Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States.
Where this comes from
- Record sourced from PubMed, PMID 34308391.
- Also identified by DOI 10.1016/j.patter.2021.100306 and PMC identifier 8267064.
- Licence recorded as CC BY-NC-ND.
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Abstract
State-level policy interventions have been critical in managing the spread of the new coronavirus. Here, we study the lag time between policy interventions and change in COVID-19 outcome trajectory in the United States. We develop a stepwise drifts random walk model to account for non-stationarity and strong temporal correlation and subsequently apply a change-point detection algorithm to estimate the number and times of change points in the COVID-19 outcome data. Furthermore, we harmonize data on the estimated change points with non-pharmaceutical interventions adopted by each state of the United States, which provides us insights regarding the lag time between the enactment of a policy and its effect on COVID-19 outcomes. We present the estimated change points for each state and the District of Columbia and find five different emerging trajectory patterns. We also provide insight into the lag time between the enactment of a policy and its effect on COVID-19 outcomes.