequencing (WGS) of isolates from cases from all seven outbreaks indicated a common source. WGS was able to provide higher discriminatory power than MLVA and will likely link more Salmonella Typhimurium cases between states and territories in the future. National harmonization of Salmonella surveillance is important for effective implementation of WGS for Salmonella outbreak investigations.

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

PubMed

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

2016-09-29

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

Anthrax Outbreaks in Bangladesh, 2009–2010

PubMed Central

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

2012-01-01

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

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...

Role of poultry in the H7N9 influenza outbreaks in China

USDA-ARS?s Scientific Manuscript database

The outbreaks of avian influenza A (H7N9) occurring in China in 2013 and 2014 have resulted in more than 370 human cases with a 30% fatality rate. Most of these infections are believed to result from exposure to infected poultry or contaminated environments as the viruses have been detected in avia...

West Nile Virus Outbreak in Houston and Harris County, Texas, USA, 2014.

PubMed

Martinez, Diana; Murray, Kristy O; Reyna, Martin; Arafat, Raouf R; Gorena, Roberto; Shah, Umair A; Debboun, Mustapha

2017-08-01

Since 2002, West Nile virus (WNV) has been detected every year in Houston and the surrounding Harris County, Texas. In 2014, the largest WNV outbreak to date occurred, comprising 139 cases and causing 2 deaths. Additionally, 1,286 WNV-positive mosquito pools were confirmed, the most reported in a single mosquito season.

An outbreak of hepatitis A in Roma populations living in three prefectures in Greece.

PubMed

Vantarakis, A; Nearxou, A; Pagonidis, D; Melegos, F; Seretidis, J; Kokkinos, P; Zarkadis, I; Parasidis, T; Alamanos, Y

2010-07-01

An outbreak of hepatitis A virus (HAV) infection affected Roma populations living in three prefectures of northeastern Greece. Between July and November 2007, 124 cases were reported. We carried out investigations to characterize the pathogen, to identify the source of infection and the route of transmission. Using the RT-PCR technique, HAV strains of the same genotype were detected in all sera from a subset of patients with acute disease. These showed more than 99.8% identity, suggesting a common source. A questionnaire was also completed to collect clinical and epidemiological information. The outbreak affected mainly Roma children aged <10 years. An inspection of Roma settlements showed that poor sanitary conditions were associated with the HAV outbreak.

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

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

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

PubMed

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

2017-07-10

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

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

Preventing Community-wide Transmission of Cryptosporidium: A Proactive Public Health Response to a Swimming Pool–Associated Outbreak — Auglaize County, Ohio, USA

PubMed Central

Cope, J.R.; Prosser, A.; Nowicki, S.; Roberts, M.W.; Scheer, D.; Anderson, C.; Longsworth, A.; Parsons, C.; Goldschmidt, D.; Johnston, S.; Bishop, H.; Xiao, L.; Hill, V.; Beach, M.; Hlavsa, M.C.

2015-01-01

Summary The incidence of recreational water–associated outbreaks in the United States has significantly increased, driven, at least in part, by outbreaks both caused by Cryptosporidium and associated with treated recreational water venues. Because of the parasite's extreme chlorine tolerance, transmission can occur even in well-maintained treated recreational water venues, (e.g., pools) and a focal cryptosporidiosis outbreak can evolve into a community-wide outbreak associated with multiple recreational water venues and settings (e.g., child care facilities). In August 2004 in Auglaize County, Ohio, multiple cryptosporidiosis cases were identified and anecdotally linked to Pool A. Within 5 days of the first case being reported, Pool A was hyperchlorinated to achieve 99.9% Cryptosporidium inactivition. A case-control study was launched to epidemiologically ascertain the outbreak source 11 days later. A total of 150 confirmed and probable cases were identified; the temporal distribution of illness onset was peaked, indicating a point-source exposure. Cryptosporidiosis was significantly associated with swimming in Pool A (matched odds ratio 121.7, 95% confidence interval 27.4–∞) but not with another venue or setting. The findings of this investigation suggest that proactive implementation of control measures, when increased Cryptosporidium transmission is detected but before an outbreak source is epidemiologically ascertained, might prevent a focal cryptosporidiosis outbreak from evolving into a community-wide outbreak. PMID:25907106

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

PubMed

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

2010-08-01

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

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

PubMed

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

2016-06-01

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

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

PubMed

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

2009-01-01

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

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.

Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014.

PubMed

Phillips, Anastasia; Sotomayor, Cristina; Wang, Qinning; Holmes, Nadine; Furlong, Catriona; Ward, Kate; Howard, Peter; Octavia, Sophie; Lan, Ruiting; Sintchenko, Vitali

2016-09-15

Salmonella Typhimurium (STM) is an important cause of foodborne outbreaks worldwide. Subtyping of STM remains critical to outbreak investigation, yet current techniques (e.g. multilocus variable number tandem repeat analysis, MLVA) may provide insufficient discrimination. Whole genome sequencing (WGS) offers potentially greater discriminatory power to support infectious disease surveillance. We performed WGS on 62 STM isolates of a single, endemic MLVA type associated with two epidemiologically independent, food-borne outbreaks along with sporadic cases in New South Wales, Australia, during 2014. Genomes of case and environmental isolates were sequenced using HiSeq (Illumina) and the genetic distance between them was assessed by single nucleotide polymorphism (SNP) analysis. SNP analysis was compared to the epidemiological context. The WGS analysis supported epidemiological evidence and genomes of within-outbreak isolates were nearly identical. Sporadic cases differed from outbreak cases by a small number of SNPs, although their close relationship to outbreak cases may represent an unidentified common food source that may warrant further public health follow up. Previously unrecognised mini-clusters were detected. WGS of STM can discriminate foodborne community outbreaks within a single endemic MLVA clone. Our findings support the translation of WGS into public health laboratory surveillance of salmonellosis.

Emergence of norovirus GI.2 outbreaks in military camps in Singapore.

PubMed

Ho, Zheng Jie Marc; Vithia, Gunalan; Ng, Ching Ging; Maurer-Stroh, Sebastian; Tan, Clive M; Loh, Jimmy; Lin, Tzer Pin Raymond; Lee, Jian Ming Vernon

2015-02-01

Simultaneous acute gastroenteritis (AGE) outbreaks occurred at two military camps. This study details the epidemiological findings, explores possible origins, and discusses preventive measures. Investigations included attack rate surveys, symptom surveys, hygiene inspections, and the testing of water, food, and stool samples. DNA/RNA was extracted from stool samples and amplified via real-time reverse transcription PCR (RT-PCR). Partial and full-length capsid nucleotide sequences were obtained, phylogenetic relationships inferred, and homology modelling of antigenic sites performed. The military outbreaks involved 775 persons and were preceded by two AGE outbreaks at restaurants in the local community. The outbreak was longer and larger in the bigger camp (21 days, attack rate 15.0%) than the smaller camp (6 days, attack rate 8.3%). Of 198 stool samples, norovirus GI.2 was detected in 32.5% (larger camp) and 28.6% (smaller camp). These were essentially identical to preceding community outbreaks. Antigenic site homology modelling also showed differences between identified and more common AGE outbreak strains (norovirus GII.4). Differences observed highlight difficulties in controlling person-to-person outbreaks among large groups in close proximity (e.g., military trainees). Distinct differences in antigenic sites may have contributed to increased immunological susceptibility of the soldiers to infection. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

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 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.

Molecular detection and point-of-care testing in Ebola virus disease and other threats: a new global public health framework to stop outbreaks.

PubMed

Kost, Gerald J; Ferguson, William; Truong, Anh-Thu; Hoe, Jackie; Prom, Daisy; Banpavichit, Arirat; Kongpila, Surin

2015-01-01

Ultrahigh sensitivity and specificity assays that detect Ebola virus disease or other highly contagious and deadly diseases quickly and successfully upstream in Spatial Care Paths™ can stop outbreaks from escalating into devastating epidemics ravaging communities locally and countries globally. Even had the WHO and CDC responded more quickly and not misjudged the dissemination of Ebola in West Africa and other world regions, mobile rapid diagnostics were, and still are, not readily available for immediate and definitive diagnosis, a stunning strategic flaw that needs correcting worldwide. This article strategizes point-of-care testing for diagnosis, triage, monitoring, recovery and stopping outbreaks in the USA and other countries; reviews Ebola molecular diagnostics, summarizes USA FDA emergency use authorizations and documents why they should not be stop-gaps; and reduces community risk from internal and external infectious disease threats by enabling public health at points of need.

Western blot (immunoblot) assay of small, round-structured virus associated with an acute gastroenteritis outbreak in Tokyo.

PubMed

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

1989-08-01

Small, round-structured virus (SRSV) was detected in a stool specimen of a patient during an acute gastroenteritis outbreak in Tokyo and was tentatively named SRSV-9. SRSV-9 was purified by sucrose velocity gradient centrifugation after CsCl density gradient centrifugation. The buoyant density of SRSV-9 appeared to be 1.36 g/ml in CsCl. A Western blot (immunoblot) assay using the biotin-avidin system revealed that SRSV-9 was antigenically related to the Hawaii agent but distinct from the Norwalk agent and contained a single major structural protein with a molecular size of 63.0 +/- 0.6 kilodaltons. The prevalence of SRSV-9 infection in Tokyo was surveyed by the Western blot antibody assay by using a crude virus preparation as the antigen. Seroconversion was observed in 56.5% of the patients involved in the outbreaks from which SRSV was detected by electron microscopy.

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.

Update on oral Chagas disease outbreaks in Venezuela: epidemiological, clinical and diagnostic approaches

PubMed Central

de Noya, Belkisyolé Alarcón; Díaz-Bello, Zoraida; Colmenares, Cecilia; Ruiz-Guevara, Raiza; Mauriello, Luciano; Muñoz-Calderón, Arturo; Noya, Oscar

2015-01-01

Orally transmitted Chagas disease has become a matter of concern due to outbreaks reported in four Latin American countries. Although several mechanisms for orally transmitted Chagas disease transmission have been proposed, food and beverages contaminated with whole infected triatomines or their faeces, which contain metacyclic trypomastigotes of Trypanosoma cruzi, seems to be the primary vehicle. In 2007, the first recognised outbreak of orally transmitted Chagas disease occurred in Venezuela and largest recorded outbreak at that time. Since then, 10 outbreaks (four in Caracas) with 249 cases (73.5% children) and 4% mortality have occurred. The absence of contact with the vector and of traditional cutaneous and Romana’s signs, together with a florid spectrum of clinical manifestations during the acute phase, confuse the diagnosis of orally transmitted Chagas disease with other infectious diseases. The simultaneous detection of IgG and IgM by ELISA and the search for parasites in all individuals at risk have been valuable diagnostic tools for detecting acute cases. Follow-up studies regarding the microepidemics primarily affecting children has resulted in 70% infection persistence six years after anti-parasitic treatment. Panstrongylus geniculatus has been the incriminating vector in most cases. As a food-borne disease, this entity requires epidemiological, clinical, diagnostic and therapeutic approaches that differ from those approaches used for traditional direct or cutaneous vector transmission. PMID:25946155

Classification of Shiga toxin-producing escherichia coli (STEC) serotypes with hyperspectral microscope imagery

NASA Astrophysics Data System (ADS)

Park, Bosoon; Windham, William R.; Ladely, Scott R.; Gurram, Prudhvi; Kwon, Heesung; Yoon, Seung-Chul; Lawrence, Kurt C.; Narang, Neelam; Cray, William C.

2012-05-01

Non-O157:H7 Shiga toxin-producing Escherichia coli (STEC) strains such as O26, O45, O103, O111, O121 and O145 are recognized as serious outbreak to cause human illness due to their toxicity. A conventional microbiological method for cell counting is laborious and needs long time for the results. Since optical detection method is promising for realtime, in-situ foodborne pathogen detection, acousto-optical tunable filters (AOTF)-based hyperspectral microscopic imaging (HMI) method has been developed for identifying pathogenic bacteria because of its capability to differentiate both spatial and spectral characteristics of each bacterial cell from microcolony samples. Using the AOTF-based HMI method, 89 contiguous spectral images could be acquired within approximately 30 seconds with 250 ms exposure time. From this study, we have successfully developed the protocol for live-cell immobilization on glass slides to acquire quality spectral images from STEC bacterial cells using the modified dry method. Among the contiguous spectral imagery between 450 and 800 nm, the intensity of spectral images at 458, 498, 522, 546, 570, 586, 670 and 690 nm were distinctive for STEC bacteria. With two different classification algorithms, Support Vector Machine (SVM) and Sparse Kernel-based Ensemble Learning (SKEL), a STEC serotype O45 could be classified with 92% detection accuracy.

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

Best practices to prevent transmission and control outbreaks of hand, foot, and mouth disease in childcare facilities: a systematic review.

PubMed

Chan, J Hy; Law, C K; Hamblion, E; Fung, H; Rudge, J

2017-04-01

Hand, foot, and mouth disease continues to cause seasonal epidemics in the Asia-Pacific Region. Since the current Enterovirus 71 vaccines do not provide cross-protection for all Enterovirus species that cause hand, foot, and mouth disease, there is an urgent need to identify appropriate detection tools and best practice to prevent its transmission and to effectively control its outbreaks. This systematic review aimed to identify characteristics of outbreak and assess the impact and effectiveness of detection tools and public health preventive measures to interrupt transmission. The findings will be used to recommend policy on the most effective responses and interventions in Hong Kong to effectively minimise and contain the spread of the disease within childcare facilities. We searched the following databases for primary studies written in Chinese or English: MEDLINE, EMBASE, Global Health, WHO Western Pacific Region Index Medicus database, China National Knowledge Infrastructure Databases, and Chinese Scientific Journals Database. Studies conducted during or retrospective to outbreaks of hand, foot, and mouth disease caused by Enterovirus 71 from 1980 to 2012 within childcare facilities and with a study population of 0 to 6 years old were included. Sixteen studies conducted on outbreaks in China showed that hand, foot, and mouth disease spread rapidly within the facility, with an outbreak length of 4 to 46 days, especially in those with delayed notification (after 24 hours) of clustered outbreak (with five or more cases discovered within the facility) to the local Center for Disease Control and Prevention and delayed implementation of a control response. The number of classes affected ranged from 1 to 13, and the attack rate for children ranged from 0.97% to 28.18%. Communication between key stakeholders about outbreak confirmation, risk assessment, and surveillance should be improved. Effective communication facilitates timely notification (within 24 hours) of clustered outbreaks to a local Center for Disease Control and Prevention. Timely implementation of a control response is effective in minimising incidence and length of an outbreak in childcare facilities. The government should provide incentives for childcare facilities to train infection control specialists who can serve as the first contact, knowledge, and communication points, as well as facilitate exchange of information and provision of support across stakeholders during a communicable disease epidemic.

Comparison of human and algorithmic target detection in passive infrared imagery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.; Hutchinson, Meredith

2003-09-01

We have designed an experiment that compares the performance of human observers and a scale-insensitive target detection algorithm that uses pixel level information for the detection of ground targets in passive infrared imagery. The test database contains targets near clutter whose detectability ranged from easy to very difficult. Results indicate that human observers detect more "easy-to-detect" targets, and with far fewer false alarms, than the algorithm. For "difficult-to-detect" targets, human and algorithm detection rates are considerably degraded, and algorithm false alarms excessive. Analysis of detections as a function of observer confidence shows that algorithm confidence attribution does not correspond to human attribution, and does not adequately correlate with correct detections. The best target detection score for any human observer was 84%, as compared to 55% for the algorithm for the same false alarm rate. At 81%, the maximum detection score for the algorithm, the same human observer had 6 false alarms per frame as compared to 29 for the algorithm. Detector ROC curves and observer-confidence analysis benchmarks the algorithm and provides insights into algorithm deficiencies and possible paths to improvement.

High-resolution melting (HRM) for genotyping bovine ephemeral fever virus (BEFV).

PubMed

Erster, Oran; Stram, Rotem; Menasherow, Shopia; Rubistein-Giuni, Marisol; Sharir, Binyamin; Kchinich, Evgeni; Stram, Yehuda

2017-02-02

In recent years there have been several major outbreaks of bovine ephemeral disease in the Middle East, including Israel. Such occurrences raise the need for quick identification of the viruses responsible for the outbreaks, in order to rapidly identify the entry of viruses that do not belong to the Middle-East BEFV lineage. This challenge was met by the development of a high-resolution melt (HRM) assay. The assay is based on the viral G gene sequence and generation of an algorithm that calculates and evaluates the GC content of various fragments. The algorithm was designed to scan 50- to 200-base-long segments in a sliding-window manner, compare and rank them using an Order of Technique of Preference by Similarity to Ideal Solution (TOPSIS) the technique for order preference by similarity to ideal solution technique, according to the differences in GC content of homologous fragments. Two fragments were selected, based on a match to the analysis criteria, in terms of size and GC content. These fragments were successfully used in the analysis to differentiate between different virus lineages, thus facilitating assignment of the viruses' geographical origins. Moreover, the assay could be used for differentiating infected from vaccinated animales (DIVA). The new algorithm may therefore be useful for development of improved genotyping studies for other viruses and possibly other microorganisms. Copyright © 2016. Published by Elsevier B.V.

Dynamics and ecological consequences of the 2013−2014 koa moth outbreak at Hakalau Forest National Wildlife Refuge.

USGS Publications Warehouse

Banko, Paul C.; Peck, Robert W.; Yelenik, Stephanie G.; Paxton, Eben H.; Bonaccorso, Frank J.; Montoya-Aiona, Kristina; Foote, David

2014-01-01

A massive outbreak of the koa moth (Geometridea: Scotorythra paludicola) defoliated more than a third of the koa (Acacia koa) forest on Hawai‘i Island during 2013−2014. This was the largest koa moth outbreak ever recorded and the first on the island since 1953. The outbreak spread to sites distributed widely around the island between 800−2,000 m elevation and in wet rainforest to dry woodland habitats. We monitored the outbreak at two windward forest sites (Laupāhoehoe and Saddle Road Kīpuka) and one leeward forest site (Kona), and we studied the dynamics of the outbreak and its impacts on the forest ecosystem at Hakalau Forest National Wildlife Refuge, our higher elevation windward site. Study sites at Hakalau included two stands of koa that were planted (reforestation stands) in former cattle pastureland about 20 years earlier and two stands of koa that were dominated by ‘ōhi‘a (Metrosideros polymorpha) and that were naturally recovering from cattle grazing (forest stands). We observed one outbreak at Hakalau, multiple outbreaks at the two other windward sites, but no outbreak at the leeward site. Caterpillars at Hakalau reached peak estimated abundances of more than 250,000 per tree and 18,000,000 per hectare, and they removed between 64−93% of the koa canopy in managed forest stands. Defoliation was more extensive in naturally recovering forest, where ‘ōhi‘a dominated and koa was less abundant, compared to the planted stands, where koa density was high. Koa trees were still growing new foliage six months after being defoliated, and leaves were produced in greater proportion to phyllodes, especially by small koa (≤ 8 cm dbh) and by larger trees in forest stands, where light levels may have remained relatively low after defoliation due to the high cover of ‘ōhi‘a. Small branches of many trees apparently died, and canopy regrowth was absent or low in 9% of koa trees and seedlings, which indicates the likely level of mortality. Between 2,000−5,000 kg/ha of frass fell during the defoliation event, resulting in the deposition of up to 200 kg/ha of highly labile nitrogen on the forest floor in less than two months. The deposition of nitrogen was detected as pulses in resin-available nitrogen in the top 5−10 cm of soil at two of three sites. These sites showed elevated soil nitrogen for about seven months. Nitrogen content of understory plant foliage, which is indicative of nitrogen uptake, suggested weak and variable effects of nitrogen deposition in the soil. Foliar nitrogen increased slightly in alien pasture grasses four months after the deposition of frass, although distinctive increases were not detected in native woody species. Birds responded to the abundance of caterpillars by increasing their activity in koa during the buildup of caterpillars and decreasing their use of koa after defoliation. During the outbreak, caterpillars increased in the diets of the two generalist insectivores we examined, and nearly all species gained weight. Bats responded to the abundance of moths by compression of active foraging into the first three hours of darkness each night after presumably having reached a digestive bottleneck. Reduced foraging activity by bats also resulted in lower indices of detectability based upon acoustic monitoring when compared to non-outbreak years. Parasitoid wasps tracked caterpillar abundance, but the low rate at which they attacked caterpillars suggests that they had little influence on the population. The predatory yellowjacket (Vespula pensylvanica) did not respond to the outbreak. Although a single, protracted outbreak occurred at Hakalau, multiple outbreaks and defoliations occurred at lower elevations. Our results provide a broad foundation for evaluating the dynamics and impacts of future Scotorythra outbreaks.

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

PubMed

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

2012-12-01

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

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

Detection of notifiable diseases through surveillance for imported plague--New York, September-October 1994.

PubMed

1994-11-11

Recent reports of bubonic and pneumonic plague outbreaks in India (1,2) prompted the New York City Department of Health (NYCDOH) and the New York State Department of Health (NYSDOH), in conjunction with CDC, to develop an emergency response plan to detect and manage suspected cases imported by international air travel. This report describes the surveillance system implemented by CDC on September 27 and supplemental efforts by NYC/NYSDOH to guide and inform physicians about the outbreak, and summarizes clinical findings for 11 travelers who had symptoms suggestive of plague.

Pseudo-outbreak of Penicillium in an outpatient obstetrics and gynecology clinic.

PubMed

Sood, Geetika; Huber, Kerri; Dam, Lisa; Riedel, Stefan; Grubb, Lisa; Zenilman, Jonathan; Perl, Trish M; Argani, Cynthia

2017-05-01

We report an unusual pseudo-outbreak of Penicillium that occurred in patients seen in an outpatient obstetrics and gynecology clinic. The pseudo-outbreak was detected in late 2012, when the microbiology department reported a series of vaginal cultures positive for Penicillium spp. Our investigation found Penicillium spp in both patient and environmental samples and was potentially associated with the practice of wetting gloves with tap water by a health care worker prior to patient examination. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Optimizing surveillance for livestock disease spreading through animal movements

PubMed Central

Bajardi, Paolo; Barrat, Alain; Savini, Lara; Colizza, Vittoria

2012-01-01

The spatial propagation of many livestock infectious diseases critically depends on the animal movements among premises; so the knowledge of movement data may help us to detect, manage and control an outbreak. The identification of robust spreading features of the system is however hampered by the temporal dimension characterizing population interactions through movements. Traditional centrality measures do not provide relevant information as results strongly fluctuate in time and outbreak properties heavily depend on geotemporal initial conditions. By focusing on the case study of cattle displacements in Italy, we aim at characterizing livestock epidemics in terms of robust features useful for planning and control, to deal with temporal fluctuations, sensitivity to initial conditions and missing information during an outbreak. Through spatial disease simulations, we detect spreading paths that are stable across different initial conditions, allowing the clustering of the seeds and reducing the epidemic variability. Paths also allow us to identify premises, called sentinels, having a large probability of being infected and providing critical information on the outbreak origin, as encoded in the clusters. This novel procedure provides a general framework that can be applied to specific diseases, for aiding risk assessment analysis and informing the design of optimal surveillance systems. PMID:22728387

Surveillance for Waterborne Disease Outbreaks Associated with Drinking Water - United States, 2013-2014.

PubMed

Benedict, Katharine M; Reses, Hannah; Vigar, Marissa; Roth, David M; Roberts, Virginia A; Mattioli, Mia; Cooley, Laura A; Hilborn, Elizabeth D; Wade, Timothy J; Fullerton, Kathleen E; Yoder, Jonathan S; Hill, Vincent R

2017-11-10

Provision of safe water in the United States is vital to protecting public health (1). Public health agencies in the U.S. states and territories* report information on waterborne disease outbreaks to CDC through the National Outbreak Reporting System (NORS) (https://www.cdc.gov/healthywater/surveillance/index.html). During 2013-2014, 42 drinking water-associated † outbreaks were reported, accounting for at least 1,006 cases of illness, 124 hospitalizations, and 13 deaths. Legionella was associated with 57% of these outbreaks and all of the deaths. Sixty-nine percent of the reported illnesses occurred in four outbreaks in which the etiology was determined to be either a chemical or toxin or the parasite Cryptosporidium. Drinking water contamination events can cause disruptions in water service, large impacts on public health, and persistent community concern about drinking water quality. Effective water treatment and regulations can protect public drinking water supplies in the United States, and rapid detection, identification of the cause, and response to illness reports can reduce the transmission of infectious pathogens and harmful chemicals and toxins.

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.

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...

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

Surface Sampling and Detection Investigations at the CDC

NASA Astrophysics Data System (ADS)

Rose, L. J.; Coulliette, A. D.

2015-03-01

The Environmental and Applied Microbiology Team is tasked with investigating disease outbreaks in healthcare settings. We will summarize and discuss applied research endeavors to understand and optimize sampling and detection of microorganisms.

Waveband selection and algorithm development to distinguish fecal contamination using multispectral imaging with solar light

USDA-ARS?s Scientific Manuscript database

Fecal contamination in fresh produce fields caused by animals or livestock entering the fields can lead to outbreaks of foodbourne illnesses. E.coli O157:H7 originating in the intestines of animals can transfer onto leafy greens via fecal matter. Leafy greens are often eaten fresh without thermal tr...

Climatology and Impact of Polar Lows in the North Atlantic: Present and Future

NASA Astrophysics Data System (ADS)

Michel, Clio; Haukeland, Magnus; Spengler, Thomas

2016-04-01

Polar lows are maritime cyclones occurring during cold air outbreaks in high latitudes. We use the Melbourne University algorithm to detect and track polar lows in the North Atlantic. The algorithm is applied to ERA-Interim reanalyses as well as high resolution (25 and 50 km) global climate model data from GFDL for present and future climates. Cyclone track densities for the GFDL present climate and the ERA-Interim reanalyses compare well for the occurrence of present day polar lows. We also present cyclone track densities for future climates under RCP4.5 and RCP8.5 for the early and late 21st century. Polar lows mainly form close to Svalbard but also along the coast of Greenland, in the Norwegian Sea and Barents Sea. We present the shifts in location and intensity of polar lows for future climates and discuss potential reasons for these changes. During their lifetime, they travel several 100 kilometres and can reach the Norwegian coast as well as off-shore infrastructures. Therefore we also assess the difference between current and future occurrence of polar lows reaching the coast of Norway as well as areas with oil platforms and active fisheries. This analysis pinpoints the exposure to current and future impacts of polar lows on these socio-economic assets.

Legionnaires' Disease Outbreak Caused by Endemic Strain of Legionella pneumophila, New York, New York, USA, 2015.

PubMed

Lapierre, Pascal; Nazarian, Elizabeth; Zhu, Yan; Wroblewski, Danielle; Saylors, Amy; Passaretti, Teresa; Hughes, Scott; Tran, Anthony; Lin, Ying; Kornblum, John; Morrison, Shatavia S; Mercante, Jeffrey W; Fitzhenry, Robert; Weiss, Don; Raphael, Brian H; Varma, Jay K; Zucker, Howard A; Rakeman, Jennifer L; Musser, Kimberlee A

2017-11-01

During the summer of 2015, New York, New York, USA, had one of the largest and deadliest outbreaks of Legionnaires' disease in the history of the United States. A total of 138 cases and 16 deaths were linked to a single cooling tower in the South Bronx. Analysis of environmental samples and clinical isolates showed that sporadic cases of legionellosis before, during, and after the outbreak could be traced to a slowly evolving, single-ancestor strain. Detection of an ostensibly virulent Legionella strain endemic to the Bronx community suggests potential risk for future cases of legionellosis in the area. The genetic homogeneity of the Legionella population in this area might complicate investigations and interpretations of future outbreaks of Legionnaires' disease.

Legionnaires’ Disease Outbreak Caused by Endemic Strain of Legionella pneumophila, New York, New York, USA, 2015

PubMed Central

Nazarian, Elizabeth; Zhu, Yan; Wroblewski, Danielle; Saylors, Amy; Passaretti, Teresa; Hughes, Scott; Tran, Anthony; Lin, Ying; Kornblum, John; Morrison, Shatavia S.; Mercante, Jeffrey W.; Fitzhenry, Robert; Weiss, Don; Raphael, Brian H.; Varma, Jay K.; Zucker, Howard A.; Rakeman, Jennifer L.; Musser, Kimberlee A.

2017-01-01

During the summer of 2015, New York, New York, USA, had one of the largest and deadliest outbreaks of Legionnaires’ disease in the history of the United States. A total of 138 cases and 16 deaths were linked to a single cooling tower in the South Bronx. Analysis of environmental samples and clinical isolates showed that sporadic cases of legionellosis before, during, and after the outbreak could be traced to a slowly evolving, single-ancestor strain. Detection of an ostensibly virulent Legionella strain endemic to the Bronx community suggests potential risk for future cases of legionellosis in the area. The genetic homogeneity of the Legionella population in this area might complicate investigations and interpretations of future outbreaks of Legionnaires’ disease. PMID:29047425

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.

Polio-Like Illness Associated With Outbreak of Upper Respiratory Tract Infection in Children.

PubMed

Crone, Megan; Tellier, Raymond; Wei, Xing-Chang; Kuhn, Susan; Vanderkooi, Otto G; Kim, Jong; Mah, Jean K; Mineyko, Aleksandra

2016-03-01

Poliomyelitis is a historically devastating neurological complication of poliovirus infection. Poliovirus vaccines have decreased the incidence of poliomyelitis to 209 global cases in 2014, with new cases of acute flaccid myelitis primarily associated with nonpolio enteroviruses. Recently, during outbreaks of enterovirus D68 throughout North America and Europe, cases of acute flaccid myelitis have been reported, suggesting another nonpolio enterovirus associated with acute flaccid myelitis. The authors describe 3 patients diagnosed with acute flaccid myelitis during a province-wide outbreak of enterovirus D68 with the virus detected in 2 of the patients. Given the significant morbidity associated with acute flaccid myelitis and potential for nonpolio enterovirus to cause outbreaks, prompt identification and notification of public health authorities are warranted. © The Author(s) 2015.

An outbreak of food-borne gastroenteritis due to sapovirus among junior high school students.

PubMed

Usuku, Shuzo; Kumazaki, Makoto; Kitamura, Katsuhiko; Tochikubo, Osamu; Noguchi, Yuzo

2008-11-01

The human sapovirus (SaV) causes acute gastroenteritis mainly in infants and young children. A food-borne outbreak of gastroenteritis associated with SaV occurred among junior high school students in Yokohama, Japan, during and after a study trip. The nucleotide sequences of the partial capsid gene derived from the students exhibited 98% homology to a SaV genogroup IV strain, Hu/Angelholm/SW278/2004/SE, which was isolated from an adult with gastroenteritis in Solna, Sweden. An identical nucleotide sequence was detected from a food handler at the hotel restaurant, suggesting that the causative agent of the outbreak was transmitted from the food handler. This is the first description of a food-borne outbreak associated with the SaV genogroup IV strain in Japan.

[Vancomycin-resistant enterococcus--chronicle of a foretold problem].

PubMed

Bonten, Marc J M; Willems, Rob J

2012-01-01

There have recently been 12 outbreaks of infection caused by vancomycin-resistant enterococci (VRE) in Dutch hospitals. Although the first VRE outbreaks were reported almost 12 years ago, such outbreaks remained uncommon and the question is why they are occurring now. Based on molecular epidemiological studies we have learned that a subpopulation of Enterococcus faecium, resistant to amoxicillin but susceptible to vancomycin, has become highly endemic in Dutch hospitals in the past 12 years. Initial analyses suggest that several transposons containing vancomycin-resistance genes have been introduced into this population, followed by nosocomial spread. We recommend that hospitals without detected VRE outbreaks screen high-risk patients for the presence of VRE. If transmission has already occurred in many hospitals, it will be extremely difficult (and costly) to eradicate VRE.

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.

Management of the 2014 Enterovirus 68 Outbreak at a Pediatric Tertiary Care Center.

PubMed

Schuster, Jennifer E; Newland, Jason G

2015-11-01

Enterovirus 68 (EV-D68) is an uncommonly recognized cause of acute respiratory tract infections. During the late summer of 2014, an international EV-D68 outbreak occurred. We review the steps of outbreak recognition and management in the context of 1 hospital's experience with the EV-D68 outbreak. We reviewed the role of Children's Mercy Hospital as one of the first hospitals to recognize the 2014 EV-D68 outbreak in the United States. The steps of outbreak management were applied to real-life examples as the outbreak unfolded at our hospital. Management of the 2014 EV-D68 outbreak was a multifaceted effort requiring close coordination with hospitals, local and state health departments, and the Centers for Disease Control and Prevention. The importance of clear and frequent communication is highlighted both intra- and interinstitutionally. Increased respiratory disease-related pediatric admissions at hospitals nationally were attributed to EV-D68. Outcomes for these children, including the association of EV-D68 with acute flaccid myelitis, remain under investigation. Following the steps of outbreak management is critical to providing optimal patient care and ensuring the health of the public. During the 2014 EV-D68 outbreak, close adherence to outbreak principles led to swift recognition of illness, rapid diagnostic measures, institution of appropriate therapies, and dissemination of information to health care providers and the public. Equally important was the subsequent identification of an increase in acute flaccid myelitis cases against the backdrop of an increase in EV-D68 detections nationally. Future prospective studies are needed to determine the true burden of EV-D68 disease, potential vaccines and therapeutics, and outcomes of children with EV-D68 infection. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.

An outbreak of influenza A(H1N1)pdm09 virus in a primary school in Vietnam.

PubMed

Duong, Tran Nhu; Tho, Nguyen Thi Thi; Hien, Nguyen Tran; Olowokure, Babatunde

2015-10-15

Despite school pupils being at greatest risk during the 2009 influenza pandemic there are limited data on outbreaks of influenza A(H1N1)pdm09 in primary schools in South-East Asia. This prospective cohort study describes an outbreak of influenza A(H1N1)pdm09 in a primary school in rural Vietnam. In total 103 cases of influenza-like illness were found among the 407 pupils in the primary school. Ten of these were laboratory confirmed cases of influenza A(H1N1)pdm09 virus. The overall attack rate (AR) was 25% (103/407), and was highest (41%) in grade 4 pupils, where the outbreak started. All cases in the outbreak presented with a mild and self-limiting illness, acute respiratory symptoms and fever. Public health interventions to contain the outbreak could explain the lower attack rates in other grades. Ill pupils were asked to stay at home. Oseltamivir was not given to pupils and the school did not close during the outbreak. The last detected case occurred 12 days following identification of the first case. This is the first report of an outbreak of influenza A(H1N1)pdm09 among pupils in a primary school in Vietnam. High attack rates in Grade 4 pupils suggest shared activities contributed to transmission. The public health response using non-pharmaceutical measures may have played a role in ending the outbreak.

Hospital-acquired listeriosis associated with sandwiches in the UK: a cause for concern.

PubMed

Little, C L; Amar, C F L; Awofisayo, A; Grant, K A

2012-09-01

Hospital-acquired outbreaks of listeriosis are not commonly reported but remain a significant public health problem. To raise awareness of listeriosis outbreaks that have occurred in hospitals and describe actions that can be taken to minimize the risk of foodborne listeriosis to vulnerable patients. Foodborne outbreaks and incidents of Listeria monocytogenes reported to the Health Protection Agency national surveillance systems were investigated and those linked to hospitals were extracted. The data were analysed to identify the outbreak/incident setting, the food vehicle, outbreak contributory factors and origin of problem. Most (8/11, 73%) foodborne outbreaks of listeriosis that occurred in the UK between 1999 and 2011 were associated with sandwiches purchased from or provided in hospitals. Recurrently in the outbreaks the infecting subtype of L. monocytogenes was detected in supplied prepacked sandwiches and sandwich manufacturing environments. In five of the outbreaks breaches in cold chain controls of food also occurred at hospital level. The outbreaks highlight the potential for sandwiches contaminated with L. monocytogenes to cause severe infection in vulnerable people. Control of L. monocytogenes in sandwich manufacturing and within hospitals is essential to minimize the potential for consumption of this bacterium at levels hazardous to health. Manufacturers supplying sandwiches to hospitals should aim to ensure absence of L. monocytogenes in sandwiches at the point of production and hospital-documented food safety management systems should ensure the integrity of the food cold chain. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2017-10-01

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

The importance of serological and molecular analyses for the diagnosis of measles cases and for meeting elimination targets in Turkey from 2007 to 2015.

PubMed

Cosgun, Yasemin; Guldemir, Dilek; Coskun, Aslihan; Yolbakan, Sultan; Kalaycioglu, Atila Taner; Korukluoglu, Gulay; Durmaz, Riza

2018-04-01

Measles is an important childhood infection targeted to be eliminated by the World Health Organization (WHO). Virus circulation has not been interrupted in the European Region because high vaccination rates could not be achieved among some countries of the WHO European Region including Turkey. The purpose of this study was to evaluate the laboratory findings of measles cases confirmed in the last nine years, to assess the epidemiological data of the cases, to determine the molecular genotyping studies and to emphasise the importance of laboratory-based surveillance in measles. From 2007 to 2010, only 18 imported cases were detected in Turkey. However, this number increased with a local outbreak of 111 cases in 2011, followed by another outbreak in 2012 in Istanbul that spread countrywide in the following two years; a total of 8661 laboratory-confirmed measles cases were reported from 2012 to 2015. After ELISA detection of a measles IgM-positive result in serum samples of potential measles cases, RT-PCR was performed with urine or nasopharyngeal swab samples of patients, and amplicons were subjected to sequencing. In the samples of 2010 and 2011, D4 and D9 genotypes were mainly detected; as of 2012, the D8 genotype has gained importance. Although D8 was also identified in 2014, in the same year genotype H1 viruses were detected in Turkey for the first time. Therefore, it is important to perform a genotypic analysis of the virus causing the outbreak, analyse epidemiological connections of the contact, determine the source of the outbreak and plan measures based on this information.

Electrochemical immunosensors for Salmonella detection in food

USDA-ARS?s Scientific Manuscript database

Pathogen detection is a critical point for the identification and the prevention of problems related to food safety. Failures at detecting contaminations in food may cause outbreaks with drastic consequences to public health. In spite of the real need for obtaining analytical results in the shortest...

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

PubMed Central

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

2014-01-01

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

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

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

[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.

Highly Pathogenic Avian Influenza Virus among Wild Birds in Mongolia

PubMed Central

Gilbert, Martin; Jambal, Losolmaa; Karesh, William B.; Fine, Amanda; Shiilegdamba, Enkhtuvshin; Dulam, Purevtseren; Sodnomdarjaa, Ruuragchaa; Ganzorig, Khuukhenbaatar; Batchuluun, Damdinjav; Tseveenmyadag, Natsagdorj; Bolortuya, Purevsuren; Cardona, Carol J.; Leung, Connie Y. H.; Peiris, J. S. Malik; Spackman, Erica; Swayne, David E.; Joly, Damien O.

2012-01-01

Mongolia combines a near absence of domestic poultry, with an abundance of migratory waterbirds, to create an ideal location to study the epidemiology of highly pathogenic avian influenza virus (HPAIV) in a purely wild bird system. Here we present the findings of active and passive surveillance for HPAIV subtype H5N1 in Mongolia from 2005–2011, together with the results of five outbreak investigations. In total eight HPAIV outbreaks were confirmed in Mongolia during this period. Of these, one was detected during active surveillance employed by this project, three by active surveillance performed by Mongolian government agencies, and four through passive surveillance. A further three outbreaks were recorded in the neighbouring Tyva Republic of Russia on a lake that bisects the international border. No HPAIV was isolated (cultured) from 7,855 environmental fecal samples (primarily from ducks), or from 2,765 live, clinically healthy birds captured during active surveillance (primarily shelducks, geese and swans), while four HPAIVs were isolated from 141 clinically ill or dead birds located through active surveillance. Two low pathogenic avian influenza viruses (LPAIV) were cultured from ill or dead birds during active surveillance, while environmental feces and live healthy birds yielded 56 and 1 LPAIV respectively. All Mongolian outbreaks occurred in 2005 and 2006 (clade 2.2), or 2009 and 2010 (clade 2.3.2.1); all years in which spring HPAIV outbreaks were reported in Tibet and/or Qinghai provinces in China. The occurrence of outbreaks in areas deficient in domestic poultry is strong evidence that wild birds can carry HPAIV over at least moderate distances. However, failure to detect further outbreaks of clade 2.2 after June 2006, and clade 2.3.2.1 after June 2010 suggests that wild birds migrating to and from Mongolia may not be competent as indefinite reservoirs of HPAIV, or that HPAIV did not reach susceptible populations during our study. PMID:22984464

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.

[Waterborne outbreak of gastroenteritis transmitted through the public water supply].

PubMed

Godoy, P; Borrull, C; Palà, M; Caubet, I; Bach, P; Nuín, C; Espinet, L; Torres, J; Mirada, G

2003-01-01

The chlorination of public water supplies has led researchers to largely discard drinking water as a potential source of gastroenteritis outbreaks. The aim of this study was to investigate an outbreak of waterborne disease associated with drinking water from public supplies. A historical cohort study was carried out following notification of a gastroenteritis outbreak in Baqueira (Valle de Arán, Spain). We used systematic sampling to select 87 individuals staying at hotels and 67 staying in apartments in the target area. Information was gathered on four factors (consumption of water from the public water supply, sandwiches, water and food in the ski resorts) as well as on symptoms. We assessed residual chlorine in drinking water, analyzed samples of drinking water, and studied stool cultures from 4 patients. The risk associated with each water source and food type was assessed by means of relative risk (RR) and 95% confidence intervals (CI). The overall attack rate was 51.0% (76/149). The main symptoms were diarrhea 87.5%, abdominal pain 80.0%, nausea 50.7%, vomiting 30.3%, and fever 27.0%. The only factor associated with a statistically significant risk of disease was consumption of drinking water (RR = 11.0; 95% CI, 1.6-74.7). No residual chlorine was detected in the drinking water, which was judged acceptable. A problem associated with the location of the chlorinator was observed and corrected. We also recommended an increase in chlorine levels, which was followed by a reduction in the number of cases. The results of stool cultures of the four patients were negative for enterobacteria. This study highlights the potential importance of waterborne outbreaks of gastroenteritis transmitted through drinking water considered acceptable and suggests the need to improve microbiological research into these outbreaks (viruses and protozoa detection).

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

Phocine distemper virus (PDV) seroprevalence as predictor for future outbreaks in harbour seals.

PubMed

Ludes-Wehrmeister, Eva; Dupke, Claudia; Harder, Timm C; Baumgärtner, Wolfgang; Haas, Ludwig; Teilmann, Jonas; Dietz, Rune; Jensen, Lasse F; Siebert, Ursula

2016-02-01

Phocine distemper virus (PDV) infections caused the two most pronounced mass mortalities in marine mammals documented in the past century. During the two outbreaks, 23,000 and 30,000 harbour seals (Phoca vitulina), died in 1988/1989 and 2002 across populations in the Wadden Sea and adjacent waters, respectively. To follow the mechanism and development of disease spreading, the dynamics of Morbillivirus-specific antibodies in harbour seal populations in German and Danish waters were examined. 522 serum samples of free-ranging harbour seals of different ages were sampled between 1990 and 2014. By standard neutralisation assays, Morbillivirus-specific antibodies were detected, using either the PDV isolate 2558/Han 88 or the related canine distemper virus (CDV) strain Onderstepoort. A total of 159 (30.5%) of the harbour seals were seropositive. Annual seroprevalence rates showed an undulating course: Peaks were seen in the post-epidemic years 1990/1991 and 2002/2003. Following each PDV outbreak, seroprevalence decreased and six to eight years after the epidemics samples were tested seronegative, indicating that the populations are now again susceptible to new PDV outbreak. After the last outbreak in 2002, the populations grew steadily to an estimated maximum (since 1975) of about 39,100 individuals in the Wadden Sea in 2014 and about 23,540 harbour seals in the Kattegat area in 2013. A re-appearence of PDV would presumably result in another epizootic with high mortality rates as encountered in the previous outbreaks. The current high population density renders harbour seals vulnerable to rapid spread of infectious agents including PDV and the recently detected influenza A virus. Copyright © 2015 Elsevier B.V. All rights reserved.

Evidence for multiple sylvatic transmission cycles during the 2016-2017 yellow fever virus outbreak, Brazil.

PubMed

Moreira-Soto, A; Torres, M C; Lima de Mendonça, M C; Mares-Guia, M A; Dos Santos Rodrigues, C D; Fabri, A A; Dos Santos, C C; Machado Araújo, E S; Fischer, C; Ribeiro Nogueira, R M; Drosten, C; Sequeira, P Carvalho; Drexler, J F; Bispo de Filippis, A M

2018-02-07

Since December 2016, Brazil has experienced an unusually large outbreak of yellow fever (YF). Whether urban transmission may contribute to the extent of the outbreak is unclear. The objective of this study was to characterize YF virus (YFV) genomes and to identify spatial patterns to determine the distribution and origin of YF cases in Minas Gerais, Espírito Santo and Rio de Janeiro, the most affected Brazilian states during the current YFV outbreak. We characterized near-complete YFV genomes from 14 human cases and two nonhuman primates (NHP), sampled from February to April 2017, retrieved epidemiologic data of cases and used a geographic information system to investigate the geospatial spread of YFV. All YFV strains were closely related. On the basis of signature mutations, we identified two cocirculating YFV clusters. One was restricted to the hinterland of Espírito Santo state, and another formed a coastal cluster encompassing several hundred kilometers. Both clusters comprised strains from humans living in rural areas and NHP. Another NHP lineage clustered in a basal relationship. No signs of adaptation of YFV strains to human hosts were detected. Our data suggest sylvatic transmission during the current outbreak. Additionally, cocirculation of two distinct YFV clades occurring in humans and NHP suggests the existence of multiple sylvatic transmission cycles. Increased detection of YFV might be facilitated by raised awareness for arbovirus-mediated disease after Zika and chikungunya virus outbreaks. Further surveillance is required, as reemergence of YFV from NHPs might continue and facilitate the appearance of urban transmission cycles. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Hepatitis A virus strains circulating during 1997-2015 in Campania, a Southern Italy region with periodic outbreaks.

PubMed

Costantino, Angela; Coppola, Nicola; Spada, Enea; Bruni, Roberto; Taffon, Stefania; Equestre, Michele; Marcantonio, Cinzia; Sagnelli, Caterina; Dell'Isola, Chiara; Tosone, Grazia; Mascolo, Silvia; Sagnelli, Evangelista; Ciccaglione, Anna Rita

2017-11-01

In Italy, the incidence of hepatitis A has progressively declined over the last 30 years, though not homogeneously throughout the country. In Campania, Southern Italy, high annual incidence rates have been reported and several periodic outbreaks have occurred. To investigate the phylogenetic and epidemiologic relationships among HAV strains circulating in Campania over the period 1997-2015, 87 hepatitis A cases were investigated. The most frequent risk factor was the consumption of raw/undercooked shellfish (75/87, 86.2%). During 1997-2002 most viral strains were subtype IA (16/23, 70%); the phylogenetic pattern suggests that the incidence peaks observed in 2000-2001 had likely been caused by multiple strains. During a large 2004 outbreak, almost all viral variants were subtype IB (38/41, 93%); most of them (22/38, 58%) were recognized to be one of two main strains (differing for just a single nucleotide), the remaining sequences were strictly related variants. In 2014/2015, only IA strains were observed; two phylogenetically related but distinct strains were responsible, respectively, for a small cluster in 2014 and an outbreak in 2015. In each outbreak, several strains unrelated to those responsible for most cases were detected in a minority of patients, documenting a background of sporadic cases occurring even in the course of outbreaks; some of them proved to be identical to strains detected 11-14 years previously. Overall, the data suggest that several related and unrelated HAV strains have endemically circulated over the last 15 years in Campania, with some strains gaining epidemic transmission likely because of a local combination of multiple factors, including inadequate waste water purification and dietary habits. © 2017 Wiley Periodicals, Inc.

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

PubMed

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

2018-01-01

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

Health information system strengthening and malaria elimination in Papua New Guinea.

PubMed

Rosewell, Alexander; Makita, Leo; Muscatello, David; John, Lucy Ninmongo; Bieb, Sibauk; Hutton, Ross; Ramamurthy, Sundar; Shearman, Phil

2017-07-05

The objective of the study was to describe an m-health initiative to strengthen malaria surveillance in a 184-health facility, multi-province, project aimed at strengthening the National Health Information System (NHIS) in a country with fragmented malaria surveillance, striving towards enhanced control, pre-elimination. A remote-loading mobile application and secure online platform for health professionals was created to interface with the new system (eNHIS). A case-based malaria testing register was developed and integrated geo-coded households, villages and health facilities. A malaria programme management dashboard was created, with village-level malaria mapping tools, and statistical algorithms to identify malaria outbreaks. Since its inception in 2015, 160,750 malaria testing records, including village of residence, have been reported to the eNHIS. These case-based, geo-coded malaria data are 100% complete, with a median data entry delay of 9 days from the date of testing. The system maps malaria to the village level in near real-time as well as the availability of treatment and diagnostics to health facility level. Data aggregation, analysis, outbreak detection, and reporting are automated. The study demonstrates that using mobile technologies and GIS in the capture and reporting of NHIS data in Papua New Guinea provides timely, high quality, geo-coded, case-based malaria data required for malaria elimination. The health systems strengthening approach of integrating malaria information management into the eNHIS optimizes sustainability and provides enormous flexibility to cater for future malaria programme needs.

Assessing the Impact of Disturbance on Carbon Stocks in Western Forests using Remote Sensing and Forest Inventory Data

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A. P.; Landguth, E.; Holden, Z. A.

2014-12-01

Forest disturbances have important impacts on regional and global carbon-climate feedbacks. Tree mortality resulting from disturbance can cause large areas to transition from carbon (C) sinks to C sources. Although severe acute disturbance, such as fire, has been quantified extensively in the literature, the impacts of disturbance that cause more spatially heterogeneous, gradual, mortality, such as beetle kill, are more difficult to quantify and have not been studied as extensively. Combining a 13 year time series of 250 meter, 16-day, MODIS Enhanced Vegetation Index (EVI) data with field data on insect mortality collected by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, we have produced large-scale maps of dead woody biomass resulting from insect epidemics. Using a change detection algorithm, we were able to determine the timing and severity of changes in EVI due to insect epidemics across the western United States. A model was created to predict biomass based on EVI and a variety of environmental variables. Using the difference between post- and pre-outbreak EVI values, we were able to estimate the loss of biomass during insect outbreaks. These biomass data were then converted to carbon as a percentage of dry biomass using the Jenkins equations. This spatially explicit map of C currently stored in beetle kill wood will allow us to assess the vulnerability of this C to re-entering the atmosphere as CO2 via combustion or decomposition.

Lessons learnt to keep Europe polio-free: a review of outbreaks in the European Union, European Economic Area, and candidate countries, 1973 to 2013.

PubMed

Derrough, Tarik; Salekeen, Alexandra

2016-04-21

Between 1973 and 2013, 12 outbreaks of paralytic poliomyelitis with a cumulative total of 660 cases were reported in the European Union, European Economic Area and candidate countries. Outbreaks lasted seven to 90 weeks (median: 24 weeks) and were identified through the diagnosis of cases of acute flaccid paralysis, for which infection with wild poliovirus was subsequently identified. In two countries, environmental surveillance was in place before the outbreaks, but did not detect any wild strain before the occurrence of clinical cases. This surveillance nonetheless provided useful information to monitor the outbreaks and their geographical spread. Outbreaks were predominantly caused by poliovirus type 1 and typically involved unvaccinated or inadequately vaccinated groups within highly immunised communities. Oral polio vaccine was primarily used to respond to the outbreaks with catch-up campaigns implemented either nationwide or in restricted geographical areas or age groups. The introduction of supplementary immunisation contained the outbreaks. In 2002, the European region of the World Health Organization was declared polio-free and it has maintained this status since. However, as long as there are non-vaccinated or under-vaccinated groups in European countries and poliomyelitis is not eradicated, countries remain continuously at risk of reintroduction and establishment of the virus. Continued efforts to reach these groups are needed in order to ensure a uniform and high vaccination coverage.

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.

Two consecutive large outbreaks of Salmonella Muenchen linked to pig farming in Germany, 2013 to 2014: Is something missing in our regulatory framework?

PubMed

Schielke, Anika; Rabsch, Wolfgang; Prager, Rita; Simon, Sandra; Fruth, Angelika; Helling, Rüdiger; Schnabel, Martin; Siffczyk, Claudia; Wieczorek, Sina; Schroeder, Sabine; Ahrens, Beate; Oppermann, Hanna; Pfeiffer, Stefan; Merbecks, Sophie Susann; Rosner, Bettina; Frank, Christina; Weiser, Armin A; Luber, Petra; Gilsdorf, Andreas; Stark, Klaus; Werber, Dirk

2017-05-04

In 2013, raw pork was the suspected vehicle of a large outbreak (n = 203 cases) of Salmonella Muenchen in the German federal state of Saxony. In 2014, we investigated an outbreak (n = 247 cases) caused by the same serovar affecting Saxony and three further federal states in the eastern part of Germany. Evidence from epidemiological, microbiological and trace-back investigations strongly implicated different raw pork products as outbreak vehicles. Trace-back analysis of S. Muenchen-contaminated raw pork sausages narrowed the possible source down to 54 pig farms, and S. Muenchen was detected in three of them, which traded animals with each other. One of these farms had already been the suspected source of the 2013 outbreak. S. Muenchen isolates from stool of patients in 2013 and 2014 as well as from food and environmental surface swabs of the three pig farms shared indistinguishable pulsed-field gel electrophoresis patterns. Our results indicate a common source of both outbreaks in the primary production of pigs. Current European regulations do not make provisions for Salmonella control measures on pig farms that have been involved in human disease outbreaks. In order to prevent future outbreaks, legislators should consider tightening regulations for Salmonella control in causative primary production settings. This article is copyright of The Authors, 2017.

Two consecutive large outbreaks of Salmonella Muenchen linked to pig farming in Germany, 2013 to 2014: Is something missing in our regulatory framework?

PubMed Central

Schielke, Anika; Rabsch, Wolfgang; Prager, Rita; Simon, Sandra; Fruth, Angelika; Helling, Rüdiger; Schnabel, Martin; Siffczyk, Claudia; Wieczorek, Sina; Schroeder, Sabine; Ahrens, Beate; Oppermann, Hanna; Pfeiffer, Stefan; Merbecks, Sophie Susann; Rosner, Bettina; Frank, Christina; Weiser, Armin A.; Luber, Petra; Gilsdorf, Andreas; Stark, Klaus; Werber, Dirk

2017-01-01

In 2013, raw pork was the suspected vehicle of a large outbreak (n = 203 cases) of Salmonella Muenchen in the German federal state of Saxony. In 2014, we investigated an outbreak (n = 247 cases) caused by the same serovar affecting Saxony and three further federal states in the eastern part of Germany. Evidence from epidemiological, microbiological and trace-back investigations strongly implicated different raw pork products as outbreak vehicles. Trace-back analysis of S. Muenchen-contaminated raw pork sausages narrowed the possible source down to 54 pig farms, and S. Muenchen was detected in three of them, which traded animals with each other. One of these farms had already been the suspected source of the 2013 outbreak. S. Muenchen isolates from stool of patients in 2013 and 2014 as well as from food and environmental surface swabs of the three pig farms shared indistinguishable pulsed-field gel electrophoresis patterns. Our results indicate a common source of both outbreaks in the primary production of pigs. Current European regulations do not make provisions for Salmonella control measures on pig farms that have been involved in human disease outbreaks. In order to prevent future outbreaks, legislators should consider tightening regulations for Salmonella control in causative primary production settings. PMID:28494842

Recognizing flu-like symptoms from videos.

PubMed

Thi, Tuan Hue; Wang, Li; Ye, Ning; Zhang, Jian; Maurer-Stroh, Sebastian; Cheng, Li

2014-09-12

Vision-based surveillance and monitoring is a potential alternative for early detection of respiratory disease outbreaks in urban areas complementing molecular diagnostics and hospital and doctor visit-based alert systems. Visible actions representing typical flu-like symptoms include sneeze and cough that are associated with changing patterns of hand to head distances, among others. The technical difficulties lie in the high complexity and large variation of those actions as well as numerous similar background actions such as scratching head, cell phone use, eating, drinking and so on. In this paper, we make a first attempt at the challenging problem of recognizing flu-like symptoms from videos. Since there was no related dataset available, we created a new public health dataset for action recognition that includes two major flu-like symptom related actions (sneeze and cough) and a number of background actions. We also developed a suitable novel algorithm by introducing two types of Action Matching Kernels, where both types aim to integrate two aspects of local features, namely the space-time layout and the Bag-of-Words representations. In particular, we show that the Pyramid Match Kernel and Spatial Pyramid Matching are both special cases of our proposed kernels. Besides experimenting on standard testbed, the proposed algorithm is evaluated also on the new sneeze and cough set. Empirically, we observe that our approach achieves competitive performance compared to the state-of-the-arts, while recognition on the new public health dataset is shown to be a non-trivial task even with simple single person unobstructed view. Our sneeze and cough video dataset and newly developed action recognition algorithm is the first of its kind and aims to kick-start the field of action recognition of flu-like symptoms from videos. It will be challenging but necessary in future developments to consider more complex real-life scenario of detecting these actions simultaneously from multiple persons in possibly crowded environments.

Dimensionality reduction in epidemic spreading models

NASA Astrophysics Data System (ADS)

Frasca, M.; Rizzo, A.; Gallo, L.; Fortuna, L.; Porfiri, M.

2015-09-01

Complex dynamical systems often exhibit collective dynamics that are well described by a reduced set of key variables in a low-dimensional space. Such a low-dimensional description offers a privileged perspective to understand the system behavior across temporal and spatial scales. In this work, we propose a data-driven approach to establish low-dimensional representations of large epidemic datasets by using a dimensionality reduction algorithm based on isometric features mapping (ISOMAP). We demonstrate our approach on synthetic data for epidemic spreading in a population of mobile individuals. We find that ISOMAP is successful in embedding high-dimensional data into a low-dimensional manifold, whose topological features are associated with the epidemic outbreak. Across a range of simulation parameters and model instances, we observe that epidemic outbreaks are embedded into a family of closed curves in a three-dimensional space, in which neighboring points pertain to instants that are close in time. The orientation of each curve is unique to a specific outbreak, and the coordinates correlate with the number of infected individuals. A low-dimensional description of epidemic spreading is expected to improve our understanding of the role of individual response on the outbreak dynamics, inform the selection of meaningful global observables, and, possibly, aid in the design of control and quarantine procedures.

Learning from Ebola Virus: How to Prevent Future Epidemics

PubMed Central

Kekulé, Alexander S.

2015-01-01

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

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

PubMed

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

2010-08-01

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

Norovirus outbreak among primary schoolchildren who had played in a recreational water fountain.

PubMed

Hoebe, Christian J P A; Vennema, Harry; de Roda Husman, Ana Maria; van Duynhoven, Yvonne T H P

2004-02-15

A gastroenteritis outbreak was associated with playing in a norovirus-contaminated recreational fountain. A retrospective cohort study was performed to estimate the magnitude of the outbreak and identify its source. Epidemiological investigation included standardized questionnaires about sex, age, school, class, risk exposures, and illness characteristics. Stool samples and environmental water samples were analyzed for the presence of bacteria, viruses, and parasites. Questionnaires were returned for 191 schoolchildren (response rate, 83%) with a mean age of 9.2 years, of whom 47% were ill (diarrhea and/or vomiting). Children were more likely to have been ill if they had played in the recreational fountain (relative risk, 10.4). Norovirus (Birmingham) was detected in 22 (88%) stool specimens from ill children and in 6 (38%) specimens from healthy children. The water sample from the fountain contained a norovirus strain that was identical to the RNA sequence found in stools. Recreational water may be the source of gastroenteritis outbreaks. Adequate water treatment can prevent these types of outbreak.

Use of a Diagonal Approach to Health System Strengthening and Measles Elimination after a Large Nationwide Outbreak in Mongolia.

PubMed

Hagan, José E; Greiner, Ashley; Luvsansharav, Ulzii-Orshikh; Lake, Jason; Lee, Christopher; Pastore, Roberta; Takashima, Yoshihiro; Sarankhuu, Amarzaya; Demberelsuren, Sodbayar; Smith, Rachel; Park, Benjamin; Goodson, James L

2017-12-01

Measles is a highly transmissible infectious disease that causes serious illness and death worldwide. Efforts to eliminate measles through achieving high immunization coverage, well-performing surveillance systems, and rapid and effective outbreak response mechanisms while strategically engaging and strengthening health systems have been termed a diagonal approach. In March 2015, a large nationwide measles epidemic occurred in Mongolia, 1 year after verification of measles elimination in this country. A multidisciplinary team conducted an outbreak investigation that included a broad health system assessment, organized around the Global Health Security Agenda framework of Prevent-Detect-Respond, to provide recommendations for evidence-based interventions to interrupt the epidemic and strengthen the overall health system to prevent future outbreaks of measles and other epidemic-prone infectious threats. This investigation demonstrated the value of evaluating elements of the broader health system in investigating measles outbreaks and the need for using a diagonal approach to achieving sustainable measles elimination.

Effects and Clinical Significance of GII.4 Sydney Norovirus, United States, 2012–2013

PubMed Central

Wikswo, Mary; Barclay, Leslie; Brandt, Eric; Storm, William; Salehi, Ellen; DeSalvo, Traci; Davis, Tim; Saupe, Amy; Dobbins, Ginette; Booth, Hillary A.; Biggs, Christianne; Garman, Katie; Woron, Amy M.; Parashar, Umesh D.; Vinjé, Jan; Hall, Aron J.

2013-01-01

During 2012, global detection of a new norovirus (NoV) strain, GII.4 Sydney, raised concerns about its potential effect in the United States. We analyzed data from NoV outbreaks in 5 states and emergency department visits for gastrointestinal illness in 1 state during the 2012–13 season and compared the data with those of previous seasons. During August 2012–April 2013, a total of 637 NoV outbreaks were reported compared with 536 and 432 in 2011–2012 and 2010–2011 during the same period. The proportion of outbreaks attributed to GII.4 Sydney increased from 8% in September 2012 to 82% in March 2013. The increase in emergency department visits for gastrointestinal illness during the 2012–13 season was similar to that of previous seasons. GII.4 Sydney has become the predominant US NoV outbreak strain during the 2012–13 season, but its emergence did not cause outbreak activity to substantially increase from that of previous seasons. PMID:23886013

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

PubMed

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

2016-03-01

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