Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

A critical analysis of the decreasing trends in tuberculosis cure indicators in Brazil, 2001-2022

OBJECTIVE

To analyze the temporal trend of tuberculosis cure indicators in Brazil.

METHODS

An ecological time-series study using administrative data of reported cases of the disease nationwide between 2001 and 2022. We estimated cure indicators for each federative unit (FU) considering individuals with pulmonary tuberculosis, tuberculosis-HIV coinfection, and those in tuberculosis retreatment. We used regression models using joinpoint regression for trend analysis, reporting the annual percentage change and the average annual percentage change.

RESULTS

For the three groups analyzed, we observed heterogeneity in the annual percentage change in the Brazilian FUs, with a predominance of significantly decreasing trends in the cure indicator in most FUs, especially at the end of the time series. When considering national indicators, an average annual percentage change of -0.97% (95% CI: -1.23 to -0.74) was identified for the cure of people with pulmonary tuberculosis, of -1.11% (95% CI: -1.42 to -0.85) for the cure of people with tuberculosis-HIV coinfection, and of -1.44% (95% CI: -1.62 to -1.31) for the cure of people in tuberculosis retreatment.

CONCLUSIONS

The decreasing trends of cure indicators in Brazil are concerning and underscore a warning to public authorities, as it points to the possible occurrence of other treatment outcomes, such as treatment discontinuity and death. This finding contradicts current public health care policies and requires urgent strategies aiming to promote follow-up of patients during tuberculosis treatment in Brazil.

Spatial Analysis of Drug-Susceptible and Multidrug-Resistant Cases of Tuberculosis, Ho Chi Minh City, Vietnam, 2020-2023

We characterized the spatial distribution of drug-susceptible (DS) and multidrug-resistant (MDR) tuberculosis (TB) cases in Ho Chi Minh City, Vietnam, a major metropolis in southeastern Asia, and explored demographic and socioeconomic factors associated with local TB burden. Hot spots of DS and MDR TB incidence were observed in the central parts of Ho Chi Minh City, and substantial heterogeneity was observed across wards. Positive spatial autocorrelation was observed for both DS TB and MDR TB. Ward-level TB incidence was associated with HIV prevalence and the male proportion of the population. No ward-level demographic and socioeconomic indicators were associated with MDR TB case count relative to total TB case count. Our findings might inform spatially targeted TB control strategies and provide insights for generating hypotheses about the nature of the relationship between DS and MDR TB in Ho Chi Minh City and the wider southeastern region of Asia.

Time series of cases and treatment outcomes from tuberculosis in Sergipe, 2012-2021

OBJECTIVE

The objectives of this study were: (1) to analyze the temporal trend of tuberculosis treatment outcomes in the state of Sergipe; (2) to identify the existence of seasonality of tuberculosis; (3) to verify the influence of the rapid molecular test (MTB-RIF) in the time series of tuberculosis and its treatment outcomes in the state of Sergipe; and (4) to verify treatment outcomes.

METHODS

Ecological study on tuberculosis and three treatment outcomes (cure, interruption of treatment, and death) extracted from Datasus. Incidence and mortality rates were calculated for the crude occurrences of cases and deaths and the proportions of cure and interruption of treatment (%). The time series was analyzed using Prais-Winsten regression from Jan to Dec/2021.

RESULTS

The total incidence rate was 36.35 cases per 100,000 inhabitants, with an increase of 0.44% per month (95%CI 0.35; 0.54). The cure rate was 64.0% with a steady trend (p>0.05). The percentage of treatment interruption was 13.3%, with a reduction of -0.73%/month (95%CI -1.11; -0.34). The total mortality rate was 1.92 deaths/100,000 inhabitants with a stationary trend. After the implementation of the MTB-RIF, there was an increase in the incidence rate of 0.65% per month. Seasonality was not identified in any of the analyses performed (p>0.05).

CONCLUSION

There was an increase in incidence rates, reduction in treatment interruption and mortality in the state of Sergipe. Seasonality was not identified. The rapid molecular test showed a growth effect on the incidence rate.

Spatial-temporal patterns and influencing factors for pulmonary tuberculosis transmission in China: an analysis based on 15 years of surveillance data

Profiting from a series of anti-tuberculosis programs in China, the number of tuberculosis (TB) cases has diminished dramatically in the past decades. However, long-term spatial-temporal variations, regional trends of prevalence, and mechanisms of determinant factors remain unclear. Age-period-cohort analysis and Bayesian space-time hierarchy statistics were conducted to identify high-risk populations and areas in mainland China, and the geographical detector model was used to evaluate the important drivers of the disease. The prevalence of pulmonary TB has declined from 73.3/100,000 in 2004 to 55.45/100,000 in 2018. A bimodal distribution was found in age groups, and the birth cohorts before 1978 had relative higher risk. The high-risk areas were mainly distributed in western China and south-central China, and several provinces in eastern China showed a potential increasing trend, including Beijing, Shanghai, Liaoning, and Guangdong province. The index of night light (Q = 0.46), the population density (Q = 0.41), PM10 (Q = 0.38), urbanization rate (Q = 0.32), and PM 2.5 (Q = 0.31) contributed substantially to the spatial distribution of pulmonary tuberculosis. The identifications of epidemic patterns, high-risk areas and influence factors would help design targeted intervention measures to achieve milestones of the end TB strategy.

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

INTRODUCTION

The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis.

METHODS

The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar.

RESULTS

A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot's location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%).

CONCLUSION

There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.

Spatiotemporally Comparative Analysis of HIV, Pulmonary Tuberculosis, HIV-Pulmonary Tuberculosis Coinfection in Jiangsu Province, China

Purpose

Pulmonary tuberculosis (PTB) is a severe chronic communicable disease that causes a heavy disease burden in China. Human Immunodeficiency Virus (HIV) and PTB coinfection dramatically increases the risk of death. This study analyzes the spatiotemporal dynamics of HIV, PTB and HIV-PTB coinfection in Jiangsu Province, China, and explores the impact of socioeconomic determinants.

Patients and Methods

The data on all notified HIV, PTB and HIV-PTB coinfection cases were extracted from Jiangsu Provincial Center for Disease Control and Prevention. We applied the seasonal index to identify high-risk periods of the disease. Time trend, spatial autocorrelation and SaTScan were used to analyze temporal trends, hotspots and spatiotemporal clusters of diseases. The Bayesian space-time model was conducted to examine the socioeconomic determinants.

Results

The case notification rate (CNR) of PTB decreased from 2011 to 2019 in Jiangsu Province, but the CNR of HIV and HIV-PTB coinfection had an upward trend. The seasonal index of PTB was the highest in March, and its hotspots were mainly distributed in the central and northern parts, such as Xuzhou, Suqian, Lianyungang and Taizhou. HIV had the highest seasonal index in July and HIV-PTB coinfection had the highest seasonal index in June, with their hotspots mainly distributed in southern Jiangsu, involving Nanjing, Suzhou, Wuxi and Changzhou. The Bayesian space-time interaction model showed that socioeconomic factor and population density were negatively correlated with the CNR of PTB, and positively associated with the CNR of HIV and HIV-PTB coinfection.

Conclusion

The spatial heterogeneity and spatiotemporal clusters of PTB, HIV and HIV-PTB coinfection are exhibited obviously in Jiangsu. More comprehensive interventions should be applied to target TB in the northern part. While in southern Jiangsu, where the economic level is well-developed and the population density is high, we should strengthen the prevention and control of HIV and HIV-PTB coinfection.

Geographic patterns and hotspots of pediatric tuberculosis: the role of socioeconomic determinants

OBJECTIVE

Children are an important demographic group for understanding overall tuberculosis epidemiology, and monitoring of childhood tuberculosis is essential for appropriate prevention. The present study sought to characterize the spatial distribution of childhood tuberculosis notification rates in continental Portugal; identify high-risk areas; and evaluate the association between childhood tuberculosis notification rates and socioeconomic deprivation.

METHODS

Using hierarchical Bayesian spatial models, we analyzed the geographic distribution of pediatric tuberculosis notification rates across 278 municipalities between 2016 and 2020 and determined high-risk and low-risk areas. We used the Portuguese version of the European Deprivation Index to estimate the association between childhood tuberculosis and area-level socioeconomic deprivation.

RESULTS

Notification rates ranged from 1.8 to 13.15 per 100,000 children under 5 years of age. We identified seven high-risk areas, the relative risk of which was significantly above the study area average. All seven high-risk areas were located in the metropolitan area of Porto or Lisbon. There was a significant relationship between socioeconomic deprivation and pediatric tuberculosis notification rates (relative risk = 1.16; Bayesian credible interval, 1.05-1.29).

CONCLUSIONS

Identified high-risk and socioeconomically deprived areas should constitute target areas for tuberculosis control, and these data should be integrated with other risk factors to define more precise criteria for BCG vaccination.

Disease burden of tuberculosis and post-tuberculosis in Inner Mongolia, China, 2016-2018 - based on the disease burden of post-TB caused by COPD

BACKGROUND

Tuberculosis (TB) remains one of the most serious infectious diseases worldwide. China has the second highest TB burden globally, but existing studies have mostly neglected the post-tuberculosis (post-TB) disease burden. This study estimated the disease burden of TB and post-TB in Inner Mongolia, China, from 2016 to 2018.

METHODS

Population data were collected from TB Information Management System. Post-TB disease burden was defined as the burden caused by Chronic Obstructive Pulmonary Disease (COPD) occurring after patients with TB were cured. To estimate the incidence rate of TB, standardized mortality rate, life expectancy, and cause eliminated life expectancy, using descriptive epidemiological, abridged life table and cause eliminated life table. On this basis, the Disability-Adjusted Life Years (DALY), Years Lived with Disability (YLD) and Years of Life Lost (YLL) due to TB were further be estimated. The data were analyzed using Excel 2016 and SPSS 26.0. Joinpoint regression models were used to estimate the time and age trends of the disease burden of TB and post-TB.

RESULTS

The TB incidence in 2016, 2017, and 2018 was 41.65, 44.30, and 55.63/100,000, respectively. The standardized mortality in the same period was 0.58, 0.65, and 1.08/100,000, respectively. From 2016 to 2018, the total DALYs of TB and post-TB were 5923.33, 6258.03, and 8194.38 person-years, and the DALYs of post-TB from 2016 to 2018 were 1555.89, 1663.33, and 2042.43 person-years. Joinpoint regression showed that the DALYs rate increased yearly from 2016 to 2018, and the rate of males was higher than that of females. TB and post-TB DALYs rates showed a rising tendency with increasing age (AAPC values were 149.6% and 157.0%, respectively, P < 0.05), which was higher in the working-age population and elderly.

CONCLUSION

The disease burden of TB and post-TB was heavy and increased year by year in Inner Mongolia from 2016 to 2018. Compared with the youngster and females, working-age population and the elderly and males had a higher disease burden. Policymakers should be paid more attention to the patients' sustained lung injury after TB cured. There is a pressing need to identify more effective measures for reducing the burden of TB and post-TB of people, to improve their health and well-being.

Spatial distribution and computational modeling for mapping of tuberculosis in Pakistan

Background

Tuberculosis (TB) like many other infectious diseases has a strong relationship with climatic parameters.

Methods

The present study has been carried out on the newly diagnosed sputum smear-positive pulmonary TB cases reported to National TB Control Program across Pakistan from 2007 to 2020. In this study, spatial and temporal distribution of the disease was observed through detailed district wise mapping and clustered regions were also identified. Potential risk factors associated with this disease depending upon population and climatic variables, i.e. temperature and precipitation were also identified.

Results

Nationwide, the incidence rate of TB was observed to be rising from 7.03% to 11.91% in the years 2007–2018, which then started to decline. However, a declining trend was observed after 2018–2020. The most populous provinces, Punjab and Sindh, have reported maximum number of cases and showed a temporal association as the climatic temperature of these two provinces is higher with comparison to other provinces. Machine learning algorithms Maxent, Support Vector Machine (SVM), Environmental Distance (ED) and Climate Space Model (CSM) predict high risk of the disease with14.02%, 24.75%, 34.81% and 43.89% area, respectively.

Conclusion

SVM has a higher significant probability of prediction in the diseased area with a 1.86 partial receiver-operating characteristics (ROC) value as compared with other models.

Impact of the COVID-19 Pandemic on the Diagnosis of Tuberculosis in Brazil: Is the WHO End TB Strategy at Risk?

Background: In 2014, the World Health Organization (WHO) launched the “post-2015 End TB strategy”, that aims to end the global tuberculosis (TB) epidemic by 2030. However, the COVID-19 pandemic has severely impacted global public health and the strict measures to control the coronavirus spread can affect the management of other diseases, such as TB. Herein, we aimed to assess the impact of the COVID-19 pandemic on the diagnosis of TB in Brazil, during 2020.

Methods: We carried out an ecological and population-based study, using spatial analysis techniques. The variables used were the new cases of TB, pulmonary tuberculosis (PTB), and also baciloscopy-positive (BP) cases in Brazil between 2015 and 2020. The percentage of changes (% change) was calculated to verify if there was an increase or decrease of TB cases in 2020, along with time trend analyses given by Joinpoint regression model. Also, interrupted time series analyses were used to assess the trend of TB diagnosis before and after the onset of the COVID-19 in Brazil. Spatial distribution maps were elaborated, considering the % change of each Brazilian state.

Findings: Data analyses showed a reduction in the diagnosis of TB (−8.3%) and PTB (−8.1%) in Brazil after the irruption of the COVID-19 pandemic. Likewise, 22 states depicted a reduction in TB diagnosis. An expressive reduction of BP cases (−17.1%) was also observed. Interestingly, interrupted time series analysis showed decline in TB and PTB diagnoses from March 2020. Spatial analyses revealed that all states had a progressive reduction of TB, PTB and PB cases, from March on, with the highest percentages of reduction in December (−100% to −75%).

Interpretation: Taken together, our analyses demonstrated a reduction in TB diagnosis after the irruption of the COVID-19 pandemic in Brazil and its regions, signaling a serious impact on the WHO “End TB Strategy” global plan.

Intra-urban variation in tuberculosis and community socioeconomic deprivation in Lisbon metropolitan area: a Bayesian approach

Background

Multidrug resistant tuberculosis (MDR-TB) is a recognized threat to global efforts to TB control and remains a priority of the National Tuberculosis Programs. Additionally, social determinants and socioeconomic deprivation have since long been associated with worse health and perceived as important risk factors for TB. This study aimed to analyze the spatial distribution of non-MDR-TB and MDR-TB across parishes of the Lisbon metropolitan area of Portugal and to estimate the association between non-MDR-TB and MDR-TB and socioeconomic deprivation.

Methods

In this study, we used hierarchical Bayesian spatial models to analyze the spatial distribution of notification of non-MDR-TB and MDR-TB cases for the period from 2000 to 2016 across 127 parishes of the seven municipalities of the Lisbon metropolitan area (Almada, Amadora, Lisboa, Loures, Odivelas, Oeiras, Sintra), using the Portuguese TB Surveillance System (SVIG-TB). In order to characterise the populations, we used the European Deprivation Index for Portugal (EDI-PT) as an indicator of poverty and estimated the association between non-MDR-TB and MDR-TB and socioeconomic deprivation.

Results

The notification rates per 10,000 population of non-MDR TB ranged from 18.95 to 217.49 notifications and that of MDR TB ranged from 0.83 to 3.70. We identified 54 high-risk areas for non-MDR-TB and 13 high-risk areas for MDR-TB. Parishes in the third [relative risk (RR) = 1.281, 95% credible interval (CrI): 1.021–1.606], fourth (RR = 1.786, 95% CrI: 1.420–2.241) and fifth (RR = 1.935, 95% CrI: 1.536–2.438) quintile of socioeconomic deprivation presented higher non-MDR-TB notifications rates. Parishes in the fourth (RR = 2.246, 95% CrI: 1.374–3.684) and fifth (RR = 1.828, 95% CrI: 1.049–3.155) quintile of socioeconomic deprivation also presented higher MDR-TB notifications rates.

Conclusions

We demonstrated significant heterogeneity in the spatial distribution of both non-MDR-TB and MDR-TB at the parish level and we found that socioeconomically disadvantaged parishes are disproportionally affected by both non-MDR-TB and MDR-TB. Our findings suggest that the emergence of MDR-TB and transmission are specific from each location and often different from the non-MDR-TB settings. We identified priority areas for intervention for a more efficient plan of control and prevention of non-MDR-TB and MDR-TB.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00949-1.

[Abandonment of tuberculosis treatment in Brazil, 2012-2018: trend and spatiotemporal distribution]

Ecological study that analyzes the trend and the spatiotemporal distribution of new cases of tuberculosis (TB) that abandoned treatment in Brazil, notified in the Notifiable Diseases Information System, in the period from 2012 to 2018. For the study of the trend used the Prais-Winsten generalized linear regression model was used and the Moran Global and Local indices for spatial analysis. The mean and median proportion of TB treatment dropout in Brazil was 10.4%. The highest averages of the indicator were concentrated in the Southeast (10.78 ± 1.38), South (10.70 ± 2.94) and North (10.35 ± 1.13), and; in the states of Rondônia (14.35 ± 2.34), Rio Grande do Sul (13.60 ± 4.23) and Rio de Janeiro (12.64 ± 1.73), only Acre and Piauí showed this indicator below 5%. In Brazil, there was a tendency towards stability in the proportion of abandonment of TB treatment, a decrease in the North, Northeast and South regions and only in the Federal District there was growth. There was a heterogeneous and non-random distribution, with five capitals comprising the High-Risk cluster. We conclude that the proportion of TB treatment abandonment in Brazil is above what is acceptable and that the identification of high-risk areas can contribute to the elaboration and strengthening of more specific control actions.

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.

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

Background

Despite the World Health Organization efforts to expand access to the tuberculosis treatment, multidrug resistant tuberculosis (MDR-TB) remains a major threat. MDR-TB represents a challenge for clinicians and staff operating in national tuberculosis (TB) programmes/centres. In sub-Saharan African countries including Burundi, MDR-TB coexists with high burden of other communicable and non-communicable diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence which well defines the at-risk population. In this study, using data from two referral anti-tuberculosis in Burundi, we model the key factors associated with MDR-TB in Burundi.

Methods

A case-control study was conducted from 1^stAugust 2019 to 15^th January 2020 in Kibumbu Sanatorium and Bujumbura anti-tuberculosis centres for cases and controls respectively. In all, 180 TB patients were selected, comprising of 60 cases and 120 controls using incidence density selection method. The associated factors were carried out by mixed effect logistic regression. Model performance was assessed by the Area under Curve (AUC). Model was internally validated via bootstrapping with 2000 replications. All analysis were done using R Statistical 3.5.0.

Results

MDR-TB was more identified among patients who lived in rural areas (51.3%), in patients’ residence (69.2%) and among those with a household size of six or more family members (59.5%).

Most of the MDR-TB cases had already been under TB treatment (86.4%), had previous contact with an MDR-TR case (85.0%), consumed tobacco (55.5%) and were diabetic (66.6 %). HIV prevalence was 32.3 % in controls and 67.7 % among cases. After modelling using mixed effects, Residence of patients (aOR= 1.31, 95%C: 1.12-1.80), living in houses with more than 6 family members (aOR= 4.15, 95% C: 3.06-5.39), previous close contact with MDR-TB (aOR= 6.03, 95% C: 4.01-8.12), history of TB treatment (aOR= 2.16, 95% C: 1.06-3.42), tobacco consumption (aOR = 3.17 ,95% C: 2.06-5.45) and underlying diabetes’ ( aOR= 4.09,95% CI = 2.01-16.79) were significantly associated with MDR-TB. With 2000 stratified bootstrap replicates, the model had an excellent predictive performance, accurately predicting 88.15% (95% C: 82.06%-92.8%) of all observations. The coexistence of risk factors to the same patients increases the risk of MDR-TB occurrence. TB patients with no any risk factors had 17.6% of risk to become MDR-TB. That probability was respectively three times and five times higher among diabetic and close contact MDR-TB patients.

Conclusion

The relatively high TB’s prevalence and MDR-TB occurrence in Burundi raises a cause for concern especially in this context where there exist an equally high burden of chronic diseases including malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12233-2.

Spatial analysis of tuberculosis cure in primary care in Rio de Janeiro, Brazil

Background

Tuberculosis (TB) presents a high burden of disease and is considered a global emergency by the World Health Organization (WHO), as the leading cause of death from infectious disease in adults. TB incidence is related directly to access to health services and socioeconomic determinants and inequality. Providing primary care settings can lead to improved access, shorter waiting times for patients, and enhanced TB case detection. The article aims to identify the spatial and temporal risk areas for TB and the relationship between TB cure and primary healthcare coverage from 2012 to 2014 in Rio de Janeiro, Brazil.

Methods

A cross-sectional study was conducted in Rio de Janeiro, Brazil. All cases of TB reported to the Information System on Diseases of Notification (SINAN) from 2012 to 2014 were included. Socioeconomic variables from the 2010 Brazilian national census were also added. Socioeconomic variables were selected from multivariate analysis using principal factors analysis. Spatial association was verified with generalized additive model (GAM). It was possible to identify areas at higher risk of failure to cure TB.

Results

TB rates showed strong positive spatial autocorrelation. TB cure rate varied according to schooling (individuals with complete secondary schooling had higher cure rates than illiterate individuals; OR 1.72, 95% CI 1.30–2.29), alcohol consumption (OR 0.47, 95% CI 0.35–0.64), contact investigation (OR 2.00, 95% CI 1.56–2.57), positive HIV serology (OR 0.31, 95% CI 0.23–0.42), and census tracts with higher elderly rates (OR 9.39, 95% CI 1.03–85.26). Individuals who had been covered by primary healthcare (PHC) for 35 to 41 months had 1.64 higher odds of cure, compared to those with no PHC coverage (95% CI 1.07–2.51).

Conclusion

A comprehensive risk map was developed, allowing public health interventions. Spatial analysis allowed identifying areas with lower odds of TB cure in the city of Rio de Janeiro. TB cure was associated statistically with time of coverage by primary healthcare. TB cure rate also varied according to sociodemographic factors like schooling, alcohol abuse, and population density.

This methodology can be generalized to other areas and/or other public health problems.

Highlights

We studied standardized municipal TB cure rates in an area of social inequality in Brazil.

TB rates showed strong positive spatial autocorrelation.

Higher rates were associated with population density and socioeconomic conditions. Illiterate individuals were less likely to achieve TB cure.

TB cure was less likely in individuals with HIV and alcohol abuse.

TB cure was greater in areas with high primary healthcare coverage.

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development

BACKGROUND

Previous research pointed to a close relationship between the incidence of tuberculosis (TB) in aging populations and socio-economic conditions, however there has been lack of studies focused on a region of unbalanced socio-economic development. The aim of this paper is to explore the spatio-temporal variation in TB incidence and examine risk determinants of the disease among aging populations in a typical region.

METHODS

Data on TB-registered cases between 2009 and 2014, in addition to social-economic factors, were collected for each district/county in Beijing, Tianjin and Hebei, a region characterized by an aging population and disparities in social-economic development. A Bayesian space-time hierarchy model (BSTHM) was used to reveal spatio-temporal variation in the incidence of TB among the elderly in this region between 2009 to 2014. GeoDetector was applied to measure the determinant power (q statistic) of risk factors for TB among the elderly.

RESULTS

The incidence of TB among the elderly exhibited geographical spatial heterogeneity, with a higher incidence in underdeveloped rural areas compared with that in urban areas. Hotspots of TB incidence risk among the elderly were mostly located in north-eastern and southern areas in the study region, far from metropolitan areas. Areas with low risk were distributed mainly in the Beijing-Tianjin metropolitan areas. Social-economic factors had a non-linear influence on elderly TB incidence, with the dominant factors among rural populations being income (q = 0.20) and medical conditions (q = 0.17). These factors had a non-linear interactive effect on the incidence of TB among the elderly, with medical conditions and the level of economic development having the strongest effect (q = 0.54).

CONCLUSIONS

The findings explain spatio-temporal variation in TB incidence and risk determinants of elderly TB in the presence of disparities in social-economic development. High-risk zones were located mainly in rural areas, far from metropolitan centres. Medical conditions and the economic development level were significantly associated with elderly TB incidence, and these factors had a non-linear interactive effect on elderly TB incidence. The findings can help to optimize the allocation of health resources and to control TB transmission in the aging population in this region.

High-risk transmission clusters of leprosy in an endemic area in the Northeastern Brazil: A retrospective spatiotemporal modelling (2001-2019)

OBJECTIVES

To analyse and map the leprosy risk areas in the state of Alagoas, an endemic region in the Northeastern Brazil, between 2001 and 2019.

METHODS

Ecological and time series study, using spatial analysis techniques. First, we analyse the epidemiological aspects of leprosy cases, using the data available in the Notifiable Diseases Information System; then, we used the segmented log-linear regression model to assess time trends. Spatial distribution was analysed by the Local Empirical Bayesian Estimator and by calculating the Global and Local Moran Index. Finally, spatiotemporal clusters were identified through scanning statistics, using the Kulldorf method of retrospective analysis.

RESULTS

We observed that Alagoas showed an average new case detection rate of 14.43/100,000 inhabitants between 2001 and 2019, being classified as highly endemic. The area of highest risk was the 9th health region (state hinterland), with increasing time trend (Annual Percentage Change/APC = 7.2; p-value < 0.05). Several clusters of high risk of leprosy transmission were verified in Alagoas, including the state capital and hinterland municipalities.

CONCLUSIONS

Our data indicate that active M. leprae transmission persists in Alagoas; that diagnosis is delayed and that there are high-risk areas, especially in inland municipalities.

Risk clusters of Schistosoma mansoni infection in an endemic state of Brazil: space-time modelling and association with socio-economic and environmental factors

BACKGROUND

We analysed the spatial distribution and the socio-economic and environmental factors (SEFs) associated with Schistosoma mansoni infection in the state of Alagoas, an important tourist area in northeastern Brazil.

METHODS

We conducted an ecological time-series study (2007-2016) on schistosomiasis cases and SEFs. We evaluated the temporal trends of schistosomiasis cases (annual percentage change [APC]) and their correlation with SEFs. Spatial analysis maps were built using QGIS and TerraView software.

RESULTS

We observed that 4.9% of the municipalities had a high prevalence of S. mansoni infection and were located mainly in the coastal strip of Alagoas state. The positivity rate for schistosomiasis decreased during the period (8.1% in 2007 to 4.9% in 2016; APC=-5.71). There was a reduction in the number of tests performed (APC=-5.05). There was a negative correlation between S. mansoni infection and the municipal human development index (ρ=-0.34) and schooling rate (ρ=-0.24). The main species of snail was Biomphalaria glabrata (94.79%), but Biomphalaria straminea showed a higher percentage of S. mansoni detection (10.11%). Lastly, Biomphalaria tenagophila specimens were identified for the first time in Alagoas (n=28).

CONCLUSIONS

Despite a reduction in the number of cases, intestinal schistosomiasis still represents a serious public health concern in Alagoas. It urgently requires planning and improvements in diagnosis, prevention programs and the state's socio-economic indicators.

Early identification of individuals at risk for loss to follow-up of tuberculosis treatment: A generalised hierarchical analysis

BACKGROUND

We characterise the loss to follow-up (locally termed abandoned) of tuberculosis treatment with individual and ecological health determinants and to identify the predictive capacity of these risk factors.

METHODS

A cohort study with individual and ecological characterisation of patients diagnosed with tuberculosis in Sergipe/Brazil from 2015 to 2018 with either loss to follow-up or completion of treatment as a therapeutic outcome was performed. The examined variables were based on the social determinants of health with descriptive analysis, binary logistic regression, a generalised hierarchical model and graphical presentation using a nomogram.

RESULTS

The loss to follow-up accounted for 18.21% of the 2,449 studied cases. The characteristics revealed that the highest abandonment percentages were people who: were male (20.0%), had black skin colour (20.3%), were aged 20-39 years (21.8%), had 4-7 years of schooling (23.6%), re-entered treatment after abandonment (36.5%), used alcohol (31.0%), used drugs (39.3%), were smokers (26.5%) and were homeless (55.4%). The ecological characteristics showed that individuals living in municipalities with a high human development index (HDI; odds ratio [OR]: 1.91) and high-income inequality (OR: 1.81) had a greater chance of not finishing the treatment. Most of these variables were identified as predictors in the generalised hierarchical model; the receiver operating characteristic curve (ROC) curve had 0.771 precision and 84.0% accuracy.

CONCLUSION

The group of identified characteristics influenced the loss to follow-up of tuberculosis treatment. This data provides evidence for the early identification of individuals who are at greater risk of abandoning tuberculosis treatment.

Space-time risk cluster of visceral leishmaniasis in Brazilian endemic region with high social vulnerability: An ecological time series study

BACKGROUND

Despite visceral leishmaniasis (VL) being epidemic in most Brazilian regions, the Northeast region is responsible for the highest morbidity and mortality outcomes within the country.

OBJECTIVE

To analyse the spatiotemporal dynamics of VL cases to identify the temporal trends and high-risk areas for VL transmission, as well as the association of the disease with social vulnerability in Brazilian Northeast.

METHODS

We carried out an ecological time series study employing spatial analysis techniques using all VL confirmed cases of 1,794 municipalities of Brazilian Northeast between the years 2000 to 2017. The Social Vulnerability Index (SVI) was used to represent the social vulnerability. Incidence rates were standardized and smoothed by the Local Empirical Bayesian Method. Time trends were examined through segmented linear regression. Spatiotemporal analysis consisted of uni- and bivariate Global and Local Moran indexes and space-time scan statistics.

RESULTS

Incidence rate remained stable and ranged from 4.84 to 3.52 cases/100,000 inhabitants. There was higher case prevalence between males (62.71%), children and adolescents (63.27%), non-white (69.75%) and urban residents (62.58%). Increasing trends of new cases were observed among adult male subjects (≥ 40 years old) and urban residents. Importantly, VL incidence showed a direct spatial dependence. Spatial and space-time clusters were identified in sertão and meio-norte sub-regions, overlapping with high social vulnerability areas.

CONCLUSIONS

VL is a persistent health issue in Brazilian Northeast and associated with social vulnerability. Space-time clustering of VL cases in socially vulnerable municipalities demands intersectoral public policies of surveillance and control, with focus on reducing inequalities and improving living conditions for regional inhabitants.

Spatial and spatiotemporal dynamics of visceral leishmaniasis in an endemic North-eastern region of Brazil

Visceral Leishmaniasis (VL) is a neglected disease with increasing incidence in Brazil, particularly in the North-eastern. The aim of this study was to analyze the spatial and spatiotemporal dynamics of VL in an endemic region of North-eastern Brazil, between 2009 and 2017. Using spatial analysis techniques, an ecological and time series study was made regarding VL cases in Sergipe filed as notifiable disease events. With data from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística, IBGE), a digital population and cartographic baseline was established. Segmented linear regression was used to examine the temporal trends. The statistical analysis methods of Global and Local Moran' I, local Bayesian empirical methodology and spatial-temporal scanning were used to produce thematic maps. High instances were found among adults, males, urban residents, non-Whites and persons with low levels of education. A decrease in the recovery rate and an increase in the proportion of urban cases and lethality was found. A heterogeneous VL distribution with spatiotemporal agglomeration on the seaside of the state was seen in Sergipe. To better manage the disease, new research is encouraged together with development of public health strategies. Further, improving health care networks, especially primary care, is suggested as this approach has a key role in health promotion, prevention and monitoring of the most prevalent diseases.

Determining the association between dengue and social inequality factors in north-eastern Brazil: A spatial modelling

Dengue is a global public health problem. The Dengue Virus (DENV) serotypes are transmitted by an Aedes aegypti mosquito. Vector control is among the primary methods to prevent the disease, especially in tropical countries. This study aimed to analyze the spatial distribution of dengue and its relationship with social inequalities using spatial modelling. An ecological study with temporal and spatial analysis was conducted in the state of Sergipe, Northeast Brazil, over a period of 18 years. Spatial modelling was used to determine the influence of space on dengue incidence and social inequalities. The epidemic rates in 2008, 2012, and 2015 were identified. Spatial modelling explained 40% of the influence of social inequalities on dengue incidence in the state. The main social inequalities related to the occurrence of dengue were the percentage of people living in extreme poverty and inadequate sanitation. The epidemic situation even increased the risk of dengue in the population of the state of Sergipe. These results demonstrate the potential of spatial modelling in determining the factors associated with dengue epidemics and are useful in planning the intersectoral public health policies.

Quality of tuberculosis information systems after record linkage

ABSTRACT Objective: to analyze the quality of a tuberculosis notification information system after record linkage and spatial and temporal distribution of tuberculosis in a Brazilian state. Method: an ecological study carried between 2006 and 2016 in Sergipe, Brazil. A deterministic linkage was performed with Notifiable Diseases Information System and Mortality Information System, recording 7,873 cases and 483 deaths. The temporal trend of tuberculosis incidence was calculated. Results: there was an increase among men (2.75%), > 60 years (6.29%), higher education (4.34%) and indigenous (4.76%). A total of 190 new cases (2.9%) was found. There was an increasing trend in tuberculosis incidence with a concentration of deaths in the metropolitan region. Conclusion: the quality of the information system showed fragility in identifying cases and deaths in Sergipe. Temporal distribution showed an increasing trend in tuberculosis incidence, and spatial distribution identified higher incidences in southeastern Brazil.