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A network Data Envelopment Analysis to estimate nations’ efficiency in the fight against SARS-CoV-2

2022-12-30Journal article Open access
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dc.contributor.authorPereira, Miguel Alves
dc.contributor.authorDinis, Duarte Caldeira
dc.contributor.authorFerreira, Diogo Cunha
dc.contributor.authorFigueira, José Rui
dc.contributor.authorMarques, Rui Cunha
dc.date.accessioned2023-10-19T15:24:42Z
dc.date.available2023-10-19T15:24:42Z
dc.date.issued2022-12-30
dc.description.abstractThe ongoing outbreak of SARS-CoV-2 has been deeply impacting health systems worldwide. In this context, it is pivotal to measure the efficiency of different nations’ response to the pandemic, whose insights can be used by governments and health authorities worldwide to improve their national COVID-19 strategies. Hence, we propose a network Data Envelopment Analysis (DEA) to estimate the efficiencies of fifty-five countries in the current crisis, including the thirty-seven Organisation for Economic Co-operation and Development (OECD) member countries, six OECD prospective members, four OECD key partners, and eight other countries. The network DEA model is designed as a general series structure with five single-division stages – population, contagion, triage, hospitalisation, and intensive care unit admission –, and considers an output maximisation orientation, denoting a social perspective, and an input minimisation orientation, denoting a financial perspective. It includes inputs related to health costs, desirable and undesirable intermediate products related to the use of personal protective equipment and infected population, respectively, and desirable and undesirable outputs regarding COVID-19 recoveries and deaths, respectively. To the best of the authors’ knowledge, this is the first study proposing a cross-country efficiency measurement using a network DEA within the context of the COVID-19 crisis. The study concludes that Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand are the countries exhibiting higher mean system efficiencies. Their national COVID-19 strategies should be studied, adapted, and used by countries exhibiting worse performances. In addition, the observation of countries with large populations presenting worse mean efficiency scores is statistically significant.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.eswa.2022.118362pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/29088
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationCentre for Management Studies of Instituto Superior Técnico
dc.relationIncorporating preference information in network DEA models for measuring efficiency and productivity in healthcare
dc.relationINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
dc.subjectData Envelopment Analysis; Simulation; Series structure; SARS-CoV-2; Efficiency measurement.pt_PT
dc.titleA network Data Envelopment Analysis to estimate nations’ efficiency in the fight against SARS-CoV-2pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Management Studies of Instituto Superior Técnico
oaire.awardTitleIncorporating preference information in network DEA models for measuring efficiency and productivity in healthcare
oaire.awardTitleINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEGE-OGE%2F30546%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00097%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F149283%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50014%2F2020/PT
oaire.citation.startPage118362pt_PT
oaire.citation.titleExpert Systems with Applicationspt_PT
oaire.citation.volume210pt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isProjectOfPublication67257955-99c7-4c26-824b-eda5314160ea
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