Evidence map›Paper›PMID 41183110›Full record

ArticlePLoS neglected tropical diseases2025

Socioeconomic markers of dengue mortality in the 100 Million Brazilian Cohort (2007-2018): A nationwide registry-based cohort study.

Luciana Lobato Cardim, Maria da Glória Teixeira, Maria da Conceição N Costa, Wema Meranda Mitka, Camila Silveira Silva Teixeira, Andreia C Santos, Gervasio Santos, André Portela Fernandes de Souza, Liam Smeeth, Mauricio L Barreto and 3 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Luciana Lobato CardimCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.ORCID 0000-0002-2262-2439
Maria da Glória TeixeiraCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.
Maria da Conceição N CostaInstituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
Wema Meranda MitkaFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Camila Silveira Silva TeixeiraCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.
Andreia C SantosFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Gervasio SantosFaculdade de Economia, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
André Portela Fernandes de SouzaFundação Getúlio Vargas, São Paulo, São Paulo, Brazil.
Liam SmeethFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Mauricio L BarretoCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.
Elizabeth B BrickleyFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Enny S PaixaoCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.
Julia M PescariniCentro de Integração de Dados e Conhecimentos para Saúde - CIDACS (Center of Data and Knowledge Integration for Health), Instituto Gonçalo Moniz, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.

Funding

British Council NewtonWellcome Trust 225925/Z/22/ZWellcome Trust 305644/Z/23/Z
6 · The paper itself

Abstract

backgroundPeople living in economically disadvantaged circumstances experience higher risks of infections and death from arboviruses. However, more evidence is needed to better understand the socioeconomic factors influencing dengue mortality. We investigated if people of lower socioeconomic conditions in Brazil are more likely to die following dengue infection. METHODOLOGY/PRINCIPAL

findingsLinking nationwide socioeconomic data from the 100 Million Brazilian Cohort with dengue disease and death records registered in Brazil between 1st January 2007 and 31st December 2018, we used multivariable hierarchical analysis to investigate the socioeconomic determinants of dengue-specific and all-cause mortality within 15 days of dengue symptom onset. Among the 3,018,131 individuals from the 100 Million Brazilian Cohort diagnosed with dengue, 1810 died from dengue (Case Fatality Rate (CFR)=0.06%, 95%CI = 0.06-0.06%) and 3076 (CFR = 0.10%, 95%CI = 0.10-0.11%) died from any cause within 15 days of dengue symptom onset. People residing in the Northeast (OR=2.32; 95%CI = 1.74-3.10) and Midwest (OR=1.68; 95%CI = 1.25-2.27) regions, self-identifying as black race/ethnicity (OR=1.58; 95%CI = 1.31-1.90), having lower level of education (OR=2.35, 95%CI = 1.17-4.73), being retired/receiving pension (OR=2.24; 95%CI = 1.76-2.86), living in a household with rudimentary sewage (OR=1.19; 95%CI = 1.04-1.37) and having >2 inhabitants per room (OR=1.31; 95%CI = 1.11-1.55) had at higher odds of dengue-specific mortality. Similar characteristics were also associated with higher all-cause mortality after dengue infection, but also included residing in North region (OR=1.60; 95%CI = 1.24-2.06) and rural areas (OR=1.12; 95%CI = 1.01-1.24), self-identifying as Asian (OR=1.65; 95%CI = 1.07-2.54) and mixed race/brown (OR=1.20; 95%CI = 1.10-1.31) and living in households with poorer quality building and sanitary conditions. CONCLUSIONS/SIGNIFICANCE: Our findings provide evidence that individuals in Brazil with lower socioeconomic condition experience increased odds of dengue-specific and all-cause mortality within 15 days of dengue symptom onset. These findings underscore the importance of ensuring equitable access to high-quality treatment for severe dengue and suggest that reducing poverty and social inequality, including through improvement of sanitation and housing, may help mitigate dengue-related mortality.

Indexed as

DengueSocioeconomic FactorsAdolescentAdultAgedBrazilChildChild, PreschoolCohort StudiesFemaleHumansInfantMaleMiddle AgedRegistriesRisk Factors

Identifiers

PMID41183110
PMCPMC12582496

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.