Work

Evaluating Population Density as a Parameter for Optimizing COVID-19 Testing: Statistical Analysis

Year: 2020

Type: article

Abstract: BACKGROUND: SARS-CoV-2 transmission risk generally increases with the proximity of those shedding the virus to those susceptible to infection. Thus, this risk is a function of both the number of people and the area they occupy. However, the latter continues to evade the COVID-19 testing policy. OBJECTIVE: The aim of this study is to analyze per capita COVID-19 testing data reported for Alabama to evaluate whether testing realignment along population density, rather than density agnostic per capita, would be more effective. METHODS: Descriptive statistical analyses were performed for population, density, COVID-19 tests administered, and positive cases for all 67 Alabama counties. RESULTS: =.02) between tests per capita and the number of cases. In terms of population density, new cases were higher in areas with a higher population density, despite relatively lower test rates as a function of density. CONCLUSIONS: Increased testing in areas with lower population density has the potential to induce a false sense of security even as cases continue to rise sharply overall.

Source: JMIRx Med

DOI: 10.2196/22195

Authors: Karim I. Budhwani, Henna Budhwani, Ben Podbielski

Institutions: University of Alabama at Birmingham, Birmingham Repertory Theatre

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,000