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ORCID

https://orcid.org/0000-0002-3744-1542

Access Type

Open Access Thesis

Document Type

thesis

Degree Program

Public Health

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2022

Month Degree Awarded

May

Abstract

The COVID-19 pandemic has heightened the need for fine-scale analysis of the clustering of cases of infectious disease in order to better understand and prevent the localized spread of infection. The students living on the University of Massachusetts, Amherst campus provided a unique opportunity to do so, due to frequent mandatory testing during the 2020-2021 academic year, and dense living conditions. The South-West dormitory area is of particular interest due to its extremely high population density, housing around half of students living on campus during normal conditions. Using data gathered by the Public Health Promotion Center (PHPC), we analyzed the clustering of SARS-CoV 2 cases in three-dimensional space as well as time within and between the three tallest occupied buildings in the Southwest dormitory area, John Quincy Adams, Kennedy, and Coolidge. We used the SaTScan program and its Space-Time Permutation Model, which searches for areas with a greater than expected number of cases. Analysis was done at various levels of spacial detail. Additionally, this analysis was compared to the purely temporal surveillance method, CDC’s Early Aberration Reporting System (EARS). Analysis with SaTScan at the room and floor level showed multiple significant clusters within the Coolidge dormitory building. Floor-level analysis was found to be as sensitive as and less burdensome than room-level analysis. We recommend using scan statistics in conjunction with other methods such as purely temporal scans and wastewater analysis to detect and respond to outbreaks on campus.

DOI

https://doi.org/10.7275/28640200

First Advisor

Andrew Lover

Second Advisor

Laura Balzer

Third Advisor

John Staudenmayer

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