Assortative social mixing and sex disparities in tuberculosis burden

Factors driving adolescent tuberculosis incidence by age and sex in 30 high-tuberculosis burden countries: a mathematical modelling study

INTRODUCTION

During adolescence, tuberculosis incidence rises, with a greater increase in males compared with females. Tuberculosis notifications and estimates infrequently disaggregate adolescent age groups. Moreover, the factors that drive the increases in overall incidence and the male-to-female (MF) ratio remain unclear.

METHODS

We constructed a mechanistic model to estimate cumulative Mycobacterium tuberculosis infection and tuberculosis disease incidence in the WHO's 30 high-tuberculosis burden countries (HBCs), which represent 86%-90% of global tuberculosis incidence. We derived infection risk from tuberculosis prevalence and assortative social mixing based on sex and age (10-14 years vs 15-19 years old). We adjusted age subgroup-specific risks of disease progression by age- and sex-specific risks of low body mass index (BMI), pregnancy and postpartum period (PPP) and HIV coinfection. We calculated population attributable fractions (PAFs) to these factors.

RESULTS

In 2019, 91.2 million (95% uncertainty interval (UI) 83.9 to 99.3 million) adolescents in the 30 HBCs had been infected with M. tuberculosis, and an estimated 1.0 million (95% UI 0.8 to 1.2 million) developed tuberculosis disease. The median PAF of tuberculosis disease to HIV, modified by antiretroviral therapy, was 1% and highest in Southern Africa. The median PAF for PPP among older adolescents of both sexes was 2.6%. The median PAF to low BMI was 16% and highest in South Asia. The MF risk ratio of tuberculosis disease was 1.2-fold higher among older adolescents, relative to young adolescents. The widening MF risk ratio was attributable mostly to low BMI, with a smaller contribution from sex-assortative social mixing.

CONCLUSION

Globally, large numbers of adolescents have been infected by M. tuberculosis and develop tuberculosis disease. Low BMI is the most important contributor to the overall incidence of tuberculosis disease, as well as to the sex difference that widens with age.

Two-centers machine learning analysis for predicting acid-fast bacilli results in tuberculosis sputum tests

Background

Tuberculosis (TB) is a chronic respiratory infectious disease caused by Mycobacterium tuberculosis, typically diagnosed through sputum smear microscopy for acid-fast bacilli (AFB) to assess the infectivity of TB.

Methods

This study enrolled 769 patients, including 641 patients from the First Affiliated Hospital of Guangxi Medical University as the training group, and 128 patients from Guangxi Hospital of the First Affiliated Hospital of Sun Yat-sen University as the validation group. Among the training cohort, 107 patients were AFB-positive, and 534 were AFB-negative. In the validation cohort, 24 were AFB-positive, and 104 were AFB-negative. Blood samples were collected and analyzed using machine learning (ML) methods to identify key factors for TB diagnosis.

Results

Several ML methods were compared, and support vector machine recursive feature elimination (SVM-RFE) was selected to construct a nomogram diagnostic model. The area under the curve (AUC) of the diagnostic model was 0.721 in the training cohort and 0.758 in the validation cohort. The model demonstrated clinical utility when the threshold was between 38% and 94%, with the NONE line above the ALL line in the decision curve analysis.

Conclusion

We developed a diagnostic model using multiple ML methods to predict AFB results, achieving satisfactory diagnostic performance.

The Impact of the Seasonal and Geographical Distribution of Tuberculosis in Sicily: A 6-Year Retrospective Study (2018-2023)

Background: Tuberculosis (TB) continues to be a major public health issue, with high mortality rates reported worldwide. It is worth noting that most of the hospitalizations for tuberculosis in the Sicilian region involve Italian-born individuals, underscoring the need to address this problem. Recent research on the geographic area and seasonality of infectious diseases, including tuberculosis, may aid in developing effective preventive measures. Objectives: This study aimed to evaluate the impact of the season and geographical area on tuberculosis disease prevalence in the Sicilian region. Methods: A retrospective study from January 2018 to May 2023 was conducted on patients with tuberculosis in the Sicilian region by analyzing computerized records on the Infectious Diseases Information System, currently named the Italian National Notification System (NSIS), of the Epidemiology Unit at Policlinico Paolo Giaccone University Hospital of Palermo and the Regional Reference Laboratory for Tuberculosis Surveillance and Control. Results: Eastern and Western Sicily were the geographical Sicilian areas with the highest frequency of patients with tuberculosis (52.2% and 42.6%, respectively). In comparison, Central Sicily had a significantly lower frequency of patients with tuberculosis (5.2%). Regarding the season, autumn was the season with the highest number of notification cases (28.9%), while spring was the season with the lowest frequency of patients with tuberculosis (19.7%). In autumn, we found significantly fewer patients with tuberculosis from Eastern Sicily (39.3%) and Central Sicily (1.5%), while Western Sicily had more patients with tuberculosis (59.3%). In spring, we found significantly more patients with tuberculosis from Eastern Sicily (64.1%), while Western and Central Sicily had significantly fewer patients with tuberculosis (23.9% and 12%, respectively). The presence of patients with tuberculosis did not significantly differ between geographical regions in summer and winter. Conclusions: Geographical area and seasonality significantly impact the distribution of tuberculosis cases in Sicily. These factors may be linked to different climatic conditions across the various geographical areas considered. Our findings suggest that climate can play a critical role in the spread of airborne infectious diseases, such as tuberculosis.

Community-Wide Universal HIV Test and Treat Intervention Reduces Tuberculosis Transmission in Rural Uganda: A Cluster-Randomized Trial

BACKGROUND

Human immunodeficiency virus (HIV) treatment reduces tuberculosis (TB) disease and mortality; however, the population-level impact of universal HIV-test-and-treat interventions on TB infection and transmission remain unclear.

METHODS

In a sub-study nested in the SEARCH trial, a community cluster-randomized trial (NCT01864603), we assessed whether a universal HIV-test-and-treat intervention reduced population-level incident TB infection in rural Uganda. Intervention communities received annual, population-level HIV testing and patient-centered linkage. Control communities received population-level HIV testing at baseline and endline. We compared estimated incident TB infection by arms, defined by tuberculin skin test conversion in a cohort of persons aged 5 and older, adjusting for participation and predictors of infection, and accounting for clustering.

RESULTS

Of the 32 trial communities, 9 were included, comprising 90 801 participants (43 127 intervention and 47 674 control). One-year cumulative incidence of TB infection was 16% in the intervention and 22% in the control; SEARCH reduced the population-level risk of incident TB infection by 27% (adjusted risk ratio = 0.73; 95% confidence interval [CI]: .57-.92, P = .005). In pre-specified analyses, the effect was largest among children aged 5-11 years and males.

CONCLUSIONS

A universal HIV-test-and-treat intervention reduced incident TB infection, a marker of population-level TB transmission. Investments in community-level HIV interventions have broader population-level benefits, including TB reductions.

The Impact of COVID-19 on the Tuberculosis Features in a Romanian Pneumology Hospital

Introduction

The COVID-19 pandemic and tuberculosis have epidemiological similarities, being transmitted airborne, favored by direct contact, crowded environments, and vulnerable biological status.

Methods

We performed a retrospective study of 45 cases of pulmonary tuberculosis associated with COVID-19 (TB+COV+) compared to 45 cases with tuberculous monoinfection (TB+COV-), hospitalized during 2021-2022.

Results

The demographic characteristics were similar in the two groups, predominating men, a median age of 51 years, living in rural areas, medium level of education and smoking. Common symptoms of the two groups were cough, weight loss, profuse sweating, loss of appetite and hemoptysis, while fever, headache, myo-arthralgias, and digestive symptoms characterized the TB+COV+ forms. The scores of radiological lesions in the TB+COV+ compared to TB+COV- group were significantly higher and persistent, revealing more frequent bilateral extensive lung lesions. There were no significant differences in the biological parameters between the two groups. Mortality was 2.2%, regardless of the association of COVID-19. The frequency of infections with Clostridioides difficile was higher in TB+COV+ cases.

Conclusion

The co-infection of COVID-19 had a mild impact on the clinical and biological expression of tuberculosis diagnosed in a pandemic context.

Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021

BACKGROUND

Tuberculosis (TB) remains a pressing public health issue, posing a significant threat to individuals' well-being and lives. This study delves into the TB incidence in Chinese mainland during 2014-2021, aiming to gain deeper insights into their epidemiological characteristics and explore macro-level factors to enhance control and prevention.

METHODS

TB incidence data in Chinese mainland from 2014 to 2021 were sourced from the National Notifiable Disease Reporting System (NNDRS). A two-stage distributed lag nonlinear model (DLNM) was constructed to evaluate the lag and non-linearity of daily average temperature (℃, Atemp), average relative humidity (%, ARH), average wind speed (m/s, AWS), sunshine duration (h, SD) and precipitation (mm, PRE) on the TB incidence. A spatial panel data model was used to assess the impact of demographic, medical and health resource, and economic factors on TB incidence.

RESULTS

A total of 6,587,439 TB cases were reported in Chinese mainland during 2014-2021, with an average annual incidence rate of 59.17/100,000. The TB incidence decreased from 67.05/100,000 in 2014 to 46.40/100,000 in 2021, notably declining from 2018 to 2021 (APC = -8.87%, 95% CI: -11.97, -6.85%). TB incidence rates were higher among males, farmers, and individuals aged 65 years and older. Spatiotemporal analysis revealed a significant cluster in Xinjiang, Qinghai, and Xizang from March 2017 to June 2019 (RR = 3.94, P < 0.001). From 2014 to 2021, the proportion of etiologically confirmed cases increased from 31.31% to 56.98%, and the time interval from TB onset to diagnosis shortened from 26 days (IQR: 10-56 days) to 19 days (IQR: 7-44 days). Specific meteorological conditions, including low temperature (< 16.69℃), high relative humidity (> 71.73%), low sunshine duration (< 6.18 h) increased the risk of TB incidence, while extreme low wind speed (< 2.79 m/s) decreased the risk. The spatial Durbin model showed positive associations between TB incidence rates and sex ratio (β = 1.98), number of beds in medical and health institutions per 10,000 population (β = 0.90), and total health expenses (β = 0.55). There were negative associations between TB incidence rates and population (β = -1.14), population density (β = -0.19), urbanization rate (β = -0.62), number of medical and health institutions (β = -0.23), and number of health technicians per 10,000 population (β = -0.70).

CONCLUSIONS

Significant progress has been made in TB control and prevention in China, but challenges persist among some populations and areas. Varied relationships were observed between TB incidence and factors from meteorological, demographic, medical and health resource, and economic aspects. These findings underscore the importance of ongoing efforts to strengthen TB control and implement digital/intelligent surveillance for early risk detection and comprehensive interventions.

Adverse drug events associated with linezolid administration: a real-world pharmacovigilance study from 2004 to 2023 using the FAERS database

Introduction: Linezolid is an oxazolidinone antibiotic that is active against drug-resistant Gram-positive bacteria and multidrug-resistant Mycobacterium tuberculosis. Real-world studies on the safety of linezolid in large populations are lacking. This study aimed to determine the adverse events associated with linezolid in real-world settings by analyzing data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: We retrospectively extracted reports on adverse drug events (ADEs) from the FAERS database from the first quarter of 2004 to that of 2023. By using disproportionality analysis including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), along with the multi-item gamma Poisson shrinker (MGPS), we evaluated whether there was a significant association between linezolid and ADE. The time to onset of ADE was further analyzed in the general population and within each age, weight, reporting population, and weight subgroups. Results: A total of 11,176 reports of linezolid as the "primary suspected" drug and 263 significant adverse events of linezolid were identified, including some common adverse events such as thrombocytopenia (n = 1,139, ROR 21.98), anaemia (n = 704, ROR 7.39), and unexpected signals that were not listed on the drug label such as rhabdomyolysis (n = 90, ROR 4.33), and electrocardiogram QT prolonged (n = 73, ROR 4.07). Linezolid-induced adverse reactions involved 27 System Organ Class (SOC). Gender differences existed in ADE signals related to linezolid. The median onset time of all ADEs was 6 days, and most ADEs (n = 3,778) occurred within the first month of linezolid use but some may continue to occur even after a year of treatment (n = 46). Conclusion: This study reports the time to onset of adverse effects in detail at the levels of SOC and specific preferred term (PT). The results of our study provide valuable insights for optimizing the use of linezolid and reducing potential side effects, expected to facilitate the safe use of linezolid in clinical settings.

Spatio-Temporal Pattern of Tuberculosis Distribution in Romania and Particulate Matter Pollution Associated With Risk of Infection

The study proposes a dynamic spatio-temporal profile of the distribution of tuberculosis incidence and air pollution in Romania, where this infectious disease induces more than 8,000 new cases annually. The descriptive analysis for the years 2012-2021 assumes an identification of the structuring patterns of mycobacterium tuberculosis risk in the Romanian population, according to gender and age, exploiting spatial modeling techniques of time series data. Through spatial autocorrelation, the degree of similarity between the analyzed territorial systems was highlighted and the relationships that are built between the analysis units in spatial proximity were investigated. By modeling the geographical distribution of tuberculosis, the spatial correlation with particulate matter (PM2.5) pollution was revealed. The identification of clusters of infected persons is an indispensable step in the construction of efficient tuberculosis management systems. The results highlight the link between the distribution of tuberculosis, air pollution and socio-economic development, which requires a detailed analysis of the epidemiological data obtained in the national tuberculosis surveillance and control program from the perspective of geographical distribution.

Drivers of sex differences in the South African adult tuberculosis incidence and mortality trends, 1990-2019

Males have higher tuberculosis incidence and mortality rates than females. This study aimed to assess how sex differences in tuberculosis incidence and mortality could be explained by sex differences in HIV, antiretroviral treatment (ART) uptake, smoking, alcohol abuse, undernutrition, diabetes, social contact rates, health-seeking patterns, and treatment discontinuation. We developed an age-sex-stratified dynamic tuberculosis transmission model and calibrated it to South African data. We estimated male-to-female (M:F) tuberculosis incidence and mortality ratios, the effect of the abovementioned factors on the M:F ratios and PAFs for the tuberculosis risk factors. Over the period 1990-2019, the M:F ratios for tuberculosis incidence and mortality rates persisted above 1.0, and the figures reached 1.70 and 1.65, respectively, by the end of 2019. In 2019, HIV contributed greater increases in tuberculosis incidence among females than males (54.5% vs. 45.6%); however, females experienced more reductions due to ART than males (38.3% vs. 17.5%). PAFs for tuberculosis incidence due to alcohol abuse, smoking, and undernutrition, in men were 51.4%, 29.5%, and 16.1%, respectively, higher than females (30.1%, 15.4%, and 10.7%, respectively); the PAF due to diabetes was higher in females than males (22.9% vs. 17.5%). Lower health-seeking rates in males accounted for a 7% higher mortality rate in men. The higher burden of tuberculosis in men highlights the need to improve men's access to routine screening and ensure earlier diagnosis. Sustained efforts in providing ART remain critical in reducing HIV-associated tuberculosis. Additional interventions to reduce alcohol abuse and tobacco smoking are also needed.

Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics

Tuberculosis (TB) killed more people globally than any other single pathogen over the past decade. Where surveillance is weak, estimating TB burden estimates uses modeling. In many African countries, increases in HIV prevalence and antiretroviral therapy have driven dynamic TB epidemics, complicating estimation of burden, trends, and potential intervention impact. We therefore develop a novel age-structured TB transmission model incorporating evolving demographic, HIV and antiretroviral therapy effects, and calibrate to TB prevalence and notification data from 12 African countries. We use Bayesian methods to include uncertainty for all TB model parameters, and estimate age-specific annual risks of TB infection, finding up to 16.0%/year in adults, and the proportion of TB incidence from recent (re)infection, finding a mean across countries of 34%. Rapid reduction of the unacceptably high burden of TB in high HIV prevalence settings will require interventions addressing progression as well as transmission.

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities

BACKGROUND

Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies.

METHODS

We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation.

RESULTS

Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]).

CONCLUSIONS

Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

Variance-based sensitivity analysis of tuberculosis transmission models

Mathematical models are widely used to provide evidence to inform policies for tuberculosis (TB) control. These models contain many sources of input uncertainty including the choice of model structure, parameter values and input data. Quantifying the role of these different sources of input uncertainty on the model outputs is important for understanding model dynamics and improving evidence for policy making. In this paper, we applied the Sobol sensitivity analysis method to a TB transmission model used to simulate the effects of a hypothetical population-wide screening strategy. We demonstrated how the method can be used to quantify the importance of both model parameters and model structure and how the analysis can be conducted on groups of inputs. Uncertainty in the model outputs was dominated by uncertainty in the intervention parameters. The important inputs were context dependent, depending on the setting, time horizon and outcome measure considered. In particular, the choice of model structure had an increasing effect on output uncertainty in high TB incidence settings. Grouping inputs identified the same influential inputs. Wider use of the Sobol method could inform ongoing development of infectious disease models and improve the use of modelling evidence in decision making.

Age-period-cohort analysis of pulmonary tuberculosis reported incidence, China, 2006-2020

Background

Tuberculosis (TB) poses a severe public health challenge in China and worldwide. This study evaluated the effects of age, period, and birth cohort on reported incidence trends of TB based on population and refined the characteristics of high-risk groups.

Methods

Aggregate data that reported pulmonary tuberculosis (PTB) cases from China Tuberculosis Management Information System (TBIMS) from 2006 to 2020 were used to analyze effect coefficients through the age–period–cohort (APC) model based on intrinsic estimator (IE) method, and converted them into relative risk (RR) to estimate trends.

Results

A total of 14.82 million cases of PTB were reported in China from 2006 to 2020, showing a continuous downward trend. The reporting rate increased with age by age group, with 70–74 years old being 2–3 times higher than that in 20–24 years old. APC analysis model showed that age effects were bimodal in 20–24 years old [RR = 2.29, 95% confidence interval (CI): 1.73–3.03] and 70–74 years old (RR = 1.95, 95% CI: 1.67–2.27), and lower than the overall average in the groups under 15 years old. Stratified results showed that the risk was higher for women under age 40 than men and higher for men over 40. The risk was higher in urban than in rural areas under 30 years old and slightly higher in rural than in urban between 30 and 64 years old. The risk for 15–34 years old was significantly higher in the east than in other regions. The period effects showed a decreasing trend, and the risk was higher in rural in recent years. Except for cohorts born in 1961–1965 and 2001–2005, where the RR increased, the later the cohort was born, the lower the risk. The cohort 1926–1930 in eastern had the highest risk (RR = 3.49, 95% CI: 2.44–4.98).

Conclusions

The reported incidence of PTB continued to decline in China from 2006 to 2020. The young (20–24 years old) and the elderly (70–74 years old) were equally at high risk. There were differences in the age, period and cohort effects on PTB incidence among gender, urban–rural and regions. Our findings better reflected the characteristics of high-risk populations, thus contributing to the development of timely and effective intervention strategies, and providing clues for etiological research.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-01009-4.

Sex-Dependent Differential Expression of Lipidic Mediators Associated with Inflammation Resolution in Patients with Pulmonary Tuberculosis

There is a sex bias in tuberculosis’s severity, prevalence, and pathogenesis, and the rates are higher in men. Immunological and physiological factors are fundamental contributors to the development of the disease, and sex-related factors could play an essential role in making women more resistant to severe forms of the disease. In this study, we evaluated sex-dependent differences in inflammatory markers. Serum samples were collected from 34 patients diagnosed with pulmonary TB (19 male and 15 female) and 27 healthy controls (18 male and 9 female). Cytokines IL2, IL4, IL6, IL8, IL10, IFNγ, TNFα, and GM-CSF, and eicosanoids PGE2, LTB4, RvD1, and Mar1 were measured using commercially available immunoassays. The MDA, a product of lipidic peroxidation, was measured by detecting thiobarbituric-acid-reactive substances (TBARS). Differential inflammation patterns between men and women were observed. Men had higher levels of IL6, IL8, and TNFα than women. PGE2 and LTB4 levels were higher in patients than healthy controls, but there were no differences for RvD1 and Mar1. Women had higher RvD1/PGE2 and RvD1/LTB4 ratios among patients. RvD1 plays a vital role in resolving the inflammatory process of TB in women. Men are the major contributors to the typical pro-inflammatory profile observed in the serum of tuberculosis patients.