scholarly journals Syndromic surveillance insights from a symptom assessment app before and during COVID-19 measures in Germany and the United Kingdom: results from repeated cross-sectional analyses

2020 ◽  
Author(s):  
Alicia Mehl ◽  
Francois Bergey ◽  
Caoimhe Cawley ◽  
Andreas Gilsdorf
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Symptom Assessment ◽  
Assessment Tools ◽  
Added Value ◽  
Cross Sectional ◽  
Syndromic Surveillance System ◽  
The United Kingdom

AbstractBackgroundUnprecedented lockdown measures have been introduced in countries across the world to mitigate the spread and consequences of COVID-19. While attention has focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to limitations of existing syndromic surveillance data and tools.ObjectiveTo explore the added value of mobile phone app-based symptom assessment tools as real time health insight providers to inform public health policy makers.MethodsA comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an Ada assessment in Germany and the United Kingdom (UK) was conducted between two periods: before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analysed using Pearson’s Chi-squared test and reported as Log2 Fold Changes (Log2 FC).ResultsBetween 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Between 34,200-37,400 symptomatic users in the UK reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany 68,600/103,200, 66.52%; UK 51,200/71,600, 72.74%). The majority (Germany 68,500/100,000, 68.45%; UK 50,900/68,800, 73.91%) were aged between 10 and 29 years, and about a quarter (Germany 26,200/100,000, 26.15%; UK 14,900/68,800, 21.65%) were between 30-59 years. 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures as compared to the Baseline period, and 34 of these were found in both countries. The following mental health symptoms (Log2 FC, P-value) were reported less often during the Measures period: inability to manage constant stress and demands at work (−1.07, P<.001), memory difficulty (−0.56, P<.001), depressed mood (−0.42, P<.001), and impaired concentration (−0.46, P<.001). Diminished sense of taste (2.26, P<.001) and hyposmia (2.20, P<.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. Fourteen of the 34 symptoms had statistically significant associations with weather variables.ConclusionsSymptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system.

scholarly journals Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses (Preprint)

2020 ◽  
Author(s):  
Alicia Mehl ◽  
Francois Bergey ◽  
Caoimhe Cawley ◽  
Andreas Gilsdorf
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Symptom Assessment ◽  
Assessment Tools ◽  
Added Value ◽  
Cross Sectional ◽  
Syndromic Surveillance System ◽  
The United Kingdom

BACKGROUND Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to the limitations of existing syndromic surveillance data and tools. OBJECTIVE The aim of this study is to explore the added value of mobile phone app–based symptom assessment tools as real-time health insight providers to inform public health policy makers. METHODS A comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an assessment within the Ada app in Germany and the United Kingdom was conducted between two periods, namely before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analyzed using a Pearson chi-square test and reported as log2 fold changes. RESULTS Overall, 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Overall, 34,200-37,400 symptomatic users in the United Kingdom reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany: 68,600/103,200, 66.52%; United Kingdom: 51,200/71,600, 72.74%). The majority were aged 10-29 years (Germany: 68,500/100,000, 68.45%; United Kingdom: 50,900/68,800, 73.91%), and about one-quarter were aged 30-59 years (Germany: 26,200/100,000, 26.15%; United Kingdom: 14,900/68,800, 21.65%). Overall, 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures period as compared to the Baseline period, and 34 of these were reported in both countries. The following mental health symptoms (log2 fold change, <i>P</i> value) were reported less often during the Measures period: <i>inability to manage constant stress and demands at work</i> (–1.07, <i>P</i>&lt;.001), <i>memory difficulty</i> (–0.56, <i>P</i>&lt;.001), <i>depressed mood</i> (–0.42, <i>P</i>&lt;.001), and <i>impaired concentration</i> (–0.46, <i>P</i>&lt;.001). <i>Diminished sense of taste</i> (2.26, <i>P</i>&lt;.001) and <i>hyposmia</i> (2.20, <i>P</i>&lt;.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. In total, 14 of the 34 symptoms had statistically significant associations with weather variables. CONCLUSIONS Symptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system.

scholarly journals Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses

10.2196/21364 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e21364
Author(s):  
Alicia Mehl ◽  
Francois Bergey ◽  
Caoimhe Cawley ◽  
Andreas Gilsdorf
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Symptom Assessment ◽  
Assessment Tools ◽  
Added Value ◽  
P Value ◽  
Syndromic Surveillance System ◽  
The United Kingdom

Background Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to the limitations of existing syndromic surveillance data and tools. Objective The aim of this study is to explore the added value of mobile phone app–based symptom assessment tools as real-time health insight providers to inform public health policy makers. Methods A comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an assessment within the Ada app in Germany and the United Kingdom was conducted between two periods, namely before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analyzed using a Pearson chi-square test and reported as log2 fold changes. Results Overall, 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Overall, 34,200-37,400 symptomatic users in the United Kingdom reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany: 68,600/103,200, 66.52%; United Kingdom: 51,200/71,600, 72.74%). The majority were aged 10-29 years (Germany: 68,500/100,000, 68.45%; United Kingdom: 50,900/68,800, 73.91%), and about one-quarter were aged 30-59 years (Germany: 26,200/100,000, 26.15%; United Kingdom: 14,900/68,800, 21.65%). Overall, 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures period as compared to the Baseline period, and 34 of these were reported in both countries. The following mental health symptoms (log2 fold change, P value) were reported less often during the Measures period: inability to manage constant stress and demands at work (–1.07, P<.001), memory difficulty (–0.56, P<.001), depressed mood (–0.42, P<.001), and impaired concentration (–0.46, P<.001). Diminished sense of taste (2.26, P<.001) and hyposmia (2.20, P<.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. In total, 14 of the 34 symptoms had statistically significant associations with weather variables. Conclusions Symptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system.

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 Surveillance on speed: Being aware of infectious diseases in migrants mass accommodations - an easy and flexible toolkit for field application of syndromic surveillance, Germany, 2016 to 2017

2018 ◽  
Vol 23 (40) ◽  
Author(s):  
Navina Sarma ◽  
Alexander Ullrich ◽  
Hendrik Wilking ◽  
Stéphane Ghozzi ◽  
Andreas K. Lindner ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Detection Algorithm ◽  
Time Data ◽  
Gastrointestinal Infections ◽  
Robert Koch Institute ◽  
Syndromic Surveillance System ◽  
Real Time Data

Europe received an increased number of migrants in 2015. Housing in inadequate mass accommodations (MA) made migrants prone to infectious disease outbreaks. In order to enhance awareness for infectious diseases (ID) and to detect clusters early, we developed and evaluated a syndromic surveillance system in three MA with medical centres in Berlin, Germany. Healthcare workers transferred daily data on 14 syndromes to the German public health institute (Robert Koch-Institute). Clusters of ID syndromes and single cases of outbreak-prone diseases produced a signal according to a simple aberration-detection algorithm that computes a statistical threshold above which a case count is considered unusually high. Between May 2016–April 2017, 9,364 syndromes were reported; 2,717 (29%) were ID, of those 2,017 (74%) were respiratory infections, 262 (10%) skin parasites, 181 (7%) gastrointestinal infections. The system produced 204 signals, no major outbreak was detected. The surveillance reinforced awareness for public health aspects of ID. It provided real-time data on migrants' health and stressed the burden of non-communicable diseases. The tool is available online and was evaluated as being feasible and flexible. It complements traditional notification systems. We recommend its usage especially when laboratory testing is not available and real-time data are needed.

scholarly journals Developing a Multidisciplinary Syndromic Surveillance Academic Research Program in the United Kingdom: Benefits for Public Health Surveillance

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 111S-115S ◽  
Author(s):  
Alex J. Elliot ◽  
Roger Morbey ◽  
Obaghe Edeghere ◽  
Iain R. Lake ◽  
Felipe J. Colón-González ◽  
...  
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Research Program ◽  
Syndromic Surveillance ◽  
Public Health Surveillance ◽  
Academic Research ◽  
Health Surveillance ◽  
The United Kingdom

scholarly journals Implementation of an automated, real-time public health surveillance system linking emergency departments and health units: rationale and methodology

CJEM ◽  
2008 ◽  
Vol 10 (02) ◽  
pp. 114-119 ◽  
Author(s):  
Kieran M. Moore ◽  
Bronwen L. Edgar ◽  
Donald McGuinness
Keyword(s):  
Public Health ◽  
Real Time ◽  
Data Streams ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Public Health Response ◽  
Term Care ◽  
Syndromic Surveillance System ◽  
The Public ◽  
Technical Specifications

ABSTRACTIn September 2004, Kingston, Frontenac, Lennox and Addington (KFL&amp;A) Public Health, in collaboration with the Public Health Division of the Ontario Ministry of Health and Long-Term Care, Queen's University, the Public Health Agency of Canada, Kingston General Hospital and Hotel Dieu Hospital, began a 2-year pilot project to implement and evaluate an emergency department (ED) chief complaint syndromic surveillance system. Our objective was to evaluate a comprehensive and readily deployable real-time regional syndromic surveillance program and to determine its ability to detect gastrointestinal or respiratory outbreaks well in advance of traditional reporting systems. In order to implement the system, modifications were made to the University of Pittsburgh's Real-time Outbreak and Disease Surveillance (RODS) system, which has been successfully integrated into public health systems, and has enhanced communication and collaboration between them and EDs. This paper provides an overview of a RODS-based syndromic surveillance system as adapted for use at a public health unit in Kingston, Ontario. We summarize the technical specifications, privacy and security considerations, data capture, classification and management of the data streams, alerting and public health response. We hope that the modifications described here, including the addition of unique data streams, will provide a benchmark for future Canadian syndromic surveillance systems.

scholarly journals Emergency department use during COVID-19 as described by syndromic surveillance

2020 ◽  
Vol 37 (10) ◽  
pp. 600-604 ◽  
Author(s):  
Helen E Hughes ◽  
Thomas C Hughes ◽  
Roger Morbey ◽  
Kirsty Challen ◽  
Isabel Oliver ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Real Time ◽  
Respiratory Infection ◽  
Acute Respiratory Infection ◽  
Syndromic Surveillance ◽  
Rapid Development ◽  
Age Groups ◽  
Age Group ◽  
Syndromic Surveillance System

On 12 March 2020 the UK entered the ‘delay phase’ of the COVID-19 pandemic response. The Public Health England Emergency Department Syndromic Surveillance System (EDSSS) carries out daily (near real-time) public health surveillance of emergency department (ED) attendances across England. This retrospective observational analysis of EDSSS data aimed to describe changes in ED attendances during March–April 2020, and identify the attendance types with the largest impact. Type 1 ED attendances were selected from 109 EDs that reported data to EDSSS for the period 1 January 2019 to 26 April 2020. The daily numbers of attendances were plotted by age group and acuity of presentation. The 2020 ’COVID-19’ period (12 March 2020 to 26 April 2020) attendances were compared with the equivalent 2019 ’pre-COVID-19’ period (14 March 2019 to 28 April 2019): in total; by hour and day of the week; age group(<1, 1-4, 15-14, 15-44, 45-64 and 65+ years); gender; acuity; and for selected syndromic indicators(acute respiratory infection, gastroenteritis, myocardial ischaemia). Daily ED attendances up to 11 March 2020 showed regular trends, highest on a Monday and reduced in children during school holidays. From 12 March 2020 ED attendances decreased across all age groups, all acuity levels, on all days and times. Across age groups the greatest percentage reductions were seen in school age children (5–14 years). By acuity, the greatest reduction occurred in the less severe presentations. Syndromic indicators showed that the greatest reductions were in non-respiratory indicators, which fell by 44–67% during 2020 COVID-19, while acute respiratory infection was reduced by −4.4% (95% CI −9.5% to 0.6%). ED attendances in England have been particularly affected during the COVID-19 pandemic due to changes in healthcare seeking behaviour. EDSSS has enabled real-time daily monitoring of these changes, which are made publicly available to facilitate action. The EDSSS provides valuable surveillance of ED attendances in England. The flexibility of EDSSS allowed rapid development of new indicators (including COVID-19-like) and reporting methods.

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 Syndromic surveillance to assess the potential public health impact of the Icelandic volcanic ash plume across the United Kingdom, April 2010

2010 ◽  
Vol 15 (23) ◽  
Author(s):  
A J Elliot ◽  
N Singh ◽  
P Loveridge ◽  
S Harcourt ◽  
S Smith ◽  
...  
Keyword(s):  
Public Health ◽  
United Kingdom ◽  
Syndromic Surveillance ◽  
Volcanic Ash ◽  
Health Impact ◽  
Public Health Impact ◽  
Binary File ◽  
The United Kingdom ◽  
Ash Plume ◽  
Potential Public Health

Binary file ES_Abstracts_Final_ECDC.txt matches

scholarly journals Can Telehealth Ontario respiratory call volume be used as a proxy for emergency department respiratory visit surveillance by public health?

CJEM ◽  
2008 ◽  
Vol 10 (01) ◽  
pp. 18-24 ◽  
Author(s):  
Adam van Dijk ◽  
Don McGuinness ◽  
Elizabeth Rolland ◽  
Kieran M. Moore
Keyword(s):  
Emergency Department ◽  
Time Series ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Time Series Data ◽  
Added Value ◽  
Series Data ◽  
Syndromic Surveillance System ◽  
Respiratory Illnesses ◽  
Call Volume

ABSTRACTObjective:There is a paucity of information regarding the usefulness of non-traditional data streams for real-time syndromic surveillance systems. The objective of this paper is to examine the temporal relation between Ontario's emergency department (ED) visits and telephone health line (Telehealth) call volume for respiratory illnesses to test the feasibility of using Ontario's Telehealth system for real-time surveillance.Methods:Retrospective time-series data from the National Ambulatory Care Reporting System (NACRS) and the Telehealth Ontario program from June 1, 2004, to March 31, 2006, were analyzed. The added value of Telehealth Ontario data was determined by comparing it temporally with NACRS data, which uses the International Classification of Diseases (ICD) 10-Canadian Enhancement coding system for discharge diagnoses.Results:Telehealth Ontario had 216 105 calls for respiratory complaints, while 819 832 ICD-coded complaints from NACRS were identified with a comparable diagnosis of respiratory illness. Telehealth Ontario call volume was heavily weighted for the 0–4 years age group (49%), while the NACRS visits were mainly from those 18–64 years old (44%). The Spearman rank correlation coefficient was calculated to be 0.97, with the time-series analysis also resulting in significant correlations at lags (semi-monthly) 0 and 1, indicating that increases in Telehealth Ontario call volume correlate with increases in NACRS discharge diagnosis data for respiratory illnesses.Conclusion:Telehealth Ontario call volume fluctuation reflects directly on ED respiratory visit data on a provincial basis. These call complaints are a timely, useful and representative data stream that shows promise for integration into a real-time syndromic surveillance system.

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