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The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study

Kiesha Prem, Yang Liu, Timothy Russell, Adam J. Kucharski, Rosalind M. Eggo, Nicholas G. Davies, Stefan Flasche, Samuel Clifford, Carl A. B. Pearson, James D Munday, Sam Abbott, Hamish Gibbs, Alicia Roselló, Billy J. Quilty, Thibaut Jombart, Fiona Sun, Charlie Diamond, Amy Gimma, Kevin van Zandvoort, Sebastian Funk, Christopher I Jarvis, W. John Edmunds, Nikos I Bosse, Joel Hellewell, Mark Jit, Petra Klepac

2020The Lancet Public Health2,315 citationsDOIOpen Access PDF

Abstract

BACKGROUND: In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world. METHODS: To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April). FINDINGS: Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66-97) and 24% (13-90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. INTERPRETATION: and the duration of infectiousness. FUNDING: Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

Topics & Concepts

OutbreakSocial distanceCoronavirus disease 2019 (COVID-19)ChinaTransmission (telecommunications)PopulationGeographyEpidemic modelDemographyEnvironmental healthMedicineComputer scienceDiseaseVirologySociologyTelecommunicationsArchaeologyInfectious disease (medical specialty)PathologyCOVID-19 epidemiological studiesInfection Control and VentilationSARS-CoV-2 detection and testing
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