José Mário Nunes da Silva

Background: Pulmonary tuberculosis (PTB) remains a major public health problem, strongly associated with social and territorial inequalities. This study aimed to analyse temporal trends, spatiotemporal transmission patterns and socioeconomic determinants of PTB in the state of Piauí, Northeast Brazil, from 2001 to 2024. Methods: An ecological study was conducted using official surveillance data on newly reported PTB cases at the municipal level. Temporal, spatial and spatiotemporal analytical methods were applied to investigate long‐term trends, transmission patterns and socioeconomic determinants associated with PTB incidence. Results: A total of 17,186 PTB cases were reported. Time‐series analysis showed a sustained decline in incidence between 2001 and 2015, followed by a period of gradual recovery starting in 2016. Seasonality remained stable, with peaks occurring between April and June. Persistent spatial heterogeneity was identified, with higher‐risk clusters concentrated in urban municipalities. Multivariate spatiotemporal time‐series analysis revealed the predominance of the endemic component, with a secondary contribution from the autoregressive component and minimal contribution from the spatiotemporal component. In the spatial Bayesian analysis, PTB incidence was associated with AIDS incidence (Relative Risk [RR] = 1.11; 95% Credible Interval [CrI]: 1.05–1.18), the number of nurses per 1000 inhabitants (RR = 1.08; 95% CrI: 1.03–1.13) and per capita municipal health expenditure (RR = 0.94; 95% CrI: 0.89–0.98). Conclusions: PTB in the Piauí exhibited heterogeneous spatiotemporal patterns, being sustained primarily by endemic factors and persistent structural inequalities. Control strategies should be territorially targeted, considering local transmission patterns and the identified determinants.

Background: Identifying high-risk areas for pulmonary tuberculosis (PTB) is essential for understanding the dynamics of disease transmission and for guiding more effective control strategies. Therefore, this study aimed to analyze the temporal trends and spatiotemporal distribution of PTB across Brazilian municipalities between 2010 and 2023. Methods: This is an ecological study using data on PTB cases reported in Brazil’s Notifiable Diseases Information System (SINAN) from 2010 to 2023. Time series analysis, global and local spatial autocorrelation, and space-time scan techniques were applied to identify temporal trends and spatial patterns of the disease at the municipal level. Results: A total of 896,062 new PTB cases were analyzed. Notification peaked mainly in March and August. The average incidence rate was 30.3 cases per 100,000 inhabitants-years. An increasing trend was observed in 13 states and the Federal District. Spatial analysis identified 804 municipalities as hotspots, with 168 showing persistent high incidence throughout the study period. A total of 28 spatiotemporal clusters were detected, involving 379 municipalities, of which 212 were classified as high priority. The most likely cluster was located in the Rio de Janeiro Metropolitan Region, encompassing 10 municipalities, with a relative risk (RR) of 2.51 between 2017 and 2023. Spatial variation in temporal trends identified 22 additional clusters, including a prominent cluster composed of 493 municipalities in the Legal Amazon, which showed an internal time trend of 1.99% annual growth and a RR of 1.51. Conclusion: The study identified persistent and expanding patterns of PTB in Brazil at both regional and national levels, revealing specific areas with higher burden and increasing trends that should be prioritized. These findings provide evidence to support decision-making at federal level while reinforce the need for regionally tailored surveillance and control strategies to ensure a more effective and equitable response to tuberculosis across the country.

Background: Tuberculosis (TB) remains a major public health challenge in Brazil, characterised by marked regional heterogeneity. This study aimed to analyse the temporal dynamics of TB in a state of northeast Brazil. Methods: This was an ecological time-series study using official TB surveillance data on newly reported TB cases from 2010 to 2024. Age-standardised incidence rates (ASIRs) were analysed through seasonal-trend decomposition by Loess (STL) and Joinpoint regression models. Furthermore, the rates were decomposed to quantify the contributions of population ageing, population growth and epidemiological changes. Results: A total of 10 690 TB cases were reported. Time-series analysis revealed consistent seasonality, with peaks occurring in March–May and October–November. The ASIR declined from 25.8 per 100 000 in 2010 to 22.6 in 2024 (average annual percentage change −1.51 [95% confidence interval −2.50 to −0.38). The decline was most pronounced among women and individuals ages 50–79 y, whereas incidence increased among younger age groups. Decomposition analysis indicated that epidemiological improvements offset demographic effects until 2015. However, from 2023 onwards, population ageing and growth became the predominant drivers, leading to a net increase in incidence. Conclusions: Although TB incidence declined overall, recent resurgence highlights the growing impact of demographic dynamics and persistent regional disparities.

Background: Despite advancements in tuberculosis (TB) control policies in Brazil, the disease remains a significant public health concern. This study aimed to analyze long-term trends and projections of pulmonary tuberculosis (PTB) incidence rates in metropolitan and non-metropolitan areas of Brazil from 2001 to 2035, as well as to quantify the contributions of demographic and epidemiological changes to these patterns. Methods: This ecological study used national PTB case notification data reported to Brazil’s Notifiable Diseases Information System from 2001 to 2020. Joinpoint regression was applied to identify changes in temporal trends. Age-period-cohort models were employed to examine the effects of age, period, and birth cohort on disease risk. A decomposition analysis was then conducted to assess the contributions of population aging, demographic growth, and epidemiological changes. Finally, Bayesian age-period-cohort models were used to project the TB burden through 2035, stratified by sex and area. Results: Between 2001 and 2020, PTB incidence declined by an average of − 2.67% (95% CI − 3.43, − 2.08) per year in metropolitan areas and − 2.54% (95% CI − 2.92, − 2.16) in non-metropolitan areas of Brazil. However, decomposition analysis showed that the absolute number of PTB cases in metropolitan areas increased, primarily driven by population growth (+ 21,610 cases in men; + 10,545 in women), with a smaller contribution from population aging (+ 2649 and + 521 cases, respectively). In non-metropolitan areas, reductions were mainly explained by epidemiological improvements (− 8314 cases in men; − 6663 in women) and population decline (− 4972 and − 2380 cases, respectively), outweighing the effects of aging. Looking ahead, projections indicate that PTB incidence will rise in metropolitan areas, from 52.6 in 2015 to 62.4 [95% credible interval (CrI): 37.1–87.8] per 100,000 by 2035, while stabilizing at relatively high levels in non-metropolitan areas, increasing from 28.4 to 33.8 per 100,000 (95% CrI: 19.3–48.3) among men. Conclusion: Metropolitan areas are projected to experience substantial increases in PTB incidence, while non-metropolitan regions are expected to stabilize at persistently high levels, particularly among men. The findings indicate that current TB control efforts in Brazil need to be strengthened for the country to meet the 2035 targets, especially in metropolitan areas. Graphical

Background: Social inequalities play a crucial role in the incidence of TB, making it plausible that they act as effect modifiers on the impact of active case-finding (ACF) strategies in the detection of the disease. We estimated the association between ACF strategies and TB detection rates and evaluated their effect modification due to social inequalities in Brazilian municipalities. Methods: We included 5033 municipalities that reported at least one new TB case. We defined the TB detection rate as the outcome variable. Our exposure variables were the proportion of primary care team (PCT) reporting community-based ACF for TB and household contact investigation (HCI) of new TB cases. We also assessed the Municipal Human Development Index (MHDI) and the Social Vulnerability Index (SVI) as potential effect modifier variables. Results: The TB detection rate was positively associated with both the proportion of PCTs conducting community-based ACF and the proportion conducting HCI. These associations weakened as MHDI increased (interaction incident rate ratio [IRR] 0.95, 95% CI 0.90 to 0.98 for ACF; IRR 0.93, 95% CI 0.89 to 0.96 for HCI) and strengthened with higher SVI values (IRR 1.11, 95% CI 1.02 to 1.22 and IRR 1.17, 95% CI 1.08 to 1.27, respectively). Conclusion: Social inequalities in Brazilian municipalities modify the effect of ACF strategies on TB detection rates.

Objective: To assess the relationship between socioeconomic factors and the provision of oral health services in Primary Healthcare with mortality due to oral cancer in Brazil.Methods: This ecological study was conducted across 1105 Brazilian municipalities, encompassing 11,412 oral health teams (OHTs). The outcome variable was the oral cancer mortality rate, standardized by age and sex. Socioeconomic factors and variables related to the oral health services provided by municipal OHTs were considered explanatory variables. We employed multilevel Poisson regression models with random effects at the municipal level to assess the association between oral cancer mortality rates and explanatory variables.Results: At the municipal level, oral cancer mortality was negatively associated with higher human and social development and greater income inequality but positively linked to higher rates of population aging and greater coverage of primary and oral healthcare services. At the OHT level, mortality reduction was observed among those who received specialized support and had greater availability of consultations. Active case‐finding for cancerous lesions and care monitoring were also linked to lower mortality. Conversely, the identification of high‐risk vulnerable patients by these teams was associated with higher mortality.Conclusion: This study suggests that oral cancer mortality in Brazilian municipalities is influenced by socioeconomic factors and the availability of oral health services.