COVID-19 cluster surveillance using exposure data collected from routine contact tracing: The genomic validation of a novel informatics-based approach to outbreak detection in England.

Contact tracing was used globally to prevent onwards transmission of COVID-19. Tracing contacts alone is unlikely to be sufficient in controlling community transmission, due to the pre-symptomatic, overdispersed and airborne nature of COVID-19 transmission. We describe and demonstrate the validity of a national enhanced contact tracing programme for COVID-19 cluster surveillance in England. Data on cases occurring between October 2020 and September 2021 were extracted from the national contact tracing system. Exposure clusters were identified algorithmically by matching ≥2 cases attending the same event, identified by matching postcode and event category within a 7-day rolling window. Genetic validity was defined as exposure clusters with ≥2 cases from different households with identical viral sequences. Exposure clusters were fuzzy matched to the national incident management system (HPZone) by postcode and setting description. Multivariable logistic regression modelling was used to determine cluster characteristics associated with genetic validity. Over a quarter of a million (269,470) exposure clusters were identified. Of the eligible clusters, 25% (3,306/13,008) were genetically valid. 81% (2684/3306) of these were not recorded on HPZone and were identified on average of one day earlier than incidents recorded on HPZone. Multivariable analysis demonstrated that exposure clusters occurring in workplaces (aOR = 5·10, 95% CI 4·23-6·17) and education (aOR = 3·72, 95% CI 3·08-4·49) settings were those most strongly associated with genetic validity. Cluster surveillance using enhanced contact tracing in England was a timely, comprehensive and systematic approach to the detection of transmission events occurring in community settings. Cluster surveillance can provide intelligence to stakeholders to support the assessment and management of clusters of COVID-19 at a local, regional, and national level. Future systems should include predictive modelling and network analysis to support risk assessment of exposure clusters to improve the effectiveness of enhanced contract tracing for outbreak detection.

Risk of transmission of SARS-CoV-2 on international flights, a retrospective cohort study using national surveillance data in England.

BACKGROUND: It is not yet fully understood to what extent in-flight transmission contributed to the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study aimed to determine the occurrence and extent of SARS-CoV-2 transmission in-flight and assess factors associated with transmission risk to inform future control strategies. METHODS: Retrospective cohort study using data obtained from contact tracing of international flights arriving in England between 02/08/2021-15/10/2021. Transmission risk was estimated by calculating the secondary attack rate (SAR). Univariable and multivariable analyses of the SAR by specific risk factors was undertaken, including: number of in-flight index cases; number of symptomatic index cases; contact vaccination status; flight duration; proximity to the index case(s); contact age. RESULTS: 11,307 index cases linked to 667,849 contacts with 5,289 secondary cases reported. In-flight SAR was 0.79% (95% CI: 0.77-0.81). Increasing numbers of symptomatic cases (when > 4 index cases compared to one index case aOR 1.85; 95% CI: 1.40-2.44) and seating proximity to an index case (seated within compared to outside of two rows OR 1.82; 95% CI: 1.50-2.22) were associated with increased risk of secondary cases. Full vaccination history was protective (aOR 0.52; 95% CI: 0.47-0.57). CONCLUSIONS: This study confirms that in-flight transmission of SARS-CoV-2 occurred. There are factors associated with increased risk of infection. Contact tracing identified exposed persons who subsequently developed infection. A targeted approach to contact tracing passengers with the highest exposure risk could be an effective use of limited public health resources.

Evaluating the impact on health outcomes of an event that resulted in a delay in contact tracing of COVID-19 cases in England, September 2020: an observational study.

OBJECTIVE: In September 2020, 15 861 SARS-CoV-2 case records failed to upload from the Second Generation Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, delaying the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on population health outcomes: transmission events, hospitalisations and mortality. Previously, a modelling study suggested a substantial impact. DESIGN: Observational study. SETTING: England. POPULATION: Individuals testing positive for SARS-CoV-2 and their reported contacts. MAIN OUTCOME MEASURES: Secondary attack rates (SARs), hospitalisations and deaths among primary and secondary contacts were calculated, compared with all other concurrent, unaffected cases. Affected SGSS records were matched to CTAS records. Successive contacts and cases were identified and matched to hospital episode and mortality outcomes. RESULTS: Initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared with the control group (3 days). This was associated with lower completion of contact tracing: 80% (95% CI: 79% to 81%) in delay group and 83% (95% CI: 83% to 84%) in control group. There was some evidence to suggest increased transmission to non-household contacts among those affected by the delay. The SAR for non-household contacts was higher among secondary contacts in the delay group than the control group (delay group: 7.9%, 95% CI: 6.5% to 9.2%; control group: 5.9%, 95% CI: 5.3% to 6.6%). There did not appear to be a significant difference between the delay and control groups in the odds of hospitalisation (crude OR: 1.1 (95% CI: 0.9 to 1.2)) or death (crude OR: 0.7 (95% CI: 0.1 to 4.0)) among secondary contacts. CONCLUSIONS: Our analysis suggests that the delay in contact tracing had a limited impact on population health outcomes; however, contact tracing was not completed for all individuals, so some transmission events might not be captured.

Epidemiology of Early Monkeypox Virus Transmission in Sexual Networks of Gay and Bisexual Men, England, 2022.

After community transmission of monkeypox virus was identified in Europe, interviews of 45 case-patients from England indicated transmission in international sexual networks of gay and bisexual men since April 2022. Interventions targeting sex-on-premises venues, geospatial dating applications, and sexual health services are likely to be critical for outbreak control.

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.

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.

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.

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.

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.

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

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

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

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

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 .

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.

A scoping review of the use of Twitter for public health research.

Public health practitioners and researchers have used traditional medical databases to study and understand public health for a long time. Recently, social media data, particularly Twitter, has seen some use for public health purposes. Every large technological development in history has had an impact on the behaviour of society. The advent of the internet and social media is no different. Social media creates public streams of communication, and scientists are starting to understand that such data can provide some level of access into the people's opinions and situations. As such, this paper aims to review and synthesize the literature on Twitter applications for public health, highlighting current research and products in practice. A scoping review methodology was employed and four leading health, computer science and cross-disciplinary databases were searched. A total of 755 articles were retreived, 92 of which met the criteria for review. From the reviewed literature, six domains for the application of Twitter to public health were identified: (i) Surveillance; (ii) Event Detection; (iii) Pharmacovigilance; (iv) Forecasting; (v) Disease Tracking; and (vi) Geographic Identification. From our review, we were able to obtain a clear picture of the use of Twitter for public health. We gained insights into interesting observations such as how the popularity of different domains changed with time, the diseases and conditions studied and the different approaches to understanding each disease, which algorithms and techniques were popular with each domain, and more.

The epidemiology and management of clusters of invasive meningococcal disease in England, 2010-15.

BACKGROUND: Guidance for public health management of invasive meningococcal disease (IMD) in in England recommends the use of antibiotic chemoprophylaxis and vaccination. We summarized clinical and epidemiological data collected during routine management of IMD clusters in England. METHODS: Data on epidemiology and operational decisions for public health management were reviewed for clusters between April 2010 and December 2015. RESULTS: Clusters were generally 2-3 cases (53/58; 91%) within a single age band <18-years. Nurseries (n = 20, 34%), households/social networks (n = 14, 24%) and schools (n = 10, 17%) were the commonest settings. Chemoprophylaxis alone was used in 36 (58%) clusters, including most serogroup B clusters (31/41; 76%). Chemoprophylaxis and vaccination was used in a further 20 (32%) clusters. Vaccine was delivered promptly (<7 days). Four clusters had cases with onset post-chemoprophylaxis; no clusters recorded cases with onset post-vaccination. No pattern was observed between interventions and setting/population at risk, and interventions were consistent with national guidance. Challenges to management included logistical issues related to intervention delivery. CONCLUSIONS: Public health management of IMD clusters presents challenges in decision-making and implementation of interventions. Nonetheless, few cases were observed following intervention. Responses were consistent with national guidance. A systematic data collection tool should be developed to support future evaluation.

Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance.

We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to assess its ability to augment existing syndromic surveillance efforts and give a better understanding of symptomatic people who do not seek healthcare advice directly. We focus on a specific syndrome-asthma/difficulty breathing. We outline data collection using the Twitter streaming API as well as analysis and pre-processing of the collected data. Even with keyword-based data collection, many of the tweets collected are not be relevant because they represent chatter, or talk of awareness instead of an individual suffering a particular condition. In light of this, we set out to identify relevant tweets to collect a strong and reliable signal. For this, we investigate text classification techniques, and in particular we focus on semi-supervised classification techniques since they enable us to use more of the Twitter data collected while only doing very minimal labelling. In this paper, we propose a semi-supervised approach to symptomatic tweet classification and relevance filtering. We also propose alternative techniques to popular deep learning approaches. Additionally, we highlight the use of emojis and other special features capturing the tweet's tone to improve the classification performance. Our results show that negative emojis and those that denote laughter provide the best classification performance in conjunction with a simple word-level n-gram approach. We obtain good performance in classifying symptomatic tweets with both supervised and semi-supervised algorithms and found that the proposed semi-supervised algorithms preserve more of the relevant tweets and may be advantageous in the context of a weak signal. Finally, we found some correlation (r = 0.414, p = 0.0004) between the Twitter signal generated with the semi-supervised system and data from consultations for related health conditions.

Monitoring epidemiological trends in back to school asthma among preschool and school-aged children using real-time syndromic surveillance in England, 2012-2016.

BACKGROUND : Back to school (BTS) asthma has been previously reported in children; however, its epidemiology and associated healthcare burden are unclear. We aimed to describe the timing and magnitude of BTS asthma using surveillance data from different health services in England. METHODS : Asthma morbidity data from emergency department attendances and general practitioner (GP) consultations between April 2012 and December 2016 were used from national syndromic surveillance systems in England. Age-specific and sex-specific rates and time series of asthma peaks relative to school term dates were described. The timing of a BTS excess period and adjusted rates of asthma relative to a baseline period were estimated using cumulative sum control chart plots and negative binomial regression. RESULTS : BTS asthma among children aged below 15 years was most pronounced at the start of the school year in September. This effect was not present among those aged 15 years and above. After controlling for sex and study year, the adjusted daily rate of childhood GP in-hours asthma consultations was 2.5-3 times higher in the BTS excess period, with a significantly higher effect among children aged 0-4 years. A distinct age-specific pattern of sex differences in asthma presentations was present, with a higher burden among males in children and among females aged over 15 years. CONCLUSION: We found evidence of a BTS asthma peak in children using surveillance data across a range of healthcare systems, supporting the need for further preventative work to reduce the impact of BTS asthma in children.