ArticleBMC public health2025
An ecological study of COVID-19 outcomes among Florida counties.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- COVID-19 vaccine hesitancy among Latinx individuals in North Texas: Understandings from a community study.Human vaccines & immunotherapeutics · 2025Article
- Navigating distrust and competing priorities during the COVID-19 pandemic: insights from Florida to strengthen cooperation.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDuring the COVID-19 pandemic, Florida reported some of the highest numbers of cases and deaths in the US; however, county-level variation in COVID-19 outcomes has yet to be comprehensively investigated. The present ecological study aimed to assess correlates of COVID-19 outcomes among Florida counties that explain variation in case rate, mortality rate, and case fatality rate (CFR) across pandemic waves.
methodWe obtained county-level administrative data and COVID-19 case reports from public repositories. We tested spatial autocorrelation to assess geographic clustering in COVID-19 case rate, mortality rate, and CFR. Stepwise linear regression was employed to investigate the association between COVID-19 outcomes and 17 demographic, socioeconomic, and health-related county-level predictors.
resultsWe found mortality rate and CFR were significantly higher in rural counties compared to urban counties, among which significant differences in vaccination coverage were also observed. Multivariate analysis found that the percentage of the population aged over 65 years, the percentage of obese people, and the percentage of the rural population were significant predictors of COVID-19 case rate. Median age, vaccination coverage, percentage of people who smoke, and percentage of the population with diabetes were significant influencing factors for CFR. Importantly, higher vaccination coverage was significantly associated with a reduction in case rate (R = -0.26, p = 0.03) and mortality (R = -0.51, p < 0.001). Last, we found that spatial dependencies play a role in explaining variations in COVID-19 CFR among Florida counties.
conclusionOur findings emphasize the need for targeted, equitable public health strategies to reduce disparities and enhance population resilience during public health crises.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.