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.

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.

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.

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.

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.

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

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.

Can syndromic surveillance help forecast winter hospital bed pressures in England?

BACKGROUND: Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions. METHODS: We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included. RESULTS: We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models. CONCLUSION: Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity.

Comparison of statistical algorithms for daily syndromic surveillance aberration detection.

MOTIVATION: Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the 'rising activity, multilevel mixed effects, indicator emphasis' (RAMMIE) method and the improved quasi-Poisson regression-based method known as 'Farrington Flexible' both currently used at Public Health England, and the 'Early Aberration Reporting System' (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data. RESULTS: We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2-3 days earlier. AVAILABILITY AND IMPLEMENTATION: R codes developed for this project are available through https://github.com/FelipeJColon/AlgorithmComparison. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study.

Major sporting events may influence attendance levels at hospital emergency departments (ED). Previous research has focussed on the impact of single games, or wins/losses for specific teams/countries, limiting wider generalisations. Here we explore the impact of the Euro 2016 football championships on ED attendances across four participating nations (England, France, Northern Ireland, Wales), using a single methodology. Match days were found to have no significant impact upon daily ED attendances levels. Focussing upon hourly attendances, ED attendances across all countries in the four hour pre-match period were statistically significantly lower than would be expected (OR 0.97, 95% CI 0.94-0.99) and further reduced during matches (OR 0.94, 95% CI 0.91-0.97). In the 4 hour post-match period there was no significant increase in attendances (OR 1.01, 95% CI 0.99-1.04). However, these impacts were highly variable between individual matches: for example in the 4 hour period following the final, involving France, the number of ED attendances in France increased significantly (OR 1.27, 95% CI 1.13-1.42). Overall our results indicate relatively small impacts of major sporting events upon ED attendances. The heterogeneity observed makes it difficult for health providers to predict how major sporting events may affect ED attendances but supports the future development of compatible systems in different countries to support cross-border public health surveillance.

A methodological framework for the evaluation of syndromic surveillance systems: a case study of England.

BACKGROUND: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. METHODS: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. RESULTS: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. CONCLUSIONS: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.

Estimating primary care attendance rates for fever in infants after meningococcal B vaccination in England using national syndromic surveillance data.

BACKGROUND: In September 2015, the United Kingdom became the first country to introduce the multicomponent group B meningococcal vaccine (4CMenB) into a national infant immunisation programme. In early clinical trials 51-61% of infants developed a fever when 4CMenB was administered with other routine vaccines. Whilst administration of prophylactic paracetamol is advised, up to 3% of parents may seek medical advice for fever following vaccination. We used research-level general practitioner consultations to identify any increase in attendances for all-cause fever in vaccine-eligible infants following 4CMenB introduction in England. METHODS: Consultations for infant all-cause fever in the year following the vaccine introduction were identified from The Phoenix Partnership (TPP) ResearchOne general practice database using Read (CTV3) codes. Average daily consultation rates and incidence rate ratios (IRRs) were calculated for vaccine-eligible age groups and compared to the two years preceding vaccine introduction. The difference between pre- and post-vaccine all-cause fever consultations was estimated. RESULTS: All-cause fever consultations in vaccine-eligible 7-10 week olds were 1.6-fold higher (IRR, 1.58; 95% CI, 1.22-2.05) compared to the two previous years and 1.5-fold higher (IRR 1.47; 95% CI, 1.17-1.86) in 15-18 week-olds. There were no significant differences in 0-6 or 11-14 week-olds. Applying the difference between pre- and post-vaccine consultation rates to the 4CMenB vaccine-eligible age groups across England estimated 1825 additional fever consultations in the year following 4CMenB introduction. CONCLUSIONS: We found a small but significant difference in all-cause fever consultation rates in vaccine-eligible infants who would have received 4CMenB with other vaccines.

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

Introduction The 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/Problem Is an Ambulance Data Syndromic Surveillance System (ADSSS) feasible and of utility in enhancing the existing suite of PHE syndromic surveillance systems? METHODS: An 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. RESULTS: The 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. CONCLUSIONS: Further 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. Todkill D , Loveridge P , Elliot AJ , Morbey RA , Edeghere O , Rayment-Bishop T , Rayment-Bishop C , Thornes JE , Smith G . 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.

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?

Introduction In 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/Problem The 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. METHODS: The 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. RESULTS: Very 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). CONCLUSIONS: Syndromic 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. Todkill D , Hughes HE , Elliot AJ , Morbey RA , Edeghere O , Harcourt S , Hughes T , Endericks T , McCloskey B , Catchpole M , Ibbotson S , Smith G . 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.

The application of a novel 'rising activity, multi-level mixed effects, indicator emphasis' (RAMMIE) method for syndromic surveillance in England.

MOTIVATION: Syndromic surveillance is the real-time collection and interpretation of data to allow the early identification of public health threats and their impact, enabling public health action. The 'rising activity, multi-level mixed effects, indicator emphasis' method was developed to provide a single robust method enabling detection of unusual activity across a wide range of syndromes, nationally and locally. RESULTS: The method is shown here to have a high sensitivity (92%) and specificity (99%) compared to previous methods, whilst halving the time taken to detect increased activity to 1.3 days. AVAILABILITY AND IMPLEMENTATION: The method has been applied successfully to syndromic surveillance systems in England providing realistic models for baseline activity and utilizing prioritization rules to ensure a manageable number of 'alarms' each day. CONTACT: roger.morbey@phe.gov.uk.

Assessing the Likely Impact of a Rotavirus Vaccination Program in England: The Contribution of Syndromic Surveillance.

BACKGROUND: In July 2013, a rotavirus vaccination program for 2- to 3-month-olds was introduced in the United Kingdom. We present an initial impact analysis of this new vaccine program using national syndromic surveillance systems. METHODS: General practitioner (GP) in-hours, GP out-of-hours, and emergency department (ED) syndromic surveillance systems were used to monitor GP consultations and ED visits for gastroenteritis, diarrhea, and vomiting. Data were stratified by age group and compared between pre- and postvaccine-year rotavirus seasons. Incidence rate ratios (IRRs) and percentage ratios were calculated for GP in-hours consultations and GP out-of-hours and ED data, respectively. RESULTS: There was a significant reduction in gastroenteritis, diarrhea, and vomiting GP in-hours consultations in children aged 0-4 years when comparing the rotavirus season in the pre- and postvaccine years (P < .001 for all indicators). IRRs illustrated a 26%-33% and 23%-31% decrease in gastroenteritis incidence in the <1 and 1-4 years age groups, respectively, across the syndromic surveillance systems. There was also an 8% decrease recorded in the 5-14 years age group in the GP in-hours and ED systems. CONCLUSIONS: Syndromic surveillance revealed a marked decline in gastroenteritis, coinciding with the introduction of the new rotavirus vaccine program in England. The largest reduction in disease was observed in infants, although some impact was also demonstrated in children aged 1-4 and 5-14 years, suggesting possible herd protection in older age groups. This study was limited to the first postvaccine year, and further analysis is required to assess the longer-term impact of the vaccine.

Development and refinement of new statistical methods for enhanced syndromic surveillance during the 2012 Olympic and Paralympic Games.

Prior to the 2012 London Olympic and Paralympic Games, new statistical methods had to be developed for the enhanced syndromic surveillance during the Games. Different methods were developed depending on whether or not historical data were available. Practical solutions were needed to cope with the required daily reporting and data quality issues. During the Games, nearly 4800 signals were tested on average each day, generating statistical alarms that were assessed to provide information on areas of potential public health concern and reassurance that no major adverse incident had occurred. GRAPHICAL ABSTRACT: spjhi;21/2/159/FIG41460458213517577 F1 fig4-1460458213517577.