Effect of socioeconomic inequalities and vulnerabilities on health-system preparedness and response to COVID-19 in Brazil: a comprehensive analysis

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dc.contributor.authorLETICIA FARIA DE CARVALHO NUNES
dc.contributor.authorRocha, Rudi
dc.contributor.authorAtun, Rifat
dc.contributor.authorMassuda, Adriano
dc.contributor.authorRache, Beatriz
dc.contributor.authorSpinola, Paula
dc.contributor.authorLago, Miguel
dc.contributor.authorCastro, Marcia C.
dc.coverage.cidadeAmsterdãpt_BR
dc.coverage.paisPaíses Baixospt_BR
dc.creatorRocha, Rudi
dc.creatorAtun, Rifat
dc.creatorMassuda, Adriano
dc.creatorRache, Beatriz
dc.creatorSpinola, Paula
dc.creatorLago, Miguel
dc.creatorCastro, Marcia C.
dc.date.accessioned2022-12-19T10:32:43Z
dc.date.available2022-12-19T10:32:43Z
dc.date.issued2021
dc.description.notesTexto completopt_BR
dc.description.otherBackground COVID-19 spread rapidly in Brazil despite the country's well established health and social protection systems. Understanding the relationships between health-system preparedness, responses to COVID-19, and the pattern of spread of the epidemic is particularly important in a country marked by wide inequalities in socioeconomic characteristics (eg, housing and employment status) and other health risks (age structure and burden of chronic disease). Methods From several publicly available sources in Brazil, we obtained data on health risk factors for severe COVID-19 (proportion of the population with chronic disease and proportion aged ≥60 years), socioeconomic vulnerability (proportions of the population with housing vulnerability or without formal work), health-system capacity (numbers of intensive care unit beds and physicians), coverage of health and social assistance, deaths from COVID-19, and state-level responses of government in terms of physical distancing policies. We also obtained data on the proportion of the population staying at home, based on locational data, as a measure of physical distancing adherence. We developed a socioeconomic vulnerability index (SVI) based on household characteristics and the Human Development Index. Data were analysed at the state and municipal levels. Descriptive statistics and correlations between state-level indicators were used to characterise the relationship between the availability of health-care resources and socioeconomic characteristics and the spread of the epidemic and the response of governments and populations in terms of new investments, legislation, and physical distancing. We used linear regressions on a municipality-by-month dataset from February to October, 2020, to characterise the dynamics of COVID-19 deaths and response to the epidemic across municipalities. Findings The initial spread of COVID-19 was mostly affected by patterns of socioeconomic vulnerability as measured by the SVI rather than population age structure and prevalence of health risk factors. The states with a high (greater than median) SVI were able to expand hospital capacity, to enact stringent COVID-19-related legislation, and to increase physical distancing adherence in the population, although not sufficiently to prevent higher COVID-19 mortality during the initial phase of the epidemic compared with states with a low SVI. Death rates accelerated until June, 2020, particularly in municipalities with the highest socioeconomic vulnerability. Throughout the following months, however, differences in policy response converged in municipalities with lower and higher SVIs, while physical distancing remained relatively higher and death rates became relatively lower in the municipalities with the highest SVIs compared with those with lower SVIs. Interpretation In Brazil, existing socioeconomic inequalities, rather than age, health status, and other risk factors for COVID-19, have affected the course of the epidemic, with a disproportionate adverse burden on states and municipalities with high socioeconomic vulnerability. Local government responses and population behaviour in the states and municipalities with higher socioeconomic vulnerability have helped to contain the effects of the epidemic. Targeted policies and actions are needed to protect those with the greatest socioeconomic vulnerability. This experience could be relevant in other low-income and middle-income countries where socioeconomic vulnerability varies greatly.pt_BR
dc.format.extentp. e782-e792pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.doihttp://dx.doi.org/10.1016/S2214-109X(21)00081-4pt_BR
dc.identifier.issn2214-109Xpt_BR
dc.identifier.issn2572-116Xpt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/5072
dc.identifier.volume9pt_BR
dc.language.isoInglêspt_BR
dc.publisherElsevierpt_BR
dc.relation.ispartofLancet Global Healthpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DO USUÁRIO VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR.pt_BR
dc.titleEffect of socioeconomic inequalities and vulnerabilities on health-system preparedness and response to COVID-19 in Brazil: a comprehensive analysispt_BR
dc.typejournal article
dspace.entity.typePublication
local.subject.cnpqCiências Sociais Aplicadaspt_BR
local.typeArtigo Científicopt_BR
relation.isAuthorOfPublication33667618-2f83-41c5-abb2-95fcb0852cd2
relation.isAuthorOfPublication.latestForDiscovery33667618-2f83-41c5-abb2-95fcb0852cd2
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