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Use este identificador para citar o ir al link de este elemento: http://hdl.handle.net/1843/54264
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Campo DCValorIdioma
dc.creatorLara de Melo Barbosa Andradept_BR
dc.creatorGilvan Ramalho Guedespt_BR
dc.creatorKenya Valeria Micaela de Souza Noronhapt_BR
dc.creatorCláudio Moisés Santos e Silvapt_BR
dc.creatorJéferson Pereira Andradept_BR
dc.creatorAlbert Smith Feitosa Suassuna Martinspt_BR
dc.date.accessioned2023-05-31T21:33:05Z-
dc.date.available2023-05-31T21:33:05Z-
dc.date.issued2021-
dc.citation.volume16pt_BR
dc.citation.issue11pt_BR
dc.citation.spage1pt_BR
dc.citation.epage24pt_BR
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0259780pt_BR
dc.identifier.issn1932-6203pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/54264-
dc.description.resumoAmazonia and the Northeast region of Brazil exhibit the highest levels of climate vulnerability in the country. While Amazonia is characterized by an extremely hot and humid climate and hosts the world largest rainforest, the Northeast is home to sharp climatic contrasts, ranging from rainy areas along the coast to semiarid regions that are often affected by droughts. Both regions are subject to extremely high temperatures and are susceptible to many tropical diseases. This study develops a multidimensional Extreme Climate Vulnerability Index (ECVI) for Brazilian Amazonia and the Northeast region based on the Alkire-Foster method. Vulnerability is defined by three components, encompassing exposure (proxied by seven climate extreme indicators), susceptibility (proxied by sociodemographic indicators), and adaptive capacity (proxied by sanitation conditions, urbanization rate, and healthcare provision). In addition to the estimated vulnerability levels and intensity, we break down the ECVI by indicators, dimensions, and regions, in order to explore how the incidence levels of climate-sensitive infectious and parasitic diseases correlate with regional vulnerability. We use the Grade of Membership method to reclassify the mesoregions into homoclimatic zones based on extreme climatic events, so climate and population/health data can be analyzed at comparable resolutions. We find two homoclimatic zones: Extreme Rain (ER) and Extreme Drought and High Temperature (EDHT). Vulnerability is higher in the ED-HT areas than in the ER. The contribution of each dimension to overall vulnerability levels varies by homoclimatic zone. In the ER zone, adaptive capacity (39%) prevails as the main driver of vulnerability among the three dimensions, in contrast with the approximately even dimensional contribution in the ED-HT. When we compare areas by disease incidence levels, exposure emerges as the most influential dimension. Our results suggest that climate can exacerbate existing infrastructure deficiencies and socioeconomic conditions that are correlated with tropical disease incidence in impoverished areas.pt_BR
dc.languageporpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentFCE - DEPARTAMENTO DE CIÊNCIAS ECONÔMICASpt_BR
dc.publisher.departmentFCE - DEPARTAMENTO DE DEMOGRAFIApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofPLOS ONEpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectAmazoniapt_BR
dc.subjectNortheast region of Brazilpt_BR
dc.subjectClimate extremespt_BR
dc.subject.otherBrasil - Climapt_BR
dc.subject.otherAmazoniapt_BR
dc.subject.otherBrasil, Nordestept_BR
dc.titleHealth-related vulnerability to climate extremes in homoclimatic zones of Amazonia and Northeast region of Brazilpt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0259780pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-8019-9480pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-8231-238Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-7174-6710pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-2251-7348pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-9157-5990pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-0333-3997pt_BR
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