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.

Predictors of unsuccessful tuberculosis treatment outcomes in Brazil: an analysis of 259,484 patient records.

INTRODUCTION: Tuberculosis (TB) causes over 1 million deaths annually. Providing effective treatment is a key strategy for reducing TB deaths. In this study, we identified factors associated with unsuccessful treatment outcomes among individuals treated for TB in Brazil. METHODS: We obtained data on individuals treated for TB between 2015 and 2018 from Brazil's National Disease Notification System (SINAN). We excluded patients with a history of prior TB disease or with diagnosed TB drug resistance. We extracted information on patient-level factors potentially associated with unsuccessful treatment, including demographic and social factors, comorbid health conditions, health-related behaviors, health system level at which care was provided, use of directly observed therapy (DOT), and clinical examination results. We categorized treatment outcomes as successful (cure, completed) or unsuccessful (death, regimen failure, loss to follow-up). We fit multivariate logistic regression models to identify factors associated with unsuccessful treatment. RESULTS: Among 259,484 individuals treated for drug susceptible TB, 19.7% experienced an unsuccessful treatment outcome (death during treatment 7.8%, regimen failure 0.1%, loss to follow-up 11.9%). The odds of unsuccessful treatment were higher with older age (adjusted odds ratio (aOR) 2.90 [95% confidence interval: 2.62-3.21] for 85-100-year-olds vs. 25-34-year-olds), male sex (aOR 1.28 [1.25-1.32], vs. female sex), Black race (aOR 1.23 [1.19-1.28], vs. White race), no education (aOR 2.03 [1.91-2.17], vs. complete high school education), HIV infection (aOR 2.72 [2.63-2.81], vs. no HIV infection), illicit drug use (aOR 1.95 [1.88-2.01], vs. no illicit drug use), alcohol consumption (aOR 1.46 [1.41-1.50], vs. no alcohol consumption), smoking (aOR 1.20 [1.16-1.23], vs. non-smoking), homelessness (aOR 3.12 [2.95-3.31], vs. no homelessness), and immigrant status (aOR 1.27 [1.11-1.45], vs. non-immigrants). Treatment was more likely to be unsuccessful for individuals treated in tertiary care (aOR 2.20 [2.14-2.27], vs. primary care), and for patients not receiving DOT (aOR 2.35 [2.29-2.41], vs. receiving DOT). CONCLUSION: The risk of unsuccessful TB treatment varied systematically according to individual and service-related factors. Concentrating clinical attention on individuals with a high risk of poor treatment outcomes could improve the overall effectiveness of TB treatment in Brazil.

Clusters of heterogeneity of tuberculosis-HIV coinfection in Brazil: a geospatial study.

OBJECTIVE: To analyze the geospatialization of tuberculosis-HIV coinfection in Brazil, from 2010 to 2021, and the correlation with socioeconomic, housing, and health indicators. METHODS: An ecological study of Brazilian municipalities and states, with data from HIV and tuberculosis information systems, previously reported by the Ministry of Health. The crude and smoothed coefficients were calculated by the local empirical Bayesian method of incidence of coinfection per 100,000 inhabitants in the population aged between 18 and 59 years. Univariate (identification of clusters) and bivariate (correlation with 20 indicators) Moran's indices were used. RESULTS: A total of 122,223 cases of coinfection were registered in Brazil from 2010 to 2021, with a mean coefficient of 8.30/100,000. The South (11.44/100,000) and North (9.93/100,000) regions concentrated the highest burden of infections. The coefficients dropped in Brazil, in all regions, in the years of covid-19 (2020 and 2021). The highest coefficients were observed in the municipalities of the states of Rio Grande do Sul, Mato Grosso do Sul, and Amazonas, with high-high clusters in the capitals, border regions, coast of the country. The municipalities belonging to the states of Minas Gerais, Bahia, Paraná, and Piauí showed low-low clusters. There was a direct correlation with human development indices and aids rates, as well as an indirect correlation with the proportion of poor or of those vulnerable to poverty and the Gini index. CONCLUSIONS: The spatial analysis of tuberculosis-HIV coinfection showed heterogeneity in the Brazilian territory and constant behavior throughout the period, revealing clusters with high-burden municipalities, especially in large urban centers and in states with a high occurrence of HIV and/or tuberculosis. These findings, in addition to alerting to the effects of the covid-19 pandemic, can incorporate strategic planning for the control of coinfection, aiming to eliminate these infections as public health problems by 2030.

Temporal trend in the incidence of tuberculosis-HIV coinfection in Brazil, by macro-region, Federative Unit, sex and age group, 2010-2021.

OBJECTIVE: To analyze the temporal trend in the incidence of tuberculosis-HIV coinfection in Brazil, by macro-region, Federative Unit, sex and age group, from 2010 to 2021. METHODS: This was a time series study using surveillance data to estimate average annual percentage changes (AAPC), and 95% confidence intervals (95%CI) via joinpoint regression. RESULTS: 122,211 cases of tuberculosis-HIV coinfection were analyzed; a falling trend was identified for Brazil as a whole (AAPC = -4.3; 95%CI -5.1;-3.7), and in the country's Southern (AAPC = -6.2; 95%CI -6.9;-5.5) and Southeast (AAPC = -4.6; 95%CI -5.6;-3.8) regions, even more so during the COVID-19 pandemic (2020-2021); the greatest falling trend was seen in Santa Catarina (AAPC = -9.3; 95%CI -10.1;-8.5), while the greatest rising trend was found in Tocantins (AAPC = 4.1; 95%CI 0.1;8.6); there was a rising trend among males, especially in Sergipe (AAPC = 3.9; 95%CI 0.4;7.9), and those aged 18 to 34 years, especially in Amapá (AAPC = 7.9; 95%CI 5.1;11.5). CONCLUSION: The burden and trends of tuberculosis-HIV coinfection were geographically and demographically disparate.

Novel stepwise approach to assess representativeness of a large multicenter observational cohort of tuberculosis patients: The example of RePORT Brazil.

BACKGROUND: A major goal of tuberculosis (TB) epidemiological studies is to obtain results that can be generalized to the larger population with TB. The ability to extrapolate findings on the determinants of TB treatment outcomes is also important. METHODS: We compared baseline clinical and demographic characteristics and determinants of anti-TB treatment outcomes between persons enrolled in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil cohort between June 2015 and June 2019, and the registry of TB cases reported to the Brazilian National TB Program (Information System for Notifiable Diseases [SINAN]) during the same time period. Multivariable regression models adjusted for the study site were performed using second-generation p-values, a novel statistical approach. Associations with unfavorable treatment outcomes were tested for both RePORT-Brazil and SINAN cohorts. FINDINGS: A total of 1,060 culture-confirmed TB patients were enrolled in RePORT-Brazil and 455,873 TB cases were reported to SINAN. Second-generation p-value analyses revealed that the cohorts were strikingly similar with regard to sex, age, use of antiretroviral therapy and positive initial smear sputum microscopy. However, diabetes, HIV infection, and smoking were more frequently documented in RePORT-Brazil. Illicit drug use, the presence of diabetes, and history of prior TB were associated with unfavorable TB treatment outcomes; illicit drug use was associated with such outcomes in both cohorts. CONCLUSIONS: There were important similarities in demographic characteristics and determinants of clinical outcomes between the RePORT-Brazil cohort and the Brazilian National registry of TB cases.

Temporal trend in the incidence of tuberculosis-HIV coinfection in Brazil, by macro-region, Federative Unit, sex and age group, 2010-2021 / Tendencia temporal de la incidencia de coinfección tuberculosis-VIH en Brasil, por macrorregión, Unidad Federativa, sexo y grupo de edad, 2010-2021 / Tendência temporal da incidência de coinfecção tuberculose-HIV no Brasil, por macrorregião, Unidade da Federação, sexo e faixa etária, 2010-2021

ABSTRACT Objective To analyze the temporal trend in the incidence of tuberculosis-HIV coinfection in Brazil, by macro-region, Federative Unit, sex and age group, from 2010 to 2021. Methods: This was a time series study using surveillance data to estimate average annual percentage changes (AAPC), and 95% confidence intervals (95%CI) via joinpoint regression. Results: 122,211 cases of tuberculosis-HIV coinfection were analyzed; a falling trend was identified for Brazil as a whole (AAPC = -4.3; 95%CI -5.1;-3.7), and in the country's Southern (AAPC = -6.2; 95%CI -6.9;-5.5) and Southeast (AAPC = -4.6; 95%CI -5.6;-3.8) regions, even more so during the COVID-19 pandemic (2020-2021); the greatest falling trend was seen in Santa Catarina (AAPC = -9.3; 95%CI -10.1;-8.5), while the greatest rising trend was found in Tocantins (AAPC = 4.1; 95%CI 0.1;8.6); there was a rising trend among males, especially in Sergipe (AAPC = 3.9; 95%CI 0.4;7.9), and those aged 18 to 34 years, especially in Amapá (AAPC = 7.9; 95%CI 5.1;11.5). Conclusion The burden and trends of tuberculosis-HIV coinfection were geographically and demographically disparate.

RESUMEN Objetivo Analizar la tendencia temporal de la incidencia de la coinfección tuberculosis-VIH en Brasil, por Macrorregión, Unidad Federativa, sexo y grupo de edad, 2010-2021. Métodos Estudio de series de tiempo, con datos de vigilancia para la estimación de cambios porcentuales anuales promedio (CPAP) e intervalos de confianza del 95% (IC95%) vía joinpoint regression. Resultados Se analizaron 122.211 casos de coinfección tuberculosis-VIH; se identificó tendencia decreciente en Brasil (CPAP = -4,3; IC95% -5,1;-3,7) y en las regiones Sur (CPAP = -6,2; IC95% -6,9;-5,5) y Sudeste (CPAP = -4,6; IC95% -5,6;-3,8), aumentando durante la pandemia de covid-19; mayor tendencia decreciente ocurrió en Santa Catarina (CPAP = -9,3; IC95% -10,1;-8,5) y creciente en Tocantins (CPAP = 4,1; IC95% 0,1;8,6); hubo tendencia al aumento en el sexo masculino, especialmente Sergipe (CPAP = 3,9; IC95% 0,4;7,9), y en los de 18 a 34 años, especialmente Amapá (CPAP = 7,9; IC95% 5,1;11,5). Conclusión Había disparidades territoriales y demográficas en la carga y las tendencias de la coinfección tuberculosis-VIH.

RESUMO Objetivo Analisar a tendência temporal da incidência da coinfecção tuberculose-HIV no Brasil, por macrorregião, Unidade da Federação, sexo e faixa etária, 2010-2021. Métodos Estudo de séries temporais, com dados de vigilância, para a estimativa de variações percentuais anuais médias (VPAM) e intervalos de confiança de 95% (IC95%), por joinpoint regression. Resultados Foram analisados 122.211 casos de coinfecção tuberculose-HIV; identificou-se tendência decrescente no país (VPAM = -4,3; IC95% 5,1;-3,7) e em suas regiões Sul (VPAM = -6,2; IC95% -6,9;-5,5) e Sudeste (VPAM = -4,6; IC95% -5,6;-3,8), acentuada durante a pandemia de covid-19 (2020-2021); observou-se maior tendência decrescente em Santa Catarina (VPAM = -9,3; IC95% -10,1;-8,5) e maior tendência crescente no Tocantins (VPAM = 4,1; IC95% 0,1;8,6); houve tendência de incremento no sexo masculino, destacando-se Sergipe (VPAM = 3,9; IC95% 0,4;7,9), e na faixa etária de 18-34 anos, sobressaindo-se o Amapá (VPAM = 7,9; IC95% 5,1;11,5). Conclusão Verificaram-se disparidades territoriais e demográficas na carga e nas tendências da coinfecção tuberculose-HIV.

Clusters of heterogeneity of tuberculosis-HIV coinfection in Brazil: a geospatial study / Clusters da heterogeneidade da coinfecção tuberculose-HIV no Brasil: um estudo geoespacial

ABSTRACT OBJECTIVE To analyze the geospatialization of tuberculosis-HIV coinfection in Brazil, from 2010 to 2021, and the correlation with socioeconomic, housing, and health indicators. METHODS An ecological study of Brazilian municipalities and states, with data from HIV and tuberculosis information systems, previously reported by the Ministry of Health. The crude and smoothed coefficients were calculated by the local empirical Bayesian method of incidence of coinfection per 100,000 inhabitants in the population aged between 18 and 59 years. Univariate (identification of clusters) and bivariate (correlation with 20 indicators) Moran's indices were used. RESULTS A total of 122,223 cases of coinfection were registered in Brazil from 2010 to 2021, with a mean coefficient of 8.30/100,000. The South (11.44/100,000) and North (9.93/100,000) regions concentrated the highest burden of infections. The coefficients dropped in Brazil, in all regions, in the years of covid-19 (2020 and 2021). The highest coefficients were observed in the municipalities of the states of Rio Grande do Sul, Mato Grosso do Sul, and Amazonas, with high-high clusters in the capitals, border regions, coast of the country. The municipalities belonging to the states of Minas Gerais, Bahia, Paraná, and Piauí showed low-low clusters. There was a direct correlation with human development indices and aids rates, as well as an indirect correlation with the proportion of poor or of those vulnerable to poverty and the Gini index. CONCLUSIONS The spatial analysis of tuberculosis-HIV coinfection showed heterogeneity in the Brazilian territory and constant behavior throughout the period, revealing clusters with high-burden municipalities, especially in large urban centers and in states with a high occurrence of HIV and/or tuberculosis. These findings, in addition to alerting to the effects of the covid-19 pandemic, can incorporate strategic planning for the control of coinfection, aiming to eliminate these infections as public health problems by 2030.

RESUMO OBJETIVO Analisar a geoespacialização da coinfecção tuberculose-HIV no Brasil, de 2010 a 2021, e a correlação com indicadores socioeconômicos, habitacionais e sanitários. MÉTODOS Estudo ecológico dos municípios e estados brasileiros, com dados dos sistemas de informação do HIV e da tuberculose, previamente relacionados pelo Ministério da Saúde. Foram calculados os coeficientes brutos e suavizados pelo método bayesiano empírico local de incidência da coinfecção, por 100 mil habitantes, na população entre 18 e 59 anos. Empregaram-se os índices de Moran univariado (identificação de clusters) e bivariado (correlação com 20 indicadores). RESULTADOS Foram registrados 122.223 casos de coinfecção no Brasil, de 2010 a 2021, com coeficiente médio de 8,30/100 mil. As regiões Sul (11,44/100 mil) e Norte (9,93/100 mil) concentraram a maior carga das infecções. Houve queda dos coeficientes no Brasil, em todas as regiões, nos anos de covid-19 (2020 e 2021). Os maiores coeficientes foram visualizados nos municípios do Rio Grande do Sul, do Mato Grosso do Sul e do Amazonas, com aglomerados alto-alto nas capitais, em regiões de fronteira e no litoral do país. Os municípios pertencentes aos estados de Minas Gerais, da Bahia, do Paraná e do Piauí apresentaram clusters baixo-baixo. Houve correlação direta com os índices de desenvolvimento humano e as taxas de aids, bem como indireta com a proporção de pobres ou vulneráveis à pobreza e o índice de Gini. CONCLUSÕES A análise espacial da coinfecção tuberculose-HIV demonstrou heterogeneidade no território brasileiro e comportamento constante ao longo do período, revelando clusters com municípios de alta carga, principalmente nos grandes centros urbanos e nos estados com ocorrência elevada do HIV e/ou da tuberculose. Esses achados, além de trazerem um alerta para os efeitos da pandemia da covid-19, podem incorporar o planejamento estratégico para o controle da coinfecção, visando à eliminação dessas infecções como problemas de saúde pública até 2030.

Impacto da implantação do teste rápido molecular para a tuberculose no Brasil / Impact of roll out of rapid molecular test for tuberculosis in Brazil

Introdução: A tuberculose (TB) ainda se apresenta como um grave problema de saúde pública no mundo, com mais de 10 milhões de casos e 1,3 milhão de mortes anualmente. Em 2020, no Brasil, foram notificados 66.819 casos novos de TB, e aproximadamente 913 casos de TB drogarresistente. Cerca de 4.500 pessoas vão a óbito, anualmente, por TB no país. Com as tecnologias atuais, a melhor estratégia para controlar a transmissão e reduzir a incidência da TB é o diagnóstico e tratamento dos casos pulmonares bacilíferos, associados ao diagnóstico e tratamento da infecção latente. O Brasil incorporou, em 2014, o teste rápido molecular (TRM), recomendando-o como estratégia inicial para diagnóstico da TB e detecção da resistência à rifampicina (TB-RR). A presente tese buscou descrever e analisar o impacto da implantação do teste rápido molecular para tuberculose sobre os indicadores programáticos para o controle da tuberculose no Brasil, e o efeito do teste rápido molecular no início do tratamento em casos de tuberculose resistentes à rifampicina e/ou multidrogarresistente. Métodos: foram realizados estudos observacionais, com dados secundários. O primeiro, trata-se de um estudo ecológico cujas unidades de análise foram os municípios que compõe a rede de teste rápido molecular para TB (RTR-TB), e foram analisados os indicadores da TB antes e depois do início de utilização do TRM. Foi utilizada a modelagem de séries temporais interrompidas pela Regressão de Prais-Winsten. O segundo estudo teve como desenho uma coorte retrospectiva, tomando o indivíduo como unidade de análise. Foi utilizado o método de análise de sobrevida para avaliar o efeito do TRM sobre o tempo entre o diagnóstico e o início do tratamento dos casos novos de TB-RR / TB-MDR. A Regressão de Cox foi utilizada para estimação dos riscos proporcionais. Resultados: no período estudado, a RTR-TB consumiu um total de 1.756.358 cartuchos de TRM, sendo 1.734.935 testes realizados. A notificação de casos novos de TB na série histórica trimestral de janeiro de 2010 a junho de 2014 apresentou tendência estacionária. Após a implantação do TRM-TB, verificou-se uma tendência de aumento médio da ordem de 0,5% (IC 95%: 0,13 - 0,87) de casos novos, por trimestre, e em todo o período pós-intervenção, houve um incremento de 8.241 casos novos de TB nos municípios da RTR-TB, um aumento de 15% (IC 95%: 10,71 - 19,46) no nível de confirmação laboratorial dos casos novos de TB, e uma queda de 8,42% (IC 95%: -15,61 - -0,62) na realização de baciloscopia. Entre 2014 e 2019, 2.071 casos de TB-RR / TB-MDR tiveram o diagnóstico da resistência por meio do TRM, e 1.592 por meio do TSA. Após a incorporação do TRM, houve uma redução no tempo médio de início do tratamento da resistência em 89 dias (p-valor < 0,0001), quando comparado ao TSA. Indivíduos diagnosticados pelo TRM apresentam maior probabilidade de iniciar o tratamento da TB-DR mais precocemente quando comparado aos indivíduos diagnosticados pelo TSA, e essa diferença é mais acentuada até os primeiros 60 dias após o diagnóstico. Indivíduos diagnosticados pelo TSA apresentaram probabilidade 78% menor de iniciar o tratamento nos primeiros 30 dias após o diagnóstico da resistência quanto comparado aos indivíduos diagnosticados pelo TRM (HRadj: 0,22; IC95%: 0,13 - 0,36), e 49% menor probabilidade de iniciar o tratamento nos primeiros seis meses após o diagnóstico quando comparado aos indivíduos diagnosticados pelo TRM (HRadj: 0,51; IC95%: 0,39 - 0,62). Conclusões: o TRM apresentou, de forma global, impacto positivo nas estratégias de controle da TB do Brasil, reestruturando a rede de diagnóstico da doença, aumentando a confirmação laboratorial, e diminuindo o tempo entre o diagnóstico e o início do tratamento da TB-RR / TB-MDR. A incorporação do TRM no SUS propiciou um diagnóstico da doença mais rápido e com maior sensibilidade, viabilizando um diagnóstico muito mais oportuno da TB-RR / TB-MDR, e encurtando o tempo para início do tratamento da TB resistente. A ampliação do diagnóstico rápido molecular por TRM para os municípios que ainda não compõe a RTR-TB podem contribuir para um melhor controle da TB no país.

Introduction: Tuberculosis (TB) still is as a serious public health problem in the world, with more than 10 million cases and 1.3 million deaths annually. In 2020, in Brazil, 66.819 new cases of TB and approximately 913 cases of drug-resistant TB were notified. About 4,500 persons die annually from TB in the country. With the current technologies available, the best strategies to control the transmission and to reduce the TB incidence is the diagnosis and treatment of the bacilliferous pulmonary cases, associated with the diagnosis and treatment of latent infection. In 2014, Brazil has incorporated the rapid molecular test (TRM), recommending it as an initial strategy for diagnosing TB and detecting rifampicin resistance (TB-RR). The present thesis describes and analyses the impact of the roll out of the TRM for TB on the programmatic indicators for TB control in Brazil, and the effect of the TRM in the beginning of the treatment in cases of tuberculosis resistant to rifampicin and/or multidrugresistent. Methods: observational studies were performed with routine data. The first study was an ecological study whose units of analysis were the municipalities that make up the rapid molecular testing network for TB (RTR-TB), and TB indicators were analyzed before and after the beginning of TRM use. The modeling of time series interrupted by the Prais-Winsten Regression was used. The second study was a retrospective cohort, whose the individual was the unit of analysis. The survival analysis method was used to assess the effect of TRM on the time between diagnosis and initiation of treatment of new cases of RR-TB / MDR-TB. Cox regression was used to estimate proportional hazards. Results: in the period studied, the RTR-TB consumed a total of 1,756,358 TRM cartridges, with 1,734,935 tests performed. The notification of new TB cases in the quarterly historical series from January 2010 to June 2014 showed a stationary trend. After the implementation of the TRM-TB, there was a trend towards an average increase of around 0.5% (95% CI: 0.13 - 0.87) of new cases, per quarter-year, and throughout the post-intervention period, there was an increase of 8,241 new TB cases in the municipalities of RTR-TB, a 15% increase (95% CI: 10.71 - 19.46) in the level of laboratory confirmation of new TB cases, and a decrease of 8.42% (95% CI: -15.61 - -0.62) in performing smear microscopy. Between 2014 and 2019, 2,071 RR-TB/MDR-TB cases were diagnosed with resistance through TRM, and 1,592 through TSA. After the incorporation of TRM, there was a reduction in the mean time of initiation of resistance treatment by 89 days (p-value < 0.0001), when compared to TSA. Individuals diagnosed by TRM are more likely to start DR-TB treatment earlier when compared to individuals diagnosed by TSA, and this difference is more accentuated up to the first 60 days after diagnosis. Persons diagnosed by TSA were 78% less likely to start the treatment in the first 30 days after the diagnosis of resistance when compared to those diagnosed by TRM (HRadj: 0.22; 95% CI: 0.13 - 0.36), and 49% lower probability of starting the treatment in the first six months after the diagnosis when compared to those diagnosed by TRM (HRadj: 0.51; 95%CI: 0.39 - 0.62). Conclusions: Overall, the TRM had a positive impact on TB control strategies in Brazil, restructuring the disease diagnosis network, increasing laboratory confirmation, and reducing the time between diagnosis and initiation of TB-RR / TB-MDR treatment. The incorporation of TRM into the Public Health System in Brazil provided a faster and more sensitive diagnosis of the disease, enabling a much more timely diagnosis of RR-TB / MDR-TB, and shortening the time to start treatment for resistant TB. The expansion of rapid molecular diagnosis by TRM to municipalities that are not yet part of the RTR-TB may contribute to better control of the disease in the country.