Abstract
Miami-Dade County zip code-level (N = 91 zip codes) coronavirus disease 2019 (COVID-19) cases (N = 89,556 as of July 21, 2020) reported from the Florida Department of Health were used to estimate rates of COVID-19 per 1,000 population at the census block group level (N = 1,594 study block groups). To identify associations between rates of COVID-19 infections and multidimensional indexes of social determinants of health (SDOH) across Miami-Dade County, Florida, I applied a global model (ordinary least squares) and a local regression model (geographically weighted regression). Findings indicated that a social disadvant- age index positively affected COVID-19 infection rates, whereas a socioeconomic status and opportunity index and a convergence of vulnerability index had an inverse but significant connection to COVID-19 infection rates over the study area. Rates of COVID-19 infections were localized to specific geographic areas and ranged from 0 to 60.75 per 1,000 population per square mile.
| Original language | English |
|---|---|
| Pages (from-to) | 1-5 |
| Number of pages | 5 |
| Journal | Preventing Chronic Disease |
| Volume | 17 |
| DOIs | |
| State | Published - Oct 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020. All rights reserved.
Funding
No funding was secured for this study. The author has no financial relationships relevant to this article and no conflicts of interest to disclose. No copyrighted surveys, instruments, or tools were used in this secondary data analysis.
ASJC Scopus Subject Areas
- Health Policy
- Public Health, Environmental and Occupational Health
Disciplines
- Health Policy
- Public Health
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