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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Published in | Geohealth Vol. 6; no. 9; pp. e2021GH000449 - n/a |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken
John Wiley & Sons, Inc
01.09.2022
John Wiley and Sons Inc American Geophysical Union (AGU) |
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Online Access | Get full text |
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Abstract | 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.
Plain Language Summary
Population density is certainly one of the key factors influencing the transmission of infectious diseases like COVID‐19. It is approximated that in continental United States, population density of 1,192 per square mile and higher presents 50% probability of getting 38,232 number of COVID‐19 cases.
Key Points
Based on data from the USA, the population density of 1,192 persons per square mile represented a 50% or higher probability of more than 38,000 COVID‐19 cumulative cases at county scale as of 30 November 2020
About 35 counties in the USA with population density greater or equal to 3,000 per square mile are at very high chances (95% or higher) of more than 43,000 cumulative cases at county scale as of 30 November 2020
Analysis shows the vulnerability of urban towns to respiratory infectious disease |
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AbstractList | 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.
Population density is certainly one of the key factors influencing the transmission of infectious diseases like COVID‐19. It is approximated that in continental United States, population density of 1,192 per square mile and higher presents 50% probability of getting 38,232 number of COVID‐19 cases.
Based on data from the USA, the population density of 1,192 persons per square mile represented a 50% or higher probability of more than 38,000 COVID‐19 cumulative cases at county scale as of 30 November 2020
About 35 counties in the USA with population density greater or equal to 3,000 per square mile are at very high chances (95% or higher) of more than 43,000 cumulative cases at county scale as of 30 November 2020
Analysis shows the vulnerability of urban towns to respiratory infectious disease 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.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. 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. Plain Language Summary Population density is certainly one of the key factors influencing the transmission of infectious diseases like COVID‐19. It is approximated that in continental United States, population density of 1,192 per square mile and higher presents 50% probability of getting 38,232 number of COVID‐19 cases. Key Points Based on data from the USA, the population density of 1,192 persons per square mile represented a 50% or higher probability of more than 38,000 COVID‐19 cumulative cases at county scale as of 30 November 2020 About 35 counties in the USA with population density greater or equal to 3,000 per square mile are at very high chances (95% or higher) of more than 43,000 cumulative cases at county scale as of 30 November 2020 Analysis shows the vulnerability of urban towns to respiratory infectious disease Abstract 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. 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. 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. Based on data from the USA, the population density of 1,192 persons per square mile represented a 50% or higher probability of more than 38,000 COVID‐19 cumulative cases at county scale as of 30 November 2020 About 35 counties in the USA with population density greater or equal to 3,000 per square mile are at very high chances (95% or higher) of more than 43,000 cumulative cases at county scale as of 30 November 2020 Analysis shows the vulnerability of urban towns to respiratory infectious disease |
Author | Nguyen, Thanh H. Usmani, Moiz Gangwar, Mayank Adams, Alison E. Colwell, Rita Jutla, Antarpreet Jamal, Yusuf Wu, Chang‐Yu |
AuthorAffiliation | 1 GeoHLab Department of Environmental Engineering Sciences University of Florida Gainesville FL USA 3 Department of Environmental Engineering Sciences University of Florida Gainesville FL USA 2 School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville FL USA 5 University of Maryland Institute of Advanced Computer Studies University of Maryland College Park MD USA 4 Civil and Environmental Engineering University of Illinois Urbana IL USA |
AuthorAffiliation_xml | – name: 2 School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville FL USA – name: 3 Department of Environmental Engineering Sciences University of Florida Gainesville FL USA – name: 5 University of Maryland Institute of Advanced Computer Studies University of Maryland College Park MD USA – name: 4 Civil and Environmental Engineering University of Illinois Urbana IL USA – name: 1 GeoHLab Department of Environmental Engineering Sciences University of Florida Gainesville FL USA |
Author_xml | – sequence: 1 givenname: Yusuf orcidid: 0000-0002-0540-7892 surname: Jamal fullname: Jamal, Yusuf organization: University of Florida – sequence: 2 givenname: Mayank orcidid: 0000-0001-7605-0256 surname: Gangwar fullname: Gangwar, Mayank organization: University of Florida – sequence: 3 givenname: Moiz orcidid: 0000-0002-2718-8387 surname: Usmani fullname: Usmani, Moiz organization: University of Florida – sequence: 4 givenname: Alison E. surname: Adams fullname: Adams, Alison E. organization: University of Florida – sequence: 5 givenname: Chang‐Yu orcidid: 0000-0002-2100-8816 surname: Wu fullname: Wu, Chang‐Yu organization: University of Florida – sequence: 6 givenname: Thanh H. orcidid: 0000-0002-5461-5233 surname: Nguyen fullname: Nguyen, Thanh H. organization: University of Illinois – sequence: 7 givenname: Rita orcidid: 0000-0001-5432-1502 surname: Colwell fullname: Colwell, Rita organization: University of Maryland – sequence: 8 givenname: Antarpreet orcidid: 0000-0002-8191-2348 surname: Jutla fullname: Jutla, Antarpreet email: ajutla@ufl.edu organization: University of Florida |
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Snippet | Pathways of transmission of coronavirus (COVID‐19) disease in the human population are still emerging. However, empirical observations suggest that dense human... Pathways of transmission of coronavirus (COVID-19) disease in the human population are still emerging. However, empirical observations suggest that dense human... Abstract Pathways of transmission of coronavirus (COVID‐19) disease in the human population are still emerging. However, empirical observations suggest that... |
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SubjectTerms | Coronaviruses COVID-19 vaccines COVID‐19 Disease transmission Economic indicators Epidemics General or Miscellaneous Geohealth Human populations Human settlements Infectious diseases Influenza Land area logistic regression Population density Probability Public Health Severe acute respiratory syndrome coronavirus 2 The COVID‐19 pandemic: linking health, society and environment threshold |
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Title | Identification of Thresholds on Population Density for Understanding Transmission of COVID‐19 |
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