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Characterizing COVID-19 waves in urban and rural districts of India
Understanding spatial determinants, i.e., social, infrastructural, and environmental features of a place, which shape infectious disease is critically important for public health. We present an exploration of the spatial determinants of reported COVID-19 incidence across India’s 641 urban and rural...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613454/ https://www.ncbi.nlm.nih.gov/pubmed/37521776 http://dx.doi.org/10.1038/s42949-022-00071-z |
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author | Pandey, Bhartendu Gu, Jianyu Ramaswami, Anu |
author_facet | Pandey, Bhartendu Gu, Jianyu Ramaswami, Anu |
author_sort | Pandey, Bhartendu |
collection | PubMed |
description | Understanding spatial determinants, i.e., social, infrastructural, and environmental features of a place, which shape infectious disease is critically important for public health. We present an exploration of the spatial determinants of reported COVID-19 incidence across India’s 641 urban and rural districts, comparing two waves (2020–2021). Three key results emerge using three COVID-19 incidence metrics: cumulative incidence proportion (aggregate risk), cumulative temporal incidence rate, and severity ratio. First, in the same district, characteristics of COVID-19 incidences are similar across waves, with the second wave over four times more severe than the first. Second, after controlling for state-level effects, urbanization (urban population share), living standards, and population age emerge as positive determinants of both risk and rates across waves. Third, keeping all else constant, lower shares of workers working from home correlate with greater infection risk during the second wave. While much attention has focused on intra-urban disease spread, our findings suggest that understanding spatial determinants across human settlements is also important for managing current and future pandemics. |
format | Online Article Text |
id | pubmed-9613454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96134542022-10-28 Characterizing COVID-19 waves in urban and rural districts of India Pandey, Bhartendu Gu, Jianyu Ramaswami, Anu npj Urban Sustain Article Understanding spatial determinants, i.e., social, infrastructural, and environmental features of a place, which shape infectious disease is critically important for public health. We present an exploration of the spatial determinants of reported COVID-19 incidence across India’s 641 urban and rural districts, comparing two waves (2020–2021). Three key results emerge using three COVID-19 incidence metrics: cumulative incidence proportion (aggregate risk), cumulative temporal incidence rate, and severity ratio. First, in the same district, characteristics of COVID-19 incidences are similar across waves, with the second wave over four times more severe than the first. Second, after controlling for state-level effects, urbanization (urban population share), living standards, and population age emerge as positive determinants of both risk and rates across waves. Third, keeping all else constant, lower shares of workers working from home correlate with greater infection risk during the second wave. While much attention has focused on intra-urban disease spread, our findings suggest that understanding spatial determinants across human settlements is also important for managing current and future pandemics. Nature Publishing Group UK 2022-10-28 2022 /pmc/articles/PMC9613454/ /pubmed/37521776 http://dx.doi.org/10.1038/s42949-022-00071-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pandey, Bhartendu Gu, Jianyu Ramaswami, Anu Characterizing COVID-19 waves in urban and rural districts of India |
title | Characterizing COVID-19 waves in urban and rural districts of India |
title_full | Characterizing COVID-19 waves in urban and rural districts of India |
title_fullStr | Characterizing COVID-19 waves in urban and rural districts of India |
title_full_unstemmed | Characterizing COVID-19 waves in urban and rural districts of India |
title_short | Characterizing COVID-19 waves in urban and rural districts of India |
title_sort | characterizing covid-19 waves in urban and rural districts of india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613454/ https://www.ncbi.nlm.nih.gov/pubmed/37521776 http://dx.doi.org/10.1038/s42949-022-00071-z |
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