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Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19

Pathways of transmission of coronavirus (COVID‐19) disease in the human population are still emerging. However, empirical observations suggest that dense human settlements are the most adversely impacted, corroborating a broad consensus that human‐to‐human transmission is a key mechanism for the rap...

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Autores principales: Jamal, Yusuf, Gangwar, Mayank, Usmani, Moiz, Adams, Alison E., Wu, Chang‐Yu, Nguyen, Thanh H., Colwell, Rita, Jutla, Antarpreet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347488/
https://www.ncbi.nlm.nih.gov/pubmed/35935574
http://dx.doi.org/10.1029/2021GH000449
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author Jamal, Yusuf
Gangwar, Mayank
Usmani, Moiz
Adams, Alison E.
Wu, Chang‐Yu
Nguyen, Thanh H.
Colwell, Rita
Jutla, Antarpreet
author_facet Jamal, Yusuf
Gangwar, Mayank
Usmani, Moiz
Adams, Alison E.
Wu, Chang‐Yu
Nguyen, Thanh H.
Colwell, Rita
Jutla, Antarpreet
author_sort Jamal, Yusuf
collection PubMed
description Pathways of transmission of coronavirus (COVID‐19) disease in the human population are still emerging. However, empirical observations suggest that dense human settlements are the most adversely impacted, corroborating a broad consensus that human‐to‐human transmission is a key mechanism for the rapid spread of this disease. Here, using logistic regression techniques, estimates of threshold levels of population density were computed corresponding to the incidence (case counts) in the human population. Regions with population densities greater than 3,000 person per square mile in the United States have about 95% likelihood to report 43,380 number of average cumulative cases of COVID‐19. Since case numbers of COVID‐19 dynamically changed each day until 30 November 2020, ca. 4% of US counties were at 50% or higher probability to 38,232 number of COVID‐19 cases. While threshold on population density is not the sole indicator for predictability of coronavirus in human population, yet it is one of the key variables on understanding and rethinking human settlement in urban landscapes.
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spelling pubmed-93474882022-08-03 Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19 Jamal, Yusuf Gangwar, Mayank Usmani, Moiz Adams, Alison E. Wu, Chang‐Yu Nguyen, Thanh H. Colwell, Rita Jutla, Antarpreet Geohealth Research Article Pathways of transmission of coronavirus (COVID‐19) disease in the human population are still emerging. However, empirical observations suggest that dense human settlements are the most adversely impacted, corroborating a broad consensus that human‐to‐human transmission is a key mechanism for the rapid spread of this disease. Here, using logistic regression techniques, estimates of threshold levels of population density were computed corresponding to the incidence (case counts) in the human population. Regions with population densities greater than 3,000 person per square mile in the United States have about 95% likelihood to report 43,380 number of average cumulative cases of COVID‐19. Since case numbers of COVID‐19 dynamically changed each day until 30 November 2020, ca. 4% of US counties were at 50% or higher probability to 38,232 number of COVID‐19 cases. While threshold on population density is not the sole indicator for predictability of coronavirus in human population, yet it is one of the key variables on understanding and rethinking human settlement in urban landscapes. John Wiley and Sons Inc. 2022-09-01 /pmc/articles/PMC9347488/ /pubmed/35935574 http://dx.doi.org/10.1029/2021GH000449 Text en © 2022 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Article
Jamal, Yusuf
Gangwar, Mayank
Usmani, Moiz
Adams, Alison E.
Wu, Chang‐Yu
Nguyen, Thanh H.
Colwell, Rita
Jutla, Antarpreet
Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title_full Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title_fullStr Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title_full_unstemmed Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title_short Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19
title_sort identification of thresholds on population density for understanding transmission of covid‐19
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347488/
https://www.ncbi.nlm.nih.gov/pubmed/35935574
http://dx.doi.org/10.1029/2021GH000449
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