How prepared is the world? Identifying weaknesses in existing assessment frameworks for global health security through a One Health approach.

The COVID-19 pandemic has exposed faults in the way we assess preparedness and response capacities for public health emergencies. Existing frameworks are limited in scope, and do not sufficiently consider complex social, economic, political, regulatory, and ecological factors. One Health, through its focus on the links among humans, animals, and ecosystems, is a valuable approach through which existing assessment frameworks can be analysed and new ways forward proposed. Although in the past few years advances have been made in assessment tools such as the International Health Regulations Joint External Evaluation, a rapid and radical increase in ambition is required. To sufficiently account for the range of complex systems in which health emergencies occur, assessments should consider how problems are defined across stakeholders and the wider sociopolitical environments in which structures and institutions operate. Current frameworks do little to consider anthropogenic factors in disease emergence or address the full array of health security hazards across the social-ecological system. A complex and interdependent set of challenges threaten human, animal, and ecosystem health, and we cannot afford to overlook important contextual factors, or the determinants of these shared threats. Health security assessment frameworks should therefore ensure that the process undertaken to prioritise and build capacity adheres to core One Health principles and that interventions and outcomes are assessed in terms of added value, trade-offs, and cobenefits across human, animal, and environmental health systems.

Long-term outcomes of SARS-CoV-2 variants and other respiratory infections: evidence from the Virus Watch prospective cohort in England.

This study compared the likelihood of long-term sequelae following infection with SARS-CoV-2 variants, other acute respiratory infections (ARIs) and non-infected individuals. Participants (n=5,630) were drawn from Virus Watch, a prospective community cohort investigating SARS-CoV-2 epidemiology in England. Using logistic regression, we compared predicted probabilities of developing long-term symptoms (>2 months) during different variant dominance periods according to infection status (SARS-CoV-2, other ARI, or no infection), adjusting for confounding by demographic and clinical factors and vaccination status. SARS-CoV-2 infection during early variant periods up to Omicron BA.1 was associated with greater probability of long-term sequalae (adjusted predicted probability (PP) range 0.27, 95% CI = 0.22-0.33 to 0.34, 95% CI = 0.25-0.43) compared with later Omicron sub-variants (PP range 0.11, 95% CI 0.08-0.15 to 0.14, 95% CI 0.10-0.18). While differences between SARS-CoV-2 and other ARIs (PP range 0.08, 95% CI 0.04-0.11 to 0.23, 95% CI 0.18-0.28) varied by period, all post-infection estimates substantially exceeded those for non-infected participants (PP range 0.01, 95% CI 0.00, 0.02 to 0.03, 95% CI 0.01-0.06). Variant was an important predictor of SARS-CoV-2 post-infection sequalae, with recent Omicron sub-variants demonstrating similar probabilities to other contemporaneous ARIs. Further aetiological investigation including between-pathogen comparison is recommended.

Bayesian reconstruction of household transmissions to infer the serial interval of COVID-19 by variants of concern: analysis from a prospective community cohort study (Virus Watch).

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.

Relative contribution of essential and non-essential activities to SARS-CoV-2 transmission following the lifting of public health restrictions in England and Wales.

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.

Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America.

Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1-31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.

The Global Health Security index and Joint External Evaluation score for health preparedness are not correlated with countries' COVID-19 detection response time and mortality outcome.

Global Health Security Index (GHSI) and Joint External Evaluation (JEE) are two well-known health security and related capability indices. We hypothesised that countries with higher GHSI or JEE scores would have detected their first COVID-19 case earlier, and would experience lower mortality outcome compared to countries with lower scores. We evaluated the effectiveness of GHSI and JEE in predicting countries' COVID-19 detection response times and mortality outcome (deaths/million). We used two different outcomes for the evaluation: (i) detection response time, the duration of time to the first confirmed case detection (from 31st December 2019 to 20th February 2020 when every country's first case was linked to travel from China) and (ii) mortality outcome (deaths/million) until 11th March and 1st July 2020, respectively. We interpreted the detection response time alongside previously published relative risk of the importation of COVID-19 cases from China. We performed multiple linear regression and negative binomial regression analysis to evaluate how these indices predicted the actual outcome. The two indices, GHSI and JEE were strongly correlated (r = 0.82), indicating a good agreement between them. However, both GHSI (r = 0.31) and JEE (r = 0.37) had a poor correlation with countries' COVID-19-related mortality outcome. Higher risk of importation of COVID-19 from China for a given country was negatively correlated with the time taken to detect the first case in that country (adjusted R2 = 0.63-0.66), while the GHSI and JEE had minimal predictive value. In the negative binomial regression model, countries' mortality outcome was strongly predicted by the percentage of the population aged 65 and above (incidence rate ratio (IRR): 1.10 (95% confidence interval (CI): 1.01-1.21) while overall GHSI score (IRR: 1.01 (95% CI: 0.98-1.01)) and JEE (IRR: 0.99 (95% CI: 0.96-1.02)) were not significant predictors. GHSI and JEE had lower predictive value for detection response time and mortality outcome due to COVID-19. We suggest introduction of a population healthiness parameter, to address demographic and comorbidity vulnerabilities, and reappraisal of the ranking system and methods used to obtain the index based on experience gained from this pandemic.

Eyeglasses and risk of COVID-19 transmission-analysis of the Virus Watch Community Cohort study.

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.

The incidence of COVID-19-related hospitalisation in migrants in the UK: Findings from the Virus Watch prospective community cohort study.

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.

Research ethics during infectious disease outbreaks: A survey of African research stakeholders using the Ebola virus disease outbreak as a case.

Conducting research during disease outbreaks can be ethically challenging as evidenced in the 2014-2016 Ebola outbreak in West Africa and COVID-19 pandemic. Yet, there has been little empirical research conducted for understanding the views and perspectives of different stakeholders regarding ethical issues in conducting research during disease outbreaks. This preliminary study was conducted to empirically explore African public health research stakeholders' views about research ethics issues during infectious disease outbreaks in Africa. We conducted an online survey of 330 participants attending the International Conference on Re-emerging and Emerging Infectious Disease (ICREID) meeting that took place from 13-15 March 2019 in Addis Ababa, Ethiopia to elicit their views on various research ethics complexities experienced in the 2014 Ebola outbreak. Study results revealed some divergent views on several ethical themes including: ethics of using unregistered interventions in outbreaks; acceptable study design; ethics review processes; risks-benefit assessment; exclusion of pregnant women and children; and biological sample and data sharing. Majority (76.3%) of respondents felt that in the absence of available standard treatments or prevention modalities, the use of investigational interventions can be ethically justifiable if there is a strong scientific rationale and favorable risk-benefit ratio. Regarding conventional placebo-controlled trials during outbreaks with high case fatality rates, respondents that considered this unethical were more than three times those that felt such design were ethically justifiable. We were somewhat surprised that a majority (almost 60%) of respondents were satisfied with the exclusion of pregnant women and children in clinical trials during outbreaks. All respondents concurred with the prioritization of informed consent for research during an outbreak. Based on our findings, research ethics guidance is needed to equip research stakeholders in dealing with ethical complexities arising in the conduct of research during emerging disease outbreaks-especially regarding using experimental interventions; placebo trial design; inclusion or justified exclusion of pregnant women and children; and biological sample/data sharing. The findings will be used in ongoing efforts of developing a consultative and coherent African-centric framework to support ethical conduct of research for future emerging infectious disease outbreaks in Africa.

Between-occupation differences in work-related COVID-19 mitigation strategies over time: Analysis of the Virus Watch Cohort in England and Wales.

OBJECTIVES: COVID-19 mitigations have had a profound impact on workplaces, however, multisectoral comparisons of how work-related mitigations were applied are limited. This study aimed to investigate (i) occupational differences in the usage of key work-related mitigations over time and (ii) workers' perceptions of these mitigations. METHODS: Employed/self-employed Virus Watch study participants (N=6279) responded to a mitigation-related online survey covering the periods of December 2020-February 2022. Logistic regression was used to investigate occupation- and time-related differences in the usage of work-related mitigation methods. Participants' perceptions of mitigation methods were investigated descriptively using proportions. RESULTS: Usage of work-related mitigation methods differed between occupations and over time, likely reflecting variation in job roles, workplace environments, legislation and guidance. Healthcare workers had the highest predicted probabilities for several mitigations, including reporting frequent hand hygiene [predicted probability across all survey periods 0.61 (95% CI 0.56-0.66)] and always wearing face coverings [predicted probability range 0.71 (95% CI 0.66-0.75) - 0.80 (95% CI 0.76-0.84) across survey periods]. There were significant cross-occupational trends towards reduced mitigations during periods of less stringent national restrictions. The majority of participants across occupations (55-88%) agreed that most mitigations were reasonable and worthwhile even after the relaxation of national restrictions; agreement was lower for physical distancing (39-44%). CONCLUSIONS: While usage of work-related mitigations appeared to vary alongside stringency of national restrictions, agreement that most mitigations were reasonable and worthwhile remained substantial. Further investigation into the factors underlying between-occupational differences could assist pandemic planning and prevention of workplace COVID-19 transmission.

Symptom profiles of community cases infected by influenza, RSV, rhinovirus, seasonal coronavirus, and SARS-CoV-2 variants of concern.

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.

A case-crossover study of the effect of vaccination on SARS-CoV-2 transmission relevant behaviours during a period of national lockdown in England and Wales.

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.

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

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.

Deprivation, essential and non-essential activities and SARS-CoV-2 infection following the lifting of national public health restrictions in England and Wales.

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.

Individuals living in deprived areas of England and Wales left home to go to work and used public transport more frequently than people living in less deprived areas of the country when under tight lockdown restrictions. They were also more likely to develop SARS-CoV-2 infection. Understanding whether these differences changed once restrictions were lifted is important to understand whether deprivation-related discrepancies in infection risk changed throughout the pandemic. We found that, after the removal of lockdown restrictions, people living in areas of the greatest deprivation continued to leave home for work or use public transport more frequently than those not living in areas of deprivation but they were less likely to visit either indoor or outdoor hospitality or leisure venues such as cafes, restaurants, bars, cinemas, theatres or visit a hairdresser or beautician than people living in areas with little deprivation. They were no longer more likely than those living in areas with little deprivation to become infected with SARS-CoV-2. This is likely because people living in areas with little deprivation were visiting hospitality and leisure venues more frequently than during lockdown and were increasing their exposure to infection in these settings, balancing out the increased infection risk posed through work and public transport to those living in deprived areas. The fact that people living in areas of deprivation were most likely exposed to SARS-CoV-2 infection through essential activities like work and public transport use while people living in areas with little deprivation were most likely exposed to infection through non-essential activities such as visiting a restaurant, pub, cinema or theatre, highlights stark disparities in an individuals' ability to choose how to limit infection exposure based on their deprivation status.

The changing contributory role to infections of work, public transport, shopping, hospitality and leisure activities throughout the SARS-CoV-2 pandemic in England and Wales.

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.

Establishing which activities and venues that were restricted in England and Wales during lockdowns were the most likely to lead to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections will help us understand how useful the restrictions were and will help us to develop proportional responses to future public health threats. We found that during periods of intense restrictions (October 2020­May 2021) many people became infected with SARS-CoV-2 if they left home to go to work or used public transport. During the period after most public health restrictions were lifted (September­mid-December 2021), while many people continued to become infected at work or if they used public transport, indoor hospitality and indoor leisure venues became increasingly important as places where people became infected. During the Omicron wave of the pandemic (December 2021­April 2022), by which point there were very few restrictions on people's activities and many people were visiting hospitality and leisure venues with increasing frequency, people continued to become infected at work and on public transport, but hospitality and leisure venues were nearly as important places where people became infected. As essential activities led to most cases during periods of tight restrictions and leisure and hospitality activities became increasingly important under periods when rules were more relaxed, it is important to recognise how vital it was to encourage people to work from home, reduce public transport use and restrict visits to leisure and hospitality settings when the country was faced with a fast-spreading virus which killed many people. Outdoor use of leisure and hospitality venues appeared to be safer than indoor use.

Bayesian reconstruction of SARS-CoV-2 transmissions highlights substantial proportion of negative serial intervals.

BACKGROUND: The serial interval is a key epidemiological measure that quantifies the time between the onset of symptoms in an infector-infectee pair. It indicates how quickly new generations of cases appear, thus informing on the speed of an epidemic. Estimating the serial interval requires to identify pairs of infectors and infectees. Yet, most studies fail to assess the direction of transmission between cases and assume that the order of infections - and thus transmissions - strictly follows the order of symptom onsets, thereby imposing serial intervals to be positive. Because of the long and highly variable incubation period of SARS-CoV-2, this may not always be true (i.e an infectee may show symptoms before their infector) and negative serial intervals may occur. This study aims to estimate the serial interval of different SARS-CoV-2 variants whilst accounting for negative serial intervals. METHODS: This analysis included 5 842 symptomatic individuals with confirmed SARS-CoV-2 infection amongst 2 579 households from September 2020 to August 2022 across England & Wales. We used a Bayesian framework to infer who infected whom by exploring all transmission trees compatible with the observed dates of symptoms, based on a wide range of incubation period and generation time distributions compatible with estimates reported in the literature. Serial intervals were derived from the reconstructed transmission pairs, stratified by variants. RESULTS: We estimated that 22% (95% credible interval (CrI) 8-32%) of serial interval values are negative across all VOC. The mean serial interval was shortest for Omicron BA5 (2.02 days, 1.26-2.84) and longest for Alpha (3.37 days, 2.52-4.04). CONCLUSIONS: This study highlights the large proportion of negative serial intervals across SARS-CoV-2 variants. Because the serial interval is widely used to estimate transmissibility and forecast cases, these results may have critical implications for epidemic control.

SARS-CoV-2 infections in migrants and the role of household overcrowding: a causal mediation analysis of Virus Watch data.

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.

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.

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.

Estimating disease burden using national linked electronic health records: a study using an English population-based cohort.

Background: Electronic health records (EHRs) have the potential to be used to produce detailed disease burden estimates. In this study we created disease estimates using national EHR for three high burden conditions, compared estimates between linked and unlinked datasets and produced stratified estimates by age, sex, ethnicity, socio-economic deprivation and geographical region. Methods: EHRs containing primary care (Clinical Practice Research Datalink), secondary care (Hospital Episode Statistics) and mortality records (Office for National Statistics) were used. We used existing disease phenotyping algorithms to identify cases of cancer (breast, lung, colorectal and prostate), type 1 and 2 diabetes, and lower back pain. We calculated age-standardised incidence of first cancer, point prevalence for diabetes, and primary care consultation prevalence for low back pain. Results: 7.2 million people contributing 45.3 million person-years of active follow-up between 2000-2014 were included. CPRD-HES combined and CPRD-HES-ONS combined lung and bowel cancer incidence estimates by sex were similar to cancer registry estimates. Linked CPRD-HES estimates for combined Type 1 and Type 2 diabetes were consistently higher than those of CPRD alone, with the difference steadily increasing over time from 0.26% (2.99% for CPRD-HES vs. 2.73 for CPRD) in 2002 to 0.58% (6.17% vs. 5.59) in 2013. Low back pain prevalence was highest in the most deprived quintile and when compared to the least deprived quintile the difference in prevalence increased over time between 2000 and 2013, with the largest difference of 27% (558.70 per 10,000 people vs 438.20) in 2013. Conclusions: We use national EHRs to produce estimates of burden of disease to produce detailed estimates by deprivation, ethnicity and geographical region. National EHRs have the potential to improve disease burden estimates at a local and global level and may serve as more automated, timely and precise inputs for policy making and global burden of disease estimation.