Determinants of drug-resistant Tuberculosis in the State of São Paulo: an approach with R-INLA

• Grant number: 17/11040-4
• Support type: Scholarships in Brazil - Doctorate
• Effective date (Start): March 01, 2018
• Effective date (End): June 30, 2020
• Field of knowledge: Health Sciences - Nursing - Public Health Nursing
• Principal researcher: Ricardo Alexandre Arcêncio
• Grantee: Luiz Henrique Arroyo
• Home Institution: Escola de Enfermagem de Ribeirão Preto (EERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Drug-resistant Tuberculosis is a threat to Tuberculosis elimination efforts globally, causing significant impacts on the health of populations and burdening health systems. Few studies have sought to understand the determinants and regions at greatest risk for the event, and this is an important lacuna to subsidize measures of prevention and control of the disease. The objective of the study is to identify the determinants of drug resistance in the State of São Paulo and to present an explanatory model of the phenomenon considering the spatial dependence and the hierarchical structure of the data. This is an ecological study to be conducted in the 645 municipalities of São Paulo. All confirmed cases of drug resistance would be considered, living in the municipalities of São Paulo and registered between 2006 and 2016 in three state databases. Data will also be used from the Single Caduceus of Social Programs of the Federal Government (CadÚnico) and Demographic Census of 2010. For the spatial analysis will be used the Bayesian hierarchical modeling to model the spatial distribution of the relative risk of the cases. Spatial dependence will be introduced assuming the conditional autoregressive structure and the unstructured effect will be modeled by a normal distribution with zero mean and large variance. In order to identify the best model of data fit, the criterion of deviance information criterion based on conditional predictive order will be considered. The analyze will be conducted in software R, using the R-INLA package. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LAURA TERENCIANI CAMPOY; ANTÔNIO CARLOS VIEIRA RAMOS; LUDMILLA LEIDIANNE LIMIRIO SOUZA; LUANA SELES ALVES; MARCOS AUGUSTO MORAES ARCOVERDE; THAÍS ZAMBONI BERRA; LUIZ HENRIQUE ARROYO; DANIELLE TALITA DOS SANTOS; RICARDO ALEXANDRE ARCÊNCIO. A distribuição espacial e a tendência temporal de recursos humanos para o Sistema Único de Saúde e para a Saúde Suplementar, Brasil, 2005 a 2016. Epidemiol. Serv. Saúde, v. 29, n. 2, p. -, 2020.

HENRIQUE ARROYO, LUIZ ARROYO; MORAES ARCOVERDE, MARCOS AUGUSTO; ALVES, JOSILENE DALIA; FUENTEALBA-TORRES, MIGUEL; CARTAGENA-RAMOS, DENISSE; SCHOLZE, ALESSANDRO ROLIM; VIEIRA RAMOS, ANTONIO CARLOS; ARCENCIO, RICARDO ALEXANDRE. Spatial analysis of cases of Tuberculosis with Mental Disorders in Sao Paulo. Revista Brasileira de Enfermagem, v. 72, n. 3, p. 654-662, MAY-JUN 2019. Web of Science Citations: 0.

LUIZ HENRIQUE ARROYO; ANTÔNIO CARLOS VIEIRA RAMOS; MELLINA YAMAMURA; THAIS ZAMBONI BERRA; LUANA SELES ALVES; AYLANA DE SOUZA BELCHIOR; DANIELLE TALITA SANTOS; JOSILENE DÁLIA ALVES; LAURA TERENCIANI CAMPOY; MARCOS AUGUSTO MORAES ARCOVERDE; VALDES ROBERTO BOLLELA; SIDNEY BOMBARDA; CARLA NUNES; RICARDO ALEXANDRE ARCÊNCIO. Predictive model of unfavorable outcomes for multidrug-resistant tuberculosis. Revista de Saúde Pública, v. 53, p. -, 2019. Web of Science Citations: 0.