Objective This study aimed to analyse the burden and temporal trends of tuberculosis (TB) incidence and mortality globally, as well as the association between mortality-to-incidence ratio (MIR) and Socio-Demographic Index (SDI).
Design A retrospective analysis of TB data from 1990 to 2019 was conducted using the Global Burden of Disease Study database.
Results Between 1990 and 2019, there was a declining trend in the global incidence and mortality of TB. High SDI regions experienced a higher declining rate than in low SDI regions during the same period. Nearly half of the new patients occurred in South Asia. In addition, there is a sex–age imbalance in the overall burden of TB, with young males having higher incidence and mortality than females. In terms of the three subtypes of TB, drug-sensitive (DS)-TB accounted for more than 90% of the incidents and deaths and experienced a decline over the past 30 years. However, drug-resistant TB (multidrug-resistant (MDR)-TB and extensively drug-resistant (XDR)-TB) showed an overall increasing trend in age-standardised incidence rates and age-standardised mortality rates, with an inflection point after the year 2000. At the regional level, South Asia and Eastern Europe remained a high burden of drug-resistant TB incidence and mortality. Interestingly, a negative correlation was found between the MIR and SDI for TB, including DS-TB, MDR-TB and XDR-TB. Notably, central sub-Saharan Africa had the highest MIR, which indicated a higher-than-expected burden given its level of sociodemographic development.
Conclusion This study provides comprehensive insights into the global burden and temporal trends of TB incidence and mortality, as well as the relationship between MIR and SDI. These findings contribute to our understanding of TB epidemiology and can inform public health strategies for prevention and management.
- Public health
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
Comprehensive analysis of tuberculosis incidence, deaths, age-standardised rate and mortality-to-incidence ratio (MIR) across various regions, Socio-Demographic Index (SDI) categories, and countries from 1990 to 2019, disaggregated by age, sex and drug resistant type where possible.
Novel exploration of tuberculosis outcomes by MIR and the relationship between MIR and SDI, specifically examining drug-resistant tuberculosis.
Utilisation of the Global Burden of Disease (GBD) database to provide robust estimates.
Limitations of the GBD database should be considered when interpreting the findings.
The study focuses on HIV-negative individuals; therefore, the results may not be directly applicable to the HIV-positive population.
Tuberculosis (TB) is a major cause of both incidence and mortality, resulting in over a million deaths each year and consistently ranking among the top 10 causes globally.1 The WHO has prioritised reducing the burden of TB globally.2 Despite some progress over the past two decades, the annual decline in global TB incidence rates has been insufficient to meet the WHO’s End TB Strategy targets,3 4 which call for a 4%–5% annual reduction in morbidity. Most TB incidence and death occur among HIV-negative individuals, despite the potential risk posed by HIV.5 Moreover, drug-resistant TB represents a looming threat to TB management efforts.6 7
Despite previous publications reports on the incidence and mortality associated with TB,8 and the proportion of mortality attributable to major risk factors such as smoking, alcohol use and diabetes,9 the global spatiotemporal pattern of HIV-negative TB and drug resistance status remains unknown. Therefore, comprehensive and in-depth analyses of HIV-negative TB and drug-resistant TB across all regions are needed, which can refine hotspot and high-risk population delineation, optimise the allocation of scarce health resources and guide public health policies. The Global Burden of Disease (GBD) provides comprehensive global data on TB, including its incidence, prevalence, mortality and temporal trends, and can serve as a valuable resource for such analyses.
Selection of input data
We obtained annual estimates of TB incidence and deaths, along with corresponding age-standardised rates (ASRs) and their 95% uncertainty intervals (UIs), among 21 GBD regions, 5 regions based on the Socio-Demographic Index (SDI) and 204 countries and territories. These estimates were stratified by sex and age among HIV-negative individuals from 1990 to 2019. The data were obtained from the online Global Health Data Exchange website (http://ghdx.healthdata.org/gbd-results-tool). The 95% UIs were determined using the GBD’s algorithm, which involved 1000 draws from the posterior distribution, with the 25th and 975th ordered values defining the uncertainty range.10 Detailed methodology for the GBD 2019 has been thoroughly described in previous studies.11 Additionally, the SDI values, summarising social and economic conditions, were obtained from the website: https://vizhub.healthdata.org/gbd-results/. SDI scores ranged from 0 to 1 and were assessed based on a combination of data on overall educational level, income per capita and fertility rate.12 According to SDI values, GBD 2019 classified 204 countries and territories into 5 SDI regions: high, high-middle, middle, low-middle and low (online supplemental table S1).13
TB subtypes and data limitations
In 2021, the WHO updated definitions for extensively drug-resistant TB (XDR-TB) and introduced a new category, pre-XDR-TB. WHO now classifies drug-resistant TB into five categories: rifampicin-resistant TB, isoniazid-resistant TB, multidrug-resistant TB (MDR-TB), pre-XDR-TB and XDR-TB.14 However, GBD 2019 does not include diseases caused by rifampicin-resistant TB, isoniazid-resistant TB and pre-XDR-TB in its model. It is worth noting that the definitions of XDR-TB used in the GBD 2019 database slightly differ from the latest WHO definition in 2021.8 9 The GBD 2019 Tuberculosis Collaborators categorised TB among HIV-negative individuals into three subtypes: drug-sensitive TB (DS-TB), this refers to TB strains that are susceptible to standard first-line anti-TB drugs; MDR-TB without extensive drug resistance (MDR-TB) is characterised by resistance to the two most effective first-line anti-TB drugs (isoniazid and rifampicin), but is not resistant to any fluoroquinolone and any second-line injectable drugs (amikacin, kanamycin or capreomycin); XDR-TB is a severe form of drug-resistant TB that is resistant to isoniazid and rifampicin, plus any fluoroquinolone and any second-line injectable drugs.8 9
The specific methods of GBD for estimating TB burden have been described in detail previously.10 ASRs, representing ASRs per 100 000 population, were calculated as weighted averages of age-specific rates, where the weights corresponded to the proportions of individuals in the respective age groups of the WHO standard population. Age-standardised incidence rate (ASIR) and age-standardised death rate (ASMR) were reported to quantify the disease burdens during a specific period. We also presented the mortality-to-incidence ratio (MIR) as an indicator of health system performance, which was derived by dividing the ASMR by the ASIR.15–17 The estimated annual percentage change (EAPC) was used to quantify the trends in the ASRs of TB. The formula was defined as Y=α+βX+ε, EAPC=100×[exp(β)−1], where Y referred to ln (ASR), X was the calendar year and ε was the error term, β represented positive or negative ASR trends, and its 95% CI could be obtained from the linear regression model.18
Additionally, we calculated the percentage change in the count of incident patients between 1990 and 2019 as the difference between the values of 2019 and 1990, divided by the value of 1990 and then multiplied by 100. Furthermore, we determined the proportion of deaths attributed to each TB subtype in different GBD regions in 2019 by dividing the number of deaths assigned to a specific TB subtype by the total number of TB deaths during that year. Furthermore, we explored the relationship between the SDI and the MIR for TB and its three subtypes using Pearson’s correlation coefficients. This analysis aimed to examine the association between socioeconomic development and TB outcomes. All statistical analyses were performed by using R V.4.1.3 (https://www.r-project.org).
Patient and public involvement
TB incidence burden and temporal trends by regions and nations
Between 1990 and 2019, there was a decline in the number of TB incident patients from 8.76 million (95% UI 7.59 to 10.06 million) to 8.50 million (95% UI 7.45 to 9.73 million). The ASIR also decreased from 172.6 to 106.7 per 100 000 population. Among the 21 geographical regions, South Asia had the highest number of incident patients (3.81 million, 95% UI 3.27 to 4.43 million) in 2019, followed by Southeast Asia (1.11 million, 95% UI 0.98 to 1.24 million). Southern Sub-Saharan Africa reported the highest ASIR (343.6 per 100 000), which did not show a substantial decline over the past three decades (with an EAPC of −0.2, 95% CI −0.41 to 0.01), followed by Central Sub-Saharan Africa (ASIR: 303.6 per 100 000). Over the past three decades, eight regions experienced an increase in the absolute number of TB incident patients, while all regions showed a decrease in ASIRs, especially in Andean Latin America, from 217.1 to 65.8 per 100 000 population, with an EAPC of −4.36 (95% CI −4.63 to −4.1) (table 1).
Regarding the 204 countries and territories examined, the ASIR of TB varied significantly across the world in 2019, with the highest ASIR observed in the Central African Republic (506.25 per 100 000), followed by Eritrea and Burundi (figure 1A and online supplemental table S2). Less than half of the countries or territories reported an increase in the number of TB incident patients from 1990 to 2019, with the highest increase of 232.56% observed in the United Arab Emirates (figure 1B, online supplemental table S2). The largest decrease in ASIR was observed in Estonia (EAPC = −4.94; 95% CI −5.47 to −4.40), followed by Croatia and Peru (figure 1C and online supplemental table S2). Only six countries or territories (South Africa, Sweden, Lesotho, Georgia, Greenland, Ukraine) represented an increasing ASIR between 1990 and 2019 (figure 1B,C and online supplemental table S2).
TB age and sex incidence patterns in five SDI regions
In 2019, the overall number of incident patients and ASIR of TB were higher in males, but a reverse sex pattern was found in age groups under 15 years in high and high-middle SDI regions, and in age groups under 25 years in low, low-middle and middle SDI regions. Across all SDI regions, the number of TB incident patients presented an initial increase and then decreased with age in both genders, reaching a peak at 20–24 years old globally in 2019 (figure 2A). The ASIR rapidly increased in both genders with increasing age, particularly after 75–79 years old (figure 2B). Over the period from 1990 to 2019, the ASIR exhibited a downward trend in both genders across the five SDI regions, with the most pronounced decrease observed in the under-14 years old age group. Notably, females experienced a more significant decrease in ASIR than males in nearly all age groups (online supplemental table S3, figure 2C,D).
Spatiotemporal dynamics of TB incidence by drug-resistance type
The ASIR of DS-TB has shown a decreasing trend over the past three decades, accounting for more than 90% of new patients in 2019 (figure 3A). Conversely, the ASIR of MDR-TB experienced a significant rise in all regions and then gradually declined with the turning point occurring in 2005 (figure 3B). The ASIR of XDR-TB exhibited rapid growth until 2010, followed by a flat trend (figure 3C). Detailed information on the ASIR of the three TB subtypes across five SDI regions from 1990 to 2019 can be found in online supplemental table S4. Specifically, in 1990, there were no reported patients of XDR-TB. Among the 21 GBD regions from 2010 to 2019, there was a significant decrease in ASIR for MDR-TB and XDR-TB in East Asia (EAPC: −7.63, 95% CI −9.51 to −5.71; EAPC: −2.96, 95% CI −4.7 to −1.18, respectively). In contrast, Oceania experienced the highest increase in ASIR for both MDR-TB and XDR-TB (EAPCs: 12.37, 95% CI 7.91 to 17.01; 17.83, 95% CI 12.75 to 23.14, respectively). In 2019, South Asia had the highest number of incident patients in DS-TB and MDR-TB accounting for 44.3% and 57.2%, respectively, and Eastern Europe had the highest number of incident patients with XDR-TB accounting for 39.2% (online supplemental table S5).
TB deaths burden and temporal trends
We further explored the global mortality rate per 100 000 population in 2019, along with the temporal trends in the past 30 years by sex and age group in HIV-negative TB individuals. Out of a total of 1.2 million global deaths in 2019, 64.5% occurred in males. By age growing, ASMR showed a V-shaped trend with the nadir occurring at 10–14 years age group in both genders. In the past 30 years, there was a declining trend in ASMR for both genders (with an EAPC of −3.56 in males and −3.77 in females). The overall burden of ASMR was higher for males than for females, but it declined more rapidly for males in over 60 years age group (table 2).
As for 21 GBD regions, there was a significant decline in the number of TB-related deaths in the past 30 years, consistent with the incidence trend observed. In 2019, nearly half of these deaths occurred in South Asia (692 000.0, 95% UI 645 000.0 to 738 000.0), followed by Eastern Sub-Saharan Africa and Southeast Asia (figure 4A and online supplemental table S6). figure 4B and online supplemental table S7 present the percentage of total deaths for TB across the 21 GBD regions in 2019, categorised by drug-resistance types. DS-TB accounted for 89.96% of TB deaths, MDR-TB accounted for 9.32%, and XDR-TB accounted for 0.72%. South Asia had the most deaths in DS-TB (453 671.52, 38.45%), MDR-TB (65 062.9, 5.51%) and XDR-TB (3354.89, 0.28%). Regarding the five SDI regions, the ASMR of DS-TB displayed a decreasing pattern from 1990 to 2019, declining at a faster rate than the ASIR. While the ASMR for MDR-TB and XDR-TB showed an upward trend until 2000, it had levelled off or reversed over the past decade (figure 3D–F, online supplemental table S4).
Tuberculosis MIR by drug-resistance type
Given the much higher incidence of DS-TB compared with MDR-TB and XDR-TB, we compared MIR in the three types of TB to evaluate the outcomes in 2019. Table 3 shows that the MIR for XDR-TB is 2.5 times higher than DS-TB and 1.3 times higher than MDR-TB. Central Sub-Saharan Africa had the highest MIR both in DS-TB, MDR-TB and XDR-TB, followed by Eastern Sub-Saharan Africa. In Central, Eastern and Western Sub-Saharan Africa, the MIR values for XDR-TB were greater than 1, indicating that the age-standardised mortality rate (ASMR) is higher than the ASIR.
TB MIR association with SDI
We analysed the relationship between regional SDI and the corresponding MIR of TB from 1990 to 2019, as detailed in online supplemental table S8. At the regional level, an inverse correlation was noted between SDI and the MIR of TB over the measurement period, although some exceptions to this association. The same trends were also observed in DS-TB, MDR-TB, XDR-TB (figure 5). For TB and its three subtypes, Eastern Sub-Saharan Africa and Central Sub-Saharan Africa exhibited MIR patterns that remained higher than anticipated levels. While East Asia and Tropical Latin America had lower MIR than expected.
This study presented an overview of the epidemiological features of TB burden in HIV-negative individuals, stratified by drug resistance type and SDI. Despite a global reduction in TB incidence and mortality, HIV-negative individuals still experienced a substantial burden of the disease, with an estimated 8.50 million new patients and 1.18 million deaths in 2019. The diverse incidence pattern across regions and the drug resistance status poses significant challenges to TB prevention and management. In 2016, only 22% of people with newly diagnosed drug-resistant TB were estimated to begin treatment, with 54% achieving successful treatment outcomes,19 which poses a growing threat to public health and an economic burden. The inflection points in ASIR and ASMR of the three TB subtypes between 2005 and 2010 may be attributed to the emergence of new drug classifications against TB and increased availability of rapid drug susceptibility testing.20–23 The WHO guidelines for the programmatic management of DR-TB and new laboratory diagnostic tools for TB management were published in 2006 and 2008,24 25 calling for rational strategies for case-finding and treatment of DR-TB patients. Rapid progress in discovering novel drugs and effective treatment regimens has also been made since 2010.26
TB is a disease of poverty, with more than 95% of deaths taking place in low-income and middle-income countries.27–29 Smoking, alcohol use and diabetes are more prevalent among poor populations,30–32 and these factors also contribute to higher TB incidence, greater risk of developing drug-resistant and worse treatment outcomes.33–35 As MIR provides a population-based indicator of survival,15 such conditions in poverty could also partially explain the negative correlation between MIR and SDI.
South Asia and Eastern Europe, primarily composed of middle-income and low-income countries, continue to bear a high burden of drug-resistant TB incidence and mortality.36 37 In particular, South Asia and Southeast Asia (constitute WHO’s South-East Asia Region), with 26% of the global population and 40% of the global poor,38 accounted for more than half the global incidence and deaths of TB in 2019. Rapid urbanisation, high-density populations, household air pollution and malnutrition due to shortages in food supply all contribute to the high incidence of TB and the associated poor treatment outcomes.39–41 Furthermore, a higher prevalence of diabetes and a burgeoning and largely unregulated private sector have resulted in extended infectiousness, acquired drug resistance and treatment failure.42–45 Despite India launching a National Tuberculosis Elimination Programme in 1997, it is still far from fulfilling its bold strategies of realising a TB-free India in 2025.46 Delays in care-seeking and delayed diagnosis fueled by stigma further increase the size of the infectious pool of TB, enhancing the risk of household contact and community transmission.47 In Eastern Europe, primary transmission of TB resistant strains due to immigration contributes to the high burden of drug-resistant TB in the European region.48 49 Inadequate healthcare system, initially weak drug quality and misuse of anti-TB drugs also contribute to the high burden of XDR-TB in the region.50 51 Additionally, conflicts in Afghanistan, Pakistan and India in South Asia, as well as Ukraine in Eastern Europe, along with the large-scale displacement caused by wars over the past two decades, have potentially increased the risk of TB development and transmission.52 53 Routine bidirectional screening and integrating management for the TB and diabetes, implementing measures to end all forms of malnutrition, improving public–private collaboration and addressing health systems constraints, destigmatising TB and strengthening targeted screening and healthcare access for vulnerable migrant populations hold significant potential for improving TB management.
Despite improvements in sociodemographic conditions, Central and Eastern Sub-Saharan Africa had a higher MIR in three types of TB than expected given their level of sociodemographic development. Despite efforts to increase access to anti-TB treatment in Africa since 2006, inadequate resources and the poor capacity for patient identification have contributed to the high disease burden of TB in Sub-Saharan Africa.54 Moreover, the disproportionate burden of TB among detainees in the region, caused by high rates of pretrial detention and overcrowding also exacerbated the spread of drug-resistant TB and poor outcomes in the region.55 Sputum-smear microscopy alone is an inadequate routine diagnostic test for TB in this region.56 More seriously, the burden of TB and drug resistance in Central Sub-Saharan Africa may be underestimated due to inadequate laboratory and diagnostic infrastructure, patient detection, recording and reporting systems.57 Oceania had the most significant increase of ASIR in MDR-TB and XDR-TB. As the most populated Pacific Island nation, Papua New Guinea is one of the 30 countries classified by the WHO as ‘high-burden’ for drug-resistant TB,58 which may because of the transmission of drug-resistant strains caused by several waves of human migrations59 60 and the lack of antimicrobial resistance surveillance systems.60
We found a sex and age disparity in the burden of TB. In 2019, males accounted for 56.0% of incident patients and 64.5% of TB deaths. Additionally, females experienced a greater decrease in ASIR than males from 1990 to 2019. Factors such as smoking, alcohol use, diabetes and access to healthcare differs between genders have been proposed to explain this gender gap.61–66 Additionally, males are at greater risk of TB due to migrants, homeless or incarcerated.67–70 Relatively to age, there was also a higher ASIR and ASMR in the older age groups for both genders. As one ages, the immune system weakens, leading to increased vulnerability to infectious diseases and poorer health outcomes.71 Although the overall burden of TB is higher in male than female, we found young females accounted for more TB incidence and mortality. The reasons for higher incidence and mortality among young females remain unclear and may be related to structural social issues, such as female’s limited access to education. In fact, TB incidence and mortality are consistently higher in the least educated populations.72 73
According to a 2017 WHO/World Bank report, at least half of the world’s population lacks access to essential health services.74 However, despite the US$6.5 billion funding for TB management in 2020, this falls short of the US$13 billion target agreed on by world leaders in the United Nations Political Declaration on Tuberculosis.75 International assistance is crucial every year to fill the funding gap for TB management in less economically developed regions.76 In light of this, the Global Fund should consider regional and population priorities in its TB funding, with the aim of enhancing TB prevention, diagnosis and treatment programmes.
This study has several limitations. First, the differences in the management of patient detection and reporting among regions have been well discussed in previous publications, highlighting the intrinsic defects of GBD estimations.11 Second, the present research did not address important risk factors associated with TB incidence and mortality, such as smoking, alcohol use and diabetes. Third, there is a lack of individual-level data within groups as this study is an ecological study focusing on the comparison of groups rather than individuals. Additionally, the focus of this study was solely on HIV-negative individuals; therefore, future research should explore the interaction between HIV and drug-resistant TB to gain a comprehensive understanding of this complex relationship.
There has been an overall decline in the global burden of HIV-negative TB, but the persistent prevalence of drug-resistant TB remains a significant challenge in low-income and middle-income regions. A negative correlation was found between MIR and SDI for TB. Central sub-Saharan Africa had a higher MIR in three types of TB than expected given their level of sociodemographic development. Furthermore, there are regional and sex–age imbalances in the overall burden of TB. These findings underscore the importance of enhancing the management and prevention of drug-resistant strains, as well as implementing targeted interventions to address TB in specific populations.
The incidence and mortality of GBD database were estimated by analysing all available data sources (including annual case notifications, prevalence surveys, population-based tuberculin surveys and estimated TB cause-specific mortality), and then the Bayesian meta-regression tool, DisMod-MR 2.1, was used to generate the estimate values. As a result, the TB mortality and incidence are represented as non-integer numbers.
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
Patient consent for publication
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Contributors YC: collecting data, analysing data, writing the manuscript, guarantor. JL, QZ, QW, LC, HC, DL, YQ, YW, JW, XX, SL and ML: writing the manuscript, submitting to the publication. revising the manuscript. All authors contributed to manuscript revision, read and approved the submitted version.
Funding This work was supported by the Natural Science Foundation of Shaanxi Province (Grant No. 2019JQ-390 to Dr. Xinming Xie, 2020JO-508 to Dr. Shaojun Li) and the Integration of Basic and Clinical Science Project of School of Basic Medical Sciences, Xi'an Jiaotong University (Grant No. YXJLRH2022034 to Dr. Xinming Xie).
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Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
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