Impact of voluntary risk-mitigation behaviour on the magnitude of a COVID-19 Omicron variant wave in England

Background The Omicron variant of SARS-CoV-2 infection poses substantial challenges to public health. In England, “plan B” mitigation measures were introduced in December 2021 including increased home working and face coverings in shops but stopped short of restrictions on social contacts. The impact of voluntary risk mitigation behaviours on future SARS-CoV-2 burden is unknown. Methods We developed a rapid online survey of risk mitigation behaviours during the winter 2021 festive period deployed to two longitudinal cohort studies in the UK (Avon Longitudinal Study of Parents and Children (ALSPAC) and TwinsUK/Covid Symptom Study (CSS) Biobank) in December 2021. Using an individualbased, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we describe the impact of the SARS-CoV-2 Omicron wave in England in terms of the effective reproduction number and cumulative infections, hospital admissions and deaths. Using the survey results, we estimated the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave. Results Over 95% of survey respondents (NALSPAC=2,686 and NTwins=6,155) reported some risk mitigation behaviours, with being fully vaccinated and using home testing kits the most frequently reported behaviours. Less than half of those respondents reported that their behaviour was due to “plan B”. We estimate that without risk mitigation behaviours, the Omicron variant is consistent with an effective reproduction number between 2.5 and 3.5. Due to the reduced vaccine effectiveness against infection with the Omicron variant, our modelled estimates suggest that between 55% and 60% of the English population could be infected during the current wave, translating into between 15,000 and 46,000 cumulative deaths, depending on assumptions about vaccine effectiveness. We estimate that voluntary risk reduction measures could reduce the effective reproduction number to between 1.8 and 2.2 and reduce the cumulative number of deaths by up to 24%. Conclusions We conclude that voluntary measures have substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission. Introduction The Omicron variant of SARS-CoV-2 has spread worldwide with extreme rapidity since its identification in November 2021 in Southern Africa and is becoming the dominant variant in multiple countries. Omicron appears to have a substantial advantage over other variants, with numbers of cases consistently doubling every 2 to 3 days[1,2]. The apparent advantage of Omicron over other variants could be due to an increase in transmission potential over the existing Delta variant, or due to mutations which render immunity from vaccination and previous infections less protective against infection than before, or a combination of both effects[3,4]. If Omicron is more transmissible than the Delta variant, but vaccine effectiveness remains high, then non-vaccinated individuals are likely to be most susceptible to infection. If on the other hand, Omicron is as or less transmissible than Delta but is able to evade immunity, then vaccinated individuals are at risk of re-infection[5]. Given the rapid spread of Omicron, public health decisions have had to be made while data are still emerging on its capacity to cause severe disease. Emerging evidence suggests that infection with Omicron is less likely to lead to severe disease and death[6,7], with considerable uncertainty. The variant first identified in the UK in September 2020, Alpha, was associated with a two-fold increased mortality over the original Wuhan variant[8,9], and the variant first identified in India, Delta, had an increased severity of an additional 50%. It is therefore not clear if the reduction in severity associated with Omicron would have similar severity to the Wuhan variant. It has been suggested that if infection with Omicron is associated with lower severity, it might be unnecessary to limit numbers of infections, and to date, social distancing restrictions have not been implemented to control transmission in England. However, severity would have to be exceptionally low to counterbalance the rapid rate of spread and increasing numbers of infections. Omicron started spreading in the UK at the end of November 2021, becoming dominant in December 2021, and is currently causing the largest number of cases yet seen for SARS-CoV-2. The Christmas period is an unusual time of year in terms of mixing patterns, with people meeting increased numbers of friends and relatives and is of high importance to many. This unusual behaviour is not captured in standard contact and behavioural surveys, making the Omicron wave more difficult to estimate. Here, we present the results of a survey developed to assess behaviours over the UK festive period and voluntary risk mitigation measures being used. We use the responses to inform an individual-based disease transmission model and estimate the potential impact voluntary risk mitigation behaviour could have on the effective reproduction number, cumulative numbers of hospital admissions and deaths in England. Methods Ethics statement Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and Local Research Ethics Committees on 25 November 2021. Participation was voluntary and only anonymised data were collected. The survey was sent out to TwinsUK participants under existing TwinsUK ethics (REC reference: EC04/015) and TwinsUK BioBank ethics (REC reference: 19/NW/0187). The survey was sent out to CSS Biobank participants under existing CSS Biobank ethics (REC reference: 20/YH/0298). Rapid survey of social contacts and risk-mitigation behaviour during December 2021 We developed an online survey about plans for Christmas 2021 to fill the gap in social contact and behavioural data. The survey covered the festive period from 20 December 2021 to 2 January 2022 and included questions about planned face-to-face interactions, numbers of households meeting indoors, vaccination and risk-mitigation behaviours (complete list of questions in the Supplementary Information). The survey was advertised to the participants of three longitudinal cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC)[10– 12] , TwinsUK [13,14] and the COVID Symptom Survey (CSS) Biobank [15]. TwinsUK and the CSS Biobank were managed by the same team and were treated as one combined cohort for this study. ALSPAC is an intergenerational prospective birth cohort from the southwest of England. The study recruited 14,541 pregnant women with expected dates of delivery between 1st April 1991 to 31st December 1992 in the county of Avon and has followed the women, their partners and children since. Full details of the cohort and study design have been described previously[10–12] and are available at www.bristol.ac.uk/alspac. The ALSPAC survey was deployed using Microsoft Forms. The survey was an anonymous, standalone survey, and data were not linked to any other data on participants. The survey link went live on 9 December 2021 and was active until 22 December 2021. Participants of ALSPAC were invited to participate via a link in the annual newsletter which went to participants on 15 December 2021 and via social media posts, although anyone with the link could complete the survey. TwinsUK is a UK registry of volunteer twins in the United Kingdom, with about 14,000 registered twins[13,14]. The Covid Symptom Study (CSS) Biobank is a longitudinal study run by researchers at King’s College London with approximately 12,000 participants [15]. The TwinsUK/CSS Biobank survey was implemented in REDCap, accessible via an anonymous link advertised in the Christmas newsletter. The survey link was active from 15 to 20 December 2021. Data from the surveys were analysed in R version 4.01. We calculated descriptive statistics by age and used a binomial general linear model to explore associations between risk mitigation behaviours. Modelling approach We used an individual-based disease model based on social contact data[16]. The basic premise behind the approach is that we calculate a distribution of individual reproduction numbers for the entire population, based on individuals’ social contacts. Say individual i has k! social contacts on a given day. Each social contact involves n" other individuals and it lasts for a time d", which acts to weight the number of contacts. Their personal individual reproduction number (i.e. the number of secondary cases they generate) is given by R! = τ)[SAR]"n"d" , "! "#$ where [SAR]" is the Omicron-specific secondary attack rate (proportion of contacts that result in secondary infection) for the setting of the social contact, either household or non-household and τ is a constant calibrated to the reproduction number R% = 7 for the Delta variant in the absence of vaccination or natural immunity. We used social contact data from the Social Contact Survey (SCS)[17] and secondary attack rates estimated by UKHSA from positive tests in contacts named to NHS Test and Trace [6]. To calculate the population-level reproduction number from the individual reproduction numbers, we assume proportionate mixing between individuals, i.e. that the probability of contacting individual j is proportional to their number of contacts over the total number of contacts in the population, R& ∑ R& & ⁄ . The population-level reproduction number therefore scales with the square of the individual-level reproduction numbers: