Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity

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• dc.contributor.author Ghaderi, Mohammad
• dc.date.accessioned 2022-05-17T11:21:22Z
• dc.date.available 2022-05-17T11:21:22Z
• dc.date.issued 2022
• dc.description.abstract Complexity, resulting from interactions among many components, is a characterizing feature of healthcare systems and related decisions. It scales up in the face of pandemics that give rise to multiple sources of uncertainty and where various contextual factors interact with each other and with policy parameters that combine to yield outcome distributions. This paper proposes a unified agent-based modeling framework to derive qualitative insights that assist and inform policy decisions related to pandemics. The general framework comprises a contagion model that explicates exogenous policy-relevant variables, as well as their links with features of the environment in which the policy decisions will be implemented. Furthermore, the framework identifies sources of uncertainty at different system layers. The characterization of the macro level, for example, as manifested in the network structure, encompasses two constitutive factors. These two factors, in turn, capture much of the stochasticity that results from the network’s inherent randomness. By synthesizing the model components further into a broader agent-based model, the current framework also accounts for heterogeneous micro-level attributes that collectively yield macro-level outcomes. Several stylized examples help establish insights into the overall tendency of complex systems to produce multidimensional outputs. A comprehensive, controlled, computational experiment offers further evidence across a range of scenarios and various policy conditions.
• dc.description.sponsorship Financial support from the Spanish Agencia Estatal de Investigación (AEI), through the Severo Ochoa Programme for Centres of Excellence in R&D (CEX2019-000915-S).
• dc.format.mimetype application/pdf
• dc.identifier.citation Ghaderi M. Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity. European Journal of Operational Research. 2022 May;298(3):1016-31. DOI: 10.1016/j.ejor.2021.08.015
• dc.identifier.doi http://dx.doi.org/10.1016/j.ejor.2021.08.015
• dc.identifier.issn 0377-2217
• dc.identifier.uri http://hdl.handle.net/10230/53121
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof European Journal of Operational Research. 2022 May;298(3):1016-31
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/CEX2019-000915-S
• dc.rights © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.keyword Stochastic simulation
• dc.subject.keyword Decision support systems
• dc.subject.keyword Contagion
• dc.subject.keyword Agent-based models
• dc.subject.keyword Random networks
• dc.title Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion