scholarly journals Evaluating Syndromic Surveillance Systems

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Iain Lake ◽  
Felipe J. Colón-González ◽  
Roger Morbey ◽  
Alex J. Elliot ◽  
Gillian E. Smith ◽  
...  
Keyword(s):  
Empirical Analysis ◽  
Pandemic Influenza ◽  
Data Streams ◽  
Syndromic Surveillance ◽  
Evaluation Framework ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Time To Detection

Syndromic surveillance systems are commonly presented in the literature but few are rigorously evaluated. We present and test an evaluation framework to examine which events can and cannot be detected, the time to detection and the efficacy of different syndromic surveillance data streams. This was achieved using four national syndromic surveillance systems in England and simulating a number of possible disease events (e.g. outbreak of pandemic influenza, (Cryptosporidium) outbreak and deliberate anthrax release). This methodology can be widely adopted to provide more empirical analysis of the effectiveness of syndromic surveillance systems worldwide.

scholarly journals How Should We Be Conducting Routine Analysis of Traditional Emergency Department Syndromic Surveillance Data?

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
David Atrubin ◽  
Michael Wiese
Keyword(s):  
Emergency Department ◽  
Best Practices ◽  
International Society ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Outbreak Detection ◽  
Surveillance Systems ◽  
Track Record ◽  
Periodic Disease

This roundtable will focus on how traditional emergency department syndromic surveillance systems should be used to conduct daily or periodic disease surveillance.  As outbreak detection using these systems has demonstrated an equivocal track record, epidemiologists have sought out other interesting uses for these systems.  Over the numerous years of the International Society for Disease Surveillance (ISDS) Conference, many of these studies have been presented; however, there has been a dearth of discussion related to how these systems should be used. This roundtable offers a forum to discuss best practices for the routine use of emergency department syndromic surveillance data.

Monitoring epidemiological trends in back to school asthma among preschool and school-aged children using real-time syndromic surveillance in England, 2012–2016

2019 ◽  
Vol 73 (9) ◽  
pp. 825-831 ◽  
Author(s):  
Nick Bundle ◽  
Neville Q Verlander ◽  
Roger Morbey ◽  
Obaghe Edeghere ◽  
Sooria Balasegaram ◽  
...  
Keyword(s):  
Syndromic Surveillance ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Baseline Period ◽  
Specific Pattern ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Asthma Morbidity ◽  
School Year ◽  
The Impact

Background Back to school (BTS) asthma has been previously reported in children; however, its epidemiology and associated healthcare burden are unclear. We aimed to describe the timing and magnitude of BTS asthma using surveillance data from different health services in England.Methods Asthma morbidity data from emergency department attendances and general practitioner (GP) consultations between April 2012 and December 2016 were used from national syndromic surveillance systems in England. Age-specific and sex-specific rates and time series of asthma peaks relative to school term dates were described. The timing of a BTS excess period and adjusted rates of asthma relative to a baseline period were estimated using cumulative sum control chart plots and negative binomial regression.Results BTS asthma among children aged below 15 years was most pronounced at the start of the school year in September. This effect was not present among those aged 15 years and above. After controlling for sex and study year, the adjusted daily rate of childhood GP in-hours asthma consultations was 2.5–3 times higher in the BTS excess period, with a significantly higher effect among children aged 0–4 years. A distinct age-specific pattern of sex differences in asthma presentations was present, with a higher burden among males in children and among females aged over 15 years.ConclusionWe found evidence of a BTS asthma peak in children using surveillance data across a range of healthcare systems, supporting the need for further preventative work to reduce the impact of BTS asthma in children.

scholarly journals The COVID-19 pandemic: a new challenge for syndromic surveillance

2020 ◽  
Vol 148 ◽  
Author(s):  
Alex J. Elliot ◽  
Sally E. Harcourt ◽  
Helen E. Hughes ◽  
Paul Loveridge ◽  
Roger A. Morbey ◽  
...  
Keyword(s):  
Public Health ◽  
Health System ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Clinical Coding ◽  
Public Health Response ◽  
Specific Symptom ◽  
Health And Social Care ◽  
The Impact

Abstract The COVID-19 pandemic is exerting major pressures on society, health and social care services and science. Understanding the progression and current impact of the pandemic is fundamental to planning, management and mitigation of future impact on the population. Surveillance is the core function of any public health system, and a multi-component surveillance system for COVID-19 is essential to understand the burden across the different strata of any health system and the population. Many countries and public health bodies utilise ‘syndromic surveillance’ (using real-time, often non-specific symptom/preliminary diagnosis information collected during routine healthcare provision) to supplement public health surveillance programmes. The current COVID-19 pandemic has revealed a series of unprecedented challenges to syndromic surveillance including: the impact of media reporting during early stages of the pandemic; changes in healthcare-seeking behaviour resulting from government guidance on social distancing and accessing healthcare services; and changes in clinical coding and patient management systems. These have impacted on the presentation of syndromic outputs, with changes in denominators creating challenges for the interpretation of surveillance data. Monitoring changes in healthcare utilisation is key to interpreting COVID-19 surveillance data, which can then be used to better understand the impact of the pandemic on the population. Syndromic surveillance systems have had to adapt to encompass these changes, whilst also innovating by taking opportunities to work with data providers to establish new data feeds and develop new COVID-19 indicators. These developments are supporting the current public health response to COVID-19, and will also be instrumental in the continued and future fight against the disease.

An Observational Study Using English Syndromic Surveillance Data Collected During the 2012 London Olympics – What did Syndromic Surveillance Show and What Can We Learn for Future Mass-gathering Events?

2016 ◽  
Vol 31 (6) ◽  
pp. 628-634 ◽  
Author(s):  
Dan Todkill ◽  
Helen E. Hughes ◽  
Alex J. Elliot ◽  
Roger A. Morbey ◽  
Obaghe Edeghere ◽  
...  
Keyword(s):  
Public Health ◽  
Observational Study ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Olympic Games ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Mass Gathering ◽  
Opening Ceremony ◽  
London 2012

AbstractIntroductionIn preparation for the London 2012 Olympic Games, existing syndromic surveillance systems operating in England were expanded to include daily general practitioner (GP) out-of-hours (OOH) contacts and emergency department (ED) attendances at sentinel sites (the GP OOH and ED syndromic surveillance systems: GPOOHS and EDSSS).Hypothesis/ProblemThe further development of syndromic surveillance systems in time for the London 2012 Olympic Games provided a unique opportunity to investigate the impact of a large mass-gathering event on public health and health services as monitored in near real-time by syndromic surveillance of GP OOH contacts and ED attendances. This can, in turn, aid the planning of future events.MethodsThe EDSSS and GPOOHS data for London and England from July 13 to August 26, 2012, and a similar period in 2013, were divided into three distinct time periods: pre-Olympic period (July 13-26, 2012); Olympic period (July 27 to August 12); and post-Olympic period (August 13-26, 2012). Time series of selected syndromic indicators in 2012 and 2013 were plotted, compared, and risk assessed by members of the Real-time Syndromic Surveillance Team (ReSST) in Public Health England (PHE). Student’s t test was used to test any identified changes in pattern of attendance.ResultsVery few differences were found between years or between the weeks which preceded and followed the Olympics. One significant exception was noted: a statistically significant increase (P value = .0003) in attendances for “chemicals, poisons, and overdoses, including alcohol” and “acute alcohol intoxication” were observed in London EDs coinciding with the timing of the Olympic opening ceremony (9:00 pm July 27, 2012 to 01:00 am July 28, 2012).ConclusionsSyndromic surveillance was able to provide near to real-time monitoring and could identify hourly changes in patterns of presentation during the London 2012 Olympic Games. Reassurance can be provided to planners of future mass-gathering events that there was no discernible impact in overall attendances to sentinel EDs or GP OOH services in the host country. The increase in attendances for alcohol-related causes during the opening ceremony, however, may provide an opportunity for future public health interventions.TodkillD, HughesHE, ElliotAJ, MorbeyRA, EdeghereO, HarcourtS, HughesT, EndericksT, McCloskeyB, CatchpoleM, IbbotsonS, SmithG. An observational study using English syndromic surveillance data collected during the 2012 London Olympics – what did syndromic surveillance show and what can we learn for future mass-gathering events?Prehosp Disaster Med. 2016;31(6):628–634.

scholarly journals Vetsyn: Veterinary Syndromic Surveillance Streamlined into one R Package

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Fernanda C. Dórea ◽  
Stefan Widgrén ◽  
Ann Lindberg
Keyword(s):  
Laboratory Test ◽  
Signal Detection ◽  
Data Streams ◽  
Syndromic Surveillance ◽  
Historical Data ◽  
R Package ◽  
Surveillance Systems ◽  
Detection Algorithms ◽  
Set Up ◽  
Monitor Data

We describe an R package that was designed to provide ready implementation of veterinary syndromic surveillance systems, from classified data to the generation of alerts. The development of the package was informed by the experience developing two systems for veterinary syndromic surveillance based on laboratory test requests. Functions are available to carry out retrospective analyses of the data available; produce an outbreak-free baseline from historical data; monitor data streams prospectively with a combination of various temporal outbreak-signal detection algorithms; set up automated email alerts in case of alarms; and set up an html interface for the system.

scholarly journals Evaluation of Syndromic Surveillance Data Streams in Animal Health

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Morgan Hennessey ◽  
Julianna B. Lenoch ◽  
Cynthia Zepeda ◽  
Leah Estberg ◽  
Judy Akkina
Keyword(s):  
Literature Review ◽  
Data Streams ◽  
Syndromic Surveillance ◽  
Data Stream ◽  
Animal Health ◽  
Surveillance Data ◽  
Surveillance Program ◽  
Poison Center ◽  
Pilot Projects ◽  
Use Of Resources

ObjectiveTo implement a systematic and uniform approach to evaluatingdata sources for syndromic surveillance within the United StatesDepartment of Agriculture (USDA) Animal and Plant HealthInspection Services (APHIS) Veterinary Services (VS) group.IntroductionUSDA-APHIS-VS utilizes several continuous data streams toincrease our knowledge of animal health and provide situationalawareness of emerging animal health issues. In addition, USDA-APHIS-VS often conducts pilot projects to see if regular data accessand analysis are feasible, and if so, if the information generated isuseful. Syndromic surveillance was developed for three goals: asyndromic monitoring system to identify new diseases, as an emergingdisease early warning system, and to provide situational awarenessof animal health status. Current efforts focus on monitoring diversedata, such as laboratory accessions or poison center calls, groupedinto syndromic or other health indicator categories, and are notintended to identify specific pre-determined diseases or pathogens.It is essential to regularly evaluate and re-evaluate the effectiveness ofour surveillance program. However, there are difficulties when usingtraditional surveillance evaluation methods, since the objectives andoutcomes of monitoring novel data streams from pilot projects arenot easily measurable. An additional challenge in the evaluation ofthese data streams is the identification of a method that can adapt tovarious context and inputs to make objective decisions. Until recently,assessment efforts have looked at the feasibility of regular analysisand reporting, but not at the utility of the information generated, northe plausibility and sustainability of longer term or expanded efforts.MethodsMethods for surveillance evaluation, syndromic surveillanceevaluation, and specifically for animal health syndromic surveillanceevaluation were researched via a literature review, exploration ofmethods used in-house on traditional surveillance systems, andthrough development over time of criteria that were seen as key tothe development of functioning, sustainable systems focusing onanimal health syndromic surveillance. Several methods were adaptedto create an approach that could organize information in a logicalmanner, clarify objectives, and make qualitative value assessmentsin situations where the quantitative aspects of costs and benefits werenot always straight forward. More than 25 articles were reviewed todetermine the best method of evaluation.ResultsThe RISKSUR Evaluation Support Tool (EVA) provided themajority of the methodology for the evaluations of our data sources.The EVA tool allows for an integrated approach for evaluation, andflexible methods to measure effectiveness and benefits of various datastreams. The most useful and common factors found to evaluate pilotdata sources of interest were how well the information generated bythe data streams could provide early detection of animal health events,and how well and how often situational awareness information onanimal health was generated. The EVA tool also helps identify andorganize criteria that are used to assess the objectives, and assignvalue.ConclusionsThe regular evaluation of syndromic surveillance data streamsin animal health is necessary to make best use of resources andmaximize benefits of data stream use. It is also useful to conductregular interim assessments on data streams in pilot phase to becertain key information for a final evaluation will be generated duringthe project. The RISKSUR EVA tool was found to be very flexibleand useful for allowing estimates of value to be made, even whenevaluating systems that do not have very specific, quantitativelymeasurable objectives. This tool provides flexibility in the selectionof attributes for evaluation, making it particularly useful whenexamining pilot project data streams. In combination with additionalreview methodologies from the literature review, a systematic anduniform approach to data stream evaluation was identified for futureuse.

scholarly journals Early spread of the 2009 influenza A(H1N1) pandemic in the United Kingdom – use of local syndromic data, May–August 2009

2011 ◽  
Vol 16 (3) ◽  
Author(s):  
S Smith ◽  
G E Smith ◽  
B Olowokure ◽  
S Ibbotson ◽  
D Foord ◽  
...  
Keyword(s):  
United Kingdom ◽  
Pandemic Influenza ◽  
Syndromic Surveillance ◽  
Local Level ◽  
Surveillance Data ◽  
The West ◽  
The United Kingdom ◽  
West Midlands ◽  
Influenza Activity ◽  
Nhs Direct

Following the confirmation of the first two cases of pandemic influenza on 27 April 2009 in the United Kingdom (UK), syndromic surveillance data from the Health Protection Agency (HPA)/QSurveillance and HPA/NHS Direct systems were used to monitor the possible spread of pandemic influenza at local level during the first phase of the outbreak. During the early weeks, syndromic indicators sensitive to influenza activity monitored through the two schemes remained low and the majority of cases were travel-related. The first evidence of community spread was seen in the West Midlands region following a school-based outbreak in central Birmingham. During the first phase several Primary Care Trusts had periods of exceptional influenza activity two to three weeks ahead of the rest of the region. Community transmission in London began slightly later than in the West Midlands but the rates of influenza-like illness recorded by general practitioners (GPs) were ultimately higher. Influenza activity in the West Midlands and London regions peaked a week before the remainder of the UK. Data from the HPA/NHS Direct and HPA/QSurveillance systems were mapped at local level and used alongside laboratory data and local intelligence to assist in the identification of hotspots, to direct limited public health resources and to monitor the progression of the outbreak. This work has demonstrated the utility of local syndromic surveillance data in the detection of increased transmission and in the epidemiological investigation of the pandemic and has prompted future spatio-temporal work.

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