title: Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis.
abstract: BACKGROUND
  The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level.
  
  
  METHODS
  We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure.
  
  
  RESULTS
  The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates.
  
  
  CONCLUSIONS
  The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.
authors.affiliation: Departamento de Medicina Social, Universidade de São Paulo, Ribeirão Preto, SP, Brasil.
authors.forename: Daiane Leite da
authors.initials: DL
authors.lastname: Roza
authors.forename: Maria do Carmo Gullaci Guimarães
authors.initials: Mdo C
authors.lastname: Caccia-Bava
authors.forename: Edson Zangiacomi
authors.initials: EZ
authors.lastname: Martinez
mesh_terms: D001499:Bayes Theorem; D001938:Brazil / Q000453:epidemiology; D018563:Disease Notification; D004522:Educational Status; D015987:Effect Modifier, Epidemiologic; D005260:Female; D063005:Health Information Systems; D006801:Humans; D015994:Incidence; D007182:Income; D008297:Male; D012307:Risk Factors; D012959:Socioeconomic Factors; D062211:Spatio-Temporal Analysis; D014376:Tuberculosis / Q000453:epidemiology*; D014505:Urban Population