Trends in tuberculosis mortality in Brazil (1990-2015): joinpoint analysis

Trends in tuberculosis incidence and mortality coefficients in Brazil, 2011-2019: analysis by inflection points

Objective

To analyze the temporal trend of tuberculosis incidence and mortality rates in Brazil between 2011 and 2019.

Methods

This was an ecological time series study of tuberculosis incidence and mortality rates in Brazil between 2011 and 2019. Data were extracted from the Notifiable Disease Information System and the Mortality Information System, and population estimates were from the Brazilian Institute of Geography and Statistics. Trends were analyzed by Joinpoint regression, which recognizes inflection points for temporal analysis.

Results

The average incidence rate of tuberculosis in Brazil in the period was 35.8 cases per 100 000 population. From 2011 to 2015, this coefficient had an annual percentage change of -1.9% (95% CI [-3.4, -0.5]) followed by an increase of 2.4% (95% CI [0.9, 3.9]) until 2019. The average mortality rate between 2011 and 2019 was 2.2 deaths per 100 000 population, with an average annual percentage change of -0.4% (95% CI [-1.0, 0.2]). Amazonas was the only state with an increase in the annual average percentage variation for the incidence rate (3.2%; 95% CI [1.3, 5.1]) and mortality rate (2.7%; 95% CI [1.0, 4.4]) over the years, while Rio de Janeiro state had an increasing inflection for incidence from 2014 to 2019 (2.4%; 95% CI [1.4, 3.5]) and annual average of decreasing percentage variation (-3.5%; 95% CI [-5.0, -1.9]).

Conclusions

During the period analyzed, a decreasing trend in incidence was observed between 2011 and 2015, and an increasing trend for the period from 2015 to 2019. On the other hand, no change in the trend for mortality was found in Brazil.

Risk-prone territories for spreading tuberculosis, temporal trends and their determinants in a high burden city from São Paulo State, Brazil

Objectives

To identify risk-prone areas for the spread of tuberculosis, analyze spatial variation and temporal trends of the disease in these areas and identify their determinants in a high burden city.

Methods

An ecological study was carried out in Ribeirão Preto, São Paulo, Brazil. The population was composed of pulmonary tuberculosis cases reported in the Tuberculosis Patient Control System between 2006 and 2017. Seasonal Trend Decomposition using the Loess decomposition method was used. Spatial and spatiotemporal scanning statistics were applied to identify risk areas. Spatial Variation in Temporal Trends (SVTT) was used to detect risk-prone territories with changes in the temporal trend. Finally, Pearson's Chi-square test was performed to identify factors associated with the epidemiological situation in the municipality.

Results

Between 2006 and 2017, 1760 cases of pulmonary tuberculosis were reported in the municipality. With spatial scanning, four groups of clusters were identified with relative risks (RR) from 0.19 to 0.52, 1.73, 2.07, and 2.68 to 2.72. With the space–time scan, four clusters were also identified with RR of 0.13 (2008–2013), 1.94 (2010–2015), 2.34 (2006 to 2011), and 2.84 (2014–2017). With the SVTT, a cluster was identified with RR 0.11, an internal time trend of growth (+ 0.09%/year), and an external time trend of decrease (− 0.06%/year). Finally, three risk factors and three protective factors that are associated with the epidemiological situation in the municipality were identified, being: race/brown color (OR: 1.26), without education (OR: 1.71), retired (OR: 1.35), 15 years or more of study (OR: 0.73), not having HIV (OR: 0.55) and not having diabetes (OR: 0.35).

Conclusion

The importance of using spatial analysis tools in identifying areas that should be prioritized for TB control is highlighted, and greater attention is necessary for individuals who fit the profile indicated as “at risk” for the disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07500-5.

Trends of Esophageal Cancer Incidence and Mortality and Its Influencing Factors in China

Purpose

To explore the esophageal cancer (EC) incidence and mortality trends and risk factors in China during 2005–2015.

Materials and Methods

The data were stratified by area (urban, rural), gender (male, female), and age groups (0 ~, 5 ~, …, 85 ~). The age-standardized incidence rate (ASIR) and mortality rate (ASMR), age-specific incidence and mortality were calculated to describe the trends, which were analyzed by Joinpoint software, negative binomial regression model, and age-period-cohort model.

Results

Trends in EC ASIR decreased markedly during 2010–2015 (APC=−6.14%, P<0.05), and the average annual percent change (AAPC) value was −8.07% (95% confidence interval (CI): −9.98~−6.12) for rural areas during 2005–2015. The ASMR was on a fast-downward trend after 2011 (APC=−6.67%, P<0.05), with AAPC values of −1.34% (95% CI: −2.56~−0.19) for males, −3.39% (95% CI: −5.65, −1.07) for females, and −9.67% (95% CI: −10.56~−8.77) for rural areas during 2005–2015. The age-specific incidence and mortality increased with age. The risk of EC for males was 3.1675 times higher than females (P<0.001), and for urban areas, it was 0.58 times larger than rural (P<0.001). The age and period effects presented an increasing trend, with a decreasing trend for the cohort effects in incidence and mortality risk. Later birth cohorts presented lower risks than previous birth cohorts.

Conclusion

ASIR and ASMR in China are higher in males than females, and higher in rural than urban areas, which have decreased during 2005–2015, especially in rural areas. The incidence increased with age up to the peak age group of 75. Area, gender, and age were independent risk factors for EC incidence.

Survival and predictors of death in tuberculosis/HIV coinfection cases in Porto Alegre, Brazil: A historical cohort from 2009 to 2013

BACKGROUND

Tuberculosis is a curable disease, which remains the leading cause of death among infectious diseases worldwide, and it is the leading cause of death in people living with HIV. The purpose is to examine survival and predictors of death in Tuberculosis/HIV coinfection cases from 2009 to 2013.

METHODS

We estimated the survival of 2,417 TB/HIV coinfection cases in Porto Alegre, from diagnosis up to 85 months of follow-up. We estimated hazard ratios and survival curves.

RESULTS

The adjusted risk ratio (aRR) for death, by age, hospitalization, and Directly Observed Treatment was 4.58 for new cases (95% CI: 1.14-18.4), 4.51 for recurrence (95% CI: 1.11-18.4) and 4.53 for return after abandonment (95% CI: 1.12-18.4). The average survival time was 72.56 ± 1.57 months for those who underwent Directly Observed Treatment and 62.61 ± 0.77 for those who did not.

CONCLUSIONS

Case classification, age, and hospitalization are predictors of death. The occurrence of Directly Observed Treatment was a protective factor that increased the probability of survival. Policies aimed at reducing the mortality of patients with TB/HIV coinfection are needed.

Temporal trends in areas at risk for concomitant tuberculosis in a hyperendemic municipality in the Amazon region of Brazil

Background

Although preventable and curable, tuberculosis (TB) still occurs in poor or developing countries, mainly in metropolitan regions of larger cities. The disease is a serious public health problem, and is directly linked to social issues. We analyzed temporal trend variations in areas at risk for concomitant TB, and characterized the clinical and epidemiological profiles of cases in a hyperendemic municipality in the Amazon region of Brazil.

Methods

This ecological study was performed in the municipality of Manaus, in northern Brazil. The population comprised cases with concomitant pulmonary and extrapulmonary TB, registered on the Notifiable Diseases Information System (SINAN), between January 1, 2009 and December 31, 2018. For risk cluster detection, spatial and spatiotemporal scanning statistical techniques were used. The Spatial Variation in Temporal Trends (SVTT) approach was used to detect and infer clusters for significantly different time trends.

Results

Between 2009 and 2018, 873 concomitant TB cases were registered in Manaus. By using purely spatial scanning statistics, we identified two risk clusters. The relative risk (RR) of the clusters was 2.21 (95% confidence interval [CI]: 1.57–2.88; P = 0.0031) and 2.03 (95% CI: 1.58–2.58; P = 0.0029). Using space-time scanning, we identified a risk cluster with an RR of 3.57 (95% CI: 2.84–4.41; P = 0.014), between 2017 and 2018. For SVTT analyses, three clusters with spatial variations were detected in the significant temporal trends: SVTT 1 (P = 0.042), SVTT 2 (P = 0.046) and SVTT 3 (P = 0.036).

Conclusions

In Brazil, several TB-determining factors such as race/color, gender, low educational level and low income overlap in needy urban areas and communities, demonstrating that it is unlikely to reach the goals, agreed and launched with the END TB Strategy within the deadlines of international agreements, if there is no reduction in existing inequities determinants and risk of illness in the country.