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Characterising the transmission dynamics between various population groups is critical for implementing effective outbreak control measures whilst minimising financial costs and societal disruption. While recent technological and methodological advances have made individual-level transmission chain data increasingly available, it remains unclear how effectively this data can inform group-level transmission patterns, particularly in small, rapidly saturating outbreak settings. We introduce a novel framework that leverages transmission chain data to estimate group transmission assortativity; this quantifies the extent to which individuals transmit within their own group compared to others. Through extensive simulations mimicking nosocomial outbreaks, we assessed the conditions under which our estimator performs effectively and established guidelines for minimal data requirements in small outbreak settings where saturation may occur rapidly. Notably, we demonstrate that detecting and quantifying transmission assortativity is most reliable when at least 30 cases have been observed in each group, before reaching their respective epidemic peaks., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Geismar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ebola virus disease poses a recurring risk to human health. We conducted a systematic review (PROSPERO CRD42023393345) of Ebola virus disease transmission models and parameters published from database inception to July 7, 2023, from PubMed and Web of Science. Two people screened each abstract and full text. Papers were extracted with a bespoke Access database, 10% were double extracted. We extracted 1280 parameters and 295 models from 522 papers. Basic reproduction number estimates were highly variable, as were effective reproduction numbers, likely reflecting spatiotemporal variability in interventions. Random-effect estimates were 15·4 days (95% CI 13·2-17·5) for the serial interval, 8·5 days (7·7-9·2) for the incubation period, 9·3 days (8·5-10·1) for the symptom-onset-to-death delay, and 13·0 days (10·4-15·7) for symptom-onset-to-recovery. Common effect estimates were similar, albeit with narrower CIs. Case-fatality ratio estimates were generally high but highly variable, which could reflect heterogeneity in underlying risk factors. Although a substantial body of literature exists on Ebola virus disease models and epidemiological parameter estimates, many of these studies focus on the west African Ebola epidemic and are primarily associated with Zaire Ebola virus, which leaves a key gap in our knowledge regarding other Ebola virus species and outbreak contexts., Competing Interests: Declaration of interests AC reports payment from Pfizer for teaching mathematical modelling of infectious diseases. PD reports payment from WHO for consulting on integrated modelling. AC was supported by the Academy of Medical Sciences Springboard scheme (reference SBF005\1044). CM acknowledges the Schmidt Foundation for research funding (grant code 6–22–63345). PD and TN received funding from Community Jameel. DJ has received funding from the Wellcome Trust and Royal Society (216427/Z/19/Z) and PhD funding from Engineering and Physical Sciences Research Council. GC-D has received funding from the Royal Society. RM has received funding from the National Institute for Health and Care Research Health Protection Research Unit in Emerging and Zoonotic Infections, a partnership between the UK Health Security Agency, University of Oxford, University of Liverpool, and Liverpool School of Tropical Medicine (grant code NIHR200907). JW has received research funding from the Wellcome Trust (grant 102169/Z/13/Z). RKN and DN have received research funding from the Medical Research Council Doctoral Training Partnership (grant MR/N014103/1). KM acknowledges research funding from the Imperial College President's PhD Scholarship. AF acknowledges funding from the commonwealth scholarship commission. KF acknowledges funding from the Bill & Melinda Gates Foundation, Gavi, and the Wellcome Trust. HJTU has received funding from the Moderna Charitable Foundation. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

The 2023 Marburg virus disease outbreaks in Equatorial Guinea and Tanzania highlighted the importance of better understanding this lethal pathogen. We did a systematic review (PROSPERO CRD42023393345) of peer-reviewed articles reporting historical outbreaks, modelling studies, and epidemiological parameters focused on Marburg virus disease. We searched PubMed and Web of Science from database inception to March 31, 2023. Two reviewers evaluated all titles and abstracts with consensus-based decision making. To ensure agreement, 13 (31%) of 42 studies were double-extracted and a custom-designed quality assessment questionnaire was used for risk of bias assessment. We present detailed information on 478 reported cases and 385 deaths from Marburg virus disease. Analysis of historical outbreaks and seroprevalence estimates suggests the possibility of undetected Marburg virus disease outbreaks, asymptomatic transmission, or cross-reactivity with other pathogens, or a combination of these. Only one study presented a mathematical model of Marburg virus transmission. We estimate an unadjusted, pooled total random effect case fatality ratio of 61·9% (95% CI 38·8-80·6; I 2 =93%). We identify epidemiological parameters relating to transmission and natural history, for which there are few estimates. This systematic review and the accompanying database provide a comprehensive overview of Marburg virus disease epidemiology and identify key knowledge gaps, contributing crucial information for mathematical models to support future Marburg virus disease epidemic responses., Competing Interests: Declaration of interests AC reports payment from Pfizer for teaching mathematical modelling of infectious diseases. PD reports payment from WHO for consulting on integrated modelling. All other authors declare no competing interests. The views expressed are those of the authors and not necessarily those of the National Institute for Health and Care Research (NIHR), UK Health Security Agency, or the Department of Health and Social Care. NI is currently employed by the Wellcome Trust. However, the Wellcome Trust had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Migrants in the United Kingdom (UK) may be at higher risk of SARS-CoV-2 exposure; however, little is known about their risk of COVID-19-related hospitalisation during waves 1-3 of the pandemic., Methods: We analysed secondary care data linked to Virus Watch study data for adults and estimated COVID-19-related hospitalisation incidence rates by migration status. To estimate the total effect of migration status on COVID-19 hospitalisation rates, we ran mixed-effect Poisson regression for wave 1 (01/03/2020-31/08/2020; wildtype), and mixed-effect negative binomial regressions for waves 2 (01/09/2020-31/05/2021; Alpha) and 3 (01/06/2020-31/11/2021; Delta). Results of all models were then meta-analysed., Results: Of 30,276 adults in the analyses, 26,492 (87.5 %) were UK-born and 3,784 (12.5 %) were migrants. COVID-19-related hospitalisation incidence rates for UK-born and migrant individuals across waves 1-3 were 2.7 [95 % CI 2.2-3.2], and 4.6 [3.1-6.7] per 1,000 person-years, respectively. Pooled incidence rate ratios across waves suggested increased rate of COVID-19-related hospitalisation in migrants compared to UK-born individuals in unadjusted 1.68 [1.08-2.60] and adjusted analyses 1.35 [0.71-2.60]., Conclusion: Our findings suggest migration populations in the UK have excess risk of COVID-19-related hospitalisations and underscore the need for more equitable interventions particularly aimed at COVID-19 vaccination uptake among migrants., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. RB has received funding from Doctors of the World (DOTW) and is the chair of the DOTW Refugee and Migrant Health Research Consortium. YB's spouse is employed by Elsevier as a Software Engineer. The other authors declare no potential conflict of interests., (© 2024 Published by Elsevier Ltd.)

Objectives: The importance of SARS-CoV-2 transmission via the eyes is unknown, with previous studies mainly focusing on protective eyewear in healthcare settings. This study aimed to test the hypothesis that wearing eyeglasses is associated with a lower risk of COVID-19., Methods: Participants from the Virus Watch prospective community cohort study responded to a questionnaire on the use of eyeglasses and contact lenses. Infection was confirmed through data linkage, self-reported positive results, and, for a subgroup, monthly capillary antibody testing. Multivariable logistic regression models, controlling for age, sex, income, and occupation, were used to identify the odds of infection depending on frequency and purpose of eyeglasses or contact lenses use., Results: A total of 19,166 participants responded to the questionnaire, with 13,681 (71.3%, CI 70.7-72.0) reporting they wore eyeglasses. Multivariable logistic regression model showed a 15% lower odds of infection for those who reported using eyeglasses always for general use (odds ratio [OR] 0.85, 95% 0.77-0.95, P = 0.002) compared to those who never wore eyeglasses. The protective effect was reduced for those who said wearing eyeglasses interfered with mask-wearing and was absent for contact lens wearers., Conclusions: People who wear eyeglasses have a moderate reduction in risk of COVID-19 infection, highlighting that eye protection may make a valuable contribution to the reduction of transmission in community and healthcare settings., Competing Interests: Declaration of competing interests ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a Governor of Wellcome Trust from 2011-2018 and is Chair of the Committee for Strategic Coordination for Health of the Public Research., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Understanding how non-household activities contributed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections under different levels of national health restrictions is vital., Methods: Among adult Virus Watch participants in England and Wales, we used multivariable logistic regressions and adjusted-weighted population attributable fractions (aPAF) assessing the contribution of work, public transport, shopping, and hospitality and leisure activities to infections., Results: Under restrictions, among 17,256 participants (502 infections), work [adjusted odds ratio (aOR) 2.01 (1.65-2.44), (aPAF) 30% (22-38%)] and transport [(aOR 1.15 (0.94-1.40), aPAF 5% (-3-12%)], were risk factors for SARS-CoV-2 but shopping, hospitality and leisure were not. Following the lifting of restrictions, among 11,413 participants (493 infections), work [(aOR 1.35 (1.11-1.64), aPAF 17% (6-26%)] and transport [(aOR 1.27 (1.04-1.57), aPAF 12% (2-22%)] contributed most, with indoor hospitality [(aOR 1.21 (0.98-1.48), aPAF 7% (-1-15%)] and leisure [(aOR 1.24 (1.02-1.51), aPAF 10% (1-18%)] increasing. During the Omicron variant, with individuals more socially engaged, among 11,964 participants (2335 infections), work [(aOR 1.28 (1.16-1.41), aPAF (11% (7-15%)] and transport [(aOR 1.16 (1.04-1.28), aPAF 6% (2-9%)] remained important but indoor hospitality [(aOR 1.43 (1.26-1.62), aPAF 20% (13-26%)] and leisure [(aOR 1.35 (1.22-1.48), aPAF 10% (7-14%)] dominated., Conclusions: Work and public transport were important to transmissions throughout the pandemic with hospitality and leisure's contribution increasing as restrictions were lifted, highlighting the importance of restricting leisure and hospitality alongside advising working from home, when facing a highly infectious and virulent respiratory infection., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ and ACH are members of the COVID-19 transmission sub-group of the Scientific Advisory Group for Emergencies (SAGE). AMJ is Chair of the UK Strategic Coordination of Health of the Public Research board and is a member of COVID National Core studies oversight group., (Copyright: © 2023 Hoskins S et al.)

Background: It is poorly understood which workers lack access to sick pay in England and Wales. This evidence gap has been of particular interest in the context of the Covid-19 pandemic given the relationship between presenteeism and infectious disease transmission., Method: This cross-sectional analysis (n = 8874) was nested within a large community cohort study based across England and Wales (Virus Watch). An online survey in February 2021 asked participants in work if they had access to paid sick leave. We used logistic regression to examine sociodemographic factors associated with lacking access to sick pay., Results: Only 66% (n = 5864) of participants reported access to sick pay. South Asian workers (adjusted odds ratio [OR] 1.40, 95% confidence interval [CI] 1.06-1.83) and those from Other minority ethnic backgrounds (OR 2.93, 95% CI 1.54-5.59) were more likely to lack access to sick pay compared to White British workers. Older workers (OR range 1.72 [1.53-1.93]-5.26 [4.42-6.26]), workers in low-income households (OR 2.53, 95% CI 2.15-2.98) and those in transport, trade, and service occupations (OR range 2.03 [1.58-2.61]-5.29 [3.67-7.72]) were also more likely to lack access to sick pay compared respectively to workers aged 25-44, those in high income households and managerial occupations., Discussion: Unwarranted age and ethnic inequalities in sick pay access are suggestive of labour market discrimination. Occupational differences are also cause for concern. Policymakers should consider expanding access to sick pay to mitigate transmission of Covid-19 and other endemic respiratory infections in the community, and in the context of pandemic preparation., (© 2023 The Authors. The International Journal of Health Planning and Management published by John Wiley & Sons Ltd.)

Background: Migrants are over-represented in SARS-CoV-2 infections globally; however, evidence is limited for migrants in England and Wales. Household overcrowding is a risk factor for SARS-CoV-2 infection, with migrants more likely to live in overcrowded households than UK-born individuals. We aimed to estimate the total effect of migration status on SARS-CoV-2 infection and to what extent household overcrowding mediated this effect., Methods: We included a subcohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1 September 2020-30 April 2021) who were aged ≥18 years, self-reported the number of rooms in their household and had no evidence of SARS-CoV-2 infection pre-September 2020. We estimated total, indirect and direct effects using Buis' logistic decomposition regression controlling for age, sex, ethnicity, clinical vulnerability, occupation, income and whether they lived with children., Results: In total, 23 478 individuals were included. 9.07% (187/2062) of migrants had evidence of infection during the study period vs 6.27% (1342/21 416) of UK-born individuals. Migrants had 22% higher odds of infection during the second wave (total effect; OR 1.22, 95% CI 1.01 to 1.47). Household overcrowding accounted for approximately 36% (95% CI -4% to 77%) of these increased odds (indirect effect, OR 1.07, 95% CI 1.03 to 1.12; proportion accounted for: indirect effect on log odds scale/total effect on log odds scale=0.36)., Conclusion: Migrants had higher odds of SARS-CoV-2 infection during the second wave compared with UK-born individuals and household overcrowding explained 36% of these increased odds. Policy interventions to reduce household overcrowding for migrants are needed as part of efforts to tackle health inequalities during the pandemic and beyond., Competing Interests: Competing interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. The other authors declare no potential conflict of interests., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Individuals living in deprived areas in England and Wales undertook essential activities more frequently and experienced higher rates of SARS-CoV-2 infection than less deprived communities during periods of restrictions aimed at controlling the Alpha (B.1.1.7) variant. We aimed to understand whether these deprivation-related differences changed once restrictions were lifted., Methods: Among 11,231 adult Virus Watch Community Cohort Study participants multivariable logistic regressions were used to estimate the relationships between deprivation and self-reported activities and deprivation and infection (self-reported lateral flow or PCR tests and linkage to National Testing data and Second Generation Surveillance System (SGSS)) between August - December 2021, following the lifting of national public health restrictions., Results: Those living in areas of greatest deprivation were more likely to undertake essential activities (leaving home for work (aOR 1.56 (1.33 - 1.83)), using public transport (aOR 1.33 (1.13 - 1.57)) but less likely to undertake non-essential activities (indoor hospitality (aOR 0.82 (0.70 - 0.96)), outdoor hospitality (aOR 0.56 (0.48 - 0.66)), indoor leisure (aOR 0.63 (0.54 - 0.74)), outdoor leisure (aOR 0.64 (0.46 - 0.88)), or visit a hairdresser (aOR 0.72 (0.61 - 0.85))). No statistical association was observed between deprivation and infection (P=0.5745), with those living in areas of greatest deprivation no more likely to become infected with SARS-CoV-2 (aOR 1.25 (0.87 - 1.79)., Conclusion: The lack of association between deprivation and infection is likely due to the increased engagement in non-essential activities among the least deprived balancing the increased work-related exposure among the most deprived. The differences in activities highlight stark disparities in an individuals' ability to choose how to limit infection exposure., Competing Interests: Competing interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ and AH are members of the COVID-19 transmission sub-group of the Scientific Advisory Group for Emergencies (SAGE). AMJ is Chair of the UK Strategic Coordination of Health of the Public Research board and is a member of COVID National Core studies oversight group., (Copyright: © 2023 Hoskins S et al.)

Respiratory viruses that were suppressed through previous lockdowns during the COVID-19 pandemic have recently started to co-circulate with SARS-CoV-2. Understanding the clinical characteristics and symptomatology of different respiratory viral infections can help address the challenges related to the identification of cases and the understanding of SARS-CoV-2 variants' evolutionary patterns. Flu Watch (2006-2011) and Virus Watch (2020-2022) are household community cohort studies monitoring the epidemiology of influenza, respiratory syncytial virus, rhinovirus, seasonal coronavirus, and SARS-CoV-2, in England and Wales. This study describes and compares the proportion of symptoms reported during illnesses infected by common respiratory viruses. The SARS-CoV-2 symptom profile increasingly resembles that of other respiratory viruses as new strains emerge. Increased cough, sore throat, runny nose, and sneezing are associated with the emergence of the Omicron strains. As SARS-CoV-2 becomes endemic, monitoring the evolution of its symptomatology associated with new variants will be critical for clinical surveillance., (© 2023. The Author(s).)

Background: The Omicron B.1.1.529 variant increased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in doubly vaccinated individuals, particularly in the Oxford-AstraZeneca COVID-19 vaccine (ChAdOx1) recipients. To tackle infections, the UK's booster vaccination programmes used messenger ribonucleic acid (mRNA) vaccines irrespective of an individual's primary course vaccine type, and prioritized the clinically vulnerable. These mRNA vaccines included the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) the Moderna COVID-19 vaccine (mRNA-1273). There is limited understanding of the effectiveness of different primary vaccination courses on mRNA booster vaccines against SARs-COV-2 infections and how time-varying confounders affect these evaluations., Methods: Trial emulation was applied to a prospective community observational cohort in England and Wales to reduce time-varying confounding-by-indication driven by prioritizing vaccination based upon age, vulnerability and exposure. Trial emulation was conducted by meta-analysing eight adult cohort results whose booster vaccinations were staggered between 16 September 2021 and 05 January 2022 and followed until 23 January 2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end of study was modelled using Cox proportional hazard models and adjusted for age, sex, minority ethnic status, clinically vulnerability and deprivation., Results: A total of 19 159 participants were analysed, with 11 709 ChAdOx1 primary courses and 7450 BNT162b2 primary courses. Median age, clinical vulnerability status and infection rates fluctuate through time. In mRNA-boosted adults, 7.4% (n = 863) of boosted adults with a ChAdOx1 primary course experienced a SARS-CoV-2 infection compared with 7.7% (n = 571) of those who had BNT162b2 as a primary course. The pooled adjusted hazard ratio (aHR) was 1.01 with a 95% confidence interval (CI) of: 0.90 to 1.13., Conclusion: After an mRNA booster dose, we found no difference in protection comparing those with a primary course of BNT162b2 with those with a ChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Workers across different occupations vary in their risk of SARS-CoV-2 infection, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase., Methods: Data from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR)., Results: Increased risk was seen in nurses (aRR = 1.44, 1.25-1.65; AF = 30%, 20-39%), doctors (aRR = 1.33, 1.08-1.65; AF = 25%, 7-39%), carers (1.45, 1.19-1.76; AF = 31%, 16-43%), primary school teachers (aRR = 1.67, 1.42- 1.96; AF = 40%, 30-49%), secondary school teachers (aRR = 1.48, 1.26-1.72; AF = 32%, 21-42%), and teaching support occupations (aRR = 1.42, 1.23-1.64; AF = 29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020-May 2021) and attenuated later (June-October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves., Conclusions: Occupational differences in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions., (© 2023. The Author(s).)

Background: Evidence suggests that individuals may change adherence to public health policies aimed at reducing the contact, transmission, and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination when they are not fully vaccinated., Objective: We aimed to estimate changes in median daily travel distance of our cohort from their registered addresses before and after receiving a SARS-CoV-2 vaccine., Methods: Participants were recruited into Virus Watch starting in June 2020. Weekly surveys were sent out to participants, and vaccination status was collected from January 2021 onward. Between September 2020 and February 2021, we invited 13,120 adult Virus Watch participants to contribute toward our tracker subcohort, which uses the GPS via a smartphone app to collect data on movement. We used segmented linear regression to estimate the median daily travel distance before and after the first self-reported SARS-CoV-2 vaccine dose., Results: We analyzed the daily travel distance of 249 vaccinated adults. From 157 days prior to vaccination until the day before vaccination, the median daily travel distance was 9.05 (IQR 8.06-10.09) km. From the day of vaccination to 105 days after vaccination, the median daily travel distance was 10.08 (IQR 8.60-12.42) km. From 157 days prior to vaccination until the vaccination date, there was a daily median decrease in mobility of 40.09 m (95% CI -50.08 to -31.10; P<.001). After vaccination, there was a median daily increase in movement of 60.60 m (95% CI 20.90-100; P<.001). Restricting the analysis to the third national lockdown (January 4, 2021, to April 5, 2021), we found a median daily movement increase of 18.30 m (95% CI -19.20 to 55.80; P=.57) in the 30 days prior to vaccination and a median daily movement increase of 9.36 m (95% CI 38.6-149.00; P=.69) in the 30 days after vaccination., Conclusions: Our study demonstrates the feasibility of collecting high-volume geolocation data as part of research projects and the utility of these data for understanding public health issues. Our various analyses produced results that ranged from no change in movement after vaccination (during the third national lock down) to an increase in movement after vaccination (considering all periods, up to 105 days after vaccination), suggesting that, among Virus Watch participants, any changes in movement distances after vaccination are small. Our findings may be attributable to public health measures in place at the time such as movement restrictions and home working that applied to the Virus Watch cohort participants during the study period., (©Vincent Nguyen, Yunzhe Liu, Richard Mumford, Benjamin Flanagan, Parth Patel, Isobel Braithwaite, Madhumita Shrotri, Thomas Byrne, Sarah Beale, Anna Aryee, Wing Lam Erica Fong, Ellen Fragaszy, Cyril Geismar, Annalan M D Navaratnam, Pia Hardelid, Jana Kovar, Addy Pope, Tao Cheng, Andrew Hayward, Robert Aldridge, Virus Watch Collaborative. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 08.03.2023.)

Background: Studies of COVID-19 vaccine effectiveness show increases in COVID-19 cases within 14 days of a first dose, potentially reflecting post-vaccination behaviour changes associated with SARS-CoV-2 transmission before vaccine protection. However, direct evidence for a relationship between vaccination and behaviour is lacking. We aimed to examine the association between vaccination status and self-reported non-household contacts and non-essential activities during a national lockdown in England and Wales., Methods: Participants (n = 1154) who had received the first dose of a COVID-19 vaccine reported non-household contacts and non-essential activities from February to March 2021 in monthly surveys during a national lockdown in England and Wales. We used a case-crossover study design and conditional logistic regression to examine the association between vaccination status (pre-vaccination vs 14 days post-vaccination) and self-reported contacts and activities within individuals. Stratified subgroup analyses examined potential effect heterogeneity by sociodemographic characteristics such as sex, household income or age group., Results: 457/1154 (39.60 %) participants reported non-household contacts post-vaccination compared with 371/1154 (32.15 %) participants pre-vaccination. 100/1154 (8.67 %) participants reported use of non-essential shops or services post-vaccination compared with 74/1154 (6.41 %) participants pre-vaccination. Post-vaccination status was associated with increased odds of reporting non-household contacts (OR 1.65, 95 % CI 1.31-2.06, p < 0.001) and use of non-essential shops or services (OR 1.50, 95 % CI 1.03-2.17, p = 0.032). This effect varied between men and women and different age groups., Conclusion: Participants had higher odds of reporting non-household contacts and use of non-essential shops or services within 14 days of their first COVID-19 vaccine compared to pre-vaccination. Public health emphasis on maintaining protective behaviours during this post-vaccination time period when individuals have yet to develop full protection from vaccination could reduce risk of SARS-CoV-2 infection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Occupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status., Methods: We used data from employed or self-employed adults who provided occupational information as part of the Virus Watch prospective cohort study (n = 19,595) and linked this to study-obtained information about vulnerability-relevant characteristics (age, medical conditions, obesity status) and work-related COVID-19 exposure based on the Job Exposure Matrix. Participant vaccination status for the first, second, and third dose of any COVID-19 vaccine was obtained based on linkage to national records and study records. We calculated proportions and Sison-Glaz multinomial 95% confidence intervals for vaccine uptake by occupation overall, by vulnerability-relevant characteristics, and by job exposure., Findings: Vaccination uptake across occupations ranged from 89-96% for the first dose, 87-94% for the second dose, and 75-86% for the third dose, with transport, trade, service and sales workers persistently demonstrating the lowest uptake. Vulnerable workers tended to demonstrate fewer between-occupational differences in uptake than non-vulnerable workers, although clinically vulnerable transport workers (76%-89% across doses) had lower uptake than several other occupational groups (maximum across doses 86%-96%). Workers with low SARS-CoV-2 exposure risk had higher vaccine uptake (86%-96% across doses) than those with elevated or high risk (81-94% across doses)., Interpretation: Differential vaccination uptake by occupation, particularly amongst vulnerable and highly-exposed workers, is likely to worsen occupational and related socioeconomic inequalities in infection outcomes. Further investigation into occupational and non-occupational factors influencing differential uptake is required to inform relevant interventions for future COVID-19 booster rollouts and similar vaccination programmes., Competing Interests: Declaration of Competing Interests The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group and is a member of the COVID-19 transmission sub-group of the Scientific Advisory Group for Emergencies (SAGE). The other authors report no conflicts of interest.]., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: We aimed to understand which non-household activities increased infection odds and contributed greatest to SARS-CoV-2 infections following the lifting of public health restrictions in England and Wales., Procedures: We undertook multivariable logistic regressions assessing the contribution to infections of activities reported by adult Virus Watch Community Cohort Study participants. We calculated adjusted weighted population attributable fractions (aPAF) estimating which activity contributed greatest to infections., Findings: Among 11 413 participants (493 infections), infection was associated with: leaving home for work (aOR 1.35 (1.11-1.64), aPAF 17%), public transport (aOR 1.27 (1.04-1.57), aPAF 12%), shopping once (aOR 1.83 (1.36-2.45)) vs. more than three times a week, indoor leisure (aOR 1.24 (1.02-1.51), aPAF 10%) and indoor hospitality (aOR 1.21 (0.98-1.48), aPAF 7%). We found no association for outdoor hospitality (1.14 (0.94-1.39), aPAF 5%) or outdoor leisure (1.14 (0.82-1.59), aPAF 1%)., Conclusion: Essential activities (work and public transport) carried the greatest risk and were the dominant contributors to infections. Non-essential indoor activities (hospitality and leisure) increased risk but contributed less. Outdoor activities carried no statistical risk and contributed to fewer infections. As countries aim to 'live with COVID', mitigating transmission in essential and indoor venues becomes increasingly relevant.

Background: The serial interval is a key epidemiological measure that quantifies the time between an infector's and an infectee's onset of symptoms. This measure helps investigate epidemiological links between cases, and is an important parameter in transmission models used to estimate transmissibility and inform control strategies. The emergence of multiple variants of concern (VOC) during the SARS-CoV-2 pandemic has led to uncertainties about potential changes in the serial interval of COVID-19. We estimated the household serial interval of multiple VOC using data collected by the Virus Watch study. This online, prospective, community cohort study followed-up entire households in England and Wales since mid-June 2020., Methods: This analysis included 5842 symptomatic individuals with confirmed SARS-CoV-2 infection among 2579 households from Sept 1, 2020, to Aug 10, 2022. SARS-CoV-2 variant designation was based upon national surveillance data of variant prevalence by date and geographical region. We used a Bayesian framework to infer who infected whom by exploring all transmission trees compatible with the observed dates of symptoms, given assumptions on the incubation period and generation time distributions using the R package outbreaker2., Findings: We characterised the serial interval of COVID-19 by VOC. The mean serial interval was shortest for omicron BA5 (2·02 days; 95% credible interval [CrI] 1·26-2·84) and longest for alpha (3·37 days; 2·52-4·04). The mean serial interval before alpha (wild-type) was 2·29 days (95% CrI 1·39-2·94), 3·11 days (2·28-3·90) for delta, 2·72 days (2·01-3·47) for omicron BA1, and 2·67 days (1·90-3·46) for omicron BA2. We estimated that 17% (95% CrI 5-26) of serial interval values are negative across all variants., Interpretation: Most methods estimating the reproduction number from incidence time series do not allow for a negative serial interval by construction. Further research is needed to extend these methods and assess biases introduced by not accounting for negative serial intervals. To our knowledge, this study is the first to use a Bayesian framework to estimate the serial interval of all major SARS-CoV-2 VOC from thousands of confirmed household cases., Funding: UK Medical Research Council and Wellcome Trust., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Vaccination constitutes the best long-term solution against Coronavirus Disease-2019; however, vaccine-derived immunity may not protect all groups equally, and the durability of protective antibodies may be short. We evaluate Spike-antibody responses following BNT162b2 or ChAdOx1-S vaccination amongst SARS-CoV2-naive adults across England and Wales enrolled in a prospective cohort study (Virus Watch). Here we show BNT162b2 recipients achieved higher peak antibody levels after two doses; however, both groups experience substantial antibody waning over time. In 8356 individuals submitting a sample ≥28 days after Dose 2, we observe significantly reduced Spike-antibody levels following two doses amongst individuals reporting conditions and therapies that cause immunosuppression. After adjusting for these, several common chronic conditions also appear to attenuate the antibody response. These findings suggest the need to continue prioritising vulnerable groups, who have been vaccinated earliest and have the most attenuated antibody responses, for future boosters., (© 2022. The Author(s).)

Objectives: Seroprevalence studies can provide a measure of SARS-CoV-2 cumulative incidence, but a better understanding of spike and nucleocapsid (anti-N) antibody dynamics following infection is needed to assess the longevity of detectability., Methods: Adults aged ≥18 years, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary blood samples, which were tested for spike antibody and anti-N. Participants self-reported vaccination dates and past medical history. Previous polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System linkage data. The primary outcome variables were seropositivity and total anti-N and spike antibody levels after PCR-confirmed infection., Results: A total of 13,802 eligible individuals provided 58,770 capillary blood samples. A total of 537 of these had a previous positive PCR-confirmed SARS-CoV-2 infection within 0-269 days of antibody sample date, among them 432 (80.45%) having a positive anti-N result. Median anti-N levels peaked between days 90 and 119 after PCR results and then began to decline. There is evidence of anti-N waning from 120 days onwards, with earlier waning for females and younger age categories., Conclusion: Our findings suggest that anti-N has around 80% sensitivity for identifying previous COVID-19 infection, and the duration of detectability is affected by sex and age., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

A range of studies globally demonstrate that the effectiveness of SARS-CoV-2 vaccines wane over time, but the total effect of anti-S antibody levels on risk of SARS-CoV-2 infection and whether this varies by vaccine type is not well understood. Here we show that anti-S levels peak three to four weeks following the second dose of vaccine and the geometric mean of the samples is nine fold higher for BNT162b2 than ChAdOx1. Increasing anti-S levels are associated with a reduced risk of SARS-CoV-2 infection (Hazard Ratio 0.85; 95%CIs: 0.79-0.92). We do not find evidence that this antibody relationship with risk of infection varies by second dose vaccine type (BNT162b2 vs. ChAdOx1). In keeping with our anti-S antibody data, we find that people vaccinated with ChAdOx1 had 1.64 times the odds (95% confidence interval 1.45-1.85) of a breakthrough infection compared to BNT162b2. We anticipate our findings to be useful in the estimation of the protective effect of anti-S levels on risk of infection due to Delta. Our findings provide evidence about the relationship between antibody levels and protection for different vaccines and will support decisions on optimising the timing of booster vaccinations and identifying individuals who should be prioritised for booster vaccination, including those who are older, clinically extremely vulnerable, or received ChAdOx1 as their primary course. Our finding that risk of infection by anti-S level does not interact with vaccine type, but that individuals vaccinated with ChAdOx1 were at higher risk of infection, provides additional support for the use of using anti-S levels for estimating vaccine efficacy., (© 2022. The Author(s).)

Background : "Lockdowns" to control serious respiratory virus pandemics were widely used during the coronavirus disease 2019 (COVID-19) pandemic.  However, there is limited information to understand the settings in which most transmission occurs during lockdowns, to support refinement of similar policies for future pandemics.  Methods : Among Virus Watch household cohort participants we identified those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outside the household.  Using survey activity data, we undertook multivariable logistic regressions assessing the contribution of activities on non-household infection risk.  We calculated adjusted population attributable fractions (APAF) to estimate which activity accounted for the greatest proportion of non-household infections during the pandemic's second wave. Results : Among 10,858 adults, 18% of cases were likely due to household transmission.  Among 10,475 participants (household-acquired cases excluded), including 874 non-household-acquired infections, infection was associated with: leaving home for work or education (AOR 1.20 (1.02 - 1.42), APAF 6.9%); public transport (more than once per week AOR 1.82 (1.49 - 2.23), public transport APAF 12.42%); and shopping (more than once per week AOR 1.69 (1.29 - 2.21), shopping APAF 34.56%).  Other non-household activities were rare and not significantly associated with infection. Conclusions: During lockdown, going to work and using public or shared transport independently increased infection risk, however only a minority did these activities.  Most participants visited shops, accounting for one-third of non-household transmission.  Transmission in restricted hospitality and leisure settings was minimal suggesting these restrictions were effective.   If future respiratory infection pandemics emerge these findings highlight the value of working from home, using forms of transport that minimise exposure to others, minimising exposure to shops and restricting non-essential activities., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ and ACH are members of the COVID-19 transmission sub-group of the Scientific Advisory Group for Emergencies (SAGE). AMJ is Chair of the UK Strategic Coordination of Health of the Public Research board and is a member of COVID National Core studies oversight group., (Copyright: © 2022 Hoskins S et al.)

Background: Workplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations across the COVID-19 pandemic in England., Methods: Data were obtained from electronic contact diaries (November 2020-November 2021) submitted by employed/self-employed prospective cohort study participants ( n =4,616). We used mixed models to investigate the effects of occupation and time for: workplace attendance, number of people sharing workspace, time spent sharing workspace, number of close contacts, and usage of face coverings., Findings: Workplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, workspace sharing and close contact increased and usage of face coverings decreased during phases of less stringent restrictions., Interpretation: Major variations in workplace contact patterns and mask use likely contribute to differential COVID-19 risk. Patterns of variation by occupation and restriction phase may inform interventions for future waves of COVID-19 or other respiratory epidemics. Across occupations, increasing workplace contact and reduced face covering usage is concerning given ongoing high levels of community transmission and emergence of variants., Funding: Medical Research Council; HM Government; Wellcome Trust., Competing Interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AJ and AH are members of the COVID-19 transmission sub-group of the Scientific Advisory Group for Emergencies (SAGE). AJ is Chair of the UK Strategic Coordination of Health of the Public Research board and is a member of COVID National Core studies oversight group., (© 2022 The Authors.)

Objectives: Risk of SARS-CoV-2 infection varies across occupations; however, investigation into factors underlying differential risk is limited. We aimed to estimate the total effect of occupation on SARS-CoV-2 serological status, whether this is mediated by workplace close contact, and how exposure to poorly ventilated workplaces varied across occupations., Methods: We used data from a subcohort (n=3775) of adults in the UK-based Virus Watch cohort study who were tested for SARS-CoV-2 anti-nucleocapsid antibodies (indicating natural infection). We used logistic decomposition to investigate the relationship between occupation, contact and seropositivity, and logistic regression to investigate exposure to poorly ventilated workplaces., Results: Seropositivity was 17.1% among workers with daily close contact vs 10.0% for those with no work-related close contact. Compared with other professional occupations, healthcare, indoor trade/process/plant, leisure/personal service, and transport/mobile machine workers had elevated adjusted total odds of seropositivity (1.80 (1.03 to 3.14) - 2.46 (1.82 to 3.33)). Work-related contact accounted for a variable part of increased odds across occupations (1.04 (1.01 to 1.08) - 1.23 (1.09 to 1.40)). Occupations with raised odds of infection after accounting for work-related contact also had greater exposure to poorly ventilated workplaces., Conclusions: Work-related close contact appears to contribute to occupational variation in seropositivity. Reducing contact in workplaces is an important COVID-19 control measure., Competing Interests: Competing interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Differential exposure to public activities may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes but has not been directly investigated. We set out to investigate whether participants in Virus Watch-a large community cohort study based in England and Wales-reported differential exposure to public activities and non-household contacts during the autumn-winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation., Methods: Participants (n=20 120-25 228 across surveys) reported their daily activities during 3 weekly periods in late November 2020, late December 2020 and mid-February 2021. Deprivation was quantified based on participants' residential postcode using English or Welsh Index of Multiple Deprivation quintiles. We used Poisson mixed-effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period., Results: Relative to participants in the least deprived areas, participants in the most deprived areas exhibited elevated risk of exposure to vehicle sharing (adjusted risk ratio (aRR) range across time points: 1.73-8.52), public transport (aRR: 3.13-5.73), work or education outside of the household (aRR: 1.09-1.21), essential shops (aRR: 1.09-1.13) and non-household contacts (aRR: 1.15-1.19) across multiple survey periods., Conclusion: Differential exposure to essential public activities-such as attending workplaces and visiting essential shops-is likely to contribute to inequalities in infection risk and outcomes. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities., Competing Interests: Competing interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. The other authors declare no competing interests., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Understanding symptomatology and accuracy of clinical case definitions for community COVID-19 cases is important for Test, Trace and Isolate (TTI) and future targeting of early antiviral treatment.   Methods: Community cohort participants prospectively recorded daily symptoms and swab results (mainly undertaken through the UK TTI system).  We compared symptom frequency, severity, timing, and duration in test positive and negative illnesses.  We compared the test performance of the current UK TTI case definition (cough, high temperature, or loss of or altered sense of smell or taste) with a wider definition adding muscle aches, chills, headache, or loss of appetite.     Results: Among 9706 swabbed illnesses, including 973 SARS-CoV-2 positives, symptoms were more common, severe and longer lasting in swab positive than negative illnesses.  Cough, headache, fatigue, and muscle aches were the most common symptoms in positive illnesses but also common in negative illnesses. Conversely, high temperature, loss or altered sense of smell or taste and loss of appetite were less frequent in positive illnesses, but comparatively even less frequent in negative illnesses.  The current UK definition had 81% sensitivity and 47% specificity versus 93% and 27% respectively for the broader definition. 1.7-fold more illnesses met the broader case definition than the current definition.  Conclusions: Symptoms alone cannot reliably distinguish COVID-19 from other respiratory illnesses. Adding additional symptoms to case definitions could identify more infections, but with a large increase in the number needing testing and the number of unwell individuals and contacts self-isolating whilst awaiting results., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a Governor of Wellcome Trust from 2011-18 and is Chair of the Committee for Strategic Coordination for Health of the Public Research., (Copyright: © 2022 Fragaszy E et al.)

Introduction: Increased transmissibility of B.1.1.7 variant of concern (VOC) in the UK may explain its rapid emergence and global spread. We analysed data from putative household infector - infectee pairs in the Virus Watch Community cohort study to assess the serial interval of COVID-19 and whether this was affected by emergence of the B.1.1.7 variant. Methods: The Virus Watch study is an online, prospective, community cohort study following up entire households in England and Wales during the COVID-19 pandemic. Putative household infector-infectee pairs were identified where more than one person in the household had a positive swab matched to an illness episode. Data on whether or not individual infections were caused by the B.1.1.7 variant were not available. We therefore developed a classification system based on the percentage of cases estimated to be due to B.1.1.7 in national surveillance data for different English regions and study weeks. Results: Out of 24,887 illnesses reported, 915 tested positive for SARS-CoV-2 and 186 likely 'infector-infectee' pairs in 186 households amongst 372 individuals were identified. The mean COVID-19 serial interval was 3.18 (95%CI: 2.55-3.81, sd=4.36) days. There was no significant difference (p=0.267) between the mean serial interval for VOC hotspots (mean = 3.64 days, (95%CI: 2.55 - 4.73)) days and non-VOC hotspots, (mean = 2.72 days, (95%CI: 1.48 - 3.96)). Conclusions: Our estimates of the average serial interval of COVID-19 are broadly similar to estimates from previous studies and we find no evidence that B.1.1.7 is associated with a change in serial intervals.  Alternative explanations such as increased viral load, longer period of viral shedding or improved receptor binding may instead explain the increased transmissibility and rapid spread and should undergo further investigation., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a Governor of Wellcome Trust from 2011-18 and is Chair of the Committee for Strategic Coordination for Health of the Public Research., (Copyright: © 2021 Geismar C et al.)

Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results: 26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43-4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54-7.15; p-value<0.001) compared with people living in under-occupied houses. Conclusion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a Governor of Wellcome Trust from 2011-18 and is Chair of the Committee for Strategic Coordination for Health of the Public Research. SVK is a member of the UK Government’s Scientific Advisory Group on Emergencies (SAGE) subgroup on ethnicity and co-chair of the Scottish Government’s Expert Reference Group on ethnicity and COVID-19., (Copyright: © 2021 Aldridge RW et al.)

Introduction: Increased transmissibility of B.1.1.7 variant of concern (VOC) in the UK may explain its rapid emergence and global spread. We analysed data from putative household infector - infectee pairs in the Virus Watch Community cohort study to assess the serial interval of COVID-19 and whether this was affected by emergence of the B.1.1.7 variant. Methods: The Virus Watch study is an online, prospective, community cohort study following up entire households in England and Wales during the COVID-19 pandemic. Putative household infector-infectee pairs were identified where more than one person in the household had a positive swab matched to an illness episode. Data on whether or not individual infections were caused by the B.1.1.7 variant were not available. We therefore developed a classification system based on the percentage of cases estimated to be due to B.1.1.7 in national surveillance data for different English regions and study weeks. Results: Out of 24,887 illnesses reported, 915 tested positive for SARS-CoV-2 and 186 likely 'infector-infectee' pairs in 186 households amongst 372 individuals were identified. The mean COVID-19 serial interval was 3.18 (95%CI: 2.55 - 3.81) days. There was no significant difference (p=0.267) between the mean serial interval for VOC hotspots (mean = 3.64 days, (95%CI: 2.55 - 4.73)) days and non-VOC hotspots, (mean = 2.72 days, (95%CI: 1.48 - 3.96)). Conclusions: Our estimates of the average serial interval of COVID-19 are broadly similar to estimates from previous studies and we find no evidence that B.1.1.7 is associated with a change in serial intervals.  Alternative explanations such as increased viral load, longer period of viral shedding or improved receptor binding may instead explain the increased transmissibility and rapid spread and should undergo further investigation., Competing Interests: Competing interests: ACH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a Governor of Wellcome Trust from 2011-18 and is Chair of the Committee for Strategic Coordination for Health of the Public Research., (Copyright: © 2021 Geismar C et al.)

Introduction: The coronavirus (COVID-19) pandemic has caused significant global mortality and impacted lives around the world. Virus Watch aims to provide evidence on which public health approaches are most likely to be effective in reducing transmission and impact of the virus, and will investigate community incidence, symptom profiles and transmission of COVID-19 in relation to population movement and behaviours., Methods and Analysis: Virus Watch is a household community cohort study of acute respiratory infections in England and Wales and will run from June 2020 to August 2021. The study aims to recruit 50 000 people, including 12 500 from minority ethnic backgrounds, for an online survey cohort and monthly antibody testing using home fingerprick test kits. Nested within this larger study will be a subcohort of 10 000 individuals, including 3000 people from minority ethnic backgrounds. This cohort of 10 000 people will have full blood serology taken between October 2020 and January 2021 and repeat serology between May 2021 and August 2021. Participants will also post self-administered nasal swabs for PCR assays of SARS-CoV-2 and will follow one of three different PCR testing schedules based on symptoms., Ethics and Dissemination: This study has been approved by the Hampstead National Health Service (NHS) Health Research Authority Ethics Committee (ethics approval number 20/HRA/2320). We are monitoring participant queries and using these to refine methodology where necessary, and are providing summaries and policy briefings of our preliminary findings to inform public health action by working through our partnerships with our study advisory group, Public Health England, NHS and government scientific advisory panels., Competing Interests: Competing interests: AH serves on the UK New and Emerging Respiratory Virus Threats Advisory Group. AMJ was a governor of Wellcome Trust from 2011 to 2018 and is chair of the Committee for Strategic Coordination for Health of the Public Research., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)