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IMPACT OF STRATEGIC PUBLIC HEALTH INTERVENTIONS TO REDUCE TUBERCULOSIS INCIDENCE IN BRAZIL: A BAYESIAN STRUCTURAL TIMESERIES SCENARIO ANALYSIS
Public health
Forecasting
Vulnerabilities
Directly observed therapy
Tuberculosis preventive therapy
Author
Affilliation
Universidade Salvador. Curso de Medicina. Salvador, BA, Brasil / Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Fiocruz Rondônia. Laboratório de Análise e Visualização de Dados. Porto Velho, RO, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil.
Boston University. School of Public Health. Department of Epidemiology. Boston, MA, USA.
Fundação Oswaldo Cruz. Fiocruz Mato Grosso do Sul. Campo Grande, MS, Brasil / Department of Epidemiology of Microbial Diseases. Yale School of Public Health. New Haven, CT, USA / Universidade Federal de Mato Grosso do Sul. Faculdade de Medicina. Campo Grande, MS, Brasil.
Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.
Universidade Federal do Rio de Janeiro. Faculdade de Medicina. Programa Acadêmico de Tuberculose. Rio de Janeiro, RJ, Brasil.
Fundação Medicina Tropical Dr. Heitor Vieira Dourado. Manaus, AM, Brasil / Universidade do Estado do Amazonas. Programa de Pós-Graduação em Medicina Tropical. Manaus, AM, Brasil / Universidade Nilton Lins. Manaus, AM, Brasil.
Vanderbilt University School of Medicine. Department of Medicine. Division of Infectious Diseases. Nashville, TN, USA.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil.
Universidade Salvador. Curso de Medicina. Salvador, BA, Brasil / Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil / Escola Bahiana de Medicina e Saúde Pública. Centro de Pesquisa Clínica. Salvador. BA, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Fiocruz Rondônia. Laboratório de Análise e Visualização de Dados. Porto Velho, RO, Brasil.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil.
Boston University. School of Public Health. Department of Epidemiology. Boston, MA, USA.
Fundação Oswaldo Cruz. Fiocruz Mato Grosso do Sul. Campo Grande, MS, Brasil / Department of Epidemiology of Microbial Diseases. Yale School of Public Health. New Haven, CT, USA / Universidade Federal de Mato Grosso do Sul. Faculdade de Medicina. Campo Grande, MS, Brasil.
Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.
Universidade Federal do Rio de Janeiro. Faculdade de Medicina. Programa Acadêmico de Tuberculose. Rio de Janeiro, RJ, Brasil.
Fundação Medicina Tropical Dr. Heitor Vieira Dourado. Manaus, AM, Brasil / Universidade do Estado do Amazonas. Programa de Pós-Graduação em Medicina Tropical. Manaus, AM, Brasil / Universidade Nilton Lins. Manaus, AM, Brasil.
Vanderbilt University School of Medicine. Department of Medicine. Division of Infectious Diseases. Nashville, TN, USA.
Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil.
Universidade Salvador. Curso de Medicina. Salvador, BA, Brasil / Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Pesquisa Clínica e Translacional. Salvador, BA, Brasil / Faculdade Zarns. Instituto de Pesquisa Clínica e Translacional. Clariens Educação. Salvador. BA, Brasil / Escola Bahiana de Medicina e Saúde Pública. Centro de Pesquisa Clínica. Salvador. BA, Brasil.
Abstract
Background: Despite government efforts, tuberculosis (TB) remains a major public health threat in Brazil. In 2023, TB incidence was 39.8 cases per 100,000 population, far above the WHO’s target of 6.7 cases per 100,000. Using national-level datasets, we investigated and forecasted the potential impact of proposed public health interventions aimed at reducing TB incidence in Brazil. Methods: Monthly TB surveillance data (January 2018–December 2023) were collected from Brazilian national reporting systems: SINAN-TB (TB cases), SITE-TB (TB drug resistance), and IL-TB (preventive therapy). These data were used to create a multivariable Bayesian Structural Time-Series (BSTS) model, with 5000 Monte-Carlo simulations, which identified key predictors of TB incidence and forecasted these rates from 2024 to 2030 under various scenarios. Findings: Vulnerabilities including incarceration, TB-HIV coinfection and TB-diabetes mellitus, as well as coverages of directly observed therapy (DOT), contact investigation and preventive treatment (TPT) completion rates, were identified as key predictors of TB incidence. Under current trends, we forecasted TB incidence in Brazil to be 42.1 [34.1–49.8] per 100,000 person-years by 2030 (mean [95% prediction intervals]). A scenario considering decreases in TB cases among vulnerable populations resulted in an absolute reduction of −10.6 [−9.4 to −12.0] in projected TB incidence. Additional reductions were seen with increased coverage of DOT, TPT adherence, and contact investigation rates (−14.4 [−13 to −16.2]), and by combining these with efforts to reduce TB cases among vulnerable populations (−23.6 [−26.3 to −41.4]), potentially lowering incidence to 18.5 [7.8–28.4] per 100,000, though still above WHO targets. Interpretation: Our findings demonstrate that interventions focused on enhancing health policies focused on decreasing TB cases among vulnerable populations, such as individuals with TB-HIV coinfection, incarcerated populations, and those with TB-diabetes comorbidity, along with improvements in health management indicators such as DOT implementation, contact investigation coverage, and TPT completion rates, are effective in reducing TB incidence nationwide.
Keywords
TuberculosisPublic health
Forecasting
Vulnerabilities
Directly observed therapy
Tuberculosis preventive therapy
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