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KMID : 1044620210540040238
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Journal of Preventive Medicine and Public Health
2021 Volume.54 No. 4 p.238 ~ p.244
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Did the Timing of State Mandated Lockdown Affect the Spread of COVID-19 Infection? A County-level Ecological Study in the United States
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Trivedi Megh M.
Das Anirudha
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Abstract
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Objectives: Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States.
Methods: A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R2 value from the multiple regression were chosen.
Results: The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment.
Conclusions: The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.
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KEYWORD
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COVID-19, Demography, Epidemiology, Pandemics, Quarantine, Socioeconomic factors
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