Factors associated with non-completion of TB preventive treatment in Brazil.

BACKGROUND: Among Brazilian initiatives to scale up TB preventive therapy (TPT) are the adoption of the 3HP regimen (12 weekly doses of rifapentine and isoniazid [INH]) in 2021 and the implementation in 2018 of the TPT surveillance information system. Since then, 63% of the 76,000 eligible individuals notified completed TPT. Recommended regimens in this period were 6H, 9H (6 or 9 months of INH) and 4R (4 months of rifampicin).OBJECTIVE: To analyse the factors associated with TPT non-completion.METHODS: We analysed the cohort of TPT notifications from 2018 to 2020. Robust variance Poisson regression model was used to verify the association of TPT non-completion with sociodemographic, clinical and epidemiological variables.RESULTS: Of the 39,973 TPT notified in the study period, 8,534 (21.5%) were non-completed, of which 7,858 (92.1%) were lost to follow-up. Age 15-60 years (relative risk [RR] 1.27, 95% confidence interval [95% CI] 1.20-1.35), TPT with isoniazid (RR 1.40, 95% CI 1.19-1.64) and Black/mixed race (RR 1.17, 95% CI 1.09-1.25) were associated with a higher risk of non-completion.CONCLUSION: Individuals in situations of social and financial vulnerability such as being Black/pardo race, younger and on longer TPT regimens were more likely to be associated with TPT incompletion.

Spatial patterns of pulmonary tuberculosis incidence and their relationship to socio-economic status in Vitoria, Brazil.

OBJECTIVE: To investigate spatial patterns of the incidence of pulmonary tuberculosis (TB) and its relationship with socio-economic status in Vitoria, Espirito Santo, Brazil. DESIGN: In a 4-year, retrospective, territory-based surveillance study of all new pulmonary TB cases conducted in Vitoria between 2002 and 2006, spatial patterns of disease incidence were compared using spatial clustering statistics (Anselin's local indicators of spatial association [LISA] and Getis-Ord Gi* statistics), smoothed empirical Bayes estimates and model-predicted incidence rates. Spatial Poisson models were fit to examine the relationship between socio-economic status and TB incidence. RESULTS: A total of 651 TB cases were reported across 78 neighborhoods, with rates ranging from 0 to 129 cases per 100,000 population. Moran's I indicated strong spatial autocorrelation among incidence rates (0.399, P < 0.0001), and four areas of high incidence were identified by LISA and Gi* statistics. Smoothed spatial empirical Bayes estimates demonstrate that two of these areas range from 70 to 90 cases/100,000, while the other two range from 40 to 70 cases/100,000. TB incidence and socio-economic status had a significant curvilinear relationship (P = 0.02). CONCLUSIONS: Data derived from these spatial statistical tools will help TB control programs to allocate TB resources to those populations most at risk of increasing TB rates and to target areas where TB control efforts need to be concentrated.

Delay in diagnosis of pulmonary tuberculosis at a primary health clinic in Vitoria, Brazil.

SETTING: Primary health clinics in Vitoria, Espirito Santo, Brazil. OBJECTIVE: To identify risk factors associated with patient and health care delays among patients seeking care at primary health clinics. METHODS: A prospective study among tuberculosis (TB) patients diagnosed in Vitoria between 1 January 2003 and 30 December 2007. A questionnaire ascertained the date of onset and duration of TB symptoms and medical records were reviewed. Between-group distributions of delay were compared and multivariate logistic regression was performed. RESULTS: Of 304 patients, 296 (97%) reported at least one TB symptom presenting for the first time to a qualified health service; 244 (80%) reported cough > 3 weeks. Median health care delay was 30 days (range 5-68), and median total delay was 110 days (range 26-784). Multivariate analysis revealed any cough (OR(adj) 7.35, 95%CI 2.40-22.5) and weight at TB diagnosis < 60 kg (OR(adj) 5.92, 95%CI 1.83-19.1) to be associated with patient delay of ≥ 30 days. Factors increasing risk of prolonged delay (≥ 90 days) were age ≥ 30 years (OR(adj) 1.93, 95%CI 1.09-3.43) and chest pain (OR(adj) 2.42, 95%CI 1.29-4.53). CONCLUSION: Improving health care workers' education regarding TB symptoms and implementing active case finding in targeted populations may reduce delays.