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Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience

India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening p...

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Autores principales: Salvatore, Maxwell, Purkayastha, Soumik, Ganapathi, Lakshmi, Bhattacharyya, Rupam, Kundu, Ritoban, Zimmermann, Lauren, Ray, Debashree, Hazra, Aditi, Kleinsasser, Michael, Solomon, Sunil, Subbaraman, Ramnath, Mukherjee, Bhramar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205583/
https://www.ncbi.nlm.nih.gov/pubmed/35714183
http://dx.doi.org/10.1126/sciadv.abp8621
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author Salvatore, Maxwell
Purkayastha, Soumik
Ganapathi, Lakshmi
Bhattacharyya, Rupam
Kundu, Ritoban
Zimmermann, Lauren
Ray, Debashree
Hazra, Aditi
Kleinsasser, Michael
Solomon, Sunil
Subbaraman, Ramnath
Mukherjee, Bhramar
author_facet Salvatore, Maxwell
Purkayastha, Soumik
Ganapathi, Lakshmi
Bhattacharyya, Rupam
Kundu, Ritoban
Zimmermann, Lauren
Ray, Debashree
Hazra, Aditi
Kleinsasser, Michael
Solomon, Sunil
Subbaraman, Ramnath
Mukherjee, Bhramar
author_sort Salvatore, Maxwell
collection PubMed
description India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening public health interventions early would have helped control transmission in the country and significantly reduced mortality during the second wave, even without harsh lockdowns. We argue that enhanced surveillance at district, state, and national levels and constant assessment of risk associated with increased transmission are critical for future pandemic responsiveness. Building on our retrospective analysis, we provide a tiered data-driven framework for timely escalation of future interventions as a tool for policy-makers.
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spelling pubmed-92055832022-06-29 Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience Salvatore, Maxwell Purkayastha, Soumik Ganapathi, Lakshmi Bhattacharyya, Rupam Kundu, Ritoban Zimmermann, Lauren Ray, Debashree Hazra, Aditi Kleinsasser, Michael Solomon, Sunil Subbaraman, Ramnath Mukherjee, Bhramar Sci Adv Social and Interdisciplinary Sciences India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening public health interventions early would have helped control transmission in the country and significantly reduced mortality during the second wave, even without harsh lockdowns. We argue that enhanced surveillance at district, state, and national levels and constant assessment of risk associated with increased transmission are critical for future pandemic responsiveness. Building on our retrospective analysis, we provide a tiered data-driven framework for timely escalation of future interventions as a tool for policy-makers. American Association for the Advancement of Science 2022-06-17 /pmc/articles/PMC9205583/ /pubmed/35714183 http://dx.doi.org/10.1126/sciadv.abp8621 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Social and Interdisciplinary Sciences
Salvatore, Maxwell
Purkayastha, Soumik
Ganapathi, Lakshmi
Bhattacharyya, Rupam
Kundu, Ritoban
Zimmermann, Lauren
Ray, Debashree
Hazra, Aditi
Kleinsasser, Michael
Solomon, Sunil
Subbaraman, Ramnath
Mukherjee, Bhramar
Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title_full Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title_fullStr Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title_full_unstemmed Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title_short Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
title_sort lessons from sars-cov-2 in india: a data-driven framework for pandemic resilience
topic Social and Interdisciplinary Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205583/
https://www.ncbi.nlm.nih.gov/pubmed/35714183
http://dx.doi.org/10.1126/sciadv.abp8621
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