Epidemiology of TB in prisoners: a metanalysis of the prevalence of active and latent TB.

BACKGROUND: Tuberculosis (TB) in prisons usually occurs at higher rates than in the general population, especially in developing countries. TB has been reported as the most common cause of death among prisoners. Studies have shown limitations for early detection of TB in prisons that seem to result from mistaken concepts about TB, delayed diagnosis mainly due to the naturalization of lack of healthcare for this population METHODS: A scoping review was performed using the methodology of the Joanna Briggs Institute to assess "What are the scientific evidences on the epidemiology of TB in the prison system?". Then, a meta-analysis was performed to assess the prevalence of TB (active and latent) TB in prisoners. The results are presented as prevalence, in percentage, through random effects models, with a confidence interval of 95%. RESULTS: Regarding active TB, the results of the metanalysis showed that countries with a high burden of TB had a prevalence of 3.54% [2.71; 4.63], countries not considered to be high burden TB countries had a prevalence of 1.43% [0.86; 2.37]. Latent TB had a prevalence of 51.61% [39.46; 63.58] in high TB burden countries and a prevalence of 40.24% [23.51; 59.61] in countries with low TB burden. In terms of development, in low- and lower-middle-income countries, the prevalence of active TB was 3.13% [1.84; 5.29] and in high- and upper-middle income countries the prevalence was 2.25% [1.70; 2.99]. The prevalence of latent TB in high- and middle-income countries was 43.77% [28.61; 60.18] and of 49.42% [45.91; 52.94] in low and lower middle-income countries. CONCLUSION: Our analysis suggests that TB, and probably other infectious diseases, find fertile ground in prisons where previous acquire social disadvantages seem to thrive-therefore, TB in prisons is a global public health problem and effective strategies are needed to control the disease are needed targeting the prison environment, including rapid health assessments to understand each context and to implement tailored and precision interventions.

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.

Tuberculosis forecasting and temporal trends by sex and age in a high endemic city in northeastern Brazil: where were we before the Covid-19 pandemic?

BACKGROUND: The aim of this study was to describe the temporal trend of tuberculosis cases according to sex and age group and evidence the level of disease before the Covid-19 pandemic in a TB high endemic city. METHODS: This was a time series study carried out in a city in northeast Brazil. The population was composed of cases of tuberculosis, excluding those with HIV-positive status, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to sex and age group, was performed. Subsequently, the progression of the trend and prediction of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average (ARIMA) model and the usual Box-Jenkins method were used to choose the most appropriate models. RESULTS: A total of 1620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both sexes, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend in the years 2002-2018, with a trend of stability. CONCLUSIONS: The study evidenced a decreasing trend in tuberculosis, even before the Covid-19 pandemic, for both sex and age; however, in a step really slow from that recommended by the World Health Organization. According to the results, the disease would have achieved a level of stability in the city next years, however it might have been aggravated by the pandemic. These findings are relevant to evidence the serious behavior and trends of TB in a high endemic scenario considering a context prior to the Covid-19 pandemic.