Identification of thresholds on population density for understanding transmission of COVID-19

Yusuf Jamal, Mayank Gangwar, Moiz Usmani, Alison Adams, Chang-Yu Wu, Thanh Huong Nguyen, Rita Colwell, Antarpreet Jutla

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article numbere2021GH000449
JournalGeoHealth
Volume6
Issue number9
Early online dateMay 5 2022
DOIs
StatePublished - Sep 2022

Keywords

  • threshold
  • COVID-19
  • logistic regression
  • population density

ASJC Scopus subject areas

  • Water Science and Technology
  • Public Health, Environmental and Occupational Health
  • Pollution
  • Waste Management and Disposal
  • Health, Toxicology and Mutagenesis
  • Management, Monitoring, Policy and Law
  • Epidemiology
  • Global and Planetary Change

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