Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil.

BACKGROUND: A diagnosis of tuberculosis (TB) does not mean that the disease will be treated successfully, since death may occur even among those who are known to the health services. Here, we aimed to analyze patient survival time from the diagnosis of TB to death, precocious deaths, and associated factors in southern Brazil. METHODS: We conducted a longitudinal study with patients who were diagnosed with TB and who died due to the disease between 2008 and 2015 in southern Brazil. The starting point for measuring survival time was the patient's diagnosis date. Techniques for survival analysis were employed, including the Kaplan-Meier test and Cox's regression. A mixed-effect model was applied for identifying the associated factors to precocious deaths. Hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (95% CI) were estimated. We defined p value <0.05 as statistically significant for all statistics applied. RESULTS: One hundred forty-six patients were included in the survival analysis, observing a median survival time of 23.5 days. We observed that alcoholism (HR=1.55, 95% CI=1.04-2.30) and being male (HR=6.49, 95% CI=1.03-2.68) were associated with death. The chance of precocious death within 60 days was 10.48 times greater than the chance of early death within 30 days. CONCLUSION: Most of the deaths occurred within 2 months after the diagnosis, during the intensive phase of the treatment. The use of alcohol and gender were associated with death, revealing inequality between men and women. This study advanced knowledge regarding the vulnerability associated with mortality. These findings must be addressed to fill a gap in the care cascades for active TB and ensure equity in health.

Effect of social development in reducing tuberculosis mortality In northeastern Brazil areas.

INTRODUCTION: Tuberculosis (TB) is the primary cause of death among infectious diseases affecting groups in extreme poverty. Social improvements could reverse this situation in Brazil. This study aims to demonstrate the spatial relationship between social development (SD) and TB mortality in Natal, a city in northeastern Brazil. METHODOLOGY: Ecological study. The study population comprised TB deaths recorded in the Mortality Information System between 2008 and 2014. The units of analysis were 59 human development units (HDUs). Raw and smoothed mortality rates were calculated using the global empirical Bayes method. Primary components analysis was used to develop the SD indicators. An association between TB mortality and SD was verified using multiple linear regression analysis. Spatial autocorrelation was verified using models with global spatial effects. Analyses were performed using Statistica version 12.0, ArcGIS version 10.2, Statistical Package for the Social Sciences version 20.0, and OpenGeoDa 1.0.1. The significance level was established at 5% (p < 0.05). RESULTS: The TB mortality rate with non-random spatial distribution ranged between 0.52 and 8.90 per 100,000 inhabitants. The spatial lag model was chosen because it presented the highest log-likelihood value, lowest AIC, and highest R2. A negative association was found between TB mortality and SD (R2 = 0.207; p = 0.03). CONCLUSIONS: The results show a negative association between TB mortality and the high SD indicator. This study can support decision-making in terms of collective projects within public health in order to link the health field to other sectors, aiming for social well-being and human development.

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.

Leprosy in urban space, areas of risk for disability and worsening of this health condition in Foz Do Iguaçu, the border region between Brazil, Paraguay and Argentina.

BACKGROUND: Leprosy is a public health problem and a challenge for endemic countries, especially in their border regions where there are intense migration flows. The study aimed to analyse the dynamics of leprosy, in order to identify areas of risk for the occurrence of the disease and disability and places where this health condition is worsening. METHOD: This ecological study considered the new cases of leprosy reported in the municipality of Foz do Iguaçu from 2003 to 2015. Spatial and spatial-temporal scan statistics were used to identify the risk areas for the occurrence of leprosy, as well as the Getis-Ord Gi and Getis-Ord Gi* methods. Areas of risk for disabilities were identified by the scan statistic and kernel density estimation. RESULTS: A total of 840 cases were reported, of which 179 (21.3%) presented Grade 1 or 2 disabilities at the time of diagnosis. Leprosy risk areas were concentrated in the Southern, Eastern and Northeastern Health Districts of the municipality. The cases of Grade 2 disability were observed with higher intensity in regions characterized by high population density and poverty. CONCLUSION: The results of the study have revealed changes in the pattern of areas at risk of leprosy according to the investigated periods. In addition, it was possible to verify disabilities as a condition present in the investigated cases, or that may be related to the late diagnosis of the disease. In the areas of risk identified, patients have reported worse physical disability after diagnostic confirmation, or indicate inadequate clinical examination, reinforcing the need for structuring leprosy control services in a qualified manner.

Detection of risk clusters for deaths due to tuberculosis specifically in areas of southern Brazil where the disease was supposedly a non-problem.

BACKGROUND: Tuberculosis (TB) is the infectious disease that kills the most people worldwide. The use of geoepidemiological techniques to demonstrate the dynamics of the disease in vulnerable communities is essential for its control. Thus, this study aimed to identify risk clusters for TB deaths and their variation over time. METHODS: This ecological study considered cases of TB deaths in residents of Londrina, Brazil between 2008 and 2015. We used standard, isotonic scan statistics for the detection of spatial risk clusters. The Poisson discrete model was adopted with the high and low rates option used for 10, 30 and 50% of the population at risk, with circular format windows and 999 replications considered the maximum cluster size. Getis-Ord Gi* (Gi*) statistics were used to diagnose hotspot areas for TB mortality. Kernel density was used to identify whether the clusters changed over time. RESULTS: For the standard version, spatial risk clusters for 10, 30 and 50% of the exposed population were 4.9 (95% CI 2.6-9.4), 3.2 (95% CI: 2.1-5.7) and 3.2 (95% CI: 2.1-5.7), respectively. For the isotonic spatial statistics, the risk clusters for 10, 30 and 50% of the exposed population were 2.8 (95% CI: 1.5-5.1), 2.7 (95% CI: 1.6-4.4), 2.2 (95% CI: 1.4-3.9), respectively. All risk clusters were located in the eastern and northern regions of the municipality. Additionally, through Gi*, hotspot areas were identified in the eastern and western regions. CONCLUSIONS: There were important risk areas for tuberculosis mortality in the eastern and northern regions of the municipality. Risk clusters for tuberculosis deaths were observed in areas where TB mortality was supposedly a non-problem. The isotonic and Gi* statistics were more sensitive for the detection of clusters in areas with a low number of cases; however, their applicability in public health is still restricted.

Areas with evidence of equity and their progress on mortality from tuberculosis in an endemic municipality of southeast Brazil.

BACKGROUND: In Brazil, people still fall ill and die from tuberculosis (TB), and this can be explained by the significant impasse in the equity of distribution of therapeutic resources to the population as a whole. The aim was to identify geographical areas which have shown progress in terms of equity (of income, schooling and urban occupancy) and test its effect on mortality from TB in a municipality of southeast Brazil. METHODS: It is an ecological study considering TB as the basic cause for deaths registered between 2006 and 2013 on the Mortality Information System and other variables obtained through the Demographic Census of the Brazilian Institute of Geography and Statistics (2010). The geographical area for analysis comprised the areas of coverage of the health services. Social indicators have been constructed through the Principal Component Analysis (PCA). The cases were geocoded and the annual mortality rate from TB was calculated with smoothing using the local empirical Bayesian method. Multiple linear regression was then performed. There was confirmation of the existence of spatial dependence of residue through the application of the Global Moran I test, and application of the Models with Global Spatial Effects, to identify the best standard of spatial regression. RESULTS: The mortality rates ranged from 0.00 to 2.8 deaths per 100,000 people, per year. In the PCA, three indicators were constructed, and designated as indicators of income, social inequality, and social equity. In multiple linear regression, the indicator of social equity was statistically significant (P < 0.0001) but had a negative association, an adjusted R2 of 28.36% and with spatial dependence (Moran I = 0.21, P = 0.003455). The best model to deal with existing spatial dependence was the Spatial Lag Model. CONCLUSIONS: The better social conditions have shown progress in reducing mortality from TB, thereby reinforcing the achievement of Sustainable Development Goals. In addition, cartography was also applied, which can be replicated in other scenarios throughout the world, using a scope distinct from that of works traditionally produced in that it places the emphasis on social equity.

Validity and reliability of the tuberculosis-related stigma scale version for Brazilian Portuguese.

BACKGROUND: Stigma associated with tuberculosis (TB) has been an object of interest in several regions of the world. The behaviour presented by patients as a result of social discrimination has contributed to delays in diagnosis and the abandonment of treatment, leading to an increase in the cases of TB and drug resistance. The identification of populations affected by stigma and its measurement can be assessed with the use of valid and reliable instruments developed or adapted to the target culture. This aim of this study was to analyse the initial psychometric properties of the Tuberculosis-Related Stigma scale in Brazil, for TB patients. METHODS: The Tuberculosis-Related Stigma scale is a specific scale for measuring stigma associated with TB, originally validated in Thailand. It presents two dimensions to be assessed, namely Community perspectives toward tuberculosis and Patient perspectives toward tuberculosis. The first has 11 items regarding the behaviour of the community in relation to TB, and the second is made up of 12 items related to feelings such as fear, guilt and sorrow in coping with the disease. A pilot test was conducted with 83 TB patients, in order to obtain the initial psychometric properties of the scale in the Brazilian Portuguese version, enabling simulation of the field study. RESULTS: As regards its psychometric properties, the scale presented acceptable internal consistency for its dimensions, with values ≥0.70, the absence of floor and ceiling effects, which is favourable for the property of scale responsiveness, satisfactory converging validity for both dimensions, with values over 0.30 for initial studies, and diverging validity, with adjustment values different from 100%. CONCLUSION: The results found show that the Tuberculosis-Related Stigma scale can be a valid and reliable instrument for the Brazilian context.

Spatial clustering and local risk of leprosy in São Paulo, Brazil.

BACKGROUND: Although the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D) is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method. METHODS: Data were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk-RR) of leprosy. Maps considering these risks and their confidence intervals were constructed. RESULTS: A total of 434 cases were identified, including 188 (43.31%) borderline leprosy and 101 (23.28%) lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75%) presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000) contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721-4.267). Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133-52.984) and 15.24 (95%CI = 10.114-22.919). CONCLUSION: These findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting.

Prevalence and evolution of Mycobacterium tuberculosis infection in tuberculosis case contacts.

INTRODUCTION: The tuberculin test is a diagnostic method for detecting latent tuberculosis (TB) infection, especially among disease contact cases. The objective of this study was to analyze the prevalence and evolution of Mycobacterium tuberculosis infection among TB contact cases. METHODS: A retrospective cohort study was performed in a reference center for TB. The study population consisted of 2,425 patients who underwent a tuberculin test from 2003 to 2010 and whose results indicated contact with individuals with TB. The data were collected from the registry book of the tuberculin tests, patient files and the Information System Records of Notification Grievance. To verify the evolution of TB, case records through September 2014 were consulted. Data were analyzed using the Statistical Package for the Social Sciences (SPSS). In all hypothesis tests, a significance level of 0.05 was used. RESULTS: From the studied sample, 435 (17.9%) contacts did not return for reading. Among the 1,990 contacts that completed the test, the prevalence of latent TB infection was 35.4%. Of these positive cases, 50.6% were referred to treatment; the dropout rate was 42.5%. Among all of the contacts, the TB prevalence was 1.8%, from which 13.2% abandoned treatment. CONCLUSIONS: The collected data indicate the need for more effective public policies to improve TB control, including administering tests that do not require a return visit for reading, enhancing contact tracing and encouraging actions that reinforce full treatment adherence.