@misc{10b4f5518a6349f29234a466d5f7fb01,
title = "Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics",
abstract = "Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.",
keywords = "Adolescent, Adult, COVID-19 Vaccines/administration & dosage, COVID-19/epidemiology, Computer Simulation, Forecasting/methods, Humans, Immune Evasion/genetics, Middle Aged, Models, Biological, Mutation, Pandemics/prevention & control, SARS-CoV-2/genetics, Stochastic Processes, United Kingdom/epidemiology, Vaccination/statistics & numerical data, Young Adult",
author = "Louise Dyson and Hill, {Edward M.} and Sam Moore and Jacob Curran-Sebastian and Tildesley, {Michael J.} and Lythgoe, {Katrina A.} and Thomas House and Lorenzo Pellis and Keeling, {Matt J.}",
note = "Funding Information: S.M. and M.J.K. were supported by the National Institute for Health Research (NIHR) [Policy Research Programme, Mathematical & Economic Modelling for Vaccination and Immunisation Evaluation, and Emergency Response; NIHR200411]. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. L.D., E.M.H., M.J.T. and M.J.K. were supported by the Medical Research Council through the COVID-19 Rapid Response Rolling Call [grant number MR/V009761/1]; L.D., M.J.T. and M.J.K. were supported by the Engineering and Physical Sciences Research Council through the MathSys CDT [grant number EP/S022244/1]; K.A.L. was supported by the Li Ka Shing Foundation; L.P. was supported by the Wellcome Trust and the Royal Society [grant number 202562/Z/16/Z]; TH was supported by the Royal Society [grant number INF/R2/180067]; TH and LP were also supported by the UK Research and Innovation COVID-19 rolling scheme [grant numbers EP/V027468/1 and MR/V028618/1] as well as the Alan Turing Institute for Data Science and Artificial Intelligence. L.D., L.P., T.H., M.J.T. and M.J.K. were supported by UKRI through the JUNIPER modelling consortium [grant number MR/V038613/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the paper. Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = dec,
day = "1",
doi = "10.1038/s41467-021-25915-7",
language = "English",
volume = "12",
series = "Nature Communications",
publisher = "Springer Nature",
edition = "1",
type = "Other",
}
