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Using spatial and temporal modeling to visualize the effects of U.S. state issued stay at home orders on COVID-19.

ABSTRACT: Coronavirus disease 2019 dominated and augmented many aspects of life beginning in early 2020. Related research and data generation developed alongside its spread. We developed a Bayesian spatio-temporal Poisson disease mapping model for estimating real-time characteristics of the coronavirus disease in the United States. We also created several dashboards for visualization of the statistical model for fellow researchers and simpler spatial and temporal representations of the disease for consumption by analysts and data scientists in the policymaking community in our region. Findings suggest that the risk of confirmed cases is higher for health regions under partial stay at home orders and lower in health regions under full stay at home orders, when compared to before stay at home orders were declared. These results confirm the benefit of state-issued stay at home orders as well as suggest compliance to the directives towards the older population for adhering to social distancing guidelines.

SUBMITTER: Carroll R

PROVIDER: S-EPMC8260658 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceTo cope with the continuing coronavirus disease 2019 (COVID-19) pandemic, state and local officials need information on the effectiveness of policies aimed at curbing disease spread, as well as state-specific characteristics, like the racial mix, associated with increased risks related to the disease.ObjectiveTo investigate whether state-imposed stay-at-home orders (SAHOs) and the proportion of African American population in a state were associated with the state-level COVID-19 cases.Design, setting, and participantsThis cross-sectional study used daily, state-level data on COVID-19 cases, tests, and fatalities from the COVID Tracking Project. Data from March 1 to May 4, 2020, for all states (except Washington state) as well as the District of Columbia were used.ExposuresThe key exposure variables were state-level SAHO (1 if in place, 0 otherwise), and proportion of state population who are African American.Main outcomes and measuresThe primary outcome was daily cumulative COVID-19 case rates. A secondary outcome was subsequent COVID-19 fatality rates, derived using mean cumulative fatality rates 21 to 28 days after each date. Multivariate regression models were estimated.ResultsThe final sample included 3023 pooled state- and day-level observations. The mean (SD) cumulative positive case rate was 103.186 (200.067) cases per 100 000 state population, the mean (SD) cumulative test rate was 744.23 (894.944) tests per 100 000 state population, and the mean (SD) subsequent cumulative fatality rate was 12.923 (21.737) deaths per 100 000 state population. There was a negative association of SAHOs with cumulative case rates (β = -1.166; 95% CI, -1.484 to -0.847; P < .001) and subsequent fatality rates (β = -0.204; 95% CI, -0.294 to -0.113; P < .001). Estimation analyses indicated that expected cumulative case rates would have been more than 200% higher and fatality rates approximately 22% higher if there were no SAHOs, as compared with SAHOs fully in place. A higher proportion of African American population was associated with higher case rates (β = 0.045; 95% CI, 0.014 to 0.077; P = .001) and fatality rates (β = 0.068; 95% CI, 0.044 to 0.091; P < .001).Conclusions and relevanceIn this cross-sectional study, SAHOs were associated with reductions in COVID-19 case rates. These findings could help inform policy makers to address the continued COVID-19 pandemic in the US. The proportion of African American population was positively associated with COVID-19 case rates, and this state-level finding adds to evidence from existing ecological studies using county-level data on racial disparities in COVID-19 infection rates and underlines the urgency of better understanding and addressing these disparities.

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Using spatial and temporal modeling to visualize the effects of U.S. state issued stay at home orders on COVID-19.

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