ArticleScientific reports2025
The impact of confounders, spillovers and interactions on social distancing policy effects estimates.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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3 authors.
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Abstract
Social distancing policies have been widely used to curb the spread of infectious diseases such as COVID-19, but assessing their effectiveness is challenging. This study shows that widely-used methods to estimate the effects of such policies, like Two-way Fixed Effects and Difference-in-Differences, are highly sensitive to accounting, or failing to account, for the simultaneous adoption of policies and the presence of spillovers across geographies stemming from human movement. By estimating a series of nonparametric models on fine-grained mobility, epidemiological, and policy data from Mexico during the COVID-19 pandemic, this research shows that failing to consider confounders, interactions, and spillovers can change the magnitude and the sign of estimated policy effects, hampering the design of optimal public policies.
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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.