Contextualizing COVID-19 spread: a county level analysis, urban versus rural, and implications for preparing for the next wave

preprint OA: closed CC-BY-4.0
🔓 Open OA copy View at publisher

Abstract

Background: : Contextual determinants of health including social, environmental, healthcare and others, are a so-called deck of cards one is dealt. The ability to modify health outcomes varies then based upon how one’s hand is played. It is thus of great interest to understand how these determinants associate with the emerging pandemic coronavirus disease 2019 (COVID-19). Methods: : To this end, we conducted a deep-dive analysis into this problem using a recently curated public dataset on COVID-19 that connects infection spread over time to a rich collection of contextual determinants for all counties of the U.S and Washington, D.C. Results: : Using random forest machine learning methodology, we identified a relevant constellation of contextual factors of disease spread which manifest differently for urban and rural counties. Conclusions: : The findings also have clear implications for better preparing for the next wave of disease.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-4.0