{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T19:25:07Z","timestamp":1766690707389,"version":"3.37.3"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>The effectiveness and sustainability of masking policies as a pandemic control measure remain uncertain. Our aim was to evaluate different masking policy types on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence and to identify factors and conditions impacting effectiveness.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Nationwide, retrospective cohort study of US counties from 4\/4\/2020\u201328\/6\/2021. Policy impacts were estimated using interrupted time-series models with the masking policy change date (eg, recommended-to-required, no-recommendation-to-recommended, no-recommendation-to-required) modeled as the interruption. The primary outcome was change in SARS-CoV-2 incidence rate during the 12 weeks after the policy change; results were stratified by coronavirus disease 2019 (COVID-19) risk level. A secondary analysis was completed using adult vaccine availability as the policy change.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In total, N = 2954 counties were included (2304 recommended-to-required, 535 no-recommendation-to-recommended, 115 no-recommendation-to-required). Overall, indoor mask mandates were associated with 1.96 fewer cases\/100 000\/week (cumulative reduction of 23.52\/100 000 residents during the 12 weeks after policy change). Reductions were driven by communities with critical and extreme COVID-19 risk, where masking mandated policies were associated with an absolute reduction of 5 to 13.2 cases\/100 000 residents\/week (cumulative reduction of 60 to 158 cases\/100 000 residents over 12 weeks). Impacts in low- and moderate-risk counties were minimal (&amp;lt;1 case\/100 000 residents\/week). After vaccine availability, mask mandates were not associated with significant reductions at any risk level.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Masking policy had the greatest impact when COVID-19 risk was high and vaccine availability was low. When transmission risk decreases or vaccine availability increases, the impact was not significant regardless of mask policy type. Although often modeled as having a static impact, masking policy effectiveness may be dynamic and condition dependent.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/cid\/ciad115","type":"journal-article","created":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T04:57:18Z","timestamp":1681880238000},"page":"203-211","source":"Crossref","is-referenced-by-count":6,"title":["Condition-Dependent and Dynamic Impacts of Indoor Masking Policies for Coronavirus Disease 2019 Mitigation: A Nationwide, Interrupted Time-Series Analysis"],"prefix":"10.1093","volume":"77","author":[{"given":"Zeynep","family":"Ertem","sequence":"first","affiliation":[{"name":"Systems Science and Industrial Engineering Department, Binghamton University, State University of New York , Binghamton, New York , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard E","family":"Nelson","sequence":"additional","affiliation":[{"name":"Division of Epidemiology, University of Utah School of Medicine , Salt Lake City, Utah , USA"},{"name":"IDEAS Center, Veterans Affairs Salt Lake City Healthcare System , Salt Lake City, Utah , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elissa M","family":"Schechter-Perkins","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Boston University School of Medicine and Boston Medical Center , Boston, Massachusetts , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amera","family":"Al-Amery","sequence":"additional","affiliation":[{"name":"Systems Science and Industrial Engineering Department, Binghamton University, State University of New York , Binghamton, New York , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xilin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Systems Science and Industrial Engineering Department, Binghamton University, State University of New York , Binghamton, New York , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9658-5124","authenticated-orcid":false,"given":"Westyn","family":"Branch-Elliman","sequence":"additional","affiliation":[{"name":"VA Boston Center for Healthcare Organization and Implementation Research (CHOIR) , Boston, Massachusetts , USA"},{"name":"VA Boston Healthcare System, Department of Medicine, Section of Infectious Diseases , West Roxbury, Massachusetts , USA"},{"name":"Department of Medicine, Harvard Medical School , Boston, Massachusetts , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,4,19]]},"reference":[{"year":"2021","author":"US Centers for Disease Control and Prevention","key":"2023072620380345700_ciad115-B1"},{"key":"2023072620380345700_ciad115-B2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/s11077-020-09381-4","article-title":"COVID-19 and the policy sciences: initial reactions and 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