Quantifying gaps in the tuberculosis care cascade in Brazil: A mathematical model study using national program data.

BACKGROUND: In Brazil, many individuals with tuberculosis (TB) do not receive appropriate care due to delayed or missed diagnosis, ineffective treatment regimens, or loss-to-follow-up. This study aimed to estimate the health losses and TB program costs attributable to each gap in the care cascade for TB disease in Brazil. METHODS AND FINDINGS: We constructed a Markov model simulating the TB care cascade and lifetime health outcomes (e.g., death, cure, postinfectious sequelae) for individuals developing TB disease in Brazil. We stratified the model by age, human immunodeficiency virus (HIV) status, drug resistance, state of residence, and disease severity, and developed a parallel model for individuals without TB that receive a false-positive TB diagnosis. Models were fit to data (adult and pediatric) from Brazil's Notifiable Diseases Information System (SINAN) and Mortality Information System (SIM) for 2018. Using these models, we assessed current program performance and simulated hypothetical scenarios that eliminated specific gaps in the care cascade, in order to quantify incremental health losses and TB diagnosis and treatment costs along the care cascade. TB-attributable disability-adjusted life years (DALYs) were calculated by comparing changes in survival and nonfatal disability to a no-TB counterfactual scenario. We estimated that 90.0% (95% uncertainty interval [UI]: 85.2 to 93.4) of individuals with TB disease initiated treatment and 10.0% (95% UI: 7.6 to 12.5) died with TB. The average number of TB-attributable DALYs per incident TB case varied across Brazil, ranging from 2.9 (95% UI: 2.3 to 3.6) DALYs in Acre to 4.0 (95% UI: 3.3 to 4.7) DALYs in Rio Grande do Sul (national average 3.5 [95% UI: 2.8 to 4.1]). Delayed diagnosis contributed the largest health losses along the care cascade, followed by post-TB sequelae and loss to follow up from TB treatment, with TB DALYs reduced by 71% (95% UI: 65 to 76), 41% (95% UI: 36 to 49), and 10% (95% UI: 7 to 16), respectively, when these factors were eliminated. Total health system costs were largely unaffected by improvements in the care cascade, with elimination of treatment failure reducing attributable costs by 3.1% (95% UI: 1.5 to 5.4). TB diagnosis and treatment of false-positive individuals accounted for 10.2% (95% UI: 3.9 to 21.7) of total programmatic costs but contributed minimally to health losses. Several assumptions were required to interpret programmatic data for the analysis, and we were unable to estimate the contribution of social factors to care cascade outcomes. CONCLUSIONS: In this study, we observed that delays to diagnosis, post-disease sequelae and treatment loss to follow-up were primary contributors to the TB burden of disease in Brazil. Reducing delays to diagnosis, improving healthcare after TB cure, and reducing treatment loss to follow-up should be prioritized to improve the burden of TB disease in Brazil.

Trends in tuberculosis incidence and mortality coefficients in Brazil, 2011-2019: analysis by inflection points.

Objective: To analyze the temporal trend of tuberculosis incidence and mortality rates in Brazil between 2011 and 2019. Methods: This was an ecological time series study of tuberculosis incidence and mortality rates in Brazil between 2011 and 2019. Data were extracted from the Notifiable Disease Information System and the Mortality Information System, and population estimates were from the Brazilian Institute of Geography and Statistics. Trends were analyzed by Joinpoint regression, which recognizes inflection points for temporal analysis. Results: The average incidence rate of tuberculosis in Brazil in the period was 35.8 cases per 100 000 population. From 2011 to 2015, this coefficient had an annual percentage change of -1.9% (95% CI [-3.4, -0.5]) followed by an increase of 2.4% (95% CI [0.9, 3.9]) until 2019. The average mortality rate between 2011 and 2019 was 2.2 deaths per 100 000 population, with an average annual percentage change of -0.4% (95% CI [-1.0, 0.2]). Amazonas was the only state with an increase in the annual average percentage variation for the incidence rate (3.2%; 95% CI [1.3, 5.1]) and mortality rate (2.7%; 95% CI [1.0, 4.4]) over the years, while Rio de Janeiro state had an increasing inflection for incidence from 2014 to 2019 (2.4%; 95% CI [1.4, 3.5]) and annual average of decreasing percentage variation (-3.5%; 95% CI [-5.0, -1.9]). Conclusions: During the period analyzed, a decreasing trend in incidence was observed between 2011 and 2015, and an increasing trend for the period from 2015 to 2019. On the other hand, no change in the trend for mortality was found in Brazil.