Date of Award

January 2021

Document Type

Open Access Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

James Hadler

Abstract

Background. Hospitalizations due to COVID-19, caused by infection with SARS-CoV-2, have disproportionately impacted many throughout the United States, particularly elderly folks, communities of color, and individuals residing in low-income neighborhoods. Objective. This study aims to describe the epidemiology of COVID-19-related hospitalizations in Connecticut in order to elucidate trends in incidence as well as health disparities. Methods. All first-time hospitalizations due to laboratory-confirmed COVID-19 from July 1 to December 31, 2020, including patients’ geocoded residential addresses, were obtained from the Connecticut Department of Public Health. Patients residing in the community were compared to those residing in congregate settings. Community patients were assigned census tract-level poverty and crowding measures based on linking their geocoded addresses to census tracts from the 2014-2018 American Community Survey, and age-adjusted incidence and relative rates were calculated across demographic and SES measures. The distributions of these data were also compared to those from March 1 to June 30, 2020, previously analyzed by COVID-NET. Results. There were 7,058 hospitalizations due to COVID-19 in Connecticut during the study period, the majority (84.3%) of which were patients residing in the community, rather than congregate settings. Hospitalization incidence was significantly higher among community patients that were aged 75 years and above, male, non-Hispanic Black, Hispanic/Latinx, Other race, and living in high poverty and/or high crowding census tracts. There were also significant trends of hospitalization with increasing poverty (P<0.001) and crowding (P<0.001). Disparities were fairly similar in nature between the July to December period and the March to June period. Conclusion. The findings of this study can be used to inform officials on how to prioritize COVID-19 public health efforts as well as address structural inequalities that exist in society.

Comments

This is an Open Access Thesis.

Open Access

This Article is Open Access

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