Evidence map›Paper›PMID 40283770›Full record

ArticleInternational journal of environmental research and public health2025

Spatial Analysis of Tuberculosis, COVID-19, and Tuberculosis/COVID-19 Coinfection in Recife, PE, Brazil.

Alene Bezerra Araújo Silva, Wayner Vieira de Souza, José Constantino Silveira Júnior, Juliana Silva de Santana, Ricardo Arraes de Alencar Ximenes

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Alene Bezerra Araújo SilvaGraduate Program in Health Sciences, Faculty of Medical Sciences, University of Pernambuco, Recife CEP 50100-010, PE, Brazil.ORCID 0009-0004-7506-1673
Wayner Vieira de SouzaDepartment of Public Health, Aggeu Magalhães Research Center, Fiocruz, Recife CEP 50.740-465, PE, Brazil.
José Constantino Silveira JúniorAggeu Magalhães Research Center, Fiocruz, Recife CEP 50.740-465, PE, Brazil.ORCID 0009-0001-7374-1016
Juliana Silva de SantanaApplied Cellular and Molecular Biology, University of Pernambuco, Recife CEP 50100-010, PE, Brazil.
Ricardo Arraes de Alencar XimenesDepartment of Tropical Medicine, Federal University of Pernambuco, Recife CEP 50670-901, PE, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) remains a public health problem, which the COVID-19 pandemic may have exacerbated. Scaling TB, COVID-19, and coinfection in area and socioeconomic contexts is an important way to detect more vulnerable groups.

objectiveTo verify, through the spatial distribution of cases of tuberculosis, COVID-19, and coinfection, the existence of an association between the risk of illness and income.

methodsAn analytical ecological study was carried out in Recife, whose unit of analysis was the neighborhood, in the year 2020. The data were collected from the SINAN-TB, NOTIFICA-PE, and IBGE Information Systems. Neighborhoods were grouped into strata according to income through K-means analysis. Incidence rates were calculated. Marshall's Local Empirical Bayesian Smoothing Method was used. Risk ratios were calculated to estimate the magnitude of association between income strata and incidence rates.

resultsA heterogeneous pattern of spatial distribution was verified for the three events addressed, compatible with the inequality of income distribution existing in Recife. For COVID-19, the highest incidence rates occurred in the strata of better-income neighborhoods. There was an association with a gradual increase in the incidence rate as income decreased for tuberculosis. Coinfection did not show a gradual increase in the incidence rate as income decreased, but a lower incidence rate was observed in the stratum of better economic conditions.

conclusionsStudies must be carried out to verify the spatial distribution of COVID-19 and its possible association with socioeconomic factors in subsequent years. There was a positive association between low income and the risk of becoming ill from tuberculosis. The lower incidence rate of coinfection in the stratum of the higher-income population suggests that the pre-existence of TB contributes to illness by COVID-19 in the low-income population.

Indexed as

CoinfectionCOVID-19TuberculosisBayes TheoremBrazilHumansIncidenceIncomeSocioeconomic FactorsSpatial AnalysiscoinfectioncoronavirusCOVID-19risk factorssocial conditionstuberculosis

Identifiers

PMID40283770
PMCPMC12027179

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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.