Analyzing the spatial determinants of local Covid-19 transmission in the United States

The Coronavirus Disease 19 (COVID-19) has quickly spread across the United States (U.S.) since community transmission was first identified in January 2020. While a number of studies have examined individual-level risk factors for COVID-19, few studies have examined geographic hotspots and community drivers associated with spatial patterns in local transmission. The objective of the study is to understand the spatial determinants of the pandemic in counties across the U.S. by comparing socioeconomic variables to case and death data from January 22nd to June 30th 2020. A cluster analysis was performed to examine areas of high-risk, followed by a three-stage regression to examine contextual factors associated with elevated risk patterns for morbidity and mortality. The factors associated with community-level vulnerability included age, disability, language, race, occupation, and urban status. We recommend that cluster detection and spatial analysis be included in population based surveillance strategies to better inform early case detection and prioritize healthcare resources. Published by Elsevier B.V.

Automated summary

This study aimed to understand the spatial determinants of COVID-19 in counties across the U.S. by comparing socioeconomic variables with case and death data. Findings indicated that age, disability, language, race, occupation, and urban status were associated with community-level vulnerability.