Results showed many advances in tuberculosis control in the 10 years analyzed, but it also points to serious obstacles that need to be solved so Brazil can eliminate tuberculosis as a public health problem.

BackgroundAlthough the Brazilian national reporting system for tuberculosis cases (SINAN) has enormous potential to generate data for policy makers, formal assessments of treatment outcomes and other aspects of TB morbidity and mortality are not produced with enough depth and rigor. In particular, the effect of HIV status on these outcomes has not been fully explored, partly due to incomplete recording in the national database.Methodology/Principal FindingsIn a retrospective cohort study, we assessed TB treatment outcomes, including rates of cure, default, mortality, transfer and multidrug resistant TB (MDR-TB) among a purposively chosen sample of 161,481 new cases reported in SINAN between 2003 and 2008. The study population included all new cases reported in the six States with the highest level of completeness of the HIV status field in the system. These cases were mostly male (67%), white (62%), had pulmonary TB (79%) and a suspect chest X ray (83%). Treatment outcomes were best for those HIV negative cases and worst for those known HIV positive patients (cure rate of 85.7% and 55.7% respectively). In multivariate modeling, the risk of having an unfavorable outcome (all outcomes except cure) was 3.09 times higher for those HIV positive compared with those HIV negative (95% CI 3.02–3.16). The risk of death and default also increased with HIV positivity. The group without a known HIV status showed intermediate outcomes between the groups above, suggesting that this group includes some with HIV infection.ConclusionsHIV status played an important role in TB treatment outcomes in the study period. The outcomes observed in those with known HIV were poor and need to be improved. Those in the group with unknown HIV status indicate the need for wider HIV testing among new TB cases.

The authors confirmed Green Tobacco Sickness in southern Brazil; the authors recommend investigation of its prevalence in tobacco-growing regions and monitoring of and education about the disease and its prevention by occupational health authorities.

O objetivo deste trabalho foi verificar a melhoria da qualidade das informações sobre a tuberculose (TB), após a vinculação de registros e a correção do encerramento por meio do linkage probabilístico do Sistema de Informações de Agravos de Notificação (SINAN) com o Sistema de Informações sobre Mortalidade (SIM). Para a vinculação de registros foi realizado o linkage entre os registros do SINAN do Brasil, anos 2008 e 2009, com o objetivo de excluir as notificações não removidas pelas rotinas do SINAN realizadas por estados e municípios. As bases de dados foram construídas de acordo com o desfecho dos casos. Para o linkage entre SINAN e SIM foi utilizada a base de dados que resultou da vinculação de registros e os registros do SIM que mencionaram TB como causa básica ou associada, entre 2008 e 2010, no Brasil. A vinculação de registros diminuiu o percentual de casos novos com encerramento por transferência, com variação de 34,8% em 2008 e 35,5% em 2009. Após o linkage entre SINAN e SIM, o percentual de óbito por TB aumentou, com variação em torno de 15%. Os resultados descrevem uma situação de alerta no que se refere à qualidade dos dados de desfecho de tratamento de TB no SINAN.

The Notifiable Diseases Information System (SINAN) enables knowledge of the profile of people with active tuberculosis (TB) in a country of continental dimensions such as Brazil. Available in all Brazilian municipalities and states, the system enables continuous consolidation of data, evaluation and monitoring of actions related to TB control in the country. The purpose of this paper is to present the specificities of SINAN-Net related to TB, including the follow-up screen, the record linkage and the follow-up report. Additionally, we describe the main variables and indicators and the challenges and limitations of the system.

Abstract

BackgroundEvidence suggests that social protection policies such as Brazil’s Bolsa Família Programme (BFP), a governmental conditional cash transfer, may play a role in tuberculosis (TB) elimination. However, study limitations hamper conclusions. This paper uses a quasi-experimental approach to more rigorously evaluate the effect of BFP on TB treatment success rate.MethodsPropensity scores were estimated from a complete-case logistic regression using covariates from a linked data set, including the Brazil’s TB notification system (SINAN), linked to the national registry of those in poverty (CadUnico) and the BFP payroll.ResultsThe average effect of treatment on the treated was estimated as the difference in TB treatment success rate between matched groups (ie, the control and exposed patients, n=2167). Patients with TB receiving BFP showed a treatment success rate of 10.58 percentage points higher (95% CI 4.39 to 16.77) than patients with TB not receiving BFP. This association was robust to sensitivity analyses.ConclusionsThis study further confirms a positive relationship between the provision of conditional cash transfers and TB treatment success rate. Further research is needed to understand how to enhance access to social protection so to optimise public health impact.

ObjectivesTo identify scenarios based on socioeconomic, epidemiological and operational healthcare factors associated with tuberculosis incidence in Brazil.DesignEcological study.SettingsThe study was based on new patients with tuberculosis and epidemiological/operational variables of the disease from the Brazilian National Information System for Notifiable Diseases and the Mortality Information System. We also analysed socioeconomic and demographic variables.ParticipantsThe units of analysis were the Brazilian municipalities, which in 2015 numbered 5570 but 5 were excluded due to the absence of socioeconomic information.Primary outcomeTuberculosis incidence rate in 2015.Data analysisWe evaluated as independent variables the socioeconomic (2010), epidemiological and operational healthcare indicators of tuberculosis (2014 or 2015) using negative binomial regression. Municipalities were clustered by the k-means method considering the variables identified in multiple regression models.ResultsWe identified two clusters according to socioeconomic variables associated with the tuberculosis incidence rate (unemployment rate and household crowding): a higher socioeconomic scenario (n=3482 municipalities) with a mean tuberculosis incidence rate of 16.3/100 000 population and a lower socioeconomic scenario (2083 municipalities) with a mean tuberculosis incidence rate of 22.1/100 000 population. In a second stage of clusterisation, we defined four subgroups in each of the socioeconomic scenarios using epidemiological and operational variables such as tuberculosis mortality rate, AIDS case detection rate and proportion of vulnerable population among patients with tuberculosis. Some of the subscenarios identified were characterised by fragility in their information systems, while others were characterised by the concentration of tuberculosis cases in key populations.ConclusionClustering municipalities in scenarios allowed us to classify them according to the socioeconomic, epidemiological and operational variables associated with tuberculosis risk. This classification can support targeted evidence-based decisions such as monitoring data quality for improving the information system or establishing integrative social protective policies for key populations.