Tuberculosis (TB) remains a significant public health challenge, necessitating accurate forecasting methodologies to support effective control and prevention strategies. This paper explores the application and comparative performance of single and hybrid time-series models for forecasting TB incidence trends specifically in Somalia. Annual TB incidence data from 2000 to 2022 were sourced from the World Bank to train and evaluate a comprehensive suite of 14 time-series models. This included five single models-ARIMA, ETS, TBATS, Theta, and NNAR-and nine hybrid model combinations (e.g., ARIMA-ETS, ARIMA-TBATS, ARIMA-ETS-TBATS). Model performance was assessed using Theil's U statistic, Mean Absolute Percentage Error (MAPE), Symmetric Mean Absolute Percentage Error (SMAPE), and Root Mean Square Error (RMSE). Among the single time-series models, the TBATS model demonstrated the best fit. However, the comparative analysis revealed that the hybrid ARIMA-ETS-TBATS model outperformed other hybrid configurations. The study highlights that hybrid modeling offers enhanced forecasting accuracy compared to single models. The resulting forecasts provide valuable insights into future TB incidence trends in Somalia. These findings underscore the importance of hybrid modeling in generating accurate data to aid informed public health decision-making and the development of targeted intervention strategies for TB control.

The present study aimed to examine the temporal dynamics of tuberculosis incidence, mortality, and TB–HIV coinfection in the First Health Region of Alagoas from 2001 to 2022, with particular attention to sex-specific differences. The analysis revealed pronounced divergences between men and women. The male series exhibited significant positive autocorrelation and high interannual variability, indicating strong temporal dependence and heightened sensitivity to external disruptions such as the COVID-19 pandemic. The female series displayed a more regular pattern without autocorrelation. Although both sexes showed declining incidence, only the reduction among women reached statistical significance; the male trend remained unstable and inconclusive. Disease burden was consistently higher among men, who accounted for most cases and maintained incidence levels above elimination targets. TB–HIV coinfection increased in both sexes, with a sharper rise among men and a statistically significant upward trend among women, accompanied by a structural shift in 2010. Additional change points in 2014 and 2018 are likely to reflect alterations in surveillance or broader public health events. The weak performance of linear models underscores the role of persistent social determinants and inequities in healthcare access. Overall, the findings demonstrate that tuberculosis remains a major public health concern and that differentiated strategies by sex are essential for effective prevention and care.

Background and aims: Tuberculosis (TB) remains a major global health concern and one of the leading causes of death among infectious diseases. Accurate surveillance of incidence trends is essential for planning and implementing effective control strategies. This study aimed to assess the temporal trends in TB incidence in Dezful, Khuzestan Province, southwestern Iran. Methods: This ecological study analyzed TB incidence data from March 21, 2011, to March 20, 2025. Data on new TB cases and population size were obtained from the Health Deputy of Dezful University of Medical Sciences. Joinpoint regression analysis was applied to estimate annual percentage changes (APCs) and average annual percentage changes (AAPCs) in TB incidence over time. Results: TB incidence was higher among males. From March 21, 2011, to March 20, 2025, the overall incidence of TB in Dezful demonstrated a statistically significant decreasing trend, with an AAPC of –3.65% (95% CI: –5.91 to –1.40). A considerable declining trend was observed in females [AAPC: –5.25% (95% CI: –7.49 to –2.98)], whereas the reduction in males [AAPC: –2.57% (95% CI: –5.28 to 0.10)] was not statistically significant. Conclusion: The incidence of TB in Dezful showed a significant decline among women over the study period, but no significant reduction was observed among men.

Introduction: Indonesia, with the world's second-highest tuberculosis (TB) burden, has targeted TB elimination (65 cases per 100,000) by 2030. This study aimed to evaluate the feasibility of achieving this goal by projecting TB incidence trends using a stochastic epidemic model that accounts for the uncertainties inherent in TB transmission dynamics in latent TB infections. Methods: The initial values for state variables and parameters were derived from a comprehensive literature review and calibrated against publicly available epidemiological data from the Indonesian Ministry of Health reports from 2018-2022. A Susceptible, Vaccinated, Three Exposed, Three Infectious, Recovered (SVE3I3R) model was developed, incorporating Gaussian noise into the exposed compartments to simulate real-world unpredictability in latent infection dynamics. The model was solved numerically using the fourth-order Runge-Kutta (RK4) method in R software. Key outcomes measured were the projected incidence of drug-susceptible TB (DS-TB), multidrug-resistant TB (MDR-TB), and extensively drug-resistant TB (XDR-TB). Results: Model projections suggest that the overall TB incidence rate will fall from 387 cases per 100,000 people in 2023 to a projected 320 cases per 100,000 by 2030. However, this remains far above the national target. While DS-TB cases decreased to 730,283, MDR-TB and XDR-TB cases were projected to surge dramatically to 120,939 cases and 104,651 individuals, respectively. The estimation signals a critical shift in the epidemic's profile. Conclusions: Indonesia is not on track to achieve its 2030 TB elimination target under current interventions. The alarming rise of drug-resistant TB necessitates an urgent, aggressive, and multifaceted policy response. This study underscores the critical value of incorporating stochasticity into epidemiological models for more realistic forecasting and public health planning in high-burden settings.

Globally, tuberculosis remains a significant public health concern. The 2022 World Health Organization report indicates that approximately 10.6 million people are infected with tuberculosis annually worldwide, resulting in 1.6 million deaths. In 2021, China ranked as the third country with the highest tuberculosis burden globally, following India and Indonesia. Xinjiang, as the westernmost region of China, experiences the most severe tuberculosis incidence. This study focuses on the Hotan region of Xinjiang, utilizing spatio-temporal statistical methods to investigate the local tuberculosis incidence trends from 2015 to 2021 and analyze potential influencing factors. Spatial autocorrelation and spatiotemporal scanning techniques were employed to assess the tuberculosis incidence trend. Furthermore, geographically weighted regression was utilized to examine the impact of meteorological and air pollution factors on tuberculosis incidence in the Hotan area from a spatial perspective. The findings revealed spatial heterogeneity in the distribution of pulmonary tuberculosis (PTB) in the Hotan area, with the identification of four spatial clusters through local spatial autocorrelation analysis. Spatiotemporal scan analysis confirmed the presence of two cluster types. Geographically weighted regression analysis identified three influencing factors, with daily average temperature showing a negative correlation with tuberculosis incidence, while PM10 and SO2 levels exhibited positive correlations. Given the dry climate, frequent sandstorms, and severe air pollution in the Hotan area, tuberculosis prevention and control efforts are under environmental pressure (it refers to the challenges posed by the region’s dry, dusty climate and poor air quality for TB control efforts). Local authorities should prioritize environmental management and enhance tuberculosis prevention and control measures.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-19880-0.

Ending tuberculosis in Gulf Cooperation Council countries: an overview of the WHO End TB Strategy 2025 milestones.

The study aimed to describe the epidemiological profile of Tuberculosis (TB) and analyze the spatial distribution and temporal trend of TB incidence and mortality in Oyo state Nigeria from 2015-2019. The study was composed of TB cases and deaths reported by the Oyo State Health Secretariat between 2015 and 2019. The purely spatial, space-time scanning and the Getis-Ord Gi* techniques were used to analyze the spatial characteristics of TB and to identify areas at risk for its occurrence and deaths based on rates in each unit of analysis - Local Government Area (LGA), while the time series analysis technique was used to assess the characteristics of TB in Oyo state over the period studied. The standardized rates of sex and age were considered for data analysis. We analyzed 28,670 new cases of pulmonary and extra pulmonary TB as well as 1142 deaths reported in all LGAs between 2015 and 2019. Ibadan South West local government had the highest rate and risk (334 cases per 100,000), solely constituting above 10% of all cases reported in all 33 LGAs and for deaths the rate was 19.01 cases/100,000 inhabitants. Ido and Oluyole LGAs were Hot Spot regions for TB with a 99% confidence interval (CI) for TB incidence; about TB mortality, five municipalities were identified with a spatial association at 95% CI. The historical series of TB incidence rate slightly increased between the years 2015-2017, with a sharp decline from then until 2019. The temporal trend for the incidence and mortality of TB in the period under study decreased. This study contributes to knowing the epidemiological profile, the spatial and temporal distribution, and areas with higher risk of TB transmission in Oyo state. This makes it possible for policy makers to target hotspot areas for intervention and disease prevention.

ObjectivesTo assess the tuberculosis (TB) incidence trends, between 2000 and 2023, in the Kingdom of Saudi Arabia (KSA), in comparison to that in different geopolitical regions where the KSA is commonly included within, and to determine whether the KSA achieved the World Health Organization (WHO) and the United Nations (UN) Sustainable Development Goals (SDGs) End TB Strategy milestones and targets, including the reduction of the total TB incidence by 20% in 2020 compared to that of 2015.MethodsThis is a retrospective observational study on the TB incidence per 100,000 population arising in a given year as reported annually to the WHO. The data was extracted from the WHO indicator dataset. TB incidence data from the KSA, the World, the Gulf Cooperation Council (GCC), the Eastern Mediterranean region (EMR), and the Middle East and North Africa (MENA) region were included. Descriptive analysis and chi-square test were used to compare incidence differences and their statistical significance.ResultsThe TB incidence per 100,000 population in KSA in 2023 was 8.4 (95% uncertainty interval [UI]: 7.6–9.3), in 2020 it was 8.7 (95% UI:7.7–9.6), in 2015 it was 12 (95% UI: 11–13), in 2000 it was 23 (95% UI: 21–26). Compared to 2023, the reduction from 2000, 2015, and 2020 were − 14.6 (63.5% p < 0.01), − 3.6 (30%), and − 0.3 (3.4%), respectively. Compared to 2015, the reduction in 2020 was − 3.3 (27.5%). For 2023, compared to the GCC countries, the KSA had the second lowest incidence after the United Arab Emirates (UAE), which was − 7.6 less than KSA (p < 0.01). The incidence in Qatar was the highest, which was + 26.6 higher than KSA (p < 0.01). Compared to the MENA and EMR, only Jordan had a lower incidence, which was − 5.0 less than KSA. Pakistan had the highest incidence rate and the highest difference from the KSA by + 268.6 (p < 0.01).ConclusionTB incidence trends are decreasing in KSA, and it is among the top three regional countries with the lowest incidence rates. Compared with 2015, KSA exceeded the 20% milestone by achieving a 27.5% reduction in 2020. The KSA is heading towards achieving the WHO and UN’s SDG End TB Strategy targets of a 50% reduction by 2025, 80% by 2030, and 90% by 2035, to fulfill the vision of a world free of TB.

This study examines the epidemiological situation of tuberculosis (TB) in the regions of the Republic of Kazakhstan over the past seven years (2018–2024), which cover the before-, during- and after-COVID-19 periods, with a focus on the risks of its emergence and spread. The analysis revealed that while TB incidence is declining, mortality remains high in the before- and during-COVID-19 periods, indicating a general decline in population health. The concentration of TB incidence in relation to geographic location was mainly in the northern, western and southern regions. Before COVID-19, TB incidence reached 48.2 cases and mortality reached a maximum of 2.4 cases per 100,000 people. In 2024, the incidence and mortality of tuberculosis significantly decreased to 33.5 (30.5%) and 1.0 (58.3%), respectively, reflecting an improvement in health indicators in the post-pandemic period. In the after-COVID-19 period, in regions with high unemployment, the incidence was higher than in the before- and during-COVID-19 periods. Nevertheless, it is important that the trend in tuberculosis incidence shows positive improvement after the COVID-19 period. In addition, a comparative analysis of tuberculosis incidence trends in different age groups and social factor groups shows that the adult population remains the most vulnerable category among the general population. The above-listed factors, as well as our analysis of tuberculosis incidence, shows that TB incidence does not always correlate with the level of vaccination in different regions of Kazakhstan, indicating a multifactorial influence on the tuberculosis epidemic.

Trends, prevalence, and determinants of unfavorable tuberculosis treatment outcomes among adult patients in Northeast Ethiopia: The race to achieve a 90% treatment success rate by 2025.

Background This study aims to analyze the trends in tuberculosis (TB) cases from 2012 to 2023 in Yingjisha, providing valuable insights for improving TB prevention and control strategies. Methods The SARIMA, TBATS, TSLM, and STSM models were used for analysis. Results The number of reported TB incidences before COVID-19 was relatively stable and exhibited clearly seasonal patterns. The TBATS, TSLM, and SARIMA models fitted RMSE were 42.77, 55.57, and 64.02, the fitted MAPE were 1.46%, 1.92% and 3.20% respectively. The Box–Ljung test for the fitted sequences and the ADF test on the model fitted series yielded p < 0.05 for the above model. When using the models for prediction, the SARIMA model was lower than the other models. There is still a large deviation between the prediction and the actual number of reported TB incidences during the COVID-19 period. Conclusions Since the outbreak of COVID-19, there has been a decrease in the number of TB incidences, which has been largely influenced by epidemiological, social, and individual psychological factors.

BackgroundThe implementation of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic may inadvertently influence the epidemiology of tuberculosis (TB). (TB). However, few studies have explored how NPIs impact the long-term epidemiological trends of TB. We aimed to estimate the impact of NPIs implemented against COVID-19 on the medium- and long-term TB epidemics and to forecast the epidemiological trend of TB in Henan.MethodsWe first collected monthly TB case data from January 2013 to September 2022, after which we used the data from January 2013 to December 2021 as a training data set to fit the Bayesian structural time series (BSTS) model and the remaining data as a testing data set to validate the model's predictive accuracy. We then conducted an intervention analysis using the BSTS model to evaluate the impact of the COVID-19 pandemic on TB epidemics and to project trends for the upcoming years.ResultsA total of 590 455 TB cases were notified from January 2013 to September 2022, resulting in an annual incidence rate of 57.4 cases per 100 000 population, with a monthly average of 5047 cases (5.35 cases per 100 000 population). The trend in TB incidence showed a significant decrease during the study period, with an annual average percentage change of −7.3% (95% confidence interval (CI) = −8.4, −6.1). The BSTS model indicated an average monthly reduction of 25% (95% CI = 17, 32) in TB case notifications from January 2020 to December 2021 due to COVID-19 (probability of causal effect = 99.80%, P = 0.002). The mean absolute percentage error in the forecast set was 14.86%, indicating relatively high predictive accuracy of the model. Furthermore, TB cases were projected to total 43 584 (95% CI = 29 471, 57 291) from October 2022 to December 2023, indicating a continued downward trend.ConclusionsCOVID-19 has had medium- and long-term impacts on TB epidemics, while the overall trend of TB incidence in Henan is generally declining. The BSTS model can be an effective option for accurately predicting the epidemic patterns of TB, and its results can provide valuable technical support for the development of prevention and control strategies.

Significance. Currently, the incidence of tuberculosis in the subjects of the Russian Federation is variable and its range ranges from ≤ 40 to ≥ 100 per 100,000 population. At the same time, the share of subjects of the Russian Federation in which the incidence of tuberculosis is low (less than 40 per 100,000 population) is 70.8% of their total number. These include all the subjects of the Russian Federation located in the Central Federal District, including the Kaluga Region. Purpose. To study the dynamics and interdependence of tuberculosis incidence rates in the Central Federal District and the Kaluga Region for the period from 2016 to 2023. Materials and methods. Information from the Federal Statistical Observation form No. 8 and Rosstat population data for Russia, the Central Federal District and the Kaluga Region for 2016-2023. The StatTech v program was used for the analysis.2.8.8 (developed by Stattech LLC, Russia). Results. In the Central Federal District in 2023, the incidence of tuberculosis decreased by 50.88% compared to 2016 and its value reached 17.4 per 100,000 population, which was 1.7 times lower than the national value. The trend of tuberculosis incidence in the Kaluga Region in 2016-2023 largely corresponded to that in the federal district: in 2016-2019, its values were higher than in the district, and by the end of 2023 they decreased to 16.6 per 100,000 population, which was lower than in the district. Positive changes in the dynamics of tuberculosis incidence among men in the federal District and the Kaluga Region were synchronous, and its values in 2023 were 25.7 and 26.3 per 100,000 population. The incidence of tuberculosis among women in the Federal District and the Kaluga Region during 2016-2023 was 2.5 and 3.3 times lower than among men and in 2023 was 10.3 and 8.0 per 100,000 population. The presence of positive changes in the tuberculosis epidemic situation in the Central Federal District and the Kaluga Region was confirmed by episodic cases of tuberculosis among people aged &lt; 17 years and 18-24 years, and their greatest accumulation among people aged &gt; 45 years, as well as a low incidence of tuberculosis among women. The structure of newly diagnosed tuberculosis patients was dominated by males, whose share in 2023 in the Central Federal District and the Kaluga Region was 68% and 75%. Given the current situation, males aged 35-44 and 45-54 should be a priority group in conducting annual population examinations aimed at early detection of tuberculosis. Conclusions. The results of the study can be used in planning organizational measures aimed at early detection of tuberculosis among the population of federal districts and subjects of the Russian Federation, where the incidence of tuberculosis is decreasing from year to year. Keywords: tuberculosis incidence; indicators of the dynamic range of tuberculosis incidence; age and sex structure of patients with tuberculosis

Background: Tuberculosis (TB), as a communicable disease, is an ongoing global epidemic that accounts for a high burden of global mortality and morbidity. Drug-resistant TB strains are one of the hurdles in controlling TB problem. TB is the most common opportunistic infection in people living with human immunodeficiency viruses (PLHIV). To accelerate progress toward the goal of ending TB by 2035, it is imperative to outline the incidence and mortality trends of TB in India. Aims and Objectives: This study aims to provide deep insights into the recent trends of TB incidence and mortality in India from 2018 to 2023. Materials and Methods: This is a cross-sectional type of observational study done, over a period of 6 years from 2018 to 2023. It included 21,223 suspected samples tested for TB and rifampicin (rif) resistance with GeneXpert CBNAAT (cepheid) for infection of Mycobacterium tuberculosis (MTB). Results: Out of total 21,223 samples tested, 17.97% of samples were positive for MTB. From the year 2018 to 2023, 9.5% decline was seen in overall TB cases. However, the diagnosis of rif resistance is in similar range for all the study years. New patients show slight decline, but previous patients show higher rif resistance. There is decreased TB incidence in PLHIV. Conclusion: Overall, the incidence of TB has decreased in the past 6 years. The acquired drug resistance was seen in 32.6% cases. The study found an overall decrease in the incidence of TB in PLHIV.

Background: Tuberculosis (TB), as a communicable disease, is an ongoing global epidemic that accounts for a high burden of global mortality and morbidity. Drug-resistant TB strains are one of the hurdles in controlling TB problem. TB is the most common opportunistic infection in people living with human immunodeficiency viruses (PLHIV). To accelerate progress toward the goal of ending TB by 2035, it is imperative to outline the incidence and mortality trends of TB in India. Aims and Objectives: This study aims to provide deep insights into the recent trends of TB incidence and mortality in India from 2018 to 2023. Materials and Methods: This is a cross-sectional type of observational study done, over a period of 6 years from 2018 to 2023. It included 21,223 suspected samples tested for TB and rifampicin (rif) resistance with GeneXpert CBNAAT (cepheid) for infection of Mycobacterium tuberculosis (MTB). Results: Out of total 21,223 samples tested, 17.97% of samples were positive for MTB. From the year 2018 to 2023, 9.5% decline was seen in overall TB cases. However, the diagnosis of rif resistance is in similar range for all the study years. New patients show slight decline, but previous patients show higher rif resistance. There is decreased TB incidence in PLHIV. Conclusion: Overall, the incidence of TB has decreased in the past 6 years. The acquired drug resistance was seen in 32.6% cases. The study found an overall decrease in the incidence of TB in PLHIV.

Tuberculosis has been one of the most common communicable diseases raising global concerns. Accurately predicting the incidence of Tuberculosis remains challenging. Here we constructed a time-series analysis and fusion tool using multi-source data, and aimed to more accurately predict the incidence trend of tuberculosis of Anhui Province from 2013 to 2023. Random forest algorithm (RF), Feature Recursive Elimination (RFE) and Least absolute shrinkage and selection operator (LASSO) were implemented to improve the derivation of features related to infectious diseases and feature work. Based on the characteristics of infectious disease data, a model of RF-RFE-LASSO integrated particle swarm optimization multiple inputs long short term memory recurrent neural network (RRL-PSO-MiLSTM) was created to perform more accurate prediction. Results showed that the PSO-MiLSTM achieved excellent prediction results compared with common single-input and multi-input time-series models (test set MSE:42.3555, MAE: 59.3333, RMSE: 146.7237, MAPE: 2.1133, R2: 0.8634). PSO-MiLSTM enriches and complements the methodological research content of calibrating the time-series predictive analysis of infectious diseases using multi-source data, and can be used as a brand-new benchmark for the analysis of influencing factors and trend prediction of infectious diseases at the public health level in the future, as well as providing a reference for incidence rate prediction of infectious diseases.

Annotation. The difficult situation regarding tuberculosis in Ukraine requires the implementation of more effective and accessible tuberculosis infection control programs in medical institutions. The goal is to study the characteristics of the incidence and analyze the structure of tuberculosis among medical workers of the Vinnytsia region from 2007 to 2023. We processed reporting forms, cards of outpatients and inpatients of 207 medical workers of the Vinnytsia region, in whom tuberculosis was confirmed from 2007 to 2023, inclusive. A retrospective and prospective analysis of official medical documentation was carried out, the results of which were subject to mathematical and statistical processing (statistical observation; group analytical statistical summary using computer images in Microsoft packages, linear univariate correlation-regression analysis). We studied the main trends in the incidence of tuberculosis among medical workers, conducted an analysis of the structure of cases of this disease in various professional categories of medical personnel of general treatment network institutions and anti-tuberculosis institutions. During the 17-year period of the study, 163 cases of tuberculosis were detected in medical workers of the general treatment network and 44 cases in anti-tuberculosis institutions. Although the average incidence of tuberculosis among medical workers over the 17-year period of the study was slightly lower than in the population of the region (46.8 per 100,000 medical workers versus 56.8 per 100,000 population of the region), nevertheless, the indicators remain consistently high. The situation with morbidity among the medical staff of anti-tuberculosis institutions requires special attention, where the incidence of tuberculosis is 17 times higher than in the general treatment network.

Background: Tuberculosis in India is a major public health problem. The National Strategic Plan 2017-2025 aims to achieve a rapid decline in burden of TB, morbidity and mortality while working towards elimination of TB in India by 2025. By proper care and treatment of TB patients, the battle against TB can be won. In the current scenario, forecasting of Tuberculosis incidence and annual case notification rate could help policy makers in planning an effective intervention at the right time keeping in mind the target for TB elimination. Objectives: 1) To study the trend of Tuberculosis in India. 2) To forecast the incidence and annual case notification rate due to Tuberculosis in India for next 3 years. Methodology: Data regarding the incidence and annual case notification rate were collected from the annual reports of Tuberculosis published by Central TB Division, Government of India. Data from the sources were collected in a data extraction sheet and entered in MS excel. Gretl software was used for data analysis. Autoregressive Integrated Moving Average (ARIMA) method was used to select the best fitted model for available time series data and using the selected model incidence and annual case notification rate were forecasted for next 3 years. Results: The study showed an upward trend in incidence and annual case notification rate in the sampling and post sampling period. According to the forecast, for the year 2025 the incidence of Tuberculosis will be 28.36 lakhs (95%CI- 26.4886, 32.8556) and annual case notification rate will be 178 (95%CI- 144, 211). Conclusion: There is an upward trend of Tuberculosis incidence and annual case notification rate in India in forecasted period. To achieve the set targets, the policy makers need to plan and implement more effective interventions at the right time.

BackgroundDespite the significant progress over the years, Tuberculosis remains a major public health concern and a danger to global health. This study aimed to analyze the spatial and temporal characteristics of the incidence of tuberculosis and its risk factors and to predict future trends in the incidence of Tuberculosis.MethodsThis study used secondary data on tuberculosis incidence and tuberculosis risk factor data from 209 countries and regions worldwide between 2000 and 2021 for analysis. Specifically, this study analyses the spatial autocorrelation of Tuberculosis incidence from 2000 to 2021 by calculating Moran’s I and identified risk factors for Tuberculosis incidence by multiple stepwise linear regression analysis. We also used the Autoregressive Integrated Moving Average model to predict the trend of Tuberculosis incidence to 2030. This study used ArcGIS Pro, Geoda and R studio 4.2.2 for analysis.ResultsThe study found the global incidence of Tuberculosis and its spatial autocorrelation trends from 2000 to 2021 showed a general downward trend, but its spatial autocorrelation trends remained significant (Moran’s I = 0.465, P < 0.001). The risk factors for Tuberculosis incidence are also geographically specific. Low literacy rate was identified as the most pervasive and profound risk factor for Tuberculosis.ConclusionsThis study shows the global spatial and temporal status of Tuberculosis incidence and risk factors. Although the incidence of Tuberculosis and Moran’s Index of Tuberculosis are both declining, there are still differences in Tuberculosis risk factors across countries and regions. Even though literacy rate is the leading risk factor affecting the largest number of countries and regions, there are still many countries and regions where gender (male) is the leading risk factor. In addition, at the current rate of decline in Tuberculosis incidence, the World Health Organization’s goal of ending the Tuberculosis pandemic by 2030 will be difficult to achieve. Targeted preventive interventions, such as health education and regular screening of Tuberculosis-prone populations are needed if we are to achieve the goal. The results of this study will help policymakers to identify high-risk groups based on differences in TB risk factors in different areas, rationalize the allocation of healthcare resources, and provide timely health education, so as to formulate more effective Tuberculosis prevention and control policies.

Given the challenges presented by drug-resistant strains of tuberculosis (TB) and the rising mobility of the population, achieving the objective of eradicating TB appears uncertain. The examination of TB incidence trends in 10 high-burden countries (HBCs) indicated a steady rise in cases, with India and China jointly accounting for nearly 70% of the burden. Projections for the future show diverse trajectories in these countries, with potential difficulties in reaching the TB elimination target, especially in Nigeria, Congo, and South Africa. The number of TB cases is on the rise. It is crucial to learn from successful strategies to improve TB prevention and control worldwide through collaborative efforts.