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 in the human population. Regions with population densities greater than 3000 person per square mile in the United States have about 95% likelihood to get infected with COVID-19. Since case numbers of COVID-19 dynamically changed each day until November 30, 2020, ca. 4% of US counties were at 50% or higher risk of COVID-19 transmission. 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.
Plane 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 1192 per square mile and higher presents 50% probability of getting infected with COVID-19.
Key Points
Based on data from the USA, the population density of 1192 persons per square mile represented a 50% or higher probability of risk of transmission of COVID-19.
About 35 counties in the USA are at very high risk of transmission potential (95% or higher) for COVID-19.
Analysis shows the vulnerability of urban towns to respiratory infectious disease
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This study did not receive any funding
Author Declarations
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Data Availability
Raw data sets are publicly available and can be accessed using weblinks provided. Datasets generated in this study are available on openly accessible data servers.
https://github.com/nytimes/covid-19-data
https://www.census.gov/data/datasets/time-series/demo/popest/2010s-counties-total.html
https://www.census.gov/library/publications/2011/compendia/usa-counties-2011.html#LND