scholarly journals Fundamental limits on inferring epidemic resurgence in real time

2021 ◽  
Author(s):  
Kris V Parag ◽  
Christl A. Donnelly
Keyword(s):  
Mathematical Models ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Reproduction Number ◽  
Pathogen Transmission ◽  
False Alarms ◽  
Surveillance Systems ◽  
Epidemic Spread ◽  
Fundamental Limits

We find that epidemic resurgence, defined as an upswing in the effective reproduction number (R) of the contagion from subcritical to supercritical values, is fundamentally difficult to detect in real time. Intrinsic latencies in pathogen transmission, coupled with often smaller incidence across periods of subcritical spread mean that resurgence cannot be reliably detected without significant delays, even if case reporting is perfect. This belies epidemic suppression (where R falls from supercritical to subcritical values), which can be ascertained 5-10 times more rapidly. These innate limits on detecting resurgence only worsen when spatial or demographic heterogeneities are incorporated. Consequently, we argue that resurgence is more effectively handled proactively, at the expense of false alarms. Responses to recrudescent infections or emerging variants of concern will more likely be timely if informed by improved syndromic surveillance systems than by optimised mathematical models of epidemic spread.

scholarly journals Are epidemic growth rates more informative than reproduction numbers?

2021 ◽  
Author(s):  
Kris V Parag ◽  
Robin N Thompson ◽  
Christl A. Donnelly
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Pathogen Transmission ◽  
Rate Of Change ◽  
Summary Statistics ◽  
Epidemic Spread ◽  
Average Ability ◽  
Transmission Mechanisms ◽  
Reproduction Numbers ◽  
Modelling Assumptions

Summary statistics, often derived from simplified models of epidemic spread, inform public health policy in real time. The instantaneous reproduction number, Rt , is predominant among these statistics, measuring the average ability of an infection to multiply. However, Rt encodes no temporal information and is sensitive to modelling assumptions. Consequently, some have proposed the epidemic growth rate, rt , i.e., the rate of change of the log-transformed case incidence, as a more temporally meaningful and model-agnostic policy guide. We examine this assertion, identifying if and when estimates of rt are more informative than those of Rt . We assess their relative strengths both for learning about pathogen transmission mechanisms and for guiding epidemic interventions in real time.

Utility of Ambulance Data for Real-Time Syndromic Surveillance: A Pilot in the West Midlands Region, United Kingdom

2017 ◽  
Vol 32 (6) ◽  
pp. 667-672 ◽  
Author(s):  
Dan Todkill ◽  
Paul Loveridge ◽  
Alex J. Elliot ◽  
Roger A. Morbey ◽  
Obaghe Edeghere ◽  
...  
Keyword(s):  
United Kingdom ◽  
Real Time ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Lessons Learned ◽  
Surveillance Systems ◽  
Preliminary Assessment ◽  
The West ◽  
Syndromic Surveillance System ◽  
West Midlands

AbstractIntroductionThe Public Health England (PHE; United Kingdom) Real-Time Syndromic Surveillance Team (ReSST) currently operates four national syndromic surveillance systems, including an emergency department system. A system based on ambulance data might provide an additional measure of the “severe” end of the clinical disease spectrum. This report describes the findings and lessons learned from the development and preliminary assessment of a pilot syndromic surveillance system using ambulance data from the West Midlands (WM) region in England.Hypothesis/ProblemIs an Ambulance Data Syndromic Surveillance System (ADSSS) feasible and of utility in enhancing the existing suite of PHE syndromic surveillance systems?MethodsAn ADSSS was designed, implemented, and a pilot conducted from September 1, 2015 through March 1, 2016. Surveillance cases were defined as calls to the West Midlands Ambulance Service (WMAS) regarding patients who were assigned any of 11 specified chief presenting complaints (CPCs) during the pilot period. The WMAS collected anonymized data on cases and transferred the dataset daily to ReSST, which contained anonymized information on patients’ demographics, partial postcode of patients’ location, and CPC. The 11 CPCs covered a broad range of syndromes. The dataset was analyzed descriptively each week to determine trends and key epidemiological characteristics of patients, and an automated statistical algorithm was employed daily to detect higher than expected number of calls. A preliminary assessment was undertaken to assess the feasibility, utility (including quality of key indicators), and timeliness of the system for syndromic surveillance purposes. Lessons learned and challenges were identified and recorded during the design and implementation of the system.ResultsThe pilot ADSSS collected 207,331 records of individual ambulance calls (daily mean=1,133; range=923-1,350). The ADSSS was found to be timely in detecting seasonal changes in patterns of respiratory infections and increases in case numbers during seasonal events.ConclusionsFurther validation is necessary; however, the findings from the assessment of the pilot ADSSS suggest that selected, but not all, ambulance indicators appear to have some utility for syndromic surveillance purposes in England. There are certain challenges that need to be addressed when designing and implementing similar systems.TodkillD, LoveridgeP, ElliotAJ, MorbeyRA, EdeghereO, Rayment-BishopT, Rayment-BishopC, ThornesJE, SmithG. Utility of ambulance data for real-time syndromic surveillance: a pilot in the West Midlands region, United Kingdom. Prehosp Disaster Med. 2017;32(6):667–672.

scholarly journals The use of syndromic surveillance to monitor the incidence of arthropod bites requiring healthcare in England, 2000–2013: a retrospective ecological study

2016 ◽  
Vol 144 (11) ◽  
pp. 2251-2259 ◽  
Author(s):  
S. NEWITT ◽  
A. J. ELLIOT ◽  
R. MORBEY ◽  
H. DURNALL ◽  
M. E. PIETZSCH ◽  
...  
Keyword(s):  
Climate Change ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Ecological Study ◽  
Health Impact ◽  
Extreme Weather Events ◽  
Surveillance Systems ◽  
Out Of Hours ◽  
Baseline Incidence ◽  
The Impact

SUMMARYClimate change experts predict the number of nuisance-biting arthropods in England will increase but there is currently no known surveillance system in place to monitor or assess the public health impact of arthropod bites. This retrospective ecological study utilized arthropod bites requiring healthcare from five national real-time syndromic surveillance systems monitoring general practitioner (GP) consultations (in-hours and out-of-hours), emergency department (ED) attendances and telephone calls to remote advice services to determine baseline incidence in England between 2000 and 2013 and to assess the association between arthropod bites and temperature. During summer months (weeks 20–40) we estimated that arthropod bites contribute a weekly median of ~4000 GP consultations, 750 calls to remote advice services, 700 ED and 1300 GP out-of-hours attendances. In all systems, incidence was highest during summer months compared to the rest of the year. Arthropod bites were positively associated with temperature with incidence rate ratios (IRRs) that ranged between systems from 1·03 [95% confidence interval (CI) 1·01–1·06] to 1·14 (95% CI 1·11–1·16). Using syndromic surveillance systems we have established and described baseline incidence of arthropod bites and this can now be monitored routinely in real time to assess the impact of extreme weather events and climate change.

scholarly journals The effectiveness of syndromic surveillance for the early detection of waterborne outbreaks: a systematic review

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Susanne Hyllestad ◽  
Ettore Amato ◽  
Karin Nygård ◽  
Line Vold ◽  
Preben Aavitsland
Keyword(s):  
Systematic Review ◽  
Early Detection ◽  
Syndromic Surveillance ◽  
Spatial Information ◽  
Environmental Data ◽  
Cochrane Library ◽  
Joint Analysis ◽  
False Alarms ◽  
Surveillance Systems ◽  
Prevention Measures

Abstract Background Waterborne outbreaks are still a risk in high-income countries, and their early detection is crucial to limit their societal consequences. Although syndromic surveillance is widely used for the purpose of detecting outbreaks days earlier than traditional surveillance systems, evidence of the effectiveness of such systems is lacking. Thus, our objective was to conduct a systematic review of the effectiveness of syndromic surveillance to detect waterborne outbreaks. Method We searched the Cochrane Library, Medline/PubMed, EMBASE, Scopus, and Web of Science for relevant published articles using a combination of the keywords ‘drinking water’, ‘surveillance’, and ‘waterborne disease’ for the period of 1990 to 2018. The references lists of the identified articles for full-text record assessment were screened, and searches in Google Scholar using the same key words were conducted. We assessed the risk of bias in the included articles using the ROBINS-I tool and PRECEPT for the cumulative body of evidence. Results From the 1959 articles identified, we reviewed 52 articles, of which 18 met the eligibility criteria. Twelve were descriptive/analytical studies, whereas six were simulation studies. There is no clear evidence for syndromic surveillance in terms of the ability to detect waterborne outbreaks (low sensitivity and high specificity). However, one simulation study implied that multiple sources of signals combined with spatial information may increase the timeliness in detecting a waterborne outbreak and reduce false alarms. Conclusion This review demonstrates that there is no conclusive evidence on the effectiveness of syndromic surveillance for the detection of waterborne outbreaks, thus suggesting the need to focus on primary prevention measures to reduce the risk of waterborne outbreaks. Future studies should investigate methods for combining health and environmental data with an assessment of needed financial and human resources for implementing such surveillance systems. In addition, a more critical thematic narrative synthesis on the most promising sources of data, and an assessment of the basis for arguments that joint analysis of different data or dimensions of data (e.g. spatial and temporal) might perform better, should be carried out. Trial registration PROSPERO: International prospective register of systematic reviews. 2019. CRD42019122332.

scholarly journals Misdiagnosis prevents accurate monitoring of transmission and burden for sub-critical pathogens: a case study of Plasmodium knowlesi malaria

2021 ◽  
Author(s):  
John H Huber
Keyword(s):  
Infectious Diseases ◽  
Branching Process ◽  
Reproduction Number ◽  
Plasmodium Knowlesi ◽  
Emerging Infectious Diseases ◽  
Pathogen Transmission ◽  
Surveillance Systems ◽  
Transmission Chain ◽  
Complete Observation

Maintaining surveillance of emerging infectious diseases presents challenges for monitoring their transmission and burden. Incomplete observation of infections and imperfect diagnosis reduce the observed sizes of transmission chains relative to their true sizes. Previous studies have examined the effect of incomplete observation on estimates of pathogen transmission and burden. However, each study assumed that, if observed, each infection was correctly diagnosed. Here, I leveraged principles from branching process theory to examine how misdiagnosis could contribute to bias in estimates of transmission and burden for emerging infectious diseases. Using the zoonotic Plasmodium knowlesi malaria as a case study, I found that, even when assuming complete observation of infections, the number of misdiagnosed cases within a transmission chain for every correctly diagnosed case could range from 0 (0 - 4) when R0 was 0.1 to 86 (0 - 837) when R0 was 0.9. Data on transmission chain sizes obtained using an imperfect diagnostic could consistently lead to underestimates of R0, the basic reproduction number, and simulations revealed that such data on up to 1,000 observed transmission chains was not powered to detect changes in transmission. My results demonstrate that misdiagnosis may hinder effective monitoring of emerging infectious diseases and that sensitivity of diagnostics should be considered in evaluations of surveillance systems.

Using real-time syndromic surveillance systems to help explore the acute impact of the air pollution incident of March/April 2014 in England

2015 ◽  
Vol 136 ◽  
pp. 500-504 ◽  
Author(s):  
Gillian E. Smith ◽  
Zharain Bawa ◽  
Yolande Macklin ◽  
Roger Morbey ◽  
Alec Dobney ◽  
...  
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Surveillance Systems

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 The Effectiveness of Syndromic Surveillance for the Early Detection of Waterborne Outbreaks: A Systematic Review

2020 ◽  
Author(s):  
Susanne Hyllestad ◽  
Ettore Amato ◽  
Karin Nygård ◽  
Vold Line ◽  
Preben Aavitsland
Keyword(s):  
Systematic Review ◽  
Early Detection ◽  
Syndromic Surveillance ◽  
Spatial Information ◽  
Conclusive Evidence ◽  
Environmental Data ◽  
Cochrane Library ◽  
False Alarms ◽  
Surveillance Systems ◽  
Prevention Measures

Abstract Background: Waterborne outbreaks are still a risk in high-income countries, and their early detection is crucial to limit their societal consequences. Although syndromic surveillance is widely used for the purpose of detecting outbreaks days earlier than traditional surveillance systems, evidence of the effectiveness of such systems is lacking. Thus, our objective was to conduct a systematic review of the effectiveness of syndromic surveillance to detect waterborne outbreaks. Method: We searched the Cochrane Library, Medline/PubMed, EMBASE, Scopus, and Web of Science for relevant published articles using a combination of the keywords ‘drinking water’, ‘surveillance’, and ‘waterborne disease’ for the period of 1990 to 2018. The references lists of the identified articles for full-text record assessment were screened, and random searches using the same key words were conducted. We assessed the risk of bias in the included articles using the ROBINS-I tool and PRECEPT for the cumulative body of evidence. Results: From the 1,955 articles identified, we reviewed 52 articles, of which 16 met the eligibility criteria. Ten were retrospective studies, whereas six were simulation studies. There is no clear evidence for syndromic surveillance in terms of the ability to detect waterborne outbreaks (low sensitivity and high specificity). However, one simulation study implied that multiple sources of signals combined with spatial information may increase the timeliness in detecting a waterborne outbreak and reduce false alarms. Conclusion: This review demonstrates that there is no conclusive evidence on the effectiveness of syndromic surveillance for the detection of waterborne outbreaks, thus suggesting the need to focus on primary prevention measures to reduce the risk of waterborne outbreaks. Future studies should investigate methods for combining health and environmental data with an assessment of needed financial and human resources for implementing such surveillance systems.

scholarly journals Syndromic surveillance: two decades experience of sustainable systems – its people not just data!

2019 ◽  
Vol 147 ◽  
Author(s):  
Gillian E. Smith ◽  
Alex J. Elliot ◽  
Iain Lake ◽  
Obaghe Edeghere ◽  
Roger Morbey ◽  
...  
Keyword(s):  
Public Health ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
Clinical Signs ◽  
Added Value ◽  
Surveillance Systems ◽  
Public Health Action ◽  
Related Data ◽  
The Impact

AbstractSyndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services.

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