Using a novel 'difference-in-differences' method and syndromic surveillance to estimate the change in local healthcare utilisation during periods of media reporting in the early stages of the COVID-19 pandemic in England.

OBJECTIVES: Syndromic surveillance supplements traditional laboratory reporting for infectious diseases monitoring. Prior to widespread COVID-19 community surveillance, syndromic surveillance was one of several systems providing real-time information on changes in healthcare-seeking behaviour. The study objective was to identify changes in healthcare utilisation during periods of high local media reporting in England using 'difference-in-differences' (DiD). STUDY DESIGN: A retrospective observational study was conducted using five media events in January-February 2020 in England on four routinely monitored syndromic surveillance indicators. METHODS: Dates 'exposed' to a media event were estimated using Google Trends internet search intensity data (terms = 'coronavirus' and local authority [LA]). We constructed a negative-binomial regression model for each indicator and event time period to estimate a direct effect. RESULTS: We estimated a four-fold increase in telehealth 'cough' calls and a 1.4-fold increase in emergency department (ED) attendances for acute respiratory illness in Brighton and Hove, when a so-called 'superspreading event' in this location was reported in local and national media. Significant decreases were observed in the Buxton (telehealth and ED attendance) and Wirral (ED attendance) areas during media reports of a returnee from an outbreak abroad and a quarantine site opening in the area respectively. CONCLUSIONS: We used a novel approach to directly estimate changes in syndromic surveillance reporting during the early phase of the COVID-19 pandemic in England, providing contextual information on the interpretation of changes in health indicators. With careful consideration of event timings, DiD is useful in producing real-time estimates on specific indicators for informing public health action.

Clinical characteristics, attendance outcomes and deaths of homeless persons in the emergency department: implications for primary health care and community prevention programmes.

OBJECTIVES: Persons experiencing homelessness (PEH) are known to be often excluded from primary health care and community prevention programmes leading to high use of hospital emergency departments (EDs). This study aimed to identify demographic features, clinical characteristics and attendance outcomes of PEH presenting to ED. STUDY DESIGN: Analysis of routinely collected data set. METHODS: Clinical presentations and drug prescription data of PEH who presented a major ED in the West Midlands region of England from 2014 to 2019 were extracted and analysed using descriptive and inferential statistics. RESULTS: During the study period, 3271 of 596,198 presentations were made by PEH; 74% PEH attendees were male. Drug- and alcohol-related conditions, as well as pain and injury constituted the most frequent reasons for presentation, contributing to over half of all presentations. A significantly higher proportion of males (n = 481, 20.3%) presented with drug and alcohol problems than females (n = 93, 11.2%) (P ≤ 0.001). However, pain was the primary reason for presentation for twice as many female patients (n = 189, 22.8%) compared with males (n = 305, 12.9%) (P < 0.001). Nearly one in five left the ED before being assessed and a total of 39 patients (1.2%) died in the ED and 785 (24.0%) required in-patient admissions to the same hospital. CONCLUSIONS: Drug, alcohol and pain including the need of opioid analgesics constituted the majority of presentations made by PEH in ED. The observed rate of death of PEH in ED is 12 times higher than the general population. A very high proportion of PEH also leave the ED before being treated. Future research should focus on strengthening community interventions, particularly to improve access to those at risk of dual diagnoses of substance misuse and mental health problems. Interventions involving multisector collaborations are needed to improve seamless discharge from ED and minimise repeat attendance. Gender differences in the nature of presentations and ED outcomes needs to be investigated further.

Machine learning to refine decision making within a syndromic surveillance service.

BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. METHODS: A record of the risk assessment process was obtained from Public Health England for all 67,505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final 'Decision' outcome made by an epidemiologist of 'Alert', 'Monitor' or 'No-action'. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of 'No-action' outcomes. RESULTS: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of 'Alert' outcomes. If the 'Alert' and 'Monitor' actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. CONCLUSIONS: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process.

Developing influenza and respiratory syncytial virus activity thresholds for syndromic surveillance in England.

Influenza and respiratory syncytial virus (RSV) are common causes of respiratory tract infections and place a burden on health services each winter. Systems to describe the timing and intensity of such activity will improve the public health response and deployment of interventions to these pressures. Here we develop early warning and activity intensity thresholds for monitoring influenza and RSV using two novel data sources: general practitioner out-of-hours consultations (GP OOH) and telehealth calls (NHS 111). Moving Epidemic Method (MEM) thresholds were developed for winter 2017-2018. The NHS 111 cold/flu threshold was breached several weeks in advance of other systems. The NHS 111 RSV epidemic threshold was breached in week 41, in advance of RSV laboratory reporting. Combining the use of MEM thresholds with daily monitoring of NHS 111 and GP OOH syndromic surveillance systems provides the potential to alert to threshold breaches in real-time. An advantage of using thresholds across different health systems is the ability to capture a range of healthcare-seeking behaviour, which may reflect differences in disease severity. This study also provides a quantifiable measure of seasonal RSV activity, which contributes to our understanding of RSV activity in advance of the potential introduction of new RSV vaccines.

Monitoring telehealth vomiting calls as a potential public health early warning system for seasonal norovirus activity in Ontario, Canada.

Norovirus is a predominant cause of infectious gastroenteritis in countries worldwide [1-5]. It accounts for approximately 50% of acute gastroenteritis (AGE) and >90% of viral gastroenteritis outbreaks [6, 7]. The incubation period ranges between 10 and 48 h and illness duration is generally 1-3 days with self-limiting symptoms; however, this duration is often longer (e.g. 4-6 days) in vulnerable populations such as hospital patients or young children [2, 8]. Symptomatic infection of norovirus presents as acute vomiting, diarrhoea, abdominal cramps and nausea, with severe vomiting and diarrhoea (non-bloody) being most common [2, 5, 9].

Estimating the burden on general practitioner services in England from increases in respiratory disease associated with seasonal respiratory pathogen activity.

Understanding the burden of respiratory pathogens on health care is key to improving public health emergency response and interventions. In temperate regions, there is a large seasonal rise in influenza and other respiratory pathogens. We have examined the associations between individual pathogens and reported respiratory tract infections to estimate attributable burden. We used multiple linear regression to model the relationship between doctor consultation data and laboratory samples from week 3 2011 until week 37 2015. We fitted separate models for consultation data with in-hours and out-of-hours doctor services, stratified by different age bands. The best fitting all ages models (R2 > 80%) for consultation data resulted in the greatest burden being associated with influenza followed by respiratory syncytial virus (RSV). For models of adult age bands, there were significant associations between consultation data and invasive Streptococcus pneumoniae. There were also smaller numbers of consultations significantly associated with rhinovirus, parainfluenza, and human metapneumovirus. We estimate that a general practice with 10 000 patients would have seen an additional 18 respiratory tract infection consultations per winter week of which six had influenza and four had RSV. Our results are important for the planning of health care services to minimise the impact of winter pressures. •Respiratory pathogen incidence explains over 80% of seasonal variation in respiratory consultation data.•Influenza and RSV are associated with the biggest seasonal rises in respiratory consultation counts.•A third of consultation counts associated with respiratory pathogens were due to influenza.

The burden of seasonal respiratory infections on a national telehealth service in England.

Seasonal respiratory illnesses present a major burden on primary care services. We assessed the burden of respiratory illness on a national telehealth system in England and investigated the potential for providing early warning of respiratory infection. We compared weekly laboratory reports for respiratory pathogens with telehealth calls (NHS 111) between week 40 in 2013 and week 29 in 2015. Multiple linear regression was used to identify which pathogens had a significant association with respiratory calls. Children aged <5 and 5-14 years, and adults over 65 years were modelled separately as were time lags of up to 4 weeks between calls and laboratory specimen dates. Associations with respiratory pathogens explained over 83% of the variation in cold/flu, cough and difficulty breathing calls. Based on the first two seasons available, the greatest burden was associated with respiratory syncytial virus (RSV) and influenza, with associations found in all age bands. The most sensitive signal for influenza was calls for 'cold/flu', whilst for RSV it was calls for cough. The best-fitting models showed calls increasing a week before laboratory specimen dates. Daily surveillance of these calls can provide early warning of seasonal rises in influenza and RSV, contributing to the national respiratory surveillance programme.

Developing and validating a new national remote health advice syndromic surveillance system in England.

Background: Public Health England (PHE) coordinates a suite of real-time national syndromic surveillance systems monitoring general practice, emergency department and remote health advice data. We describe the development and informal evaluation of a new syndromic surveillance system using NHS 111 remote health advice data. Methods: NHS 111 syndromic indicators were monitored daily at national and local level. Statistical models were applied to daily data to identify significant exceedances; statistical baselines were developed for each syndrome and area using a multi-level hierarchical mixed effects model. Results: Between November 2013 and October 2014, there were on average 19 095 NHS 111 calls each weekday and 43 084 each weekend day in the PHE dataset. There was a predominance of females using the service (57%); highest percentage of calls received was in the age group 1-4 years (14%). This system was used to monitor respiratory and gastrointestinal infections over the winter of 2013-14, the potential public health impact of severe flooding across parts of southern England and poor air quality episodes across England in April 2014. Conclusions: This new system complements and supplements the existing PHE syndromic surveillance systems and is now integrated into the routine daily processes that form this national syndromic surveillance service.

Association between glycaemic control and common infections in people with Type 2 diabetes: a cohort study.

AIM: To investigate the impact of glycaemic control on infection incidence in people with Type 2 diabetes. METHODS: We compared infection rates during 2014 in people with Type 2 diabetes and people without diabetes in a large primary care cohort in the UK (the Royal College of General Practitioners Research and Surveillance Centre database). We performed multilevel logistic regression to investigate the impact of Type 2 diabetes on presentation with infection, and the effect of glycaemic control on presentation with upper respiratory tract infections, bronchitis, influenza-like illness, pneumonia, intestinal infectious diseases, herpes simplex, skin and soft tissue infections, urinary tract infections, and genital and perineal infections. People with Type 2 diabetes were stratified by good [HbA1c < 53 mmol/mol (< 7%)], moderate [HbA1c 53-69 mmol/mol (7-8.5%)] and poor [HbA1c > 69 mmol/mol (> 8.5%)] glycaemic control using their most recent HbA1c concentration. Infection incidence was adjusted for important sociodemographic factors and patient comorbidities. RESULTS: We identified 34 278 people with Type 2 diabetes and 613 052 people without diabetes for comparison. The incidence of infections was higher in people with Type 2 diabetes for all infections except herpes simplex. Worsening glycaemic control was associated with increased incidence of bronchitis, pneumonia, skin and soft tissue infections, urinary tract infections, and genital and perineal infections, but not with upper respiratory tract infections, influenza-like illness, intestinal infectious diseases or herpes simplex. CONCLUSIONS: Almost all infections analysed were more common in people with Type 2 diabetes. Infections that are most commonly of bacterial, fungal or yeast origin were more frequent in people with worse glycaemic control.

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

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

What is the utility of using syndromic surveillance systems during large subnational infectious gastrointestinal disease outbreaks? An observational study using case studies from the past 5 years in England.

Syndromic surveillance systems in England have demonstrated utility in the early identification of seasonal gastrointestinal illness (GI) tracking its spatio-temporal distribution and enabling early public health action. There would be additional public health utility if syndromic surveillance systems could detect or track subnational infectious disease outbreaks. To investigate using syndromic surveillance for this purpose we retrospectively identified eight large GI outbreaks between 2009 and 2014 (four randomly and four purposively sampled). We then examined syndromic surveillance information prospectively collected by the Real-time Syndromic Surveillance team within Public Health England for evidence of possible outbreak-related changes. None of the outbreaks were identified contemporaneously and no alerts were made to relevant public health teams. Retrospectively, two of the outbreaks - which happened at similar times and in proximal geographical locations - demonstrated changes in the local trends of relevant syndromic indicators and exhibited a clustering of statistical alarms, but did not warrant alerting local health protection teams. Our suite of syndromic surveillance systems may be more suited to their original purposes than as means of detecting or monitoring localized, subnational GI outbreaks. This should, however, be considered in the context of this study's limitations; further prospective work is needed to fully explore the use of syndromic surveillance for this purpose. Provided geographical coverage is sufficient, syndromic surveillance systems could be able to provide reassurance of no or minor excess healthcare systems usage during localized GI incidents.

Emergency department syndromic surveillance providing early warning of seasonal respiratory activity in England.

Seasonal respiratory infections place an increased burden on health services annually. We used a sentinel emergency department syndromic surveillance system to understand the factors driving respiratory attendances at emergency departments (EDs) in England. Trends in different respiratory indicators were observed to peak at different points during winter, with further variation observed in the distribution of attendances by age. Multiple linear regression analysis revealed acute respiratory infection and bronchitis/bronchiolitis ED attendances in patients aged 1-4 years were particularly sensitive indicators for increasing respiratory syncytial virus activity. Using near real-time surveillance of respiratory ED attendances may provide early warning of increased winter pressures in EDs, particularly driven by seasonal pathogens. This surveillance may provide additional intelligence about different categories of attendance, highlighting pressures in particular age groups, thereby aiding planning and preparation to respond to acute changes in EDs, and thus the health service in general.

Polystyrene as a model system to probe the impact of ambient gas chemistry on polymer surface modifications using remote atmospheric pressure plasma under well-controlled conditions.

An atmospheric pressure plasma jet (APPJ) was used to treat polystyrene (PS) films under remote conditions where neither the plume nor visible afterglow interacts with the film surface. Carefully controlled conditions were achieved by mounting the APPJ inside a vacuum chamber interfaced to a UHV surface analysis system. PS was chosen as a model system as it contains neither oxygen nor nitrogen, has been extensively studied, and provides insight into how the aromatic structures widespread in biological systems are modified by atmospheric plasma. These remote treatments cause negligible etching and surface roughening, which is promising for treatment of sensitive materials. The surface chemistry was measured by X-ray photoelectron spectroscopy to evaluate how ambient chemistry, feed gas chemistry, and plasma-ambient interaction impact the formation of specific moieties. A variety of oxidized carbon species and low concentrations of NOx species were measured after APPJ treatment. In the remote conditions used in this work, modifications are not attributed to short-lived species, e.g., O atoms. It was found that O3 does not correlate with modifications, suggesting that other long-lived species such as singlet delta oxygen or NOx are important. Indeed, surface-bound NO3 was observed after treatment, which must originate from gas phase NOx as neither N nor O are found in the pristine film. By varying the ambient and feed gas chemistry to produce O-rich and O-poor conditions, a possible correlation between the oxygen and nitrogen composition was established. When oxygen is present in the feed gas or ambient, high levels of oxidation with low concentrations of NO3 on the surface were observed. For O-poor conditions, NO and NO2 were measured, suggesting that these species contribute to the oxidation process, but are easily oxidized when oxygen is present. That is, surface oxidation limits and competes with surface nitridation. Overall, surface oxidation takes place easily, but nitridation only occurs under specific conditions with the overall nitrogen content never exceeding 3%. Possible mechanisms for these processes are discussed. This work demonstrates the need to control plasma-ambient interactions and indicates a potential to take advantage of plasma-ambient interactions to fine-tune the reactive species output of APP sources, which is required for specialized applications, including polymer surface modifications and plasma medicine.

Internet-based remote health self-checker symptom data as an adjuvant to a national syndromic surveillance system.

Syndromic surveillance is an innovative surveillance tool used to support national surveillance programmes. Recent advances in the use of internet-based health data have demonstrated the potential usefulness of these health data; however, there have been limited studies comparing these innovative health data to existing established syndromic surveillance systems. We conducted a retrospective observational study to assess the usefulness of a national internet-based 'symptom checker' service for use as a syndromic surveillance system. NHS Direct online data were extracted for 1 August 2012 to 1 July 2013; a time-series analysis on the symptom categories self-reported by online users was undertaken and compared to existing telehealth syndromic data. There were 3·37 million online users of the internet-based self-checker compared to 1·43 million callers to the telephone triage health service. There was a good correlation between the online and telephone triage data for a number of syndromic indicators including cold/flu, difficulty breathing and eye problems; however, online data appeared to provide additional early warning over telephone triage health data. This assessment has illustrated some potential benefit of using internet-based symptom-checker data and provides the basis for further investigating how these data can be incorporated into national syndromic surveillance programmes.

Self-sampling for community respiratory illness: a new tool for national virological surveillance.

This report aims to evaluate the usefulness of self-sampling as an approach for future national surveillance of emerging respiratory infections by comparing virological data from two parallel surveillance schemes in England. Nasal swabs were obtained via self-administered sampling from consenting adults (≥ 16 years-old) with influenza symptoms who had contacted the National Pandemic Flu Service (NPFS) health line during the 2009 influenza pandemic. Equivalent samples submitted by sentinel general practitioners participating in the national influenza surveillance scheme run jointly by the Royal College of General Practitioners (RCGP) and Health Protection Agency were also obtained. When comparable samples were analysed there was no significant difference in results obtained from self-sampling and clinician-led sampling schemes. These results demonstrate that self-sampling can be applied in a responsive and flexible manner, to supplement sentinel clinician-based sampling, to achieve a wide spread and geographically representative way of assessing community transmission of a known organism.

Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes.

General Practitioner consultation rates for influenza-like illness (ILI) are monitored through several geographically distinct schemes in the UK, providing early warning to government and health services of community circulation and intensity of activity each winter. Following on from the 2009 pandemic, there has been a harmonization initiative to allow comparison across the distinct existing surveillance schemes each season. The moving epidemic method (MEM), proposed by the European Centre for Disease Prevention and Control for standardizing reporting of ILI rates, was piloted in 2011/12 and 2012/13 along with the previously proposed UK method of empirical percentiles. The MEM resulted in thresholds that were lower than traditional thresholds but more appropriate as indicators of the start of influenza virus circulation. The intensity of the influenza season assessed with the MEM was similar to that reported through the percentile approach. The MEM pre-epidemic threshold has now been adopted for reporting by each country of the UK. Further work will continue to assess intensity of activity and apply standardized methods to other influenza-related data sources.

Detection of varying influenza circulation within England in 2012/13: informing antiviral prescription and public health response.

BACKGROUND: Subnational variation of 2009 pandemic influenza activity in England has been reported; however, little work has been published on this topic for seasonal influenza. If variation is present, this knowledge may assist with both identifying the onset of influenza epidemics, informing community antiviral prescription and local health planning. METHODS: An end-of-season analysis of influenza surveillance systems (acute respiratory outbreaks, primary care consultations, virological testing, influenza-confirmed secondary care admissions and excess all-cause mortality) was undertaken at national and subnational levels for 2012/13 when influenza B and A(H3N2) dominated. RESULTS: National community antiviral prescription was recommended in Week 51 following national threshold exceedance. However, this was preceded up to 2 weeks by subnational influenza activity in 2/9 regions in England. Regional variation in circulation of influenza subtypes was observed and severe influenza surveillance data sources were able to monitor the subnational impact. CONCLUSIONS: Evidence of virological activity in two or more regions above a threshold indicated the onset of the 2012/13 season. Subnational thresholds should be determined and evaluated in order to improve timeliness of the national antiviral alert. During the season, outputs should be reported at levels that can inform local public health responses and variation considered when retrospectively evaluating the impact of interventions.

The Cold Weather Plan evaluation: an example of pragmatic evidence-based policy making?

OBJECTIVES: An evaluation of the Cold Weather Plan (CWP) for England 2011-2012 was undertaken in April 2012 to generate the basis for further revisions. It is widely considered good practice to formulate and revise policy on the basis of the best available evidence. This paper examines whether the evaluation is an example of pragmatic evidence-based policy-making. STUDY DESIGN: A process evaluation with a formative multimethods approach. METHODS: An electronic survey and national workshop were conducted alongside the production of a number of summary reports from the Health Protection Agency surveillance systems and Met Office meteorological data. The Department of Health and the Met Office were consulted on how the evaluation recommendations shaped the revised CWP and Met Office Cold Weather Alerting System respectively. RESULTS: The Cold Weather Plan survey had 442 responses, a majority from Local Authorities, and from all regions of England. Thematic analysis generated qualitative data, which along with feedback from the workshop were synthesized into six main recommendations. Reviewing the new CWP and the Met Office Cold Weather Alerting System revealed significant modifications on the basis of the evaluation. CONCLUSIONS: The evaluation sets the context for cold weather and health during the 2011-2012 winter. This study shows that the CWP 2012-2013 was revised on the basis of the national evaluation recommendations and is an example of pragmatic evidence-based policy-making.

Using an Emergency Department Syndromic Surveillance System to investigate the impact of extreme cold weather events.

This report describes the development of novel syndromic cold weather public health surveillance indicators for use in monitoring the impact of extreme cold weather on attendances at EDs, using data from the 2010-11 and 2011-12 winters. A number of new surveillance indicators were created specifically for the identification and monitoring of cold weather related ED attendances, using the diagnosis codes provided for each attendance in the Emergency Department Syndromic Surveillance System (EDSSS), the first national syndromic surveillance system of its kind in the UK. Using daily weather data for the local area, a time series analysis to test the sensitivity of each indicator to cold weather was undertaken. Diagnosis codes relating to a health outcome with a potential direct link to cold weather were identified and assigned to a number of 'cold weather surveillance indicators'. The time series analyses indicated strong correlations between low temperatures and cold indicators in nearly every case. The strongest fit with temperature was cold related fractures in females, and that of snowfall was cold related fractures in both sexes. Though currently limited to a small number of sentinel EDs, the EDSSS has the ability to give near real-time detail on the magnitude of the impact of weather events. EDSSS cold weather surveillance fits well with the aims of the Cold Weather Plan for England, providing information on those particularly vulnerable to cold related health outcomes severe enough to require emergency care. This timely information aids those responding to and managing the effects on human health, both within the EDs themselves and in the community as a whole.

Uptake and impact of a new live attenuated influenza vaccine programme in England: early results of a pilot in primary school-age children, 2013/14 influenza season.

As part of the introduction and roll-out of a universal childhood live-attenuated influenza vaccination programme, 4­11 year-olds were vaccinated in seven pilot areas in England in the 2013/14 influenza season. This paper presents the uptake and impact of the programme for a range of disease indicators. End-of-season uptake was defined as the number of children in the target population who received at least one dose of influenza vaccine. Between week 40 2013 and week 15 2014, cumulative disease incidence per 100,000 population (general practitioner consultations for influenza-like illness and laboratory-confirmed influenza hospitalisations), cumulative influenza swab positivity in primary and secondary care and cumulative proportion of emergency department respiratory attendances were calculated. Indicators were compared overall and by age group between pilot and non-pilot areas. Direct impact was defined as reduction in cumulative incidence based on residence in pilot relative to non-pilot areas in 4­11 year-olds. Indirect impact was reduction between pilot and non-pilot areas in <4 year-olds and >11 year-olds. Overall vaccine uptake of 52.5% (104,792/199,475) was achieved. Although influenza activity was low, a consistent, though not statistically significant, decrease in cumulative disease incidence and influenza positivity across different indicators was seen in pilot relative to non-pilot areas in both targeted and non-targeted age groups, except in older age groups, where no difference was observed for secondary care indicators.