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, 2022)
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