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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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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. |
format | Online Article Text |
id | pubmed-9205583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
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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