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

Autor: Budhwani, Karim I1,2 (AUTHOR), Budhwani, Henna2 (AUTHOR), Podbielski, Ben3 (AUTHOR)
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Zdroj: Journal of Medical Internet Research. Feb2021, Vol. 23 Issue 2, pN.PAG-N.PAG. 1p.
Abstrakt: Related Articles Preprint: https://preprints.jmir.org/preprint/22195 Peer-Review Report by Anonymous: https://med.jmirx.org/2021/1/e27103/ Peer-Review Report by Ayman A Allam (Reviewer CK): https://med.jmirx.org/2021/1/e27257/ Author Responses to Peer-Review Reports: https://med.jmirx.org/2021/1/e27258/ 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. JMIRx Med 2021;2(1):e22195 doi:10.2196/22195 [ABSTRACT FROM AUTHOR]
Databáze: Library, Information Science & Technology Abstracts
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