BackgroundThe World Health Organization (WHO) launched the “End TB Strategy”, which aims to reduce tuberculosis (TB) mortality by 95% by 2035, Brazil has made a commitment to this, however, one challenge is achieving the goal in the border region, where the TB situation is more critical. The proposal was to analyse the spatial mortality due to TB and its socio-economic determinants in the general population, around the border areas of Brazil, Paraguay and Argentina, as well as the temporal trend in this region.MethodThis ecological study considered the cases of TB deaths of residents of Foz do Iguaçu (BR), with its units of analysis being the census sectors. The standardized mortality rate was calculated for each area. Socioeconomic variables data were obtained from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE). The scan statistic was applied to calculate the spatial relative risk (RR), considering a 95% confidence interval (CI). Spatial dependence was analysed using the Global Bivariate Moran I and Local Bivariate Moran I (LISA) to test the relationship between the socioeconomic conditions of the urban areas and mortality from TB. Analysis of the temporal trend was also performed using the Prais-Winsten test.ResultsA total of 74 cases of TB death were identified, of which 53 (71.6%) were male and 51 (68.9%) people of white skin colour. The mortality rate ranged from 0.28 to 22.75 cases per 100,000 inhabitants. A spatial relative risk area was identified, RR = 5.07 (95% CI 1.79–14.30). Mortality was associated with: proportion of people of brown skin colour (I: 0.0440, p = 0.033), income (low income I: − 0.0611, p = 0.002; high income I: − 0.0449, p = 0.026) and density of residents (3 and 4 residents, I: 0.0537, p = 0.007; 10 or more residents, I: − 0.0390, p = 0.035). There was an increase in the mortality rate in people of brown skin colour (6.1%; 95% CI = 0.029, 0.093).ConclusionDeath due to TB was associated with income, race resident density and social conditions. Although the TB mortality rate is stationary in the general population, it is increasing among people of brown skin colour.

BackgroundBrazil is the only country in Latin America that has adopted a national health system. This causes differences in access to health among Latin American countries and induces noticeable migration to Brazilian regions to seek healthcare. This phenomenon has led to difficulties in the control and elimination of diseases related to poverty, such as leprosy. The aim of this study was to evaluate social determinants and their relationship with the risk of leprosy, as well as to examine the temporal trend of its occurrence in a Brazilian municipality located on the tri-border area between Brazil, Paraguay and Argentina.MethodsThis ecological study investigated newly-diagnosed cases of leprosy between 2003 and 2015. Exploratory analysis of the data was performed through descriptive statistics. For spatial analysis, geocoding of the data was performed using spatial scan statistic techniques to obtain the Relative Risk (RR) for each census tract, with their respective 95% confidence intervals calculated. The Bivariate Moran I test, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to analyze the spatial relationships of social determinants and leprosy risk. The temporal trend of the annual coefficient of new cases was obtained through the Prais-Winsten regression. A standard error of 5% was considered statistically significant (p < 0.05).ResultsOf the 840 new cases identified in the study, there was a predominance of females (n = 427, 50.8%), of white race/color (n = 685, 81.6%), age range 15 to 59 years (n = 624, 74.3%), and incomplete elementary education (n = 504, 60.0%). The results obtained from multivariate analysis revealed that the proportion of households with monthly nominal household income per capita greater than 1 minimum wage (β = 0.025, p = 0.036) and people of brown race (β = -0.101, p = 0.024) were statistically-significantly associated with risk of illness due to leprosy. These results also confirmed that social determinants and risk of leprosy were significantly spatially non-stationary. Regarding the temporal trend, a decrease of 4% (95% CI [-0.053, -0.033], p = 0.000) per year was observed in the rate of detection of new cases of leprosy.ConclusionThe social determinants income and race/color were associated with the risk of leprosy. The study’s highlighting of these social determinants can contribute to the development of public policies directed toward the elimination of leprosy in the border region.

OBJECTIVE: to analyze the temporal trend, identify the factors related and elaborate a predictive model for unfavorable treatment outcomes for multidrug-resistant tuberculosis (MDR-TB). METHODS: Retrospective cohort study with all cases diagnosed with MDR-TB between the years 2006 and 2015 in the state of São Paulo. The data were collected from the state system of TB cases notifications (TB-WEB). The temporal trend analyzes of treatment outcomes was performed through the Prais-Winsten analysis. In order to verify the factors related to the unfavorable outcomes, abandonment, death with basic cause TB and treatment failure, the binary logistic regression was used. Pictorial representations of the factors related to treatment outcome and their prognostic capacity through the nomogram were elaborated. RESULTS: Both abandonment and death have a constant temporal tendency, whereas the failure showed it as decreasing. Regarding the risk factors for such outcomes, using illicit drugs doubled the odds for abandonment and death. Besides that, being diagnosed in emergency units or during hospitalizations was a risk factor for death. On the contrary, having previous multidrug-resistant treatments reduced the odds for the analyzed outcomes by 33%. The nomogram presented a predictive model with 65% accuracy for dropouts, 70% for deaths and 80% for failure. CONCLUSIONS: The modification of the current model of care is an essential factor for the prevention of unfavorable outcomes. Through predictive models, as presented in this study, it is possible to develop patient-centered actions, considering their risk factors and increasing the chances for cure.

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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.

This study aimed to analyse the geographical distribution of COVID-19 and to identify highrisk areas in space and time for the occurrence of cases and deaths in the indigenous population of Brazil. This is an ecological study carried out between 24 March and 26 October 2020 whose units of analysis were the Special Indigenous Sanitary Districts. The Getis-Ord General G and Getis-Ord Gi* techniques were used to verify the spatial association of the phenomena and a retrospective space−time scan was performed. There were 32041 confirmed cases of COVID-19 and 471 deaths. The non-randomness of cases (z score = 5.40; p <0.001) and deaths (z score = 3.83; p <0.001) were confirmed. Hotspots were identified for cases and deaths in the north and midwest regions of Brazil. Sixteen high-risk space−time clusters were identified for the occurrence of cases with a higher RR=21.23 (p <0.001) and four risk clusters for deaths with a higher RR=80.33 (p <0.001). These clusters were identified from 22 May and were active until 10 October 2020. The results indicate critical areas in the indigenous territories of Brazil and contribute to better directing the actions of control of COVID-19 in this population.

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.

Aim: We hypothesized that IL-1β concentrations are augmented in overweight adolescents, who do not display metabolic syndrome. Additionally, we aimed to correlate the IL-1β concentrations with several established risk factors for CVD. Methods: Overweight or control subjects, aging from 14-18 years, were classified according to their adjusted body mass index and evaluated for biochemical and anthropometric parameters. The proinflammatory cytokine IL-1β was assessed in the serum. Results: Increased body fat percentage, waist circumference, triglycerides, total cholesterol, Very Low-Density Lipoprotein (VLDL) cholesterol, Low-Density Lipoprotein (LDL) cholesterol, Castelli I index, IL-1β, and IL-8 levels, were observed in overweight adolescents. No differences were observed in systolic blood pressure, diastolic blood pressure, glucose or High-Density Lipoprotein (HDL) cholesterol. Positive correlations between IL-1β with anthropometric and or biochemical parameters were found. Conclusion: In conclusion, increased IL-1β levels correlate to dyslipidemic factors and may further support low-grade inflammation. IL-1β may further predict the early onset of cardiovascular disease in this population, taking into consideration its important regulatory role.