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BACKGROUND: On April 17, 2020, the State of New York (NY) implemented an Executive Order that requires all people in NY to wear a face mask or covering in public settings where social distancing cannot be maintained. Although the Centers for Disease Control and Prevention recommended face mask use by the general public, there is a lack of evidence on the effect of face mask policies on the spread of COVID-19 at the state level. OBJECTIVE: To assess the impact of the Executive Order on face mask use on COVID-19 cases and mortality in NY. DESIGN: A comparative interrupted time series analysis was used to assess the impact of the Executive Order in NY with Massachusetts (MA) as a comparison state. PARTICIPANTS: We analyzed data on COVID-19 in NY and MA from March 25 to May 6, 2020. INTERVENTION: The Executive Order on face mask use in NY. MAIN MEASURES: Daily numbers of COVID-19 confirmed cases and deaths. KEY RESULTS: The average daily number of confirmed cases in NY decreased from 8549 to 5085 after the Executive Order took effect, with a trend change of 341 (95% CI, 187–496) cases per day. The average daily number of deaths decreased from 521 to 384 during the same two time periods, with a trend change of 52 (95% CI, 44–60) deaths per day. Compared to MA, the decreasing trend in NY was significantly greater for both daily numbers of confirmed cases (P = 0.003) and deaths (P < 0.001). CONCLUSIONS: The Executive Order on face mask use in NY led to a significant decrease in both daily numbers of COVID-19 confirmed cases and deaths. Findings from this study provide important evidence to support state-level policies that require face mask use by the general public. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06476-9.
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10.1007/s11606-020-06476-9
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document_parses/pdf_json/d8c1f16fcd3f6ee84c465e6bd05b9c37a4547cdc.json
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document_parses/pmc_json/PMC7837644.xml.json
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Evaluating the Impact of New York’s Executive Order on Face Mask Use on COVID-19 Cases and Mortality: a Comparative Interrupted Times Series Study
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