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Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India

The resurgence of the May 2021 COVID-19 wave in India not only pointed to the explosive speed with which SARS-CoV-2 can spread in vulnerable populations if unchecked, but also to the gross misreading of the status of the pandemic when decisions to reopen the economy were made in March 2021. In this...

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Autores principales: Michael, Edwin, Newcomb, Ken, Mubayi, Anuj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021811/
https://www.ncbi.nlm.nih.gov/pubmed/36962906
http://dx.doi.org/10.1371/journal.pgph.0001382
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author Michael, Edwin
Newcomb, Ken
Mubayi, Anuj
author_facet Michael, Edwin
Newcomb, Ken
Mubayi, Anuj
author_sort Michael, Edwin
collection PubMed
description The resurgence of the May 2021 COVID-19 wave in India not only pointed to the explosive speed with which SARS-CoV-2 can spread in vulnerable populations if unchecked, but also to the gross misreading of the status of the pandemic when decisions to reopen the economy were made in March 2021. In this combined modelling and scenario-based analysis, we isolated the population and policy-related factors underlying the May 2021 viral resurgence by projecting the growth and magnitude of the health impact and demand for hospital care that would have arisen if the spread was not impeded, and by evaluating the intervention options best able to curb the observed rapidly developing contagion. We show that only by immediately re-introducing a moderately high level of social mitigation over a medium-term period alongside a swift ramping up of vaccinations could the country be able to contain and ultimately end the pandemic safely. We also show that delaying the delivery of the 2(nd) dose of the Astra Zeneca vaccine, as proposed by the Government of India, would have had only slightly more deleterious impacts, supporting the government’s decision to vaccinate a greater fraction of the population with at least a single dose as rapidly as possible. Our projections of the scale of the virus resurgence based on the observed May 2021 growth in cases and impacts of intervention scenarios to control the wave, along with the diverse range of variable control actions taken by state authorities, also exemplify the importance of shifting from the use of science and knowledge in an ad hoc reactive fashion to a more effective proactive strategy for assessing and managing the risk of fast-changing hazards, like a pandemic. We show that epidemic models parameterized with data can be used in combination with plausible intervention scenarios to enable such policy-making.
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spelling pubmed-100218112023-03-17 Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India Michael, Edwin Newcomb, Ken Mubayi, Anuj PLOS Glob Public Health Research Article The resurgence of the May 2021 COVID-19 wave in India not only pointed to the explosive speed with which SARS-CoV-2 can spread in vulnerable populations if unchecked, but also to the gross misreading of the status of the pandemic when decisions to reopen the economy were made in March 2021. In this combined modelling and scenario-based analysis, we isolated the population and policy-related factors underlying the May 2021 viral resurgence by projecting the growth and magnitude of the health impact and demand for hospital care that would have arisen if the spread was not impeded, and by evaluating the intervention options best able to curb the observed rapidly developing contagion. We show that only by immediately re-introducing a moderately high level of social mitigation over a medium-term period alongside a swift ramping up of vaccinations could the country be able to contain and ultimately end the pandemic safely. We also show that delaying the delivery of the 2(nd) dose of the Astra Zeneca vaccine, as proposed by the Government of India, would have had only slightly more deleterious impacts, supporting the government’s decision to vaccinate a greater fraction of the population with at least a single dose as rapidly as possible. Our projections of the scale of the virus resurgence based on the observed May 2021 growth in cases and impacts of intervention scenarios to control the wave, along with the diverse range of variable control actions taken by state authorities, also exemplify the importance of shifting from the use of science and knowledge in an ad hoc reactive fashion to a more effective proactive strategy for assessing and managing the risk of fast-changing hazards, like a pandemic. We show that epidemic models parameterized with data can be used in combination with plausible intervention scenarios to enable such policy-making. Public Library of Science 2022-12-13 /pmc/articles/PMC10021811/ /pubmed/36962906 http://dx.doi.org/10.1371/journal.pgph.0001382 Text en © 2022 Michael et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Michael, Edwin
Newcomb, Ken
Mubayi, Anuj
Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title_full Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title_fullStr Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title_full_unstemmed Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title_short Data-driven scenario-based model projections and management of the May 2021 COVID-19 resurgence in India
title_sort data-driven scenario-based model projections and management of the may 2021 covid-19 resurgence in india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021811/
https://www.ncbi.nlm.nih.gov/pubmed/36962906
http://dx.doi.org/10.1371/journal.pgph.0001382
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