A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality

Leon Danon*, Ellen Brooks-Pollock, Mick Bailey, Matt Keeling

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

33 Citations (Scopus)

Abstract

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.
Original languageEnglish
Article number20200272
Number of pages8
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Early online date31 May 2021
DOIs
Publication statusPublished - 19 Jul 2021

Fingerprint

Dive into the research topics of 'A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality'. Together they form a unique fingerprint.

Cite this