Voluntary risk mitigation behaviour can reduce impact of SARS-CoV-2: a real-time modelling study of the January 2022 Omicron wave in England

BMC Medicine

Research Article

Leon Danon¹  Francesca Scarabel²  Lorenzo Pellis³  Maria Paz Garcia⁴  Claire J. Steves⁴  Vicky Bowyer⁴  Kate Northstone⁵  Amy Thomas⁵  Ellen Brooks-Pollock⁵  Nicholas J. Timpson⁶  Emily Nixon⁷  David A. Matthews⁸ 

[1] Department of Engineering Mathematics, University of Bristol, Bristol, UK;Department of Mathematics, University of Manchester, Manchester, UK;Department of Mathematics, University of Manchester, Manchester, UK;School of Biological Sciences, University of Bristol, Bristol, UK;Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK;Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK;Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK;MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK;Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK;The Alan Turing Institute, London, UK;School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK;

关键词: SARS-CoV-2;    Omicron variant;    Behaviour change;    Infectious disease modelling;    Scenario modelling;    policy;    Interventions;    Longitudinal cohort studies;   

DOI  :  10.1186/s12916-022-02714-5

 received in 2022-02-16, accepted in 2022-12-15,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundPredicting the likely size of future SARS-CoV-2 waves is necessary for public health planning. In England, voluntary “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.MethodsWe developed a rapid online survey of risk mitigation behaviours ahead of the winter 2021 festive period and deployed in 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 individual-based, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we predicted the potential 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 survey results, we estimated in real-time the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave.ResultsOver 95% of survey respondents (NALSPAC = 2686 and NTwins = 6155) reported some risk mitigation behaviours, with vaccination and using home testing kits reported most frequently. 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 12,000 and 46,000 cumulative deaths, depending on assumptions about severity and vaccine effectiveness. The actual number of deaths was 15,208 (26 November 2021–1 March 2022). 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%.ConclusionsPredicting future infection burden is affected by uncertainty in disease severity and vaccine effectiveness estimates. In addition to biological uncertainty, we show that voluntary measures substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission.

【 授权许可】

CC BY   
© The Author(s) 2023

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