ArticlePloS one2022
Policy and behavioral response to shock events: An agent-based model of the effectiveness and equity of policy design features.
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.
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Who cites it
8 citing papers in PubMed.
- Start from the end: Policy exploration to inform effective and consistent interventions applied to COVID-19 in St. Louis.PNAS nexus · 2026Article
- 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 · 2025Article
- Harnessing multi-output machine learning approach and dynamical observables from network structure to optimize COVID-19 intervention strategies.Biology methods & protocols · 2025Article
- Adaptive behaviour during epidemics: a social risk appraisal approach to modelling dynamics.Journal of the Royal Society, Interface · 2025Article
- Evaluating equity-promoting interventions to prevent race-based inequities in influenza outcomes.medRxiv : the preprint server for health sciences · 2024Article
- Article
- Predicting firm creation in rural Texas: A multi-model machine learning approach to a complex policy problem.PloS one · 2023Article
- Predicting and preventing COVID-19 outbreaks in indoor environments: an agent-based modeling study.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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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.