Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States

Tanujit Dey; Jaechoul Lee; Sounak Chakraborty; Jay Chandra; Anushka Bhaskar; Kenneth Zhang; Anchal Bhaskar; Francesca Dominici

doi:10.1016/j.patter.2021.100306

Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States

Tanujit Dey, Jaechoul Lee, Sounak Chakraborty, Jay Chandra, Anushka Bhaskar, Kenneth Zhang, Anchal Bhaskar, Francesca Dominici

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

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.

Original language	English (US)
Article number	100306
Journal	Patterns
Volume	2
Issue number	8
DOIs	https://doi.org/10.1016/j.patter.2021.100306
State	Published - Aug 13 2021
Externally published	Yes

Keywords

change point
COVID-19
DSML 3: Development/Pre-production: Data science output has been rolled out/validated across multiple domains/problems
hypothesis testing
interventions
log-normal distribution
non-pharmaceutical
time series

ASJC Scopus subject areas

General Decision Sciences

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10.1016/j.patter.2021.100306

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title = "Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States",

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.",

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AU - Chandra, Jay

AU - Bhaskar, Anushka

AU - Zhang, Kenneth

AU - Bhaskar, Anchal

AU - Dominici, Francesca

PY - 2021/8/13

Y1 - 2021/8/13

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AB - 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.

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Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States

Abstract

Keywords

ASJC Scopus subject areas

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