Are Stay-at-Home and Face Mask Orders Effective in Slowing Down COVID-19 Transmission? – A Statistical Study of U.S. Case Counts in 2020

Wang Ping () and Le Huy ()
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Wang Ping: Greenberg School of Risk Management, St John’s University, 101 Astor Place, New York, NY, 10003, USA
Le Huy: Greenberg School of Risk Management, Insurance and Actuarial Science, St John’s University, New York, NY, USA

Asia-Pacific Journal of Risk and Insurance, 2023, vol. 17, issue 1, 1-32

Abstract: Whether the stay-at-home order and face mask mandate are effective in slowing down the COVID-19 virus transmission is up for debate. To investigate this matter, we employ a unique angle. A two-wave logistic equation is proposed and then fitted to the cumulative case counts of all 50 states in the U.S. from the onset to early December of 2020 when vaccinating begins at large scale. The data period is confined to isolate the effects of executive orders from that of vaccination. The length of the first wave’s accelerating phase is regressed on variables describing the stay-at-home order and face mask mandate, along with control variables. A state’s lockdown duration is discovered to be negatively related to the time it takes for the virus to transit from accelerating to decelerating rates. This finding provides statistical support to the executive orders and can be useful in guiding risk management of future pandemics.

Keywords: COVID-19; stay-at-home; mask; logistic; pandemic management (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/apjri-2022-0007

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