ArticlePreventing chronic disease2020
Variation in Risk of COVID-19 Infection and Predictors of Social Determinants of Health in Miami-Dade County, Florida.
Article in Preventing chronic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Geographic disparities in violent crime during the COVID-19 lockdown in Miami-Dade County, Florida, 2018-2020.Journal of experimental criminology · 2023Article
- Community vulnerability to the COVID-19 pandemic: A narrative synthesis from an ecological perspective.Journal of global health · 2022Article
- Geospatial Perspectives on the Intersection of Chronic Disease and COVID-19.Preventing chronic disease · 2022Article
- Assessing COVID-19 risk with temporal indices and geographically weighted ordinal logistic regression in US counties.PloS one · 2022Article
- [Social inequalities in the regional spread of SARS-CoV-2 infections].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2021Article
- Association of Socioeconomic Characteristics With Disparities in COVID-19 Outcomes in Japan.JAMA network open · 2021Article
Corrections and comments
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Authors and funding
1 author.
Funding
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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 disadvantage 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.
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