A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality.
human movement
modelling
seasonality
spatial
Journal
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
ISSN: 1471-2970
Titre abrégé: Philos Trans R Soc Lond B Biol Sci
Pays: England
ID NLM: 7503623
Informations de publication
Date de publication:
19 07 2021
19 07 2021
Historique:
entrez:
31
5
2021
pubmed:
1
6
2021
medline:
11
6
2021
Statut:
ppublish
Résumé
An outbreak of a novel coronavirus was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable human-to-human transmission in England. We adapted an existing national-scale metapopulation model to capture the spread of COVID-19 in England and Wales. We used 2011 census data to inform population sizes and movements, together with parameter estimates from the outbreak in China. We predict that the epidemic will peak 126 to 147 days (approx. 4 months) after the start of person-to-person transmission in the absence of controls. Assuming biological parameters remain unchanged and transmission persists from February, we expect the peak to occur in June. Starting location and model stochasticity have a minimal impact on peak timing. However, realistic parameter uncertainty leads to peak time estimates ranging from 78 to 241 days following sustained transmission. Seasonal changes in transmission rate can substantially impact the timing and size of the epidemic. We provide initial estimates of the epidemic potential of COVID-19. These results can be refined with more precise parameters. Seasonal changes in transmission could shift the timing of the peak into winter, with important implications for healthcare capacity planning. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK.
Identifiants
pubmed: 34053261
doi: 10.1098/rstb.2020.0272
pmc: PMC8165591
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
20200272Subventions
Organisme : Medical Research Council
ID : MC_PC_19067
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_19067/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V038613/1
Pays : United Kingdom
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