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Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave.

Published version
Peer-reviewed

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Authors

Blake, Joshua 
van Leeuwen, Edwin 
Gent, Nick 
De Angelis, Daniela  ORCID logo  https://orcid.org/0000-0001-6619-6112

Abstract

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Description

Funder: Public Health England; Id: http://dx.doi.org/10.13039/501100002141

Keywords

ARTICLES, Research articles, real-time, dynamics, COVID-19, Bayesian, nowcasting, forecasting

Journal Title

Philos Trans R Soc Lond B Biol Sci

Conference Name

Journal ISSN

0962-8436
1471-2970

Volume Title

376

Publisher

The Royal Society
Sponsorship
Medical Research Council (MC UU 00002/11)
Health Technology Assessment Programme (11/46/03)