Statistical Analysis of COVID-19 Case Data from U.S. Colleges

Pommersheim, Catherine, School of Engineering and Applied Science, University of Virginia
French, Brent, MD-BIOM Biomedical Eng, University of Virginia

The COVID-19 pandemic, caused by the virus SARS-CoV-2, began as an outbreak in Wuhan, China in late 2019 and made its way to the United States in early 2020. Since then, restrictions have been enacted to limit disease transmission and protect the public from infection. Initial confusion surrounding the most effective policies led to widespread distrust of the scientific community which manifested as the anti-mask and anti-vaccine movements that gained momentum throughout the pandemic. In order to more quickly assemble a response against a disease to limit infections and establish trust in public health officials and institutions, COVID-19 transmission will be analyzed to identify which policies are most effective in limiting its spread. Colleges in the United States will serve as the subjects of this study as they mimic semi-urban population dynamics with the added ability to monitor positive COVID-19 cases among the student body. To perform this investigation, regional variance in mask compliance was analyzed, trends in COVID-19 positive case data were identified, and a review of individual schools’ preventative measures were compared to provide insight into how to best limit COVID-19 transmission. The results unexpectedly showed little association between strict COVID-19 policies and the proportion of positive cases out of undergraduate populations. In fact, schools with high proportions of COVID-19 cases report implementing thorough policies which is seen at both UVA and Johns Hopkins. The most significant confounding variable revealed through further investigation is policy compliance levels from individual student bodies which must be investigated and accounted for to fully understand COVID-19 transmission patterns.

BS (Bachelor of Science)
COVID-19, transmission, compliance, public health policy
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