e10534
SPATIAL ANALYSIS TECHNIQUES FOR DETECTING TUBERCULOSIS/HIV COINFECTION: AN INTEGRATIVE REVIEW
Authors: Livia Fernanda Siqueira Santos , Janiel Conceição da Silva , Daianne Santos de Souza , Livia Maia Pascoal , Adriana Gomes Nogueira Ferreira , Floriacy Stabnow Santos , Marcelino Santos Neto
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The objective was to analyze the national and international scientific production about the spatial analysis techniques used in the detection of tuberculosis/HIV co-infection in the world. It is an integrative literature review, which used the PICo strategy to elaborate the guiding question: What is the scientific evidence related to the use of spatial analysis techniques in the detection of tuberculosis / HIV co-infection in the world? Searches were conducted in the LILACS, PubMed® and MEDLINE® databases, and in the SciELO electronic library in January 2020, using the descriptors “Tuberculosis (TB) HIV coinfection”, “spatial analysis”, “disease notification”, “risk area”,“ TB / HIV”,“ spatiotemporal ”isolated and / or combined. Articles available in full in Portuguese, English and Spanish were included, excluding dissertations, theses, literature reviews and editorial notes. 16 articles were analyzed, published from 2006 onwards. All used secondary data, with an ecological design. Area data analysis techniques, Bayesian analysis, global and local Moran, scanning statistics, Gaussian geostatic model and Krigagem were used to determine the heterogeneous distribution of the co-infection, with emphasis on the prevalence and mortality coefficients, especially in scenarios such as Brazil and Africa. The diversity of spatial analysis techniques identified, with emphasis on analysis of area data and Bayesian analysis, contributed to assessment and identification of risk factors for indicators of morbidity and mortality to co-infection, targets for action and planning of public health policies, enabling the implementation of actions focused on curative and preventive issues, based on the reduction of socio-spatial inequalities in different scenarios.