Evidence map›Paper›PMID 35061776›Full record

ArticlePloS one2022

Policy and behavioral response to shock events: An agent-based model of the effectiveness and equity of policy design features.

Vivek Shastry, D Cale Reeves, Nicholas Willems, Varun Rai

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Closing the Gap in Race-based Inequities for Seasonal Influenza Hospitalizations: A Modeling Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vivek ShastryLBJ School of Public Affairs, The University of Texas at Austin, Austin, TX, United States of America.ORCID 0000-0002-0916-1981
D Cale ReevesLBJ School of Public Affairs, The University of Texas at Austin, Austin, TX, United States of America.
Nicholas WillemsDepartment of Mechanical Engineering, The University of Texas at Austin, Austin, TX, United States of America.ORCID 0000-0001-5999-9312
Varun RaiLBJ School of Public Affairs, The University of Texas at Austin, Austin, TX, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the aftermath of shock events, policy responses tend to be crafted under significant time constraints and high levels of uncertainty. The extent to which individuals comply with different policy designs can further influence how effective the policy responses are and how equitably their impacts are distributed in the population. Tools which allow policymakers to model different crisis trajectories, policy responses, and behavioral scenarios ex ante can provide crucial timely support in the decision-making process. Set in the context of COVID-19 shelter in place policies, in this paper we present the COVID-19 Policy Evaluation (CoPE) tool, which is an agent-based modeling framework that enables researchers and policymakers to anticipate the relative impacts of policy decisions. Specifically, this framework illuminates the extent to which policy design features and behavioral responsiveness influence the efficacy and equity of policy responses to shock events. We show that while an early policy response can be highly effective, the impact of the timing is moderated by other aspects of policy design such as duration and targeting of the policy, as well as societal aspects such as trust and compliance among the population. More importantly, we show that even policies that are more effective overall can have disproportionate impacts on vulnerable populations. By disaggregating the impact of different policy design elements on different population groups, we provide an additional tool for policymakers to use in the design of targeted strategies for disproportionately affected populations.

Indexed as

COVID-19Health EquityHealth PolicyPolicy MakingHumansSystems Analysis

Identifiers

PMID35061776
PMCPMC8782474

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Registered trials

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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.