Mortality related to tuberculosis-HIV/AIDS co-infection in Brazil, 2000-2011: epidemiological patterns and time trends

Factors Associated with the Effectiveness of Regimens for the Treatment of Tuberculosis in Patients Coinfected with HIV/AIDS: Cohort 2015 to 2019

(1) Background: Infection with the Human Immunodeficiency Virus (HIV) is a significant challenge for tuberculosis (TB) control, with increasing mortality rates worldwide. Moreover, the loss to follow-up is very high, with low adherence to treatment, resulting in unfavorable endpoints. This study aimed to analyze the effectiveness of TB treatment in patients coinfected with HIV/AIDS and its associated factors. (2) Methods: Patients coinfected with TB and HIV/AIDS at a Reference Hospital for infectious diseases were followed up for a maximum of one year from the start of TB treatment until cure or censorship (death, abandonment, and transfer) from 2015 to 2019. The Cox proportional model was used to identify risk factors for effectiveness. (3) Results: Of the 244 patients included in the cohort, 58.2% (142/244) had no treatment effectiveness, 12.3% (30/244) died, and 11.1% (27/244) abandoned treatment. Viral suppression at the onset of TB treatment (HR = 1.961, CI = 1.123-3.422), previous use of Antiretroviral Therapy (HR = 1.676, CI = 1.060-2.651), new cases (HR = 2.407, CI = 1.197-3.501), not using illicit drugs (HR = 1.763, CI = 1.141-2.723), and using the basic TB regimen (HR = 1.864, CI = 1.084-3.205) were significant variables per the multivariate Cox regression analysis. (4) Conclusion: TB treatment for most TB patients coinfected with HIV/AIDS was not effective. This study identified that an undetectable viral load at the beginning of the disease, previous use of ART, not using illicit drugs and not having previously taken anti-TB treatment are factors associated with successful TB treatment.

The burden of tuberculosis and attributable risk factors in Brazil, 1990-2017: results from the Global Burden of Disease Study 2017

Background

Tuberculosis (TB) continues to be an important cause of fatal and non-fatal burden in Brazil. In this study, we present estimates for TB burden in Brazil from 1990 to 2017 using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017).

Methods

This descriptive study used GBD 2017 findings to report years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) of TB in Brazil by sex, age group, HIV status, and Brazilian states, from 1990 to 2017. We also present the TB burden attributable to independent risk factors such as smoking, alcohol use, and diabetes. Results are reported in absolute number and age-standardized rates (per 100,000 inhabitants) with 95% uncertainty intervals (UIs).

Results

In 2017, the number of DALYs due to TB (HIV-negative and HIV-positive combined) in Brazil was 284,323 (95% UI: 240,269–349,265). Among HIV-negative individuals, the number of DALYs was 196,366 (95% UI: 189,645–202,394), while 87,957 DALYs (95% UI: 50,624–146,870) were estimated among HIV-positive individuals. Between 1990 and 2017, the absolute number and age-standardized rates of DALYs due to TB at the national level decreased by 47.0% and 68.5%, respectively. In 2017, the sex–age-specific TB burden was highest among males and in children under-1 year and the age groups 45–59 years. The Brazilian states with the highest age-standardized DALY rates in 2017 were Rio de Janeiro, Pernambuco, and Amazonas. Age-standardized DALY rates decreased for all 27 Brazilian states between 1990 and 2017. Alcohol use accounted for 47.5% of national DALYs due to TB among HIV-negative individuals in 2017, smoking for 17.9%, and diabetes for 7.7%.

Conclusions

GBD 2017 results show that, despite the remarkable progress in reducing the DALY rates during the period, TB remains as an important and preventable cause of health lost to due premature death and disability in Brazil. The findings reinforce the importance of strengthening TB control strategies in Brazil through integrated and multisectoral actions that enable the access to prevention, early diagnosis, and timely treatment, with emphasis on high-risk groups and populations most vulnerable to the disease in the country.

Spatiotemporal trends of Chagas disease-related mortality in the Northeast of Brazil, 2007–2017

Chagas disease (CD) is a neglected disease and endemic in Brazil. In the Brazilian Northeast Region, it affects millions of people. Therefore, it is necessary to identify the spatiotemporal trends of CD mortality in the Northeast of Brazil. This ecological study was designed, in which the unit of analysis was the municipality of the Brazilian northeast. The data source was the Information System of Mortality. It was calculated relative risk from socioeconomic characteristics. Mortality rates were smoothed by the Local Empirical Bayes method. Spatial dependency was analysed by the Global and Local Moran Index. Scan spatial statistics were also used. A total of 11 287 deaths by CD were notified in the study. An expressive parcel of this number was observed among 70-year-olds or more (n = 4381; 38.8%), no schooling (n = 4381; 38.8%), mixed-race (n = 4381; 62.3%), male (n = 6875; 60.9%). It was observed positive spatial autocorrelation, mostly in municipalities of the state of Bahia, Piauí (with high-high clusters), and Maranhão (with low-low clusters). The spatial scan statistics has presented a risk of mortality in 24 purely spatial clusters (P < 0.05). The study has identified the spatial pattern of CD mortality mostly in Bahia and Piauí, highlighting priority areas in planning and control strategies of the health services.

Temporal pattern of tuberculosis cure, mortality, and treatment abandonment in Brazilian capitals

Objective:

to analyze the temporal pattern of tuberculosis cure, mortality, treatment abandonment in Brazilian capitals.

Method:

this is an ecological study whose data source was the Information System of Notifiable Diseases for Tuberculosis (Sistema de Informação de Agravos de Notificação para Tuberculose). For analysis of temporal evolution, regressions by join points were performed considering the annual percentage variation and the significance of the trend change with 95% confidence interval.

Results:

542,656 cases of tuberculosis were found, with emphasis on a 3% decrease per year in the cure rate for Campo Grande (interval: −5.0 - −0.9) and a 3.5% increase for Rio de Janeiro (interval: 1.9 - 4.7). Regarding abandonment, it decreased 10.9% per year in Rio Branco (interval: −15.8 - −5.7) and increased 12.8% per year in Fortaleza (interval: 7.6 - 18.3). For mortality, a decreasing or stationary tendency was identified, with a greater decrease (7.8%) for Porto Velho (interval:−11.0 - −5.0) and a lower one (2.5%) in Porto Alegre (interval:−4.5 - −0.6).

Conclusion:

the rates of cure and abandonment are far from the ones recommended by the World Health Organization, showing that Brazilian capitals need interventions aimed at changing this pattern.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.