Tracking COVID-19 in England and Wales: Insights from Virus Watch - a prospective community cohort study (preprint)

BackgroundVirus Watch is a prospective community cohort study of COVID-19 of 28{square},527 households in England and Wales designed to estimate the incidence of PCR-confirmed COVID-19 in those with respiratory presentations and examine symptom profiles and transmission of COVID-19 in relation to population movement and behaviour. The Office for National Statistics (ONS) COVID-19 infection survey (CIS) was the largest regular survey of COVID-19 infections and antibodies in the UK and included 227,797 households. In this analysis, we aimed to compare incidence rate estimates from the two studies to understand differences in estimates from the two study designs. MethodsWe used the Virus Watch prospective community cohort study to estimate the overall SARS-CoV-2 incidence rate and incidence rate by age in England and Wales from June 2020 to February 2023. Virus Watch data consisted of self-reported laboratory COVID-19 test results and linkage to the Second Generation Surveillance System, the UK national database for COVID-19 testing. We compared our findings with modelled incidence rates from ONS CIS using 3-day rolling Pearsons correlation to measure synchrony. Results58,628 participants were recruited into the Virus Watch study between June 2020 and March 2022, of whom 52,526 (90%) were reported to be living in England and 1,532 (2.6%) in Wales. COVID-19 incidence rates were initially similar across age groups until the Delta wave when rates increased at different magnitudes. During the Omicron BA.1, the 0-14 age group had the highest incidence rates, which shifted to the 25-44 age group with Omicron BA.2, 4, and 5 dominance. We found strong synchrony between Virus Watch and ONS CIS COVID-19 incidence estimates for England and Wales, both with and without the incorporation of linked national testing data into the Virus Watch study. In particular, the magnitude and trend of Virus Watch- and ONS-estimated rates for England were generally consistent, although Virus Watch-estimated peaks of infection during the Omicron BA.1 and 2 waves were found to be lower than estimates from the ONS. ConclusionOur findings suggest that the Virus Watch research approach is a low-cost and effective method for on-going surveillance of COVID-19 regardless of the availability of national testing in the UK. Similar approaches can also be utilised by low-resource settings to provide accurate incidence rate estimates to better monitor and respond to COVID-19 as well as other acute respiratory diseases in the future.

Examining the association of live virus neutralisation activity of capillary microsamples and risk of SARS-CoV-2 infections: a nested case control study within the Virus Watch community cohort (preprint)

Due to the proliferation of new SARS-CoV-2 variants, most COVID-19 cases are now caused by post-vaccine infections and a substantial proportion are reinfections. While prior research on correlates of protection has focused on the role of anti-spike antibodies, the results of the corresponding antibody assays may not accurately predict the risk of infection with new SARS-CoV-2 variants. In this study, we investigated the association between live virus neutralising antibody activity and SARS-CoV-2 infection risk using self-administered capillary microsample blood tests from VirusWatch participants. The study was conducted during the transition between the dominance of the B.1.617.2 (Delta) and B.1.1.529 (Omicron BA.1) SARS-CoV-2 variants, enabling us to investigate the association between variant-specific virus inhibition and subsequent infections within each dominance period. Greater inhibition of Omicron BA.1 live virus was associated with a reduction in infection risk during both the Delta and Omicron BA.1 dominance periods. Delta virus inhibition was associated with infection risk reduction during the Delta dominance period, but we found no association between Delta inhibition and protection against infection during the Omicron BA.1 dominance period. Our results are consistent with earlier findings and suggest that variant-specific serosurveillance of immunity and protection against SARS-CoV-2 infection at the population level could inform public health policy in near-real time using inexpensive and accessible home-based testing.

Assessing the causal effect of air pollution on risk of SARS-CoV-2 infection (preprint)

IntroductionEmerging evidence suggests association of air pollution exposure with risk of SARS-CoV-2 infection, but many of these findings are limited by study design, lack of individual-level covariate data or are specific to certain subpopulations. We aim to evaluate causal effects of air pollution on risk of infection, whilst overcoming these limitations. MethodsConcentrations for black carbon(BC), particulate matter 10(PM10), particulate matter 2.5(PM2.5), nitrogen dioxide(NO2) and oxides of nitrogen(NOx) from the Department of Environment, Food and Rural Affairs (DEFRA) and Effect of Low-level Air Pollution: A Study in Europe (ELAPSE) were linked to postcodes of 53,683 Virus Watch study participants. The primary outcome was first SARS-CoV-2 infection, between 1st September 2020 and 30th April 2021. Regression analysis used modified Poisson with robust estimates, clustered by household, adjusting for individual (e.g., age, sex, ethnicity) and environmental covariates(e.g., population density, region) to estimate total and direct effects. ResultsSingle pollutant analysis showed the direct effect of higher risk of SARS-CoV-2 infection with increased exposure to PM2.5(RR1.11,95%CI 1.08;1.15), PM10(RR1.06,95%CI 1.04;1.09), NO2(RR1.04,95%CI 1.04;1.05) and NOx(RR1.02,95%CI 1.02;1.02) per 1{micro}g/m3 increment with DEFRA 2015-19 data. Sensitivity analyses altering covariates, exposure window and modelled air pollution data source produced similar estimates. Higher risk of SARS-CoV-2 per 10-5m-1 increment of BC (RR1.86, 95%CI 1.62;2.14) was observed using ELAPSE data. ConclusionLong term exposure to higher concentrations of air pollutions increases the risk of SARS-CoV-2 infection, highlighting that adverse health effects of air pollution is not only limited to non-communicable diseases.

Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour (preprint)

[bullet] Virus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours. [bullet] 28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022 [bullet] Data collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital. [bullet] Nested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555). [bullet] Study data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.

SARS-CoV-2 infections in migrants and the role of household overcrowding: A causal mediation analysis of Virus Watch data (preprint)

Background: Migrants are over-represented in severe acute respiratory syndrome coronavirus-2 (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 sub-cohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1st September 2020-30th April 2021) who were aged at least 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% (187/2,062) of migrants had evidence of infection during the study period versus 6.27% (1,342/21,416) of UK-born individuals. Migrants had 22% higher odds of infection during the second wave (total effect; OR:1.22, 95%CI:1.01-1.47). Household overcrowding accounted for approximately 32% of these increased odds (indirect effect, OR:1.07, 95%CI:1.03-1.12; proportion accounted for: indirect effect[7]/total effect[22]=0.32). Conclusion: Migrants had higher odds of SARS-CoV-2 infection during the second wave compared with UK-born individuals and household overcrowding explained 32% 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.

Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study (preprint)

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.

Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort (preprint)

Abstract Importance The Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individual's primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters. Objective To evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders. Design Trial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation. Setting Prospective observational study using the Virus Watch community cohort in England and Wales. Participants People over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity. Exposures ChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine. Results Across eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course. Conclusion and Relevance In mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.

Comparative effectiveness of ChAdOx1 versus BNT162b2 vaccines against SARS-CoV-2 infections in England and Wales: A cohort analysis using trial emulation in the Virus Watch community data (preprint)

Introduction: Infections of SARS-CoV-2 in vaccinated individuals have been increasing globally. Understanding the associations between vaccine type and a post-vaccination infection could help prevent further COVID-19 waves. In this paper, we use trial emulation to understand the impact of a phased introduction of the vaccine in the UK driven by vulnerability and exposure status. We estimate the comparative effectiveness of COVID-19 vaccines (ChAdOx1 versus BNT162b2) against post-vaccination infections of SARS-CoV-2 in a community setting in England and Wales. Method: Trial emulation was conducted by pooling results from six cohorts whose recruitment was staggered between 1st January 2021 and 31st March 2021 and followed until 12th November 2021. Eligibility for each trial was based upon age (18+ at the time of vaccination), without prior signs of infection or an infection within the first 14 days of the first dose. Time from vaccination of ChAdOx1 or BNT162b2 until SARS-CoV-2 infection (positive polymerase chain reaction or lateral flow test after 14 of the vaccination) was modelled using Cox proportional hazards model for each cohort and adjusted for age at vaccination, gender, minority ethnic status, clinically vulnerable status and index of multiple deprivation quintile. For those without SARS-CoV-2 infection during the study period, follow-up was until loss-of-follow-up or end of study (12th November 2021). Pooled hazard ratios were generated using random-effects meta-analysis. Results: Across six cohorts, there were a total of 21,283 participants who were eligible and vaccinated with either ChAdOx1 (n = 13,813) or BNT162b2 (n = 7,470) with a median follow-up time of 266 days (IQR: 235 - 282). By November 12th 2021, 750 (5.4%) adults who had ChAdOx1 as their vaccine experienced a SARS-CoV-2 infection, compared to 296 (4.0%) who had BNT162b2. We found that people who received ChAdOx1 vaccinations had 10.54 per 1000 people higher cumulative incidence for SARS-CoV-2 infection compared to BNT162b2 for infections during a maximum of 315 days of follow-up. When adjusted for age at vaccination, sex, minority ethnic status, index of multiple deprivation, and clinical vulnerability status, we found a pooled adjusted hazard ratio of 1.35 [HR: 1.35, 95%CI: 1.15 - 1.58], demonstrating a 35% increase in SARS-CoV-2 infections in people who received ChAdOx1 compared to BNT162b2. Discussion: We found evidence of greater effectiveness of receiving BNT162b2 compared to ChAdOx1 vaccines against SARS-CoV-2 infection in England and Wales during a time period when Delta became the most prevalent variant of concern. Our findings demonstrate the importance of booster (third) doses to maintain protection and suggest that these should be prioritised to those who received ChAdOx1 as their primary course.

Workplace Contact Patterns in England during the COVID-19 Pandemic: Analysis of the Virus Watch prospective cohort study (preprint)

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 and over time during the COVID-19 pandemic in England. Methods: Data were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared 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, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases. Interpretation: Major variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.

Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales (preprint)

Background: Workers differ in their risk of SARS-CoV-2 infection according to their occupation, 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 October 2021, after adjustment for potential confounding and stratification by pandemic phase. Methods: Data from 12,182 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 each occupational group based on adjusted risk ratios (aRR). Findings: Increased risk was seen in nurses (aRR=1.90 [1.40-2.40], AF=47%); doctors (1.74 [1.26-2.40], 42%); carers (2.18 [1.63-2.92], 54%); teachers (primary = 1.94 [1.44- 2.61], 48%; secondary =1.64, [1.23-2.17], 39%), and warehouse and process/plant workers (1.58 [1.20-2.09], 37%) compared to both office-based professional occupations (reported above) and all other occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers demonstrated persistently elevated risk. Interpretation: Occupational differentials in SARS-CoV-2 infection risk are robust to adjustment for socio-demographic, health-related, and activity-related potential confounders. Patterns of differential infection risk varied over time, and ongoing excess risk was observed in education professionals. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.

Relative contribution of leaving home for work or education, transport, shopping and other activities on risk of acquiring COVID-19 infection outside the household in the second wave of the pandemic in England and Wales (preprint)

BackgroundWith the potential for and emergence of new COVID-19 variants, such as the reportedly more infectious Omicron, and their potential to escape the existing vaccines, understanding the relative importance of which non-household activities increase risk of acquisition of COVID-19 infection is vital to inform mitigation strategies. MethodsWithin an adult subset of the Virus Watch community cohort study, we sought to identify which non-household activities increased risk of acquisition of COVID-19 infection and which accounted for the greatest proportion of non-household acquired COVID-19 infections during the second wave of the pandemic. Among participants who were undertaking antibody tests and self-reporting PCR and lateral flow tests taken through the national testing programme, we identified those who were thought to be infected outside the household during the second wave of the pandemic. We used exposure data on attending work, using public or shared transport, using shops and other non-household activities taken from monthly surveys during the second wave of the pandemic. We used multivariable logistic regression models to assess the relative independent contribution of these exposures on risk of acquiring infection outside the household. We calculated Adjusted Population Attributable Fractions (APAF - the proportion of non-household transmission in the cohort thought to be attributable to each exposure) based on odds ratios and frequency of exposure in cases. ResultsBased on analysis of 10475 adult participants including 874 infections acquired outside the household, infection was independently associated with: leaving home for work (AOR 1.20 (1.02 - 1.42) p=0.0307, APAF 6.9%); public transport use (AOR for use more than once per week 1.82 (1.49 - 2.23) p<0.0001, APAF for public transport 12.42%); and shopping (AOR for shopping more than once per week 1.69 (1.29 - 2.21) P=0.0003, APAF for shopping 34.56%). Other non-household activities such as use of hospitality and leisure venues were rare due to restrictions and there were no significant associations with infection risk. ConclusionsA high proportion of the second wave of the pandemic was spent under conditions where people were being advised to work from home where possible, and to minimize exposure to shops, and a wide range of other businesses were subject to severe restrictions. Vaccines were being rolled out to high-risk groups. During this time, going to work was an important risk factor for infection but public transport use likely accounted for a lot of this risk. Only a minority of the cohort left home for work or used public or shared transport. By contrast, the majority of participants visited shops and this activity accounted for about one-third of non-household transmission.

Changes in mobility pre and post first SARS-CoV-2 vaccination: findings from a prospective community cohort study including GPS movement tracking in England and Wales (Virus Watch) (preprint)

Abstract Background: Some evidence suggests that individuals may change adherence to public health policies aimed at reducing contact, transmission and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination. In this study, we aim to estimate the rate of change in average daily travel distance from a participant's registered address before and after SARS-CoV-2 vaccination. Method: 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 onwards. Between September 2020 and February 2021, we invited 13,120 adult Virus Watch participants to contribute towards our tracker sub-cohort which uses the Global Positioning System (GPS) 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 analysed the daily travel distance of 228 vaccinated adults. Between 157 days prior to vaccination until the day before vaccination, the median daily travel distance travelled was 8.9km (IQR: 3.50km, 24.17km). Between the day of vaccination and 100 days after vaccination, the median daily travel distance travelled was 10.30km (IQR: 4.11, 27.53km). Between 157 days prior to vaccination and the vaccination date, there was a daily median decrease in mobility of 40m (95%CI: -51m, -31m, p-value <0.001) per day. After the removal of outlier data, and between the vaccination date and 99 days after vaccination, there was a median daily increase in movement of 45.0m (95%CI: 25m, 65m, p-value = <0.001). Restricting the analysis to the 3rd national lockdown (4th of January 2021 to the 5th of April 2021), we found a median daily movement increase of 9m (95%CI: -25m, 45m, p = 0.57) in the 30 days prior to vaccination and the vaccination date, and a median daily movement increase of 10m (95%CI: -60m, 94m, p-value = 0.69) 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 for understanding public health issues. Our results are consistent with both an increase and decrease in movement after vaccination and suggest that, amongst Virus Watch participants, any changes in movement distances post-vaccination are small.

Relative perceived importance of different settings for SARS-CoV2 acquisition in England and Wales: Analysis of the Virus Watch Community Cohort (preprint)

We aimed to assess the relative importance of different settings for SARS-CoV2 transmission in a large community cohort. We demonstrate the importance of home, work and education as venues for transmission. In children, education was most important and in older adults essential shopping was of high importance. Our findings support public health messaging about infection control at home, advice on working from home and restrictions in different venues.

Occupation, Work-Related Contact, and SARS-CoV-2 Anti-Nucleocapsid Serological Status: Findings from the Virus Watch prospective cohort study (preprint)

BackgroundWorkers differ in their risk of acquiring SARS-CoV-2 infection according to their occupation; however, few studies have been able to control for multiple confounders or investigate the work-related factors that drive differences in occupational risk. Using data from the Virus Watch community cohort study in England and Wales, we set out to estimate the total effect of occupation on SARS-CoV-2 serological status, whether this is mediated by frequency of close contact within the workplace, and how exposure to poorly ventilated workplaces varied across occupations. MethodsWe used data from a sub-cohort (n =3761) of adults ([≥]18) tested for SARS-CoV-2 anti-nucleocapsid antibodies between 01 February-28 April 2021 and responded to a questionnaire about work during the pandemic. Anti-nucleocapsid antibodies were used as a proxy of prior natural infection with COVID-19. We used logistic decomposition to estimate the total and direct effect of occupation and indirect effect of workplace contact frequency on odds of seropositivity, adjusting for age, sex, household income and region. We investigated the relationship between occupation and exposure to poorly-ventilated workplace environments using ordinal logistic regression. ResultsSeropositivity was 16.0% (113/707) amongst workers with daily close contact, compared to 12.9% (120/933) for those with intermediate-frequency contact and 9.6% (203/2121) for those with no work-related close contact. Healthcare (OR= 2.14, 95% CI 1.47,3.12), indoor trade, process and plant (2.09, 1.31,3.33), leisure and personal service (1.96, 1.004,3.84), and transport and mobile machine (2.17, 1.12,4.18) workers had elevated total odds of SARS-CoV-2 seropositivity compared to other professional and associate occupations. Frequency of workplace contact accounted for a variable part of the increased odds in different occupational groups (OR range 1.04 [1.0004,1.07] - 1.22 [1.07, 1.38]). Healthcare workers and indoor trades and process plant workers continued to have raised odds of infection after accounting for work-related contact, and also had had greater odds of frequent exposure to poorly-ventilated workplaces (respectively 2.15 [1.66, 2.79] and (1.51, [1.12, 2.04]). DiscussionMarked variations in occupational odds of seropositivity remain after accounting for age, sex, region, and household income. Close contact in the workplace appears to contribute substantially to this variation. Reducing frequency of workplace contact is a critical part of COVID-19 control measures.

Serial interval of COVID-19 and the effect of Variant B.1.1.7: analyses from a prospective community cohort study (Virus Watch). (preprint)

Introduction Increased transmissibility of B.1.17 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.1.17 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 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.1.17 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 Variants of Concern (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.

Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales (preprint)

Background: Differential exposure to public activities and non-household contacts 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 different levels of 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=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants' postcode of residence using English or Welsh Indices 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 persistently exhibited elevated risk of exposure to vehicle sharing (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 in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. 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.