Use of Population Weighted Density Index for Coronavirus Spread in the United States

Abstract

**Background:** Understanding how population density affected the transmission of COVID-19 is vitally important, since crowded cities were the epicenters for the disease. Since human contact was the main cause of the spread, population-weighted densities have been shown to be a better measure than conventional densities, since the variation in density across subareas matters more than the density in the total area. **Objectives:** This study investigates the impact of population-weighted density and other demographics on the rate of COVID-19 spread in the United States. **Methods:** The study considers population-weighted density and many other demographics. The population-weighted density index is the weighted average of density across the tracts, where tracts are weighted by population. Multivariate analysis has been used to determine the elasticity of the spread. **Results:** Using U.S. county-level data, we calculated the elasticity of COVID-19 spread with respect to population-weighted density to be 0.085 after controlling for other factors. In addition to the density, the proportion of people over 65 years of age, the number of total healthcare workers, and average temperature in each county positively contributed to the case numbers, while education level and income per capita had a negative effect. **Discussion:** For the spread, understanding the population characteristics and dynamics is as important as understanding the infectious disease itself. This will help policy makers to utilize and reallocate the resources more effectively. If the spread is successfully contained early, there will be less stress placed upon the healthcare system, resulting in better healthcare access for those who are sick. **Conclusions:** Our analysis suggests that population-weighted density can be a useful tool to control and manage outbreaks, especially within the early stage of the spread. We presented the early dynamics of the spread and recommended a policy measure on how to transfer healthcare workers from low-spread-risk areas to high-spread-risk areas to utilize resources better.