ArticlePLOS global public health2022
County-level societal predictors of COVID-19 cases and deaths changed through time in the United States: A longitudinal ecological study.
Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Scientific breakthroughs in the COVID-19 era: embracing Ernst Mayr towards an epistemic renewal of Medicine.Einstein (Sao Paulo, Brazil) · 2026Article
- Stability and Volatility in the Contextual Predictors of Working-Age Mortality in the United States.Journal of health and social behavior · 2025Article
- Neighbourhood immigrant density and COVID-19 infection and hospitalisation among healthcare workers in Sweden: a register-based observational study.BMJ public health · 2025Article
- County-level societal predictors of COVID-19 cases and deaths changed through time in the United States: A longitudinal ecological study.PLOS global public health · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
People of different racial/ethnic backgrounds, demographics, health, and socioeconomic characteristics have experienced disproportionate rates of infection and death due to COVID-19. This study tests if and how county-level rates of infection and death have changed in relation to societal county characteristics through time as the pandemic progressed. This longitudinal study sampled monthly county-level COVID-19 case and death data per 100,000 residents from April 2020 to March 2022, and studied the relationships of these variables with racial/ethnic, demographic, health, and socioeconomic characteristics for 3125 or 97.0% of U.S. counties, accounting for 96.4% of the U.S. population. The association of all county-level characteristics with COVID-19 case and death rates changed significantly through time, and showed different patterns. For example, counties with higher population proportions of Black, Native American, foreign-born non-citizen, elderly residents, households in poverty, or higher income inequality suffered disproportionately higher COVID-19 case and death rates at the beginning of the pandemic, followed by reversed, attenuated or fluctuating patterns, depending on the variable. Patterns for counties with higher White versus Black population proportions showed somewhat inverse patterns. Counties with higher female population proportions initially had lower case rates but higher death rates, and case and death rates become more coupled and fluctuated later in the pandemic. Counties with higher population densities had fluctuating case and death rates, with peaks coinciding with new variants of COVID-19. Counties with a greater proportion of university-educated residents had lower case and death rates throughout the pandemic, although the strength of this relationship fluctuated through time. This research clearly shows that how different segments of society are affected by a pandemic changes through time. Therefore, targeted policies and interventions that change as a pandemic unfolds are necessary to mitigate its disproportionate effects on vulnerable populations, particularly during the first six months of a pandemic.
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Registered trials
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