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https://www.arca.fiocruz.br/handle/icict/70255
SPATIAL ANALYSIS OF TUBERCULOSIS, COVID-19, AND TUBERCULOSIS/COVID-19 COINFECTION IN RECIFE, PE, BRAZIL
Author
Affilliation
Programa de Pós-Graduação em Ciências da Saúde, Faculdade de Ciências Médicas, Universidade de Pernambuco, Recife, PE, Brasil.
Fundação Oswaldo Cruz. Instituto Aggeu Magalhães. Departamento de Saúde Pública Recife, PE, Brasil
Fundação Oswaldo Cruz. Instituto Aggeu Magalhães. Recife, PE, Brasil.
Universidade de Pernambuco. Biologia Celular e Molecular Aplicada. Recife, PE, Brasil.
Universidade Federal de Pernambuco. Departamento de Medicina Tropical. Recife, PE, Brasil.
Universidade de Pernambuco. Departamento de Clínica Médica. Recife, PE, Brasil.
Fundação Oswaldo Cruz. Instituto Aggeu Magalhães. Departamento de Saúde Pública Recife, PE, Brasil
Fundação Oswaldo Cruz. Instituto Aggeu Magalhães. Recife, PE, Brasil.
Universidade de Pernambuco. Biologia Celular e Molecular Aplicada. Recife, PE, Brasil.
Universidade Federal de Pernambuco. Departamento de Medicina Tropical. Recife, PE, Brasil.
Universidade de Pernambuco. Departamento de Clínica Médica. Recife, PE, Brasil.
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.
Objective: To 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.
Methods: An 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.
Results: A 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.
Conclusions: Studies 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.
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