Estimating underreporting of leprosy in Brazil using a Bayesian approach.

BACKGROUND: Leprosy remains concentrated among the poorest communities in low-and middle-income countries and it is one of the primary infectious causes of disability. Although there have been increasing advances in leprosy surveillance worldwide, leprosy underreporting is still common and can hinder decision-making regarding the distribution of financial and health resources and thereby limit the effectiveness of interventions. In this study, we estimated the proportion of unreported cases of leprosy in Brazilian microregions. METHODOLOGY/PRINCIPAL FINDINGS: Using data collected between 2007 to 2015 from each of the 557 Brazilian microregions, we applied a Bayesian hierarchical model that used the presence of grade 2 leprosy-related physical disabilities as a direct indicator of delayed diagnosis and a proxy for the effectiveness of local leprosy surveillance program. We also analyzed some relevant factors that influence spatial variability in the observed mean incidence rate in the Brazilian microregions, highlighting the importance of socioeconomic factors and how they affect the levels of underreporting. We corrected leprosy incidence rates for each Brazilian microregion and estimated that, on average, 33,252 (9.6%) new leprosy cases went unreported in the country between 2007 to 2015, with this proportion varying from 8.4% to 14.1% across the Brazilian States. CONCLUSIONS/SIGNIFICANCE: The magnitude and distribution of leprosy underreporting were adequately explained by a model using Grade 2 disability as a marker for the ability of the system to detect new missing cases. The percentage of missed cases was significant, and efforts are warranted to improve leprosy case detection. Our estimates in Brazilian microregions can be used to guide effective interventions, efficient resource allocation, and target actions to mitigate transmission.

Effectiveness of a conditional cash transfer programme on TB cure rate: a retrospective cohort study in Brazil.

BACKGROUND: Despite the efforts of the National Tuberculosis Programme, TB cure rates in Brazil are sub-optimal. The End TB Strategy for post-2015 identifies conditional cash transfer interventions as powerful tools to improve TB control indicators, including TB cure rate. This study aims to inform the new policy by evaluating the role of the Bolsa Familia Programme (BFP), one of the largest conditional cash transfer programmes in the world, on TB cure rates in Brazil. METHODS: We undertook a retrospective cohort study, based on an unprecedented record linkage of socioeconomic and health data, to compare cases of patients newly diagnosed with TB in 2010 receiving BFP cash benefits (n=5788) with those who did not (n=1467) during TB treatment. We used Poisson regression with robust variance to estimate the relative risks for TB cure adjusted for known confounders. RESULTS: The cure rate among patients exposed to BFP during TB treatment was 82.1% (4752/5788), 5.2% higher than among those not exposed. This was confirmed after controlling for TB type, diabetes mellitus, HIV status and other relevant clinical and socioeconomic covariates (RR=1.07, 95% CI 1.04 to 1.11 for cure rates among BFP beneficiaries). This association seemed higher for patients not under directly observed treatment (RR=1.11; 95% CI 1.05 to 1.16). CONCLUSIONS: Although further research is needed, this study suggests that conditional cash transfer programmes can contribute to improve TB cure rate in Brazil.