{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:56:56Z","timestamp":1781888216072,"version":"3.54.5"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Local COVID-19 policies are increasingly recognized as determinants of variation in disease transmission and other health outcomes. There is significant geographic variability in policy implementation, but little understanding of factors contributing to policy variation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data and methods<\/jats:title>\n                    <jats:p>\n                      Using data from the US COVID-19 County Policy Database, we analyzed correlates of county-level policy implementation (\n                      <jats:italic>N<\/jats:italic>\n                      \u202f=\u202f309 counties in 50 states across 2020\u20132021). Using multivariable regression, we examined the association of county characteristics with policy comprehensiveness overall and across three policy domains (containment\/closure, economic support, public health). We focused on county characteristics capturing sociodemographic, political, and environmental factors that may represent predictors of policy adoption.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Urbanicity was positively associated with increased adoption of more public health policies, Democratic voter percentages were positively associated with increased adoption of all policies, and average temperature was negatively associated with adoption of all policies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings provide insight into the possible predictors of the variation in local policy implementation during the COVID-19 pandemic, as well as informing future policy research and public health crisis management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1797664","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:43:58Z","timestamp":1781887438000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A cross-sectional analysis of county-level determinants of pandemic-era policy implementation"],"prefix":"10.3389","volume":"14","author":[{"given":"Natasha J.","family":"Williams","sequence":"first","affiliation":[{"name":"NYU Langone Health, Department of Population Health, Institute for Excellence in Health Equity","place":["New York, NY, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie F.","family":"Molina","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, University of California, San Francisco","place":["San Francisco, CA, United States"]},{"name":"Department of Medicine, Division of Clinical Informatics and Digital Transformation, University of California, San Francisco","place":["San Francisco, CA, United States"]},{"name":"Action Research Center for Health, University of California, San Francisco","place":["San Francisco, CA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy","family":"Yunyu Chiang","sequence":"additional","affiliation":[{"name":"UCSF Division of General Internal Medicine, Department of Medicine at the San Francisco General Hospital and Trauma Center, University of California, San Francisco","place":["San Francisco, CA, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soo","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of California, San Francisco","place":["San Francisco, CA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Brandner","sequence":"additional","affiliation":[{"name":"Department 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