How do social-economic differences in urban areas affect tuberculosis mortality in a city in the tri-border region of Brazil, Paraguay and Argentina

Modeling tuberculosis transmission flow in China, 2010-2012

BACKGROUND

China has the third largest number of TB cases in the world, and the average annual floating population in China is more than 200 million, the increasing floating population across regions has a tremendous potential for spreading infectious diseases, however, the role of increasing massive floating population in tuberculosis transmission is yet unclear in China.

METHODS

29,667 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China. Spatial variation of TB transmission was measured by geodetector q-statistic and spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors.

RESULTS

Tuberculosis transmission flow presented spatial heterogeneity. The Pearl River Delta in southern China and the Yangtze River Delta along China's east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. Some impact factors showed different spatial associations with tuberculosis transmission flow. A 10% increase in per capita GDP was associated with 10.2% in 2010 or 2.1% in 2012 decrease in tuberculosis outflows from the provinces of origin, and 1.2% in 2010 or 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow in 2012. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 14.0% in 2010 or 3.6% in 2012 increase in outflows from the origin, 44.2% in 2010 or 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows in 2012. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 2.2% in 2010 or 1.1% in 2012 increase in tuberculosis inflows to the destinations, 5.2% in 2010 or 2.0% in 2012 increase in outflows from the origins, 11.5% in 2010 or 2.2% in 2012 increase in intraprovincial flows.

CONCLUSIONS

Tuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation, regional socio-economic characteristics had diverse and statistically significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants.

Deaths among tuberculosis patients of the western state of India: A secondary record based analytical study on its determinants

INTRODUCTION

India has a significant TB burden, and ongoing attempts are being made to eradicate the disease. Globally, the number of TB deaths is declining, but not quickly enough to meet the End TB Goals. The National Strategic Plan (NSP) 2017-2025 in India set in motion an ambitious effort to expand the scope and efficacy of the National Tuberculosis Elimination Program (NTEP).

METHODS

A descriptive retrospective study based on secondary data was conducted on information obtained from the electronic TB notification register for 2019, abstracted from Ni-kshay. Further, descriptive analysis was undertaken to identify the factors associated with deaths and successful treatment outcomes. The binomial logistic regression model estimates the crude relative risk and a 95% confidence interval to describe the association between predictor variables and TB treatment outcomes.

RESULTS

After applying the eligibility criteria for the study population, a total of 1,44,643 (88%) TB patients were included in the study. 1,35,934 (94%) TB patients had completed the treatment and survived, while 8709 (6%) TB patients died. A significant association of treatment outcomes was observed in age, gender, key population, site of diseases, type of case, type of health facilities, HIV and Diabetes. When a logistic regression was applied, the model showed the association of the independent variables with the risk of death in TB patients.

CONCLUSION

The epidemiological factors associated with treatment outcomes among TB patients should be audited systematically. A structure of TB death surveillance and response system should be established with a mortality audit, including a community-based death review (CBDR) and a facility-based medical audit (FBMA) in case the patient is hospitalized or discharged from a hospital.

Risk areas for the occurrence of leprosy in border countries of South America - Brazil and Argentina

OBJECTIVE

The aim was to analyze the spatial association and relative risk (RR) of leprosy cases diagnosed in southern Brazil and in the Argentinean province of Misiones during 2010 to 2016.

METHODS

This ecological-type epidemiological study analyzed data from the Health Ministries of both countries. The analysis included frequency measures, spatial autocorrelation, RR cluster analysis and map construction.

RESULTS

A hyperendemic occurrence was identified in all study regions, in the state of Paraná 71.2% of the municipalities were hyperendemic and in Misiones, Argentina 41.2%. The GI* statistical analysis showed clusters of high incidence rates in the state of Paraná and low-risk clusters in much of the state of Rio Grande do Sul, both in Brazil. The analysis indicated an area with RR equal to 3.87 - (p < .0001) when considering the entire territory and an RR of 2.80 - (p < .0001) excluding the state of Paraná, with the number of departments of Misiones, Argentina included in the risk clusters increasing significantly.

CONCLUSIONS

The findings indicate a high probability of similar illness in adjacent areas, according to their relative position in space, as the occurrence of the disease is influenced by neighboring clusters.

Performance evaluation of tuberculosis control in Brazilian municipalities

OBJECTIVE

To evaluate the performance of tuberculosis control in Brazilian municipalities.

METHODS

This is an ecological study on Brazilian municipalities that notified at least four new cases of tuberculosis, with a minimum of one new case of pulmonary tuberculosis between 2015 and 2018. The municipalities were stratified according to the population in < 50 thousand, 50-100 thousand, 100-300 thousand, and > 300 thousand inhabitants, and the k-means method was used to group them within each population range according to the performance of six indicators of the disease.

RESULTS

A total of 2,845 Brazilian municipalities were included, comprising 98.5% (208,007/211,174) of new tuberculosis cases in the period. For each population range, three groups (A, B, and C) of municipalities were identified according to the performance of the indicators: A, the most satisfactory; B, the intermediates; and C, the least satisfactory. Municipalities in group A with < 100 thousand inhabitants presented results above the targets for laboratory confirmation (≥ 72%), abandonment (≤ 5%), and cure (≥ 90%), and comprised 2% of new cases of the disease. Conversely, municipalities of groups B and C presented at least five indicators with results below the targets - HIV testing (< 100%), contact investigation (< 90%), directly observed therapy (< 90%), abandonment (> 5%), and cure (< 90%) -, and corresponded to 66.7% of new cases of tuberculosis. In group C of municipalities with > 300 thousand inhabitants, which included 19 of the 27 capitals and 43.1% of new cases of tuberculosis, the lowest percentages of contact investigation (mean = 56.4%) and directly observed therapy (mean = 15.4%) were verified, in addition to high abandonment (mean = 13.9%) and low coverage of primary health care (mean = 66.0%).

CONCLUSIONS

Most new cases of tuberculosis occurred in municipalities with unsatisfactory performance for disease control. Expanding the coverage of primary health care in these places can reduce abandonment and increase the contact investigation and directly observed therapy.

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.

Impact of socio-economic factors on Tuberculosis treatment outcomes in north-eastern Uganda: a mixed methods study

BACKGROUND

Tuberculosis (TB) is a major public health problem and at 48%, Karamoja in North-Eastern Uganda has the lowest treatment success rate nationally. Addressing the social determinants of TB is crucial to ending TB. This study sought to understand the extent and ways in which socio-economic factors affect TB treatment outcomes in Karamoja.

METHODS

We conducted a convergent parallel mixed methods study in 10 TB Diagnostic and Treatment Units. The study enrolled former TB patients diagnosed with drug-susceptible TB between April 2018 and March 2019. Unit TB and laboratory registers were reviewed to identify pre-treatment losses to follow-up. Four focus group discussions with former TB patients and 18 key informant interviews with healthcare workers were conducted. Principle component analysis was used to generate wealth quintiles that were compared to treatment outcomes using the proportion test. The association between sociodemographic characteristics and TB treatment outcomes was evaluated using the chi-square test and multiple logistic regression.

RESULTS

A total of 313 participants were randomly selected from 1184 former TB patients recorded in the unit TB registers. Of these, 264 were contacted in the community and consented to join the study: 57% were male and 156 (59.1%) participants had unsuccessful treatment outcomes. The wealthiest quintile had a 58% reduction in the risk of having an unsuccessful treatment outcome (adj OR = 0.42, 95% CI 0.18-0.99, p = 0.047). People who were employed in the informal sector (adj OR = 4.71, 95% CI 1.18-18.89, p = 0.029) and children under the age of 15 years who were not in school or employed (adj OR = 2.71, 95% CI 1.11-6.62, p = 0.029) had significantly higher odds of unsuccessful treatment outcome. Analysis of the pre-treatment loss to follow-up showed that 17.2% of patients with pulmonary bacteriologically confirmed TB did not initiate treatment with a higher proportion among females (21.7%) than males (13.5%). Inadequate food, belonging to migratory communities, stigma, lack of social protection, drug stock-outs and transport challenges affected TB treatment outcomes.

CONCLUSIONS

This study confirmed that low socio-economic status is associated with poor TB treatment outcomes emphasizing the need for multi- and cross-sectoral approaches and socio-economic enablers to optimise TB care.

Preliminary Text Analysis from Medical Records for TB Diagnosis Support

Tuberculosis is an infectious disease that is spread through the air from one person to another and is one of the top ten causes of death in the world according to the World Health Organization. From biomedical engineering, decision support systems based on artificial intelligence have shown advantages for healthcare personnel in tasks such as diagnosis and screening. A specific area of the artificial intelligence is the natural language processing, however, most of these approaches are based on available data. This paper shows the construction of a dataset based on medical records of subjects suspected of tuberculosis. In addition, an initial exploration of the contents of the constructed dataset and how this approach can be followed by a natural language processing to support tuberculosis diagnosis in data demanding scenarios are presented.Clinical Relevance- In some developing countries as Colombia, it is difficult to develop systems based on artificial intelligence due to the availability of data. This proposal holds a strategy to build a dataset to train machine learning models, and to obtain support diagnosis tools, employing natural language from the medical scenario from text written by health professionals in the medical record. In this way, trained models based on this information available can be employed in places where medical infrastructure is precarious.

Tuberculosis Death Epidemiology and Its Associated Risk Factors in Sabah, Malaysia

Tuberculosis (TB) is a leading killer from a single infectious agent globally. In 2019, Malaysia's TB incidence rate was 92 per 100,000 population, and the TB mortality rate was estimated at 4 cases per 100,000 population per year. However, the state of Sabah had a higher burden of TB with a notification rate of 128 per 100,000 population and a TB case fatality rate of 8% compared to the national figure. This study aims to provide a comprehensive report on TB deaths epidemiology and its associated factors at a sub-national level. This nested case-control study used Sabah State Health Department TB surveillance data from the Malaysia national case-based TB registry (MyTB) between 2014 and 2018. Cases were defined as all-cause TB deaths that occurred before anti-TB treatment completion from the time of TB diagnosis. Controls were randomly selected from TB patients who completed anti-TB treatment. The TB mortality rate had increased significantly from 9.0/100,000 population in 2014 to 11.4/100,000 population in 2018. The majority of TB deaths occurred in the first two months of treatment. TB-related deaths were primarily due to advanced disease or disseminated TB, whereas non-TB-related deaths were primarily due to existing comorbidities. Many important independent risk factors for TB deaths were identified which are useful to address the increasing TB mortality rate.

Characterisation of tuberculosis mortality in informal settlements in Nairobi, Kenya: analysis of data between 2002 and 2016

BACKGROUND

Tuberculosis (TB) remains one of the key public health problems in Africa. Due to multifaceted challenges, its burden is poorly described in informal settlements. We describe tuberculosis mortality in two informal settlements in Nairobi, Kenya.

METHODS

This is a secondary analysis of 2002-2016 verbal autopsy data from informal settlements in the Nairobi Urban Health Demographic Surveillance System (NUHDSS). A descriptive analysis of deaths assigned as caused by TB was done. Pearson chi-square tests were used to determine differences between socio-demographic factors. Logistic regression was carried out to examine the risk of death from TB within the characteristics.

RESULTS

There were 6218 deaths in the NUHDSS within the period of analysis, of which 930 (14.96%) were deaths from TB. The average number of TB deaths per year was 62(SD 23.9). There was a reduction in TB deaths from 21.2% in 2005 to 1.7% in 2016. Males had 1.39 higher odds of dying from TB than females (AOR 1.39; 95% CI 1.18-1.64; p-value < 0.001). Compared to those aged 30-39 years, the ≥50-year-olds had a 42% lower chance of dying from TB (AOR 0.57; 95% CI 0.47-0.73; p-value < 0.001). Those dying at home had 1.39 odds of dying from TB as compared to those who died in a health facility(AOR 1.93; 95% CI 1.17-1.64; p value< 0.001).

CONCLUSION

There was a reduction in TB deaths over the study period. Males had the highest risk of death. There is a need to strengthen TB surveillance and access to TB diagnosis and treatment within informal settlements to enhance early diagnosis and treatment.

High prevalence of gastroschisis in Brazilian triple side border: A socioenvironmental spatial analysis

This research investigated the spatial association between socioenvironmental factors and gastroschisis in Brazilian triple side border. A geographic analysis for gastroschisis prevalence was performed considering census sector units using Global Moran Index, Local Indicator of Spatial Association Analysis and Getis Ord statistics. Sociodemographic factors included rate of adolescent and parturients over 35 years; population with no income and above 5 minimum wages; rate of late prenatal; and proximity to power transmission lines. Logistic regression models were applied to verify the association between socio-environmental factors and prevalence of gastroschisis. No global spatial correlation was observed in the distribution of gastroschisis (Moran´s I = 0.006; p = 0.319). However, multiple logistic regression showed census sectors with positive cases had higher probability to power transmission lines proximity (OR 3,47; CI 95% 1,11–10,79; p = 0,031). Yet, spatial scan statistic showed low risk for gastroschisis in southern city region (OR = 0; p = 0.035) in opposite to power transmission lines location. The study design does not allow us to attest the causality between power transmission lines and gastroschisis but these findings support the potential exposure risk of pregnant to electromagnetic fields.

Bayesian spatio-temporal models for mapping TB mortality risk and its relationship with social inequities in a region from Brazilian Legal Amazon

BACKGROUND

Reducing TB mortality is a great challenge in Brazil due to its territorial extension, cultural variations and economic and political crises, which impact the health system. This study aimed to estimate in space and time the risk of TB mortality and test its relationship with social inequities.

METHODS

This was an ecological study that included deaths from TB between 2006 and 2016 in Cuiabá, Brazilian Legal Amazon. Bayesian models based on the integrated nested Laplace approximation approach were used to estimate spatio-temporal RRs. RRs for TB mortality were obtained according to the covariables representative of social inequities.

RESULTS

The risk of TB mortality was stable between 2006 and 2016 and high-risk areas were identified throughout the municipality studied. Regarding social inequities, income was an important factor associated with TB mortality risk, as an increase of 1 SD in income resulted in a 35.4% (RR 0.646; CI 95% 0.476 to 0.837) decrease in risk.

CONCLUSIONS

The results provided evidence of areas with higher TB mortality risks that have persisted over time and are related to social inequities. Advancing social policies and protections in these areas will contribute to achieving the WHO's End TB strategy.

Tuberculosis deaths are predictable and preventable: Comprehensive assessment and clinical care is the key

The goal of reducing tuberculosis (TB) mortality in the END TB Strategy can be achieved if TB deaths are considered predictable and preventable. This will require programs to examine and address some key gaps in the understanding of the distribution and determinants of TB mortality and the current model of assessment and care in high burden countries.

Most deaths in high-burden countries occur in the first eight weeks of treatment and in those belonging to the age group of 15–49 years, living in poverty, with HIV infection and/or low body mass index (BMI). Deaths result from extensive disease, comorbidities like advanced HIV disease complicated with other infections (bacterial, fungal, bloodstream), and moderate-severe undernutrition. Most early deaths in patients with TB, even with TB-HIV co-infection, are due to TB itself.

Comprehensive assessment and clinical care are a prerequisite of patient-centered care. Simple independent predictors of death like unstable vital signs, BMI, mid-upper arm circumference, or inability to stand or walk unaided can be used by programs for risk assessment. Programs need to define criteria for referral for inpatient care, address the paucity of hospital beds and develop and implement guidelines for the clinical management of seriously ill patients with TB, advanced HIV disease and severe undernutrition as co-morbidities. Programs should also consider notification and audit of all TB deaths, similar to audit of maternal deaths, and address the issues in delays in diagnosis, treatment, and quality of care.

Determinants associated with areas with higher tuberculosis mortality rates: an ecological study

OBJECTIVE

To characterise tuberculosis deaths in a region of northeast Brazil during the period from 2006 to 2017 and to identify determinants associated with areas with higher tuberculosis mortality rates.

METHODS

Ecological descriptive study of deaths from tuberculosis with multivariate mapping and logistic regression, carried out from 2006 to 2017 in the 75 municipalities of Sergipe, Brazil. The focus of the analysis was the mean mortality rate from tuberculosis, dichotomised according to the median. The independent variables were selected based on the conceptual model of the social determinants of health.

RESULTS

Mortality due to tuberculosis in Sergipe, Brazil, was most prevalent among males, mixed-race people, and people over 40 years old and with a low level of education. Multivariate logistic regression identified the mean incidence rate for tuberculosis (aOR: 1.06), the proportion of HIV testing (aOR: 7.10), people without primary education and with informal occupation (aOR: 1.26) and people living in urban households without waste collection service (aOR: 0.10) as determinants associated to municipalities with higher tuberculosis mortality rates, with area under the ROC curve of 84% (P-value 0.000). Mapping revealed evident spatial variability.

CONCLUSIONS

The tuberculosis epidemic in Brazil is determined by access to health services, especially the provision of HIV testing among those diagnosed with tuberculosis, accelerated urbanisation with large pockets of poverty and unsanitary housing conditions, corroborating global trends.

Factors associated with mortality from tuberculosis in Iran: an application of a generalized estimating equation-based zero-inflated negative binomial model to national registry data

OBJECTIVES

Tuberculosis (TB) is a global public health problem that causes morbidity and mortality in millions of people per year. The purpose of this study was to examine the relationship of potential risk factors with TB mortality in Iran.

METHODS

This cross-sectional study was performed on 9,151 patients with TB from March 2017 to March 2018 in Iran. Data were gathered from all 429 counties of Iran by the Ministry of Health and Medical Education and Statistical Center of Iran. In this study, a generalized estimating equation-based zero-inflated negative binomial model was used to determine the effect of related factors on TB mortality at the community level. For data analysis, R version 3.4.2 was used with the relevant packages.

RESULTS

The risk of mortality from TB was found to increase with the unemployment rate (β^=0.02), illiteracy (β^=0.04), household density per residential unit (β^=1.29), distance between the center of the county and the provincial capital (β^=0.03), and urbanization (β^=0.81). The following other risk factors for TB mortality were identified: diabetes (β^=0.02), human immunodeficiency virus infection (β^=0.04), infection with TB in the most recent 2 years (β^=0.07), injection drug use (β^=0.07), long-term corticosteroid use (β^=0.09), malignant diseases (β^=0.09), chronic kidney disease (β^=0.32), gastrectomy (β^=0.50), chronic malnutrition (β^=0.38), and a body mass index more than 10% under the ideal weight (β^=0.01). However, silicosis had no effect.

CONCLUSIONS

The results of this study provide useful information on risk factors for mortality from TB.