{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T09:41:44Z","timestamp":1779356504021,"version":"3.51.4"},"reference-count":61,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T00:00:00Z","timestamp":1671408000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Risk Institute"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>In March 2020, Ohio, along with many other states, enacted a stay-at-home order (i.e., \u201cshutdown\u201d) to limit the spread of COVID-19. As a result of lower traffic, crashes should also have declined. We investigated whether crash rates declined in Ohio during the stay-at-home order and explore possible predictors for the decrease, such as reduced travel in compliance with the order, along with speeding, alcohol, and drug use. In addition, we examined whether support for President Trump would relate to greater travel and greater crashes (particularly during the stay-at-home order, when greater travel indicated lower compliance). The overall rate of crashes fell as people stayed home, mainly due to a decline in minor crashes. In contrast, the rate of serious crashes did not fall. Instead, percentage of alcohol-related crashes increased during the stay-at-home order, and the reduction in travel was associated with greater speeding-related crashes. Because alcohol and speeding tend to increase crash severity, these two factors may explain why severe crash rates were not reduced by lower traffic. Instead, it appears that those drivers remaining on the roads during the shutdown may have been more prone to risky behaviors, evidenced by a greater percentage of alcohol-related crashes across the state during the shutdown and greater speed-related crashes in counties with less traffic. In addition, county-level support for President Trump indirectly predicted greater rates of crashes (of all types) via increased travel (i.e., lower compliance with the shutdown), even while controlling for county-level income, rurality, and Appalachian region. Importantly, this mediated effect was stronger during the weeks of the shutdown, when greater travel indicated lower compliance. Thus, lower compliance with the stay-at-home order and increased risky driving behaviors by remaining drivers may explain why lower traffic did not lead to lower serious crashes.<\/jats:p>","DOI":"10.1371\/journal.pone.0279160","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T18:26:05Z","timestamp":1671474365000},"page":"e0279160","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Ironic effects of political ideology and increased risk-taking in Ohio drivers during COVID-19 shutdown"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1168-325X","authenticated-orcid":true,"given":"Mason Alexander","family":"Shihab","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2844-4995","authenticated-orcid":true,"given":"Brittany","family":"Shoots-Reinhard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2022,12,19]]},"reference":[{"key":"pone.0279160.ref001","article-title":"See which states and cities have told residents to stay at home","author":"S Mervosh","year":"2020","journal-title":"The New York Times [Internet]"},{"key":"pone.0279160.ref002","article-title":"Traffic and Pollution Plummet as U.S. Cities Shut Down for Coronavirus","author":"B Plumer","year":"2020","journal-title":"The New York Times"},{"issue":"1","key":"pone.0279160.ref003","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s13104-019-4881-0","article-title":"Motor vehicle fatalities during Memorial Day weekends, 1981\u20132016","volume":"13","author":"Y Tang","year":"2020","journal-title":"BMC Research Notes."},{"key":"pone.0279160.ref004","article-title":"Time Series Analysis and Forecast of Crash Fatalities during Six Holiday Periods [Internet]","author":"C Liu","year":"2004","journal-title":"National Center for Statistics and Analysis"},{"key":"pone.0279160.ref005","volume-title":"COVID-19 law enforcement analysis & resources: Traffic crashes and fatality\/fatal crash rates [Fact sheet] [Internet]","author":"National Policing Institute","year":"2020"},{"key":"pone.0279160.ref006","volume-title":"Effect of the COVID-Crisis on Traffic Crashes in North Carolina","author":"North Carolina Department of Transportation","year":"2020"},{"key":"pone.0279160.ref007","doi-asserted-by":"crossref","first-page":"106399","DOI":"10.1016\/j.aap.2021.106399","article-title":"Evaluation of motor vehicle crash rates during and after the COVID-19-associated stay-at-home order in Connecticut","volume":"162","author":"ML Doucette","year":"2021","journal-title":"Accident Analysis & Prevention"},{"key":"pone.0279160.ref008","author":"Governors Highway Safety Association","year":"2020","journal-title":"Absent Traffic Jams, Many Drivers Getting More Reckless [Internet]."},{"issue":"1","key":"pone.0279160.ref009","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/0001-4575(93)90102-3","article-title":"Velocity change and fatality risk in a crash\u2014A rule of thumb","volume":"25","author":"HC Joksch","year":"1993","journal-title":"Accident Analysis & Prevention"},{"key":"pone.0279160.ref010","volume-title":"Accidents on main rural highways related to speed, driver, and vehicle","author":"DH Solomon","year":"1964"},{"key":"pone.0279160.ref011","doi-asserted-by":"crossref","first-page":"106225","DOI":"10.1016\/j.aap.2021.106225","article-title":"Speeding through the pandemic: Perceptual and psychological factors associated with speeding during the COVID-19 stay-at-home period","volume":"159","author":"A Tucker","year":"2021","journal-title":"Accident Analysis & Prevention"},{"issue":"1","key":"pone.0279160.ref012","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.paid.2012.08.005","article-title":"Revised reinforcement sensitivity theory: The impact of FFFS and stress on driving","volume":"54","author":"RD Morton","year":"2013","journal-title":"Personality and Individual Differences"},{"key":"pone.0279160.ref013","author":"National Center for Health Statistics","journal-title":"Household Pulse Survey: Anxiety and Depression [Internet]"},{"key":"pone.0279160.ref014","article-title":"U.S. Alcohol Sales Increase 55 Percent in One Week Amid Coronavirus Pandemic","author":"J. 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