ArticlePatterns (New York, N.Y.)2021
Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States.
Article in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Comparative efficiency of Asian surgical systems in COVID-19 response: a multi-level longitudinal benchmarking study.BMJ public health · 2026Article
- Dispatcher-assisted cardiopulmonary resuscitation for out-of-hospital cardiac arrest patients: a site-level analysis of the PAROS trial.Resuscitation plus · 2026Article
- Local Clustering for Functional Data.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2025Article
- Enhancing epidemic forecasting with a physics-informed spatial identity neural network.PloS one · 2025Article
- Spatiotemporal pattern of leprosy in southwest China from 2010 to 2020: an ecological study.BMC public health · 2024Observational
- Differences in COVID-19 cyclicity and predictability among U.S. counties and states reflect the effectiveness of protective measures.Scientific reports · 2023Article
- "Having vaccines is good but not enough": Requirements for optimal COVID-19 immunization program in Vietnam.Frontiers in public health · 2023Article
- Article
- The polarization of politics and public opinion and their effects on racial inequality in COVID mortality.PloS one · 2022Article
- Joint External Evaluation scores and communicable disease deaths: An ecological study on the difference between epidemics and pandemics.PLOS global public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.