Role of Geographic Risk Factors in COVID-19 Epidemiology: Longitudinal Geospatial Analysis.

ABSTRACT:

Objective

To perform a geospatial and temporal trend analysis for coronavirus disease 2019 (COVID-19) in a Midwest community to identify and characterize hot spots for COVID-19.

Participants and methods

We conducted a population-based longitudinal surveillance assessing the semimonthly geospatial trends of the prevalence of test confirmed COVID-19 cases in Olmsted County, Minnesota, from March 11, 2020, through October 31, 2020. As urban areas accounted for 84% of the population and 86% of all COVID-19 cases in Olmsted County, MN, we determined hot spots for COVID-19 in urban areas (Rochester and other small cities) of Olmsted County, MN, during the study period by using kernel density analysis with a half-mile bandwidth.

Results

As of October 31, 2020, a total of 37,

SUBMITTER: Juhn YJ 

PROVIDER: S-EPMC8272975 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature