Did anonymity in self-administered questionnaires improve disclosure of sensitive information during the 2022 mpox outbreak in England? An observational study.

BACKGROUND: Between May 6, 2022, and Jan 16, 2023, 3555 mpox cases were reported in England, predominantly in gay, bisexual, and other men who have sex with men. Initially, the UK Health Security agency administered questionnaires to laboratory-detected cases via telephone calls. From June, 2022, cases were requested by text or email to complete the questionnaire online, with optional anonymous completion. To inform future approaches, we assess whether anonymity improved disclosure of sensitive information. METHODS: In this observational study we analysed questionnaire data completed by people with a laboratory-detected case of mpox. We included questionnaires that were completed from May 25, 2022, to Jan 16, 2023, and restricted them to anonymous or identifiable self-completed responses. Questionnaires with forename, surname, and birth date, or an ID emailed to participants, which therefore could link to laboratory data, were considered identifiable. Questionnaires without any personal identifiable information were considered anonymous. We compared the responses to seven sensitive risk factor or exposure questions using Pearson's χ2. FINDINGS: All 3555 people diagnosed with mpox infection in England were invited to complete the questionnaire through either phone call or web link.We obtained 1075 (30%) completed questionnaires, with a response rate decreasing from 45% in May to 20% in July 2022. We included 531 self-completed questionnaires in this analysis, of which 259 (49%) were anonymous and 272 (51%) were identifiable. The median age of participants was 39 years, with 514 (97%) men, 12 (2%) women, and five (1%) other. The largest ethnic groups were white (79%; n=422) and mixed or multiple ethnic groups (9%; n=47). Results of all seven questions were similar: 98% (n=254/259) of anonymous and 97% (n=265/272) of identifiable cases answered all seven questions, 49% (n=127) and 54% (n=147) reported a sexually transmitted infection diagnosis in the past 12 months (p=0·2), 24% (n=63) and 27% (n=73) reported ten or more sexual partners in the past 3 months (p=0·8), and 15% (n=38) and 18% (n=50) reported knowing another person with mpox infection (p=0·5), respectively. INTERPRETATION: Transitioning to self-completed questionnaires resulted in reduced uptake, although optional anonymity possibly prevented a steeper drop. Anonymity did not appear to affect reporting of sensitive information, specifically of sexual behaviours or history associated with mpox risk, which reinforces results of previous literature. Our interpretation is limited, however, by relatively low questionnaire uptake, and by only analysing reported rather than true risk. The decision to implement anonymous questionnaires should therefore weigh the potential benefits of increased uptake against the disadvantage of restricted data linkage. FUNDING: None.

Emergency department attendances and inpatient admissions due to mpox infection, England, 2022.

OBJECTIVES: In 2022, a global outbreak of mpox was reported. In the UK, it predominantly affected gay, bisexual and men who have sex with men (GBMSM). The study objectives were to describe the impact of the mpox outbreak on healthcare service usage in England in 2022, particularly emergency department (ED) attendance, inpatient admission and a number of bed days. Additionally, we wanted to explore whether pre-exposure prophylaxis (PrEP) usage, as a marker of condomless anal intercourse, which increases the risk of sexually transmitted infections associated with compromised skin integrity, was associated with higher ED attendance or hospital attendance. METHODS: Data on adult males with laboratory-confirmed mpox were linked with hospital records and described. Using routinely collected data and self-reported exposure data (including PrEP usage) from surveillance questionnaires, multinomial regression was used to estimate adjusted relative risk ratios (aRRRs) with 95% CIs for ED attendance and hospital admission compared with those not admitted. RESULTS: Among 3542 adult males with mpox during May to December 2022, 544 (15.4%) attended ED and 202 (5.7%) were admitted to the hospital. London had the most cases (2393, 68.7%), ED attendances (391, 71.9%) and hospital admissions (121, 59.9%). In multinomial regression, we found strong evidence that compared with people living with HIV, the aRRR for hospital admissions was higher in those not using PrEP (6.9 (95% CI 2.3 to 20.6) vs 4.9 (95% CI 1.7 to 14.1)). The aRRR for ED attendance was 0.63 (95% CI 0.36 to 1.1) for those not using PrEP versus 0.49 (95% CI 0.31 to 0.79). CONCLUSIONS: This outbreak had a considerable impact on health services, particularly in high-incidence areas. Commissioners of sexual and healthcare services should review plans for healthcare provision for similar sexually transmitted infection or novel outbreaks among GBMSM or naïve populations in the future. Further studies are needed to confirm and identify reasons for the higher likelihood of hospital admission seen for GBMSM without HIV infection.

Influence of SARS-CoV-2 surveillance outputs produced by the UK health security agency (UKHSA) outbreak surveillance team on decision-making by local stakeholders.

BACKGROUND: The UK Health Security Agency (UKHSA) COVID-19 Outbreak Surveillance Team (OST) was established in June 2020 to provide Local Authorities (LAs) in England with surveillance intelligence to aid their response to the SARS-CoV-2 epidemic. Reports were produced using standardised metrics in an automated format. Here we evaluate how the SARS-CoV-2 surveillance reports influenced decision making, how resources evolved and how they could be refined to meet the requirements of stakeholders in the future. METHODS: Public health professionals (n = 2,400) involved in the COVID-19 response from the 316 English LAs were invited to take part in an online survey. The questionnaire covered five themes: (i) report use; (ii) influence of surveillance outputs on local intervention strategies; (iii) timeliness; (iv) current and future data requirements; and (v) content development. RESULTS: Of the 366 respondents to the survey, most worked in public health, data science, epidemiology, or business intelligence. Over 70% of respondents used the LA Report and Regional Situational Awareness Report daily or weekly. The information had been used by 88% to inform decision making within their organisations and 68% considered that intervention strategies had been instituted as a result of these decisions. Examples of changes instigated included targeted communications, pharmaceutical and non-pharmaceutical interventions, and the timing of interventions. Most responders considered that the surveillance content had reacted well to evolving demands. The majority (89%) said that their information requirements would be met if the surveillance reports were incorporated into the COVID-19 Situational Awareness Explorer Portal. Additional information suggested by stakeholders included vaccination and hospitalisation data as well as information on underlying health conditions, infection during pregnancy, school absence and wastewater testing. CONCLUSIONS: The OST surveillance reports were a valuable information resource used by local stakeholders in their response to the SARS-CoV-2 epidemic. Control measures that affect disease epidemiology and monitoring requirements need to be considered in the continuous maintenance of surveillance outputs. We identified areas for further development and, since the evaluation, information on repeat infections and vaccination data have been included in the surveillance reports. Furthermore, timeliness of publications has been improved by updating the data flow pathways.

Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study.

BACKGROUND: Norovirus is associated with approximately 18% of the global burden of gastroenteritis and affects all age groups. There is currently no licensed vaccine or available antiviral treatment. However, well-designed early warning systems and forecasting can guide nonpharmaceutical approaches to norovirus infection prevention and control. OBJECTIVE: This study evaluates the predictive power of existing syndromic surveillance data and emerging data sources, such as internet searches and Wikipedia page views, to predict norovirus activity across a range of age groups across England. METHODS: We used existing syndromic surveillance and emerging syndromic data to predict laboratory data indicating norovirus activity. Two methods are used to evaluate the predictive potential of syndromic variables. First, the Granger causality framework was used to assess whether individual variables precede changes in norovirus laboratory reports in a given region or an age group. Then, we used random forest modeling to estimate the importance of each variable in the context of others with two methods: (1) change in the mean square error and (2) node purity. Finally, these results were combined into a visualization indicating the most influential predictors for norovirus laboratory reports in a specific age group and region. RESULTS: Our results suggest that syndromic surveillance data include valuable predictors for norovirus laboratory reports in England. However, Wikipedia page views are less likely to provide prediction improvements on top of Google Trends and Existing Syndromic Data. Predictors displayed varying relevance across age groups and regions. For example, the random forest modeling based on selected existing and emerging syndromic variables explained 60% variance in the ≥65 years age group, 42% in the East of England, but only 13% in the South West region. Emerging data sets highlighted relative search volumes, including "flu symptoms," "norovirus in pregnancy," and norovirus activity in specific years, such as "norovirus 2016." Symptoms of vomiting and gastroenteritis in multiple age groups were identified as important predictors within existing data sources. CONCLUSIONS: Existing and emerging data sources can help predict norovirus activity in England in some age groups and geographic regions, particularly, predictors concerning vomiting, gastroenteritis, and norovirus in the vulnerable populations and historical terms such as stomach flu. However, syndromic predictors were less relevant in some age groups and regions likely due to contrasting public health practices between regions and health information-seeking behavior between age groups. Additionally, predictors relevant to one norovirus season may not contribute to other seasons. Data biases, such as low spatial granularity in Google Trends and especially in Wikipedia data, also play a role in the results. Moreover, internet searches can provide insight into mental models, that is, an individual's conceptual understanding of norovirus infection and transmission, which could be used in public health communication strategies.

Preliminary investigation of a significant national Cryptosporidium exceedance in the United Kingdom, August 2023 and ongoing.

Routine laboratory surveillance has identified an unprecedented and ongoing exceedance of Cryptosporidium spp. across the United Kingdom, notably driven by C. hominis transmission, since 14 August 2023. Information from 477 reported cases in England and Wales, followed up with a standardised exposure questionnaire as of 25 September 2023, identified foreign travel in 250 (54%) of 463 respondents and swimming in 234 (66%) of 353 cases. A significant, common exposure has not yet been identified in first analyses.

Cross-sectional household transmission study of Cryptosporidium shows that C. hominis infections are a key risk factor for spread.

BACKGROUND: Infection with the Cryptosporidium parasite causes over 4000 cases of diagnosed illness (cryptosporidiosis) in England and Wales each year. The incidence of sporadic disease has not been sufficiently established, and how frequently this arises from contact with other infected people is not well documented. This project aimed to explore potential transmission in the home and attempt to identify asymptomatic infections, which might play a role in transmission. Risk factors and characteristics associated with spread of infection in the home were described including any differences between Cryptosporidium species. METHODS: The study identified cryptosporidiosis cases from North West England and Wales over a year and invited them and their household to take part. Each household was sent a study pack containing study information and a questionnaire, and stool sample kits to provide samples from consenting household members. Cryptosporidium-positive stool samples, identified by immunofluorescence microscopy, were characterised using molecular methods to help describe any patterns of transmission. Characteristics of households with and without additional cases were described, and compared using odds ratios (OR) and a multivariable logistic regression identified independent risk factors for household transmission. Data collection ran for one year, beginning in September 2018 with an initial pilot phase. RESULTS: We enrolled 128 index cases and their households. Additional illness occurred in over a quarter of homes, each reporting an average of two additional cases. The majority of these were undiagnosed and unreported to surveillance. This burden was even greater in households where the index case was infected with C. hominis versus C. parvum, or the index case was under five years old, with mums and siblings most at risk of secondary infection. Only having an index case of C. hominis was independently associated with transmission in the multivariable model (OR 4.46; p = 0.01). CONCLUSIONS: Cryptosporidium was a considerable burden in the home. At-risk homes were those where the index was less than five years old and/or infected with C. hominis. Of particular risk were female caregivers and siblings. Hygiene advice should be specifically directed here. This work provides evidence for humans as sources of C. hominis infection and that person-person is a key pathway. We recommend that all stools submitted for the investigation of gastrointestinal pathogens are tested for Cryptosporidium to better capture cases, inclusion of speciation data in routine surveillance, and the consideration of specific clinical advice on prevention for high-risk homes.

Can cases and outbreaks of norovirus in children provide an early warning of seasonal norovirus infection: an analysis of nine seasons of surveillance data in England UK.

BACKGROUND: Children are important transmitters of norovirus infection and there is evidence that laboratory reports in children increase earlier in the norovirus season than in adults. This raises the question as to whether cases and outbreaks in children could provide an early warning of seasonal norovirus before cases start increasing in older, more vulnerable age groups. METHODS: This study uses weekly national surveillance data on reported outbreaks within schools, care homes and hospitals, general practice (GP) consultations for infectious intestinal disease (IID), telehealth calls for diarrhoea and/or vomiting and laboratory norovirus reports from across England, UK for nine norovirus seasons (2010/11-2018/19). Lagged correlation analysis was undertaken to identify lead or lag times between cases in children and those in adults for each surveillance dataset. A partial correlation analysis explored whether school outbreaks provided a lead time ahead of other surveillance indicators, controlling for breaks in the data due to school holidays. A breakpoint analysis was used to identify which surveillance indicator and age group provided the earliest warning of the norovirus season each year. RESULTS: School outbreaks occurred 3-weeks before care home and hospital outbreaks, norovirus laboratory reports and NHS 111 calls for diarrhoea, and provided a 2-week lead time ahead of NHS 111 calls for vomiting. Children provided a lead time ahead of adults for norovirus laboratory reports (+ 1-2 weeks), NHS 111 calls for vomiting (+ 1 week) and NHS 111 calls for diarrhoea (+ 1 week) but occurred concurrently with adults for GP consultations. Breakpoint analysis revealed an earlier seasonal increase in cases among children compared to adults for laboratory, GP and NHS 111 data, with school outbreaks increasing earlier than other surveillance indicators in five out of nine surveillance years. CONCLUSION: These findings suggest that monitoring cases and outbreaks of norovirus in children could provide an early warning of seasonal norovirus infection. However, both school outbreak data and syndromic surveillance data are not norovirus specific and will also capture other causes of IID. The use of school outbreak data as an early warning indicator may be improved by enhancing sampling in community outbreaks to confirm the causative organism.

Public acceptability of a technology-mediated stool sample collection platform to inform community-based surveillance of infectious intestinal disease: a pilot study.

BACKGROUND: In the UK approximately a quarter of the population experience infectious intestinal disease (IID) each year. However, only 2% present to primary care, preventing a true determination of community burden and pathogen aetiology. The aim of this pilot study was to gauge public acceptability of a technology-mediated platform for reporting episodes of IID and for providing stool samples. METHODS: This study employed a cross-sectional online survey design, targeting individuals 16 + years old within Liverpool City Region, UK. Information sought included demographics, comfortability of reporting illness and IID symptoms, willingness to provide stool, and favoured stool-provision method. Univariable logistic regression was used to examine associations between demographic variables and providing a stool sample. Odds ratios (OR) and associated 95% confidence intervals (CIs) were produced. RESULTS: A total of 174 eligible participants completed the survey, with 69% female. The sample was skewed towards younger populations, with 2.9% aged 65 + years. Nearly a third (29%) had a household income of less than £30,000 per annum and 70% had attained a degree or higher. The majority identified as White British (81%) and 11% identified as ethnicities typically grouped Black, Asian and minority ethnic (BAME). Three quarters of participants were either 'Comfortable' or 'Very Comfortable' with reporting illness (75%) and with answering symptom-related questions (79%); 78% reported that they would provide a stool sample. Upon univariable analysis, increasing age - being 55 + (OR 6.28, 95% CI 1.15-117.48), and lower income (OR 2.5, 95% CI 1.02-6.60), was associated with willingness to provide a stool sample. Additionally, respondents identifying as BAME ethnicities and men may be less inclined to provide a stool sample. CONCLUSIONS: This pilot study assessed the acceptability of technology-mediated platforms for reporting IID and provision of stool samples in the community. Respondents were biased towards younger, technologically inclined, more affluent and educated populations. Acceptability for reporting illness and providing a stool sample through technology-mediated platforms was high. While older populations were under-represented, they were more likely to agree to provide a stool sample. Qualitative research is required to better reach older and more deprived populations, and to understand potential age, gender and ethnic differences in compliance with stool sampling.

Transmission dynamics of COVID-19 in household and community settings in the United Kingdom, January to March 2020.

BackgroundHouseholds appear to be the highest risk setting for COVID-19 transmission. Large household transmission studies in the early stages of the pandemic in Asia reported secondary attack rates ranging from 5 to 30%.AimWe aimed to investigate the transmission dynamics of COVID-19 in household and community settings in the UK.MethodsA prospective case-ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. We estimated household secondary attack rates (SAR), serial intervals and individual and household basic reproduction numbers. The incubation period was estimated using known point source exposures that resulted in secondary cases.ResultsWe included 233 households with two or more people with 472 contacts. The overall household SAR was 37% (95% CI: 31-43%) with a mean serial interval of 4.67 days, an R0 of 1.85 and a household reproduction number of 2.33. SAR were lower in larger households and highest when the primary case was younger than 18 years. We estimated a mean incubation period of around 4.5 days.ConclusionsRates of COVID-19 household transmission were high in the UK for ages above and under 18 years, emphasising the need for preventative measures in this setting. This study highlights the importance of the FFX protocol in providing early insights on transmission dynamics.

Community transmission of monkeypox in the United Kingdom, April to May 2022.

Between 7 and 25 May, 86 monkeypox cases were confirmed in the United Kingdom (UK). Only one case is known to have travelled to a monkeypox virus (MPXV) endemic country. Seventy-nine cases with information were male and 66 reported being gay, bisexual, or other men who have sex with men. This is the first reported sustained MPXV transmission in the UK, with human-to-human transmission through close contacts, including in sexual networks. Improving case ascertainment and onward-transmission preventive measures are ongoing.

Enhancing epidemiological surveillance of the emergence of the SARS-CoV-2 Omicron variant using spike gene target failure data, England, 15 November to 31 December 2021.

When SARS-CoV-2 Omicron emerged in 2021, S gene target failure enabled differentiation between Omicron and the dominant Delta variant. In England, where S gene target surveillance (SGTS) was already established, this led to rapid identification (within ca 3 days of sample collection) of possible Omicron cases, alongside real-time surveillance and modelling of Omicron growth. SGTS was key to public health action (including case identification and incident management), and we share applied insights on how and when to use SGTS.

Epidemiological and clinical characteristics of early COVID-19 cases, United Kingdom of Great Britain and Northern Ireland.

OBJECTIVE: To describe the clinical presentation, course of disease and health-care seeking behaviour of the first few hundred cases of coronavirus disease 2019 (COVID-19) in the United Kingdom of Great Britain and Northern Ireland. METHODS: We implemented the World Health Organization's First Few X cases and contacts investigation protocol for COVID-19. Trained public health professionals collected information on 381 virologically confirmed COVID-19 cases from 31 January 2020 to 9 April 2020. We actively followed up cases to identify exposure to infection, symptoms and outcomes. We also collected limited data on 752 symptomatic people testing negative for COVID-19, as a control group for analyses of the sensitivity, specificity and predictive value of symptoms. FINDINGS: Approximately half of the COVID-19 cases were imported (196 cases; 51.4%), of whom the majority had recent travel to Italy (140 cases; 71.4%). Of the 94 (24.7%) secondary cases, almost all reported close contact with a confirmed case (93 cases; 98.9%), many through household contact (37 cases; 39.8%). By age, a lower proportion of children had COVID-19. Most cases presented with cough, fever and fatigue. The sensitivity and specificity of symptoms varied by age, with nonlinear relationships with age. Although the proportion of COVID-19 cases with fever increased with age, for those with other respiratory infections the occurrence of fever decreased with age. The occurrence of shortness of breath also increased with age in a greater proportion of COVID-19 cases. CONCLUSION: The study has provided useful evidence for generating case definitions and has informed modelling studies of the likely burden of COVID-19.

The spatio-temporal distribution of COVID-19 infection in England between January and June 2020.

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application of our results is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.

Human-to-Human Transmission of Monkeypox Virus, United Kingdom, October 2018.

In September 2018, monkeypox virus was transmitted from a patient to a healthcare worker in the United Kingdom. Transmission was probably through contact with contaminated bedding. Infection control precautions for contacts (vaccination, daily monitoring, staying home from work) were implemented. Of 134 potential contacts, 4 became ill; all patients survived.

Consistent high prevalence of undiagnosed blood-borne virus infection in patients attending large urban emergency departments in England.

Understanding local viral hepatitis and HIV epidemiology is essential if WHO elimination targets are to be achieved. We demonstrate a consistently high prevalence of undiagnosed active infection in urban emergency department attendees in England, with variations in local risk groups crucial to informing targeted testing initiatives.

A descriptive epidemiological study of the incidence of newly diagnosed Lyme disease cases in a UK primary care cohort, 1998-2016.

BACKGROUND: Primary care is likely to see the highest number of Lyme disease patients. Despite this, there is limited published data regarding Lyme disease patients accessing primary care in the UK. We aim to describe trends in the incidence of a new diagnosis, and demographics of patients identified in a primary care electronic health database. METHODS: A descriptive epidemiological study of Lyme disease coded patients in UK primary care. 3725 patients coded for Lyme disease during 1998-2016 were identified within The Health Improvement Network (THIN). Incidence rates and the demographics of cases identified were described. Poisson regression was used to analyse socio-demographic characteristics of the cases. RESULTS: There was an increase in annual crude incidence rates, peaking in 2015 at 5.47 (95% CI 4.85-6.14) cases per 100,000 population per year. Multivariable analysis showed there were significant differences in the ages of those affected, incidence of a new diagnosis rose as deprivation levels improved, and that there was a higher incidence of cases living in rural areas compared to urban areas. There was no significant difference between sexes for the UK. Cases were significantly more likely to identify with being white compared to the national population. CONCLUSIONS: An increasing incidence of patients newly coded with Lyme disease related Read codes was identified using data from a UK national primary care database. By comparing these incidence figures with national laboratory-confirmed surveillance data, a multiplication factor of 2.35 (95%CI 1.81-2.88) can be calculated in order to estimate the annual number of cases seen in primary care. The significant socio-demographic variables associated with a Lyme disease diagnosis likely reflect a complex interplay of socio-economic issues, which needs to be further explored. Future work is needed to examine the treatment and management of patients within this database.

Emergency department syndromic surveillance systems: a systematic review.

BACKGROUND: Syndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally. METHODS: We systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases. RESULTS: In total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan). CONCLUSIONS: EDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future. PROSPERO NUMBER: CRD42017069150 .

What proportion of care home outbreaks are caused by norovirus? An analysis of viral causes of gastroenteritis outbreaks in care homes, North East England, 2016-2018.

BACKGROUND: Outbreaks of infectious gastroenteritis are common in care homes for the elderly. Norovirus can cause these outbreaks, but diagnosis is frequently based solely on clinical characteristics. Our objective in this study was to describe the epidemiology of norovirus and other gastrointestinal pathogens in these settings. METHODS: We analysed surveillance data from gastroenteritis outbreaks reported in North East England between 04 July 2016 to 01 July 2018. Stool samples taken during these outbreaks were tested for a range of viral and bacterial pathogens. We described the epidemiology of these outbreaks and explored the characteristics of norovirus outbreaks versus from other viral causes using multivariable logistic regression. RESULTS: From the 566 care home gastroenteritis outbreaks in this study, we found that norovirus was the pathogen most frequently isolated. Norovirus was detected in 64% of outbreaks with a pathogen identified. Sapovirus was found in 13%; rotavirus in 11%. We found that norovirus outbreaks were associated with higher attack rates (aOR 1.03, 95% CI 1.01-1.05) and fewer cases sampled (aOR 0.74, 95% CI 0.60-0.91), compared to outbreaks caused by other viral pathogens. CONCLUSIONS: These results are important as they quantify the contribution of norovirus to gastroenteritis outbreaks in care homes. Given this evidence, we emphasize the importance of non-specific outbreak interventions that can affect the impact of all such outbreaks. We further recommend that these findings are used to inform the implementation strategies of any norovirus-specific interventions such as a norovirus vaccine.

Estimating the burden of care home gastroenteritis outbreaks in England, 2014-2016.

BACKGROUND: Outbreaks of infectious gastroenteritis in care homes are common, with norovirus a frequent cause. In England there is no co-ordinated national surveillance system. We aimed to estimate the burden of these outbreaks. METHODS: Using a generalised linear mixed effects regression model we described the relationship between the observed number of care home outbreaks and covariates. Estimated model parameters were used to infer uplift in the number of outbreaks expected if all areas were subjected to enhanced surveillance. From this we then estimated the total burden of care home gastroenteritis outbreaks in this period. RESULTS: We estimated a total of 14,146 care home gastroenteritis outbreaks in England during 2014-2016; this is 47% higher than the reported total and a rate of 32.4 outbreaks per 100 care homes per year. The median number of outbreaks from the model estimates was 31 (IQR 20-46) compared to 19 (IQR 12-34) reported from routine surveillance. CONCLUSIONS: This estimated care home gastroenteritis burden in England indicates that current surveillance substantially underestimates the number of outbreaks, by almost half. Improving this surveillance could provide better epidemiological knowledge of the burden of norovirus to inform public health policy, particularly with the advent of norovirus vaccines.

Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland.

BACKGROUND: Analysis of social media is an emerging method with potential as a tool for disease surveillance. Twitter may offer a route for surveillance by using tweeting habits as a proxy for disease incidence. Previous work has focused on temporal patterns and have proven to be successful. However, the identification of geographical patterns has been limited by a combination of Twitter's data collection policies and by exploring diseases that have a high prevalence and high levels of awareness with the public. We propose that, by performing a restricted geographical search strategy on a disease with a relatively low incidence, one may be able to explore spatial patterns. Here, Lyme disease in the United Kingdom and the Republic of Ireland is used as a case example. OBJECTIVE: To explore whether the tweeting habits of British and Irish Twitter users matched the known spatio-temporal epidemiology of Lyme disease in these respective countries. METHODS: All Tweets containing the word 'Lyme' were collected between the 1st of July 2017 and the 30th June 2018, restricted by geography (a 375-mile radius around the geographical centre of Great Britain) and by language (English-only tweets). Tweets were removed which referred to locations that included 'Lyme' within their name (e.g. Lyme Regis). Only original tweets were analysed. Daily and monthly time series were created and compared to national Lyme disease surveillance figures. A map of the number of Twitter users tweeting about Lyme disease per 100,000 population per local authority was created. This was formerly compared to national surveillance data for England and Wales using an exploratory spatial data analysis approach. RESULTS: During the study period, 13,757 original tweets containing the word 'Lyme', and excluding place names relating to Lyme, were collected. The mean number of daily tweets was 38 (range: 12-276). There was strong seasonality with the highest number of tweets in the summer, this matched the known epidemiology of Lyme disease. Of the 5212 of users who tweeted about Lyme disease, 51.8% had a user profile location that could be matched to a local authority in the United Kingdom or Republic of Ireland. The mean number of Twitter users tweeting about Lyme disease per 100,000 population per local authority was 3.7. The areas with the highest incidence were south-west England and the Highlands of Scotland. When comparing these figures to English and Welsh Lyme disease surveillance figures they showed a significant positive spatial correlation (p = 0.002). CONCLUSIONS: The tempo-spatial pattern of Twitter users tweeting about Lyme disease matches the known disease epidemiology. The degree of geographical concordance between Twitter users' locations and national surveillance reports, indicate that Twitter has the potential to be used in to identify potential disease hotspots based on the levels of social media 'noise'. There is scope for further work to test the robustness of Twitter as an adjunct 'measure of concern' disease surveillance tool. However, caution must be taken as national media stories can skew data and Twitter users may not provide reliable facts in the data that they share on the platform.