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

Academic 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: Tests reported per capita appeared to suggest widespread statewide testing. However, there was little correlation (r=0.28, P=.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.
  • Authors

    Keywords

  • COVID-19, SARS-CoV-2, coronavirus, infectious diseases, per capita, policy, population density, testing
  • Digital Object Identifier (doi)

    Pubmed Id

  • 7822186
  • Author List

  • Budhwani KI; Budhwani H; Podbielski B
  • Start Page

  • e22195
  • Volume

  • 2
  • Issue

  • 1