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.

scholarly journals What did Syndromic Surveillance Show During London 2012? Lessons for Mass Gatherings

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Dan Todkill ◽  
Helen Hughes ◽  
Alex Elliot ◽  
Roger Morbey ◽  
Obaghe Edeghere ◽  
...  
Keyword(s):  
Public Health ◽  
General Practitioner ◽  
Syndromic Surveillance ◽  
Lessons Learned ◽  
Surveillance Systems ◽  
Mass Gathering ◽  
Daily Number ◽  
Mass Gatherings ◽  
London 2012 ◽  
The Impact

This paper investigates the impact of the London 2012 Olympic and Paralympic Games on syndromic surveillance systems coordinated by Public Health England. The Games had very little obvious impact on the daily number of ED attendances and general practitioner consultations both nationally, and within London. These results provide valuable lessons learned for future mass gathering events.

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.

Emergency Medical Services and Syndromic Surveillance: A Comparison With Traditional Surveillance and Effects on Timeliness

2021 ◽  
Vol 136 (1_suppl) ◽  
pp. 72S-79S
Author(s):  
Peter J. Rock ◽  
Dana Quesinberry ◽  
Michael D. Singleton ◽  
Svetla Slavova
Keyword(s):  
Public Health ◽  
Time Series ◽  
Emergency Medical Services ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Medical Services ◽  
Opioid Overdose ◽  
Billing Data ◽  
Public Health Response ◽  
Emergency Medical

Objective Traditional public health surveillance of nonfatal opioid overdose relies on emergency department (ED) billing data, which can be delayed substantially. We compared the timeliness of 2 new data sources for rapid drug overdose surveillance—emergency medical services (EMS) and syndromic surveillance—with ED billing data. Methods We used data on nonfatal opioid overdoses in Kentucky captured in EMS, syndromic surveillance, and ED billing systems during 2018-2019. We evaluated the time-series relationships between EMS and ED billing data and syndromic surveillance and ED billing data by calculating cross-correlation functions, controlling for influences of autocorrelations. A case example demonstrates the usefulness of EMS and syndromic surveillance data to monitor rapid changes in opioid overdose encounters in Kentucky during the COVID-19 epidemic. Results EMS and syndromic surveillance data showed moderate-to-strong correlation with ED billing data on a lag of 0 ( r = 0.694; 95% CI, 0.579-0.782; t = 9.73; df = 101; P < .001; and r = 0.656; 95% CI, 0.530-0.754; t = 8.73; df = 101; P < .001; respectively) at the week-aggregated level. After the COVID-19 emergency declaration, EMS and syndromic surveillance time series had steep increases in April and May 2020, followed by declines from June through September 2020. The ED billing data were available for analysis 3 months after the end of a calendar quarter but closely followed the trends identified by the EMS and syndromic surveillance data. Conclusion Data from EMS and syndromic surveillance systems can be reliably used to monitor nonfatal opioid overdose trends in Kentucky in near–real time to inform timely public health response.

Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

2009 ◽  
Vol 3 (S1) ◽  
pp. S29-S36 ◽  
Author(s):  
Lori Uscher-Pines ◽  
Corey L. Farrell ◽  
Steven M. Babin ◽  
Jacqueline Cattani ◽  
Charlotte A. Gaydos ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
The United States ◽  
Essential Elements ◽  
System Response ◽  
Surveillance Systems ◽  
Health Departments ◽  
Public Health Response ◽  
Syndromic Surveillance System

ABSTRACTObjectives: To describe current syndromic surveillance system response protocols in health departments from 8 diverse states in the United States and to develop a framework for health departments to use as a guide in initial design and/or enhancement of response protocols.Methods: Case study design that incorporated in-depth interviews with health department staff, textual analysis of response plans, and a Delphi survey of syndromic surveillance response experts.Results: All 8 states and 30 of the 33 eligible health departments agreed to participate (91% response rate). Fewer than half (48%) of surveyed health departments had a written response protocol, and health departments reported conducting in-depth investigations on fewer than 15% of syndromic surveillance alerts. A convened panel of experts identified 32 essential elements for inclusion in public health protocols for response to syndromic surveillance system alerts.Conclusions: Because of the lack of guidance, limited resources for development of response protocols, and few examples of syndromic surveillance detecting previously unknown events of public health significance, health departments have not prioritized the development and refinement of response protocols. Systems alone, however, are not effective without an organized public health response. The framework proposed here can guide health departments in creating protocols that will be standardized, tested, and relevant given their goals with such systems. (Disaster Med Public Health Preparedness. 2009;3(Suppl 1):S29–S36)

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 Using real-time syndromic surveillance to monitor the health effects of air pollution

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Sally Harcourt ◽  
Lydia Izon-Cooper ◽  
Felipe D. Colón-González ◽  
Roger Morbey ◽  
Gillian Smith ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Air Pollution ◽  
Syndromic Surveillance ◽  
Health Care Seeking ◽  
Surveillance Systems ◽  
Care Seeking ◽  
Health Care Seeking Behaviour ◽  
The Impact ◽  
Care Seeking Behaviour

ObjectiveTo explore the utility of syndromic surveillance systems for detecting and monitoring the impact of air pollution incidents on health-care seeking behaviour in England between 2012 and 2017.IntroductionThe negative effect of air pollution on human health is well documented illustrating increased risk of respiratory, cardiac and other health conditions. [1] Currently, during air pollution episodes Public Health England (PHE) syndromic surveillance systems [2] provide a near real-time analysis of the health impact of poor air quality. In England, syndromic surveillance has previously been used on an ad hoc basis to monitor health impact; this has usually happened during widespread national air pollution episodes where the air pollution index has reached ‘High’ or ‘Very High’ levels on the UK Daily Air Quality Index (DAQI). [3-5]We now aim to undertake a more systematic approach to understanding the utility of syndromic surveillance for monitoring the health impact of air pollution. This would improve our understanding of the sensitivity and specificity of syndromic surveillance systems for contributing to the public health response to acute air pollution incidents; form a baseline for future interventions; assess whether syndromic surveillance systems provide a useful tool for public health alerting; enable us to explore which pollutants drive changes in health-care seeking behaviour; and add to the knowledge base.MethodsThe systematic approach will involve accessing historical data for air pollution incidents and syndromic surveillance data over the period 2012-17 across England. We will use PM10, PM2.5, ozone, NO2 , SO2 and DAQI data to define air pollution periods, and historical syndromic surveillance system data for respiratory syndromes (asthma, difficulty breathing, wheeze, cough, bronchitis, sore throat and allergic rhinitis), cardiac (all cardiovascular and myocardial infarction) and eye irritation/conjunctivitis syndromes. We will use regression modelling and cross-correlation analyses to determine the effects of air pollution, weather and pollen upon these syndromes and thus provide evidence of the sensitivity of these systems. Historical data on additional environmental variables including temperature and precipitation, humidity and thunderstorm activity, pollen and fungal spores will be accounted for in the regression models, as well as data on influenza and respiratory syncytial virus (RSV) laboratory reports. We will include sub-national geographies and age/gender analyses in the study depending on the data availability and suitability.ResultsInitial results presented will include the preliminary descriptive epidemiology with a focus on asthma and the impact of air pollution incidents on health-care seeking behaviour using data from the PHE national syndromic surveillance systems.ConclusionsWe aim to demonstrate an innovative use of syndromic surveillance data to explore the impact of air pollution incidents on health-care seeking behaviour in England, in turn improving our understanding of the sensitivity and specificity of these systems for detecting the impact of air pollution incidents and to contribute to the knowledge base. This understanding will improve the public health response to future incidents.References1. World Health Organization (WHO). Preventing disease through healthy environments. Exposure to air pollution: A major public health concern. (http://www.who.int/ipcs/features/air_pollution.pdf). Accessed 28/09/20172. Public Health England. Syndromic surveillance: systems and analyses. (https://www.gov.uk/government/collections/syndromic-surveillance-systems-and-analyses). Accessed 20/09/20173. Department for Environment Food and Rural Affairs (Defra). Daily Air Quality Index (DAQI). (https://uk-air.defra.gov.uk/air-pollution/daqi). Accessed 28/06/20174. Smith GE, et al. Using real-time syndromic surveillance systems to help explore the acute impact of the air pollution incident of March/April 2014 in England. Environ Res 2015; 136: 500-504.5. Elliot AJ, et al. Monitoring the effect of air pollution episodes on health care consultations and ambulance call-outs in England during March/April 2014: A retrospective observational analysis. Environ Pollut 2016; 214: 903-911.

scholarly journals Linking Antimicrobial Resistance Surveillance Data to Provincial Hospital Records: A Descriptive Study of Patient and Facility-level Characteristics

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Seungwon Lee ◽  
Paul E Ronksley ◽  
Stephanie Garies ◽  
Hude Quan ◽  
Peter Faris ◽  
...  
Keyword(s):  
Public Health ◽  
Patient Safety ◽  
Population Based ◽  
Surveillance Data ◽  
Infection Prevention And Control ◽  
Surveillance Systems ◽  
Discharge Abstract Database ◽  
Public Health Perspective ◽  
Safety Practices ◽  
The Impact

IntroductionAntimicrobial resistance (AMR) is an emerging phenomenon where microorganisms develop resistance against treatment antimicrobials, resulting in ineffective clinical interventions. The recent development of AMR surveillance systems at global and national stages highlights the growing importance of this topic from a public health perspective. Objectives and ApproachThe objective was to link standardized population-based hospital AMR surveillance data with hospitalizationrecords to inform patient safety practices in Alberta, Canada. Incident inpatient cases of Methicillin-Resistant Staphylococcus aureus (MRSA),identified by Alberta Health Services Provincial Infection Prevention and Control(IPC) Surveillance from five acute care facilities in the Calgary zone (April 2011 to March 2016),were deterministically linked to the Discharge Abstract Database using Provincial Healthcare Number and gender. The incident cohort was stratified into hospital-acquired (HA-MRSA) and community-acquired MRSA (CA-MRSA) cases. Descriptive statistics were used to describe the patient outcomes and facility characteristics of these two groups. ResultsA total of 2550 unique patients, representing 93.5% of the surveillance cohort, were successfully linked to hospitalization records. A total of 1259 patients belonged to HA-MRSA categories and 1291 patients belonged to CA-MRSA categories. Patients with HA-MRSA had longer hospital stays, were older, were more likely to have prior hospitalizations, had higher Charlson Comorbidity Scores, and were more likely to die in hospital when compared to patients with CA-MRSA. HA-MRSA results emphasized the important roles of in-hospital patient safety practices whereas CA-MRSA results alluded to the impact of community public health and primary care services onthe risk of hospitalization, although detected CA-MRSA numbers were likely underestimated due to selection bias within our linked cohort. Conclusion/ImplicationsThis is first Canadian study describing HA-MRSA and CA-MRSA using linked population databases. It offers a glimpse into the intricate relationship between patient health and our healthcare system. This knowledge represents an important step forwarding building IPC strategies for managing AMR and improving outcomes in Alberta and in Canada.

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.

scholarly journals The Effects of Social Distancing Policies on non-SARS-CoV-2 Respiratory Pathogens

2021 ◽  
Author(s):  
Jeff Nawrocki ◽  
Katherine Olin ◽  
Martin C Holdrege ◽  
Joel Hartsell ◽  
Lindsay Meyers ◽  
...  
Keyword(s):  
Public Health ◽  
Influenza A ◽  
Detection Rate ◽  
Respiratory Illness ◽  
Respiratory Pathogens ◽  
Public Health Response ◽  
Mixed Effect ◽  
Detection Rates ◽  
Social Distancing ◽  
The Impact

Abstract Background The initial focus of the US public health response to COVID-19 was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-SARS-CoV-2 respiratory pathogens typically circulating across multiple US states. Methods Linear mixed-effect models were implemented to explore the effects of five social distancing policies on non-SARS-CoV-2 respiratory pathogens across nine states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week-by-week to historical rates to determine when the detection rates were different. Results Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. Total detection rate in April 2020 was 35% less than historical average. Many of the pathogens driving this difference fell below historical detection rate ranges within two weeks of initial policy implementation. Conclusion This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

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