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Challenges in control of COVID-19: short doubling time and long delay to effect of interventions

Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods,...

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Autores principales: Pellis, Lorenzo, Scarabel, Francesca, Stage, Helena B., Overton, Christopher E., Chappell, Lauren H. K., Fearon, Elizabeth, Bennett, Emma, Lythgoe, Katrina A., House, Thomas A., Hall, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165602/
https://www.ncbi.nlm.nih.gov/pubmed/34053267
http://dx.doi.org/10.1098/rstb.2020.0264
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author Pellis, Lorenzo
Scarabel, Francesca
Stage, Helena B.
Overton, Christopher E.
Chappell, Lauren H. K.
Fearon, Elizabeth
Bennett, Emma
Lythgoe, Katrina A.
House, Thomas A.
Hall, Ian
author_facet Pellis, Lorenzo
Scarabel, Francesca
Stage, Helena B.
Overton, Christopher E.
Chappell, Lauren H. K.
Fearon, Elizabeth
Bennett, Emma
Lythgoe, Katrina A.
House, Thomas A.
Hall, Ian
author_sort Pellis, Lorenzo
collection PubMed
description Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods, we estimated that, when unconstrained, European COVID-19 confirmed cases doubled on average every 3 days (range 2.2–4.3 days) and Italian hospital and intensive care unit admissions every 2–3 days; values that are significantly lower than the 5–7 days dominating the early published literature. Furthermore, we showed that the impact of physical distancing interventions was typically not seen until at least 9 days after implementation, during which time confirmed cases could grow eightfold. We argue that such temporal patterns are more critical than precise estimates of the time-insensitive basic reproduction number R(0) for initiating interventions, and that the combination of fast growth and long detection delays explains the struggle in countries' outbreak response better than large values of R(0) alone. One year on from first reporting these results, reproduction numbers continue to dominate the media and public discourse, but robust estimates of unconstrained growth remain essential for planning worst-case scenarios, and detection delays are still key in informing the relaxation and re-implementation of interventions. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
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spelling pubmed-81656022021-06-03 Challenges in control of COVID-19: short doubling time and long delay to effect of interventions Pellis, Lorenzo Scarabel, Francesca Stage, Helena B. Overton, Christopher E. Chappell, Lauren H. K. Fearon, Elizabeth Bennett, Emma Lythgoe, Katrina A. House, Thomas A. Hall, Ian Philos Trans R Soc Lond B Biol Sci Articles Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods, we estimated that, when unconstrained, European COVID-19 confirmed cases doubled on average every 3 days (range 2.2–4.3 days) and Italian hospital and intensive care unit admissions every 2–3 days; values that are significantly lower than the 5–7 days dominating the early published literature. Furthermore, we showed that the impact of physical distancing interventions was typically not seen until at least 9 days after implementation, during which time confirmed cases could grow eightfold. We argue that such temporal patterns are more critical than precise estimates of the time-insensitive basic reproduction number R(0) for initiating interventions, and that the combination of fast growth and long detection delays explains the struggle in countries' outbreak response better than large values of R(0) alone. One year on from first reporting these results, reproduction numbers continue to dominate the media and public discourse, but robust estimates of unconstrained growth remain essential for planning worst-case scenarios, and detection delays are still key in informing the relaxation and re-implementation of interventions. 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/PMC8165602/ /pubmed/34053267 http://dx.doi.org/10.1098/rstb.2020.0264 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
Pellis, Lorenzo
Scarabel, Francesca
Stage, Helena B.
Overton, Christopher E.
Chappell, Lauren H. K.
Fearon, Elizabeth
Bennett, Emma
Lythgoe, Katrina A.
House, Thomas A.
Hall, Ian
Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title_full Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title_fullStr Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title_full_unstemmed Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title_short Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
title_sort challenges in control of covid-19: short doubling time and long delay to effect of interventions
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165602/
https://www.ncbi.nlm.nih.gov/pubmed/34053267
http://dx.doi.org/10.1098/rstb.2020.0264
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