The Epidemiology of Chickenpox in England, 2016-2022: An Observational Study Using General Practitioner Consultations.

Chickenpox is a common childhood disease caused by varicella-zoster virus (VZV). VZV vaccination is not part of the UK childhood immunisation programme, but its potential inclusion is regularly assessed. It is therefore important to understand the ongoing burden of VZV in the community to inform vaccine policy decisions. General practitioner (GP) chickenpox consultations were studied from 1 September 2016 to 9 December 2022. Over the study period, the mean weekly chickenpox consultation rate per 100,000 population in England was 3.4, with a regular peak occurring between weeks 13 and 15. Overall, rates decreased over time, from a mean weekly rate of 5.5 in 2017 to 4.2 in 2019. The highest mean weekly rates were among children aged 1-4 years. There was no typical epidemic peak during the COVID-19 pandemic, but in 2022, rates were proportionally higher among children aged < 1 year old compared to pre-pandemic years. Chickenpox GP consultation rates decreased in England, continuing a longer-term decline in the community. The COVID-19 pandemic impacted rates, likely caused by the introduction of non-pharmaceutical interventions to prevent SARS-CoV-2 transmission. The lasting impact of the interruption of typical disease transmission remains to be seen, but it is important to monitor the chickenpox burden to inform decisions on vaccine programmes.

Comparison of surveillance systems for monitoring COVID-19 in England: a retrospective observational study.

BACKGROUND: During the COVID-19 pandemic, cases were tracked using multiple surveillance systems. Some systems were completely novel, and others incorporated multiple data streams to estimate case incidence and prevalence. How well these different surveillance systems worked as epidemic indicators is unclear, which has implications for future disease surveillance and outbreak management. The aim of this study was to compare case counts, prevalence and incidence, timeliness, and comprehensiveness of different COVID-19 surveillance systems in England. METHODS: For this retrospective observational study of COVID-19 surveillance systems in England, data from 12 surveillance systems were extracted from publicly available sources (Jan 1, 2020-Nov 30, 2021). The main outcomes were correlations between different indicators of COVID-19 incidence or prevalence. These data were integrated as daily time-series and comparisons undertaken using Spearman correlation between candidate alternatives and the most timely (updated daily, clinical case register) and the least biased (from comprehensive household sampling) COVID-19 epidemic indicators, with comparisons focused on the period of Sept 1, 2020-Nov 30, 2021. FINDINGS: Spearman statistic correlations during the full focus period between the least biased indicator (from household surveys) and other epidemic indicator time-series were 0·94 (95% CI 0·92 to 0·95; clinical cases, the most timely indicator), 0·92 (0·90 to 0·94; estimates of incidence generated after incorporating information about self-reported case status on the ZoeApp, which is a digital app), 0·67 (95% CI 0·60 to 0·73, emergency department attendances), 0·64 (95% CI 0·60 to 0·68, NHS 111 website visits), 0·63 (95% CI 0·56 to 0·69, wastewater viral genome concentrations), 0·60 (95% CI 0·52 to 0·66, admissions to hospital with positive COVID-19 status), 0·45 (95% CI 0·36 to 0·52, NHS 111 calls), 0·08 (95% CI -0·03 to 0·18, Google search rank for "covid"), -0·04 (95% CI -0·12 to 0·05, in-hours consultations with general practitioners), and -0·37 (95% CI -0·46 to -0·28, Google search rank for "coronavirus"). Time lags (-14 to +14 days) did not markedly improve these rho statistics. Clinical cases (the most timely indicator) captured a more consistent proportion of cases than the self-report digital app did. INTERPRETATION: A suite of monitoring systems is useful. The household survey system was the most comprehensive and least biased epidemic monitor, but not very timely. Data from laboratory testing, the self-reporting digital app, and attendances to emergency departments were comparatively useful, fairly accurate, and timely epidemic trackers. FUNDING: National Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, a partnership between the UK Health Security Agency, King's College London, and the University of East Anglia.

Machine learning forecasts for seasonal epidemic peaks: Lessons learnt from an atypical respiratory syncytial virus season.

Seasonal peaks in infectious disease incidence put pressures on health services. Therefore, early warning of the timing and magnitude of peak activity during seasonal epidemics can provide information for public health practitioners to take appropriate action. Whilst many infectious diseases have predictable seasonality, newly emerging diseases and the impact of public health interventions can result in unprecedented seasonal activity. We propose a Machine Learning process for generating short-term forecasts, where models are selected based on their ability to correctly forecast peaks in activity, and can be useful during atypical seasons. We have validated our forecasts using typical and atypical seasonal activity, using respiratory syncytial virus (RSV) activity during 2019-2021 as an example. During the winter of 2020/21 the usual winter peak in RSV activity in England did not occur but was 'deferred' until the Spring of 2021. We compare a range of Machine Learning regression models, with alternate models including different independent variables, e.g. with or without seasonality or trend variables. We show that the best-fitting model which minimises daily forecast errors is not the best model for forecasting peaks when the selection criterion is based on peak timing and magnitude. Furthermore, we show that best-fitting models for typical seasons contain different variables to those for atypical seasons. Specifically, including seasonality in models improves performance during typical seasons but worsens it for the atypical seasons.

Understanding the impact of the COVID-19 pandemic response on GI infection surveillance trends in England, January 2020-April 2022.

Stepwise non-pharmaceutical interventions and health system changes implemented as part of the COVID-19 response have had implications on the incidence, diagnosis, and reporting of other communicable diseases. Here, we established the impact of the COVID-19 outbreak response on gastrointestinal (GI) infection trends using routinely collected surveillance data from six national English laboratory, outbreak, and syndromic surveillance systems using key dates of governmental policy to assign phases for comparison between pandemic and historic data. Following decreases across all indicators during the first lockdown (March-May 2020), bacterial and parasitic pathogens associated with foodborne or environmental transmission routes recovered rapidly between June and September 2020, while those associated with travel and/or person-to-person transmission remained lower than expected for 2021. High out-of-season norovirus activity was observed with the easing of lockdown measures between June and October 2021, with this trend reflected in laboratory and outbreak systems and syndromic surveillance indicators. Above expected increases in emergency department (ED) attendances may have reflected changes in health-seeking behaviour and provision. Differential reductions across specific GI pathogens are indicative of the underlying routes of transmission. These results provide further insight into the drivers for transmission, which can help inform control measures for GI infections.

DiD IT?: a differences-in-differences investigation tool to quantify the impact of local incidents on public health using real-time syndromic surveillance health data.

Syndromic surveillance was originally developed to provide early warning compared to laboratory surveillance, but it is increasing used for real-time situational awareness. When a potential threat to public health is identified, a rapid assessment of its impact is required for public health management. When threats are localised, analysis is more complex as local trends need to be separated from national trends and differences compared to unaffected areas may be due to confounding factors such as deprivation or age distributions. Accounting for confounding factors usually requires an in-depth study, which takes time. Therefore, a tool is required which can provide a rapid estimate of local incidents using syndromic surveillance data.Here, we present 'DiD IT?', a new investigation tool designed to measure the impact of local threats to public health. 'DiD IT?' uses a difference-in-differences statistical approach to account for temporal and spatial confounding and provide a direct estimate of impact due to incidents. Temporal confounding differences are estimated by comparing unaffected locations during and outside of exposure periods. Whilst spatial confounding differences are estimated by comparing unaffected and exposed locations outside of the exposure period. Any remaining differences can be considered to be the direct effect of the local incident.We illustrate the potential utility of the tool through four examples of localised health protection incidents in England. The examples cover a range of data sources including general practitioner (GP) consultations, emergency department (ED) attendances and a telehealth call and online health symptom checker; and different types of incidents including, infectious disease outbreak, mass-gathering, extreme weather and an industrial fire. The examples use the UK Health Security Agency's ongoing real-time syndromic surveillance systems to show how results can be obtained in near real-time.The tool identified 700 additional online difficulty breathing assessments associated with a severe thunderstorm, 53 additional GP consultations during a mumps outbreak, 2-3 telehealth line calls following an industrial fire and that there was no significant increase in ED attendances during the G7 summit in 2021.DiD IT? can provide estimates for the direct impact of localised events in real-time as part of a syndromic surveillance system. Thus, it has the potential for enhancing surveillance and can be used to evaluate the effectiveness of extending national surveillance to a more granular local surveillance.

Epidemiology of respiratory syncytial virus in children younger than 5 years in England during the COVID-19 pandemic, measured by laboratory, clinical, and syndromic surveillance: a retrospective observational study.

BACKGROUND: Seasonal epidemics of respiratory syncytial virus (RSV) cause a clinically significant burden of disease among young children. Non-pharmaceutical interventions targeted at SARS-CoV-2 have affected the activity of other respiratory pathogens. We describe changes in the epidemiology of RSV among children younger than 5 years in England since 2020. METHODS: Surveillance data on RSV infections, comprising laboratory-confirmed cases, proportion of positive tests, hospital admissions for RSV-attributable illness, and syndromic indicators for RSV-associated disease (emergency department attendances for acute bronchitis or bronchiolitis, non-emergency health advice telephone service [NHS 111] calls for cough, general practitioner [GP] in-hours consultations for respiratory tract infections, and GP out-of-hours contacts for acute bronchitis or bronchiolitis) were analysed from Dec 29, 2014 to March 13, 2022, for children younger than 5 years. Data were extracted from national laboratory, clinical, and syndromic surveillance systems. Time-series analyses using generalised linear models were used to estimate the effect of non-pharmaceutical interventions targeting SARS-CoV-2 on RSV indicators, with absolute and relative changes calculated by comparing observed and predicted values. FINDINGS: RSV-associated activity was reduced for all RSV indicators during winter 2020-21 in England, with 10 280 (relative change -99·5% [95% prediction interval -100·0 to -99·1]) fewer laboratory-confirmed cases, 22·2 (-99·6%) percentage points lower test positivity, 92 530 (-80·8% [-80·9 to -80·8]) fewer hospital admissions, 96 672 (-73·7% [-73·7 to -73·7]) fewer NHS 111 calls, 2924 (-88·8% [-90·4 to -87·2]) fewer out-of-hours GP contacts, 91 304 (-89·9% [-90·0 to -89·9]) in-hours GP consultations, and 27 486 (-85·3% [-85·4 to -85·2]) fewer emergency department attendances for children younger than 5 years compared with predicted values based on winter seasons before the COVID-19 pandemic. An unprecedented summer surge of RSV activity occurred in 2021, including 11 255 (1258·3% [1178·3 to 1345·8]) extra laboratory-confirmed cases, 11·6 percentage points (527·3%) higher test positivity, 7604 (10·7% [10·7 to 10·8]) additional hospital admissions, 84 425 (124·8% [124·7 to 124·9]) more calls to NHS 111, 409 (39·0% [36·6 to 41·8]) more out-of-hours GP contacts, and 9789 (84·9% [84·5 to 85·4]) more emergency department attendances compared with the predicted values, although there were 21 805 (-34·1% [-34·1 to -34·0]) fewer in-hours GP consultations than expected. Most indicators were also lower than expected in winter 2021-22, although to a lesser extent than in winter 2020-21. INTERPRETATION: The extraordinary absence of RSV during winter 2020-21 probably resulted in a cohort of young children without natural immunity to RSV, thereby raising the potential for increased RSV incidence, out-of-season activity, and health-service pressures when measures to restrict SARS-CoV-2 transmission were relaxed. FUNDING: None.

Estimating the Impact of Air Pollution on Healthcare-Seeking Behaviour by Applying a Difference-in-Differences Method to Syndromic Surveillance Data.

Syndromic surveillance data were used to estimate the direct impact of air pollution on healthcare-seeking behaviour, between 1 April 2012 and 31 December 2017. A difference-in-differences approach was used to control for spatial and temporal variations that were not due to air pollution and a meta-analysis was conducted to combine estimates from different pollution periods. Significant increases were found in general practitioner (GP) out-of-hours consultations, including a 98% increase (2-386, 95% confidence interval) in acute bronchitis and a 16% (3-30) increase in National Health Service (NHS) 111 calls for eye problems. However, the numbers involved are small; for instance, roughly one extra acute bronchitis consultation in a local authority on a day when air quality is poor. These results provide additional information for healthcare planners on the impacts of localised poor air quality. However, further work is required to identify the separate impact of different pollutants.

The Utility of Ambulance Dispatch Call Syndromic Surveillance for Detecting and Assessing the Health Impact of Extreme Weather Events in England.

Extreme weather events present significant global threats to health. The National Ambulance Syndromic Surveillance System collects data on 18 syndromes through chief presenting complaint (CPC) codes. We aimed to determine the utility of ambulance data to monitor extreme temperature events for action. Daily total calls were observed between 01/01/2018−30/04/2019. Median daily 'Heat/Cold' CPC calls during "known extreme temperature" (identified a priori), "extreme temperature"; (within 5th or 95th temperature percentiles for central England) and meteorological alert periods were compared to all other days using Wilcoxon signed-rank test. During the study period, 12,585,084 calls were recorded. In 2018, median daily "Heat/Cold" calls were higher during periods of known extreme temperature: heatwave (16/day, 736 total) and extreme cold weather events (28/day, 339 total) compared to all other days in 2018 (6/day, 1672 total). Median daily "Heat/Cold" calls during extreme temperature periods (16/day) were significantly higher than non-extreme temperature periods (5/day, p < 0.001). Ambulance data can be used to identify adverse impacts during periods of extreme temperature. Ambulance data are a low resource, rapid and flexible option providing real-time data on a range of indicators. We recommend ambulance data are used for the surveillance of presentations to healthcare related to extreme temperature events.

Mental Health Presentations Across Health Care Settings During the First 9 Months of the COVID-19 Pandemic in England: Retrospective Observational Study.

BACKGROUND: The COVID-19 pandemic has resulted in an unprecedented impact on the day-to-day lives of people, with several features potentially adversely affecting mental health. There is growing evidence of the size of the impact of COVID-19 on mental health, but much of this is from ongoing population surveys using validated mental health scores. OBJECTIVE: This study investigated the impact of the pandemic and control measures on mental health conditions presenting to a spectrum of national health care services monitored using real-time syndromic surveillance in England. METHODS: We conducted a retrospective observational descriptive study of mental health presentations (those calling the national medical helpline, National Health Service [NHS] 111; consulting general practitioners [GPs] in and out-of-hours; calling ambulance services; and attending emergency departments) from January 1, 2019, to September 30, 2020. Estimates for the impact of lockdown measures were provided using an interrupted time series analysis. RESULTS: Mental health presentations showed a marked decrease during the early stages of the pandemic. Postlockdown, attendances for mental health conditions reached higher than prepandemic levels across most systems-a rise of 10% compared to that expected for NHS 111 and 21% for GP out-of-hours service-while the number of consultations to GP in-hours service was 13% lower compared to the same time previous year. Increases were observed in calls to NHS 111 for sleep problems. CONCLUSIONS: These analyses showed marked changes in the health care attendances and prescribing for common mental health conditions across a spectrum of health care provision, with some of these changes persisting. The reasons for such changes are likely to be complex and multifactorial. The impact of the pandemic on mental health may not be fully understood for some time, and therefore, these syndromic indicators should continue to be monitored.

Impact of the COVID-19 pandemic on gastrointestinal infection trends in England, February-July 2020.

OBJECTIVE: To establish the impact of the first 6 months of the COVID-19 outbreak response on gastrointestinal (GI) infection trends in England. DESIGN: Retrospective ecological study using routinely collected national and regional surveillance data from seven UK Health Security Agency coordinated laboratory, outbreak and syndromic surveillance systems using key dates of UK governmental policy change to assign phases for comparison between 2020 and historic data. RESULTS: Decreases in GI illness activity were observed across all surveillance indicators as COVID-19 cases began to peak. Compared with the 5-year average (2015-2019), during the first 6 months of the COVID-19 response, there was a 52% decrease in GI outbreaks reported (1544 vs 3208 (95% CI 2938 to 3478)) and a 34% decrease in laboratory confirmed cases (27 859 vs 42 495 (95% CI 40 068 to 44 922)). GI indicators began to rise during the first lockdown and lockdown easing, although all remained substantially lower than historic figures. Reductions in laboratory confirmed cases were observed across all age groups and both sexes, with geographical heterogeneity observed in diagnosis trends. Health seeking behaviour changed substantially, with attendances decreasing prior to lockdown across all indicators. CONCLUSIONS: There has been a marked change in trends of GI infections in the context of the COVID-19 pandemic. The drivers of this change are likely to be multifactorial; while changes in health seeking behaviour, pressure on diagnostic services and surveillance system ascertainment have undoubtably played a role, there has likely been a true decrease in the incidence for some pathogens resulting from the control measures and restrictions implemented. This suggests that if some of these changes in behaviour such as improved hand hygiene were maintained, then we could potentially see sustained reductions in the burden of GI illness.

Spike in Asthma Healthcare Presentations in Eastern England during June 2021: A Retrospective Observational Study Using Syndromic Surveillance Data.

Thunderstorm asthma is often characterised by a sudden surge in patients presenting with exacerbated symptoms of asthma linked to thunderstorm activity. Here, we describe a large spike in asthma and difficulty breathing symptoms observed across parts of England on 17 June 2021. The number of healthcare presentations during the asthma event was compared to expected levels for the overall population and across specific regions. Across affected geographical areas, emergency department attendances for asthma increased by 560% on 17 June compared to the average number of weekday daily attendances during the previous 4 weeks. General practitioner out of hours contacts increased by 349%, National Health Service (NHS) 111 calls 193%, NHS 111 online assessments 581% and ambulance call outs 54%. Increases were particularly noted in patient age groups 5-14 and 15-44 years. In non-affected regions, increases were small (<10%) or decreased, except for NHS 111 online assessments where there was an increase of 39%. A review of the meteorological conditions showed several localised, weak, or moderate thunderstorms specifically across parts of Southeast England on the night of June 16. In this unprecedented episode of asthma, the links to meteorologically defined thunderstorm activity were not as clear as previous episodes, with less evidence of 'severe' thunderstorm activity in those areas affected, prompting further discussion about the causes of these events and implications for public health management of the risk.

Describing the indirect impact of COVID-19 on healthcare utilisation using syndromic surveillance systems.

BACKGROUND: Since the end of January 2020, the coronavirus (COVID-19) pandemic has been responsible for a global health crisis. In England a number of non-pharmaceutical interventions have been introduced throughout the pandemic, including guidelines on healthcare attendance (for example, promoting remote consultations), increased handwashing and social distancing. These interventions are likely to have impacted the incidence of non-COVID-19 conditions as well as healthcare seeking behaviour. Syndromic Surveillance Systems offer the ability to monitor trends in healthcare usage over time. METHODS: This study describes the indirect impact of COVID-19 on healthcare utilisation using a range of syndromic indicators including eye conditions, mumps, fractures, herpes zoster and cardiac conditions. Data from the syndromic surveillance systems monitored by Public Health England were used to describe the number of contacts with NHS 111, general practitioner (GP) In Hours (GPIH) and Out-of-Hours (GPOOH), Ambulance and Emergency Department (ED) services over comparable periods before and during the pandemic. RESULTS: The peak pandemic period in 2020 (weeks 13-20), compared to the same period in 2019, displayed on average a 12% increase in NHS 111 calls, an 11% decrease in GPOOH consultations, and a 49% decrease in ED attendances. In the GP In Hours system, conjunctivitis consultations decreased by 64% and mumps consultations by 31%. There was a 49% reduction in attendance at EDs for fractures, and there was no longer any weekend increase in ED fracture attendances, with similar attendance patterns observed across each day of the week. There was a decrease in the number of ED attendances with diagnoses of myocardial ischaemia. CONCLUSION: The COVID-19 pandemic drastically impacted healthcare utilisation for non-COVID-19 conditions, due to a combination of a probable decrease in incidence of certain conditions and changes in healthcare seeking behaviour. Syndromic surveillance has a valuable role in describing and understanding these trends.

Developing a sentinel syndromic surveillance system using school-absenteeism data, example monitoring absences over the 2020 COVID-19 pandemic.

This study describes the development of a pilot sentinel school absence syndromic surveillance system. Using data from a sample of schools in England the capability of this system to monitor the impact of disease on school absences in school-aged children is shown, using the coronavirus disease 2019 (COVID-19) pandemic period as an example. Data were obtained from an online app service used by schools and parents to report their children absent, including reasons/symptoms relating to absence. For 2019 and 2020, data were aggregated into daily counts of 'total' and 'cough' absence reports. There was a large increase in the number of absence reports in March 2020 compared to March 2019, corresponding to the first wave of the COVID-19 pandemic in England. Absence numbers then fell rapidly and remained low from late March 2020 until August 2020, while lockdown was in place in England. Compared to 2019, there was a large increase in the number of absence reports in September 2020 when schools re-opened in England, although the peak number of absences was smaller than in March 2020. This information can help provide context around the absence levels in schools associated with COVID-19. Also, the system has the potential for further development to monitor the impact of other conditions on school absence, e.g. gastrointestinal infections.

Evaluating multi-purpose syndromic surveillance systems - a complex problem.

Surveillance systems need to be evaluated to understand what the system can or cannot detect. The measures commonly used to quantify detection capabilities are sensitivity, positive predictive value and timeliness. However, the practical application of these measures to multi-purpose syndromic surveillance services is complex. Specifically, it is very difficult to link definitive lists of what the service is intended to detect and what was detected. First, we discuss issues arising from a multi-purpose system, which is designed to detect a wide range of health threats, and where individual indicators, e.g. 'fever', are also multi-purpose. Secondly, we discuss different methods of defining what can be detected, including historical events and simulations. Finally, we consider the additional complexity of evaluating a service which incorporates human decision-making alongside an automated detection algorithm. Understanding the complexities involved in evaluating multi-purpose systems helps design appropriate methods to describe their detection capabilities.

Investigating regional variation of respiratory infections in a general practice syndromic surveillance system.

BACKGROUND: Established surveillance systems can follow trends in community disease and illness over many years. However, within England there are known regional differences in healthcare utilisation, which can affect interpretation of trends. Here, we explore regional differences for a range of respiratory conditions using general practitioner (GP) consultation data. METHODS: Daily data for respiratory conditions were extracted from a national GP surveillance system. Average daily GP consultation rates per 100 000 registered patient population were calculated by each region of England and for each study year (2013-17). Consultation rates and incidence rate ratios were also calculated for each condition by deprivation quintile and by rural, urban, and conurbation groups. RESULTS: Upper and lower respiratory tract infections and asthma were higher in the North and the Midlands than in London and the South, were highest in the most deprived groups and tended to be higher in more urban areas. Influenza-like illness was highest in the least deprived and rural areas. CONCLUSIONS: There are consistent differences in GP consultation rates across the English regions. This work has improved our understanding and interpretation of GP surveillance data at regional level and will guide more accurate public health messages.

Environmental factors associated with general practitioner consultations for allergic rhinitis in London, England: a retrospective time series analysis.

OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186 401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m3, relative risk (RR) 3.33, 95% CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m3, RR 1.69, 95% CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95% CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO2) appeared to be associated with increased consultations (for the category 70-85 µg/m3, RR 1.33, 95% CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20 mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO2 concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.

Demographic and socioeconomic patterns in healthcare-seeking behaviour for respiratory symptoms in England: a comparison with non-respiratory symptoms and between three healthcare services.

OBJECTIVE: This study will analyse respiratory contacts to three healthcare services that capture more of the community disease burden than acute data sources, such as hospitalisations. The objective is to explore associations between contacts to these services and the patient's age, gender and deprivation. Results will be compared between healthcare services, and with non-respiratory contacts to explore how contacts differ by service and illness. It is crucial to investigate the sociodemographic patterns in healthcare-seeking behaviour to enable targeted public health interventions. DESIGN: Ecological study. SETTING: Surveillance of respiratory contacts to three healthcare services in England: telehealth helpline (NHS111); general practitioner in-hours (GPIH); and general practitioner out of hours unscheduled care (GPOOH). PARTICIPANTS: 13 million respiratory contacts to NHS111, GPIH and GPOOH. OUTCOME MEASURES: Respiratory contacts to NHS111, GPIH and GPOOH, and non-respiratory contacts to NHS111 and GPOOH. RESULTS: More respiratory contacts were observed for females, with 1.59, 1.73, and 1.95 times the rate of contacts to NHS111, GPOOH and GPIH, respectively. When compared with 15-44 year olds, there were 37.32, 18.66 and 6.21 times the rate of respiratory contacts to NHS111, GPOOH and GPIH in children <1 year. There were 1.75 and 2.70 times the rate of respiratory contacts in the most deprived areas compared with the least deprived to NHS111 and GPOOH. Elevated respiratory contacts were observed for males <5 years compared with females <5 years. Healthcare-seeking behaviours between respiratory and non-respiratory contacts were similar. CONCLUSION: When contacts to services that capture more of the disease burden are explored, the demographic patterns are similar to those described in the literature for acute systems. Comparable results were observed between respiratory and non-respiratory contacts suggesting that when a wider spectrum of disease is explored, sociodemographic factors may be the strongest influencers of healthcare-seeking behaviour.

Using emergency department syndromic surveillance to investigate the impact of a national vaccination program: A retrospective observational study.

BACKGROUND: Rotavirus infection is a common cause of gastroenteritis in children worldwide, with a high mortality burden in developing countries, particularly during the first two years of life. Rotavirus vaccination was introduced into the United Kingdom childhood vaccination schedule in July 2013, with high coverage (>90%) achieved by June 2016. We used an emergency department (ED) syndromic surveillance system to assess the impact of the rotavirus vaccination programme, specifically through the demonstration of any immediate and continuing impact on ED gastroenteritis visits in England. METHODS: This retrospective, observational study used syndromic surveillance data collected from 3 EDs in the two years before (July 2011-June 2013) and 3 years post (July 2013-June 2016) introduction of rotavirus vaccination. The weekly levels of ED visits for gastroenteritis (by age group and in total) during the period before rotavirus vaccination was first described alongside the findings of laboratory surveillance of rotavirus during the same period. An interrupted time-series analysis was then performed to demonstrate the impact of rotavirus vaccination introduction on gastroenteritis ED visit levels. RESULTS: During the two years before vaccine introduction ED visits for gastroenteritis in total and for the 0-4 years age group were seen to rise and fall in line with the seasonal rotavirus increases reported by laboratory surveillance. ED gastroenteritis visits by young children were lower in the three years following introduction of rotavirus vaccination (reduced from 8% of visits to 6% of visits). These attendance levels in young children (0-4years) remained higher than in older age groups, however the previously large seasonal increases in children were greatly reduced, from peaks of 16% to 3-10% of ED visits per week. CONCLUSIONS: ED syndromic surveillance demonstrated a reduction in gastroenteritis visits following rotavirus vaccine introduction. This work establishes ED syndromic surveillance as a platform for rapid impact assessment of future vaccine programmes.

Adapting Syndromic Surveillance Baselines After Public Health Interventions.

BACKGROUND: Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. METHODS: We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. RESULTS: Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). CONCLUSION: Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.