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Open Access Thesis
Master of Science (M.S.)
Year Degree Awarded
Month Degree Awarded
U.S. state governments have implemented numerous policies to help mitigate the spread of COVID-19. While there is strong biological evidence supporting the wearing of face masks or coverings in public spaces, the impact of public masking policies remains unclear. We aimed to evaluate how early versus delayed implementation of state-level public masking orders impacted subsequent COVID-19 growth rates. We defined “early” implementation as having a state-level mandate in place before September 1, 2020, the approximate start of the school-year. We defined COVID-19 growth rates as the relative increase in confirmed cases 7, 14, 21, 30, 45, 60-days after September 1. Primary analyses used targeted maximum likelihood estimation (TMLE) with Super Learner and considered a wide range of potential confounders to account for differences between states. In secondary analyses, we took an unadjusted approach and calculated the average COVID-19 growth rate among early-implementing states divided by the average COVID-19 growth rate among late-implementing states. At a national level, the expected growth rate after 14-days was 4%lower with early vs. delayed implementation (aRR: 0.96; 95%CI: 0.95-0.98). Associations did not plateau over time, but instead grew linearly. After 60-days, the expected growth rate was 16% lower with early vs. delayed implementation (aRR:0.84; 95%CI: 0.78-0.91). Unadjusted estimates were exaggerated (e.g. 60-day RR:0.72; 95%CI: 0.60-0.84). Sensitivity analyses varying the timing of the masking order yielded similar results. In both the short and long term, state-level public masking mandates were associated with lower COVID-19 growth rates. Given their low-cost and minimal (if any) impact on the economy, masking policies are promising public health strategies to mitigate further spread of COVID-19.
Laura B. Balzer
Nicholas G. Reich
Wong, Angus K., "Evaluating Public Masking Mandates on COVID-19 Growth Rates in U.S. States" (2021). Masters Theses. 1080.