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Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies

2023Journal article Open access
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dc.contributor.authorAlves, André
dc.contributor.authorMarques da Costa, Nuno
dc.contributor.authorMorgado, Paulo
dc.contributor.authorMarques da Costa, Eduarda
dc.date.accessioned2023-05-02T15:23:01Z
dc.date.available2023-05-02T15:23:01Z
dc.date.issued2023
dc.description.abstractAbstract Background COVID-19 caused the largest pandemic of the twenty-frst century forcing the adoption of containment policies all over the world. Many studies on COVID-19 health determinants have been conducted, mainly using multivariate methods and geographic information systems (GIS), but few attempted to demonstrate how knowing social, economic, mobility, behavioural, and other spatial determinants and their efects can help to contain the disease. For example, in mainland Portugal, non-pharmacological interventions (NPI) were primarily dependent on epidemiological indicators and ignored the spatial variation of susceptibility to infection. Methods We present a data-driven GIS-multicriteria analysis to derive a spatial-based susceptibility index to COVID-19 infection in Portugal. The cumulative incidence over 14 days was used in a stepwise multiple linear regression as the target variable along potential determinants at the municipal scale. To infer the existence of thresholds in the relationships between determinants and incidence the most relevant factors were examined using a bivariate Bayesian change point analysis. The susceptibility index was mapped based on these thresholds using a weighted linear combination. Results Regression results support that COVID-19 spread in mainland Portugal had strong associations with factors related to socio-territorial specifcities, namely sociodemographic, economic and mobility. Change point analysis revealed evidence of nonlinearity, and the susceptibility classes refect spatial dependency. The spatial index of susceptibility to infection explains with accuracy previous and posterior infections. Assessing the NPI levels in relation to the susceptibility map points towards a disagreement between the severity of restrictions and the actual propensity for transmission, highlighting the need for more tailored interventions. Conclusions This article argues that NPI to contain COVID-19 spread should consider the spatial variation of the susceptibility to infection. The fndings highlight the importance of customising interventions to specifc geographical contexts due to the uneven distribution of COVID-19 infection determinants. The methodology has the potential for replication at other geographical scales and regions to better understand the role of health determinants in explaining spatiotemporal patterns of diseases and promoting evidence-based public health policies.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlves, A., Marques da Costa, N., Morgado, Paulo, & Marques da Costa, E. (2023). Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies. International Journal of Health Geographics, 22(8). https://doi.org/10.1186/s12942-023-00329-4pt_PT
dc.identifier.doi10.1186/s12942-023-00329-4pt_PT
dc.identifier.issn1476-072X
dc.identifier.urihttp://hdl.handle.net/10451/57301
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherBMC, Springer Naturept_PT
dc.relationUIDB/00295/2020pt_PT
dc.relationUIDP/00295/2020pt_PT
dc.relationProject COMPRI_Mov—Get to Know More for Intervention in the context of mobility- ID: 613765655)pt_PT
dc.relation.publisherversionhttps://ij-healthgeographics.biomedcentral.com/articles/10.1186/s12942-023-00329-4pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectCOVID-19pt_PT
dc.subjectHealth determinantspt_PT
dc.subjectGISpt_PT
dc.subjectMulticriteria decision analysispt_PT
dc.subjectNon-pharmacological interventionspt_PT
dc.subjectSpatial-based policiespt_PT
dc.subjectSpatiotemporal analysispt_PT
dc.titleUncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policiespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue8pt_PT
oaire.citation.titleInternational Journal of Health Geographicspt_PT
oaire.citation.volume22pt_PT
person.familyNameAlves
person.familyNameMarques da Costa
person.familyNameMorgado
person.familyNameMarques da Costa
person.givenNameAndré
person.givenNameNuno
person.givenNamePaulo
person.givenNameEduarda
person.identifier1462449
person.identifier1579929
person.identifier0000000069223123
person.identifier.ciencia-idF111-646A-98EF
person.identifier.ciencia-idCD13-CD27-2ACD
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person.identifier.ciencia-id981E-1D2A-E5A6
person.identifier.orcid0000-0002-8979-8906
person.identifier.orcid0000-0003-4859-9668
person.identifier.orcid0000-0002-3220-4943
person.identifier.orcid0000-0001-5070-3562
person.identifier.ridN-9118-2013
person.identifier.ridJ-9673-2012
person.identifier.ridN-8979-2013
person.identifier.scopus-author-id57222062850
person.identifier.scopus-author-id56399055900
person.identifier.scopus-author-id36741880600
person.identifier.scopus-author-id55648727700
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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