ArticlePloS one2022
A machine learning and clustering-based approach for county-level COVID-19 analysis.
Article in PloS one, 2022. 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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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
6 citing papers in PubMed.
- Observational
- The U.S. diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis.Primary care diabetes · 2026Article
- Can past variants of SARS-CoV-2 predict the impact of future variants? Machine learning for early warning of US counties at risk.Health care management science · 2025Article
- Trends in epidemics pertaining to notifiable infectious diseases in China and prediction models for key diseases: a case study of Ziyang County.BMC public health · 2025Article
- Ten Americas: a systematic analysis of life expectancy disparities in the USA.Lancet (London, England) · 2024Article
- Longitudinal Cluster Analysis of Hemodialysis Patients with COVID-19 in the Pre-Vaccination Era.Life (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world. Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease. In part, this is due to variation in human behavior and environmental factors that impact disease propagation. This is especially true for regionally specific predictive models due to either limited case histories or other unique factors characterizing the region. This paper employs both supervised and unsupervised methods to identify the critical county-level demographic, mobility, weather, medical capacity, and health related county-level factors for studying COVID-19 propagation prior to the widespread availability of a vaccine. We use this feature subspace to aggregate counties into meaningful clusters to support more refined disease analysis efforts.
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