ArticleBMC public health2021
Identifying US County-level characteristics associated with high COVID-19 burden.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Urban and Rural Disparities in COVID-19 Outcomes in the United States: A Systematic Review.Medical care research and review : MCRR · 2025Pooled it
- Geographic Trends and Geospatial Analysis of Head and Neck Fellowship-Trained Surgeons.Head & neck · 2026Article
- INTEGRATIVE ECOLOGICAL REGRESSION ANALYSIS OF U.S. COUNTY AND STATE LEVEL COVID-19 DEATH DATA FOR STUDYING HEALTH DISPARITY ASSOCIATIONS.The annals of applied statistics · 2025Article
- Trajectories and patterns of US counties' policy responses to the COVID-19 pandemic: A sequence analysis approach.SSM - population health · 2025Article
- Mobile health clinics in a rural setting: a cost analysis and time motion study of La Clínica in Oregon, United States.BMC health services research · 2025Observational
- A Neighborhood-level analysis of mental health distress and income inequality as quasi-longitudinal risk of reported COVID-19 infection and mortality outcomes in Chicago.Dialogues in health · 2023Article
- Using wastewater to overcome health disparities among rural residents.Geoforum; journal of physical, human, and regional geosciences · 2023Article
- Racial residential segregation and COVID-19 vaccine uptake: an analysis of Georgia USA county-level data.BMC public health · 2023Article
- Impact of the COVID-19 pandemic on cancer patients in western Pennsylvania: rural-urban disparities.Cancer causes & control : CCC · 2023Article
- Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence.The Science of the total environment · 2022Article
- Iterative data-driven forecasting of the transmission and management of SARS-CoV-2/COVID-19 using social interventions at the county-level.Scientific reports · 2022Article
- Spatial Clustering of County-Level COVID-19 Rates in the U.S.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundIdentifying county-level characteristics associated with high coronavirus 2019 (COVID-19) burden can help allow for data-driven, equitable allocation of public health intervention resources and reduce burdens on health care systems.
methodsSynthesizing data from various government and nonprofit institutions for all 3142 United States (US) counties, we studied county-level characteristics that were associated with cumulative and weekly case and death rates through 12/21/2020. We used generalized linear mixed models to model cumulative and weekly (40 repeated measures per county) cases and deaths. Cumulative and weekly models included state fixed effects and county-specific random effects. Weekly models additionally allowed covariate effects to vary by season and included US Census region-specific B-splines to adjust for temporal trends.
resultsRural counties, counties with more minorities and white/non-white segregation, and counties with more people with no high school diploma and with medical comorbidities were associated with higher cumulative COVID-19 case and death rates. In the spring, urban counties and counties with more minorities and white/non-white segregation were associated with increased weekly case and death rates. In the fall, rural counties were associated with larger weekly case and death rates. In the spring, summer, and fall, counties with more residents with socioeconomic disadvantage and medical comorbidities were associated greater weekly case and death rates.
conclusionsThese county-level associations are based off complete data from the entire country, come from a single modeling framework that longitudinally analyzes the US COVID-19 pandemic at the county-level, and are applicable to guiding government resource allocation policies to different US counties.
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.