Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Birrell, Paul, Blake, Joshua, van Leeuwen, Edwin, Gent, Nick, De Angelis, Daniela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165585/
https://www.ncbi.nlm.nih.gov/pubmed/34053254
http://dx.doi.org/10.1098/rstb.2020.0279
_version_ 1783701353843916800
author Birrell, Paul
Blake, Joshua
van Leeuwen, Edwin
Gent, Nick
De Angelis, Daniela
author_facet Birrell, Paul
Blake, Joshua
van Leeuwen, Edwin
Gent, Nick
De Angelis, Daniela
author_sort Birrell, Paul
collection PubMed
description 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’.
format Online
Article
Text
id pubmed-8165585
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher The Royal Society
record_format MEDLINE/PubMed
spelling pubmed-81655852021-06-03 Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave Birrell, Paul Blake, Joshua van Leeuwen, Edwin Gent, Nick De Angelis, Daniela Philos Trans R Soc Lond B Biol Sci Articles 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’. The Royal Society 2021-07-19 2021-05-31 /pmc/articles/PMC8165585/ /pubmed/34053254 http://dx.doi.org/10.1098/rstb.2020.0279 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Birrell, Paul
Blake, Joshua
van Leeuwen, Edwin
Gent, Nick
De Angelis, Daniela
Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title_full Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title_fullStr Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title_full_unstemmed Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title_short Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave
title_sort real-time nowcasting and forecasting of covid-19 dynamics in england: the first wave
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165585/
https://www.ncbi.nlm.nih.gov/pubmed/34053254
http://dx.doi.org/10.1098/rstb.2020.0279
work_keys_str_mv AT birrellpaul realtimenowcastingandforecastingofcovid19dynamicsinenglandthefirstwave
AT blakejoshua realtimenowcastingandforecastingofcovid19dynamicsinenglandthefirstwave
AT vanleeuwenedwin realtimenowcastingandforecastingofcovid19dynamicsinenglandthefirstwave
AT gentnick realtimenowcastingandforecastingofcovid19dynamicsinenglandthefirstwave
AT deangelisdaniela realtimenowcastingandforecastingofcovid19dynamicsinenglandthefirstwave