Risk factors associated with drug-resistant tuberculosis in prisons in Sao Paulo State, Brazil (2006-2016).

INTRODUCTION: Prisons are high-risk settings for drug-resistant tuberculosis because the prevalence of the tuberculosis (TB) is much higher than in the general population. This study to investigated the factors associated with drug-resistant tuberculosis in prisons in the state of São Paulo, Brazil. METHODOLOGY: Retrospective cohort of drug-resistant TB cases for incarcerated people in São Paulo state, reported in the Tuberculosis Patient Control System between 2006 and 2016. To analyze the factors associated with drug-resistant TB, the backward method (likelihood ratio) was used, determining the adjusted odds ratio and respective 95%CI coefficients. Multiple models were proposed to adjust for potential confusion and interaction. The best fit model was selected based on the lowest Akaike information criterion coefficient. RESULTS: In total, 473 drug-resistant tuberculosis cases were reported in the prison population of Sao Paulo state, the majority were male. The cases that presented negative results for sputum smear and sputum culture had, respectively, an aOR=0.6 and aOR=0.16 for drug-resistant tuberculosis in relation to the cases with positive results. The cases where the patient had AIDS and reported alcoholism, respectively, an aOR=1.47 and aOR=1.60 for drug-resistant TB. Individuals with a background treatment history for TB presented a stronger association with drug-resistant tuberculosis, aOR=35.08. CONCLUSIONS: Sputum spear, sputum culture, chest X-ray, AIDS, alcoholism and background treatment history for TB were factors associated with resistance to antituberculosis drugs among prisoners. This is useful for the implementation of disease control measures related to the detection and monitoring of cases in the prison system.

Social risk and its association with tuberculosis mortality in a context of high inequality in South Brazil: A geo-epidemiology analysis.

BACKGROUND: Tuberculosis (TB) is one of the top 10 causes of death worldwide; in 2016, over 95% of TB deaths occurred in low- and middle-income countries. Although the incidence and deaths from TB have decreased in Brazil in recent years, the disease has increased in the vulnerable population, whose diagnosis is more delayed and the chances for abandonment and deaths are significantly higher. This study aimed to identify high-risk areas for TB mortality and evidence their social determinants through a sensitive tailored social index, in a context of high inequality in South Brazil. METHODS: A multistep statistical methodology was developed, based on spatial clustering, categorical principal components analysis, and receiver operating characteristic curves (ROC). This study considered 138 spatial units in Curitiba, South Brazil. TB deaths (2008-2015) were obtained from the National Information Mortality System and social variables from the Brazilian Human Development Atlas (2013). RESULTS: There were 128 TB deaths recorded in the study: the mortality rate was 0.9/100,000 inhabitants, minimum-maximum: 0-25.51/100,000, with a mean (standard deviation) of 1.07 (2.71), and 78 space units had no deaths. One risk cluster of TB mortality was found in the south region (RR=2.64, p=0.01). Considering the social variables, several clusters were identified in the social risk indicator (SRI): income (899.82/1752.94; 0.024), GINI Index (0.41/0.45; 0.010), and overcrowding (25.07/15.39; 0.032). The SRI showed a high capacity to discriminate the TB mortality areas (area under ROC curve 0.865, 95% CI: 0.796-0.934). CONCLUSIONS: A powerful risk map (SRI) was developed, allowing tailored and personalised interventions. The south of Curitiba was identified as a high-risk area for TB mortality and the majority of social variables. This methodological approach can be generalised to other areas and/or other public health problems.

Social determinants of deaths from pneumonia and tuberculosis in children in Brazil: an ecological study.

OBJECTIVE: To identify the risk areas of deaths due to unspecified pneumonia and tuberculosis (TB) in children, and to identify if there is a relationship between these events with higher TB incidence and social determinants. METHODS: Ecological study carried out in Brazil. All cases of TB or unspecified pneumonia deaths in children under 5 years of age reported between 2006 and 2016 were included and collected through Department of Informatics of the Unified Health System (Brazil's electronic database). The Spatial Scan Statistics was used to identify areas at higher risk of dying from this event. The spatial association was verified through the Getis-Ord techniques. The Bivariate Moran Global Index was used to verify the spatial autocorrelation between the two events. To identify the association of TB and pneumonia deaths with endemic areas of pulmonary TB and social determinants, four explanatory statistical models were identified. RESULTS: A total of 21 391 cases of pneumonia and 238 cases of TB were identified. Spatial scanning analysis enabled the detection of four clusters of risk for TB (relative risk, RR, between 3.30 and 18.18) and 22 clusters for pneumonia (RR between 1.38 and 5.24). The spatial association of the events was confirmed (z-score 3.74 and 64.34) and spatial autocorrelation between events (Moran Index:0.031 (p=0.001)). The zero-inflated negative binomial distribution was chosen, and an association for both events was identified with the TB incidence rate (OR 5.3, 95% CI 2.85 to 9.84; OR 6.63, 95% CI 5.62 to 7.81), with the Gini Index (OR 1.78, 95% CI 1.12 to 2.82; OR 4.22, 95% CI 3.63 to4.92). Primary care coverage showed an inverse association for both events (OR 0.10, 95% CI 0.67 to 0.17; OR 0.18, 95% CI 0.15 to 0.21) for pneumonia). Finally, a family that benefited from the Bolsa Família Programme had an inverse association for deaths from pneumonia (OR 0.81, 95% CI 0.52 to 1.25). CONCLUSIONS: The results do not just contribute to reduce mortality in children, but mainly contribute to prevent premature deaths through identification of critical areas in Brazil, which is crucial to qualify health surveillance services.