Time trends in tuberculosis mortality across the BRICS: an age-period-cohort analysis for the GBD 2019

Background: Tuberculosis is the leading cause of death from a single infectious agent among the HIV-negative population and ranks first among the HIV-positive population. However, few studies have assessed tuberculosis trends in Brazil, Russia, India, China and South Africa (BRICS) or with an emphasis on HIV status. This study assesses the time trends of tuberculosis mortality across the BRICS with an emphasis on HIV status from 1990 to 2019. Methods: We obtained tuberculosis data from the Global Burden of Disease 2019 study (GBD 2019). We calculated the relative proportion of tuberculosis to all communicable, maternal, neonatal, and nutritional diseases by HIV status across the BRICS. We used age-period-cohort modelling to estimate cohort and period effects in tuberculosis from 1990 to 2019, and calculated net drift (overall annual percentage change), local drift (annual percentage change in each age group), longitudinal age curves (expected longitudinal age-specific rate), and period (cohort) relative risks. Findings: There were 549,522 tuberculosis deaths across the BRICS in 2019, accounting for 39.3% of global deaths. Among HIV-negative populations, the age-standardised mortality rate (ASMR) of tuberculosis in BRICS remained far higher than that of high-income Asia Pacific countries, especially in India (36.1 per 100 000 in 2019, 95% UI [30.7, 42.6]) and South Africa (40.1 per 100 000 in 2019, 95% UI [36.8, 43.7]). China had the fastest ASMR reduction across the BRICS, while India maintained the largest tuberculosis death numbers with an annual decrease much slower than China’s (-4.1 vs -8.0%). Among HIV-positive populations, the ASMR in BRICS surged from 0.24 per 100 000 in 1990 to 5.63 per 100 000 in 2005, and then dropped quickly to 1.70 per 100 000 in 2019. Brazil was the first country to reverse the upward trend of HIV/AIDS-tuberculosis (HIV-TB) mortality in 1995, and achieved the most significant reduction (-3.32% per year). The HIV-TB mortality in South Africa has realised much progress since 2006, but still has the heaviest HIV-TB burden across the BRICS (ASMR: 70.0 per 100 000 in 2019). We also found unfavourable trends among HIV-negative middle-aged (35-55) adults of India, men over 50 in the HIV-negative population and whole HIV-positive population of South Africa, and women aged 45-55 years of Russia. China had little progress in its HIV-positive population with worsening period risks from 2010 to 2019, and higher risks in the younger cohorts born after 1980. Interpretation: BRICS’ actions on controlling tuberculosis achieved positive results, but the overall improvements were less than those in high-income Asia Pacific countries. BRICS and other high-burden countries should strengthen specified public health approaches and policies targeted at different priority groups in each country. Funding: National Natural Science Foundation of China (82073573; 72074009), Peking University Global Health and Infectious Diseases Group. We obtained the data in this study from GBD 2019 public datasets available from http://ghdx.healthdata.org/gbd-results-tool (accessed on October 29, 2020). We restricted the analysis to age- and sex-mortality resulting from tuberculosis. The GBD study uses deidentified data from the second data source was aggregated by the Institute for Health Metrics and Evaluation, University of Washington. Therefore, a waiver of informed consent was reviewed and approved by the University of Washington Institutional Review Board. GBD 2019 provides a total of 369 diseases and injuries for 204 countries with multi-level secondary data sources from vital registration systems, surveillance systems, and verbal autopsies.1 In GBD 2019, tuberculosis cases were identified based on the International Classification of Diseases, version 10 (ICD-10). The discharge diagnosis codes for HIV-negative tuberculosis are A10–19.9, B90–90.9, K67.3, K93.0, M49.0, and P37.0; for HIV-positive tuberculosis, the ICD 10 code is B20.0.1 To model mortality due to tuberculosis among HIV-negative individuals, the database included vital registration data (21 505 site-years), verbal autopsy data (705 site-years), sample-based vital registration data (825 site-years), and mortality surveillance data (680 site-years). To estimate HIV-TB mortality, this database included vital registration data (438 site-years) and HIV-TB cases recorded in the tuberculosis register from WHO. The data in this study inherits the limitations of the GBD study, including that the Disease Surveillance Point system did not cover some remote and poorer areas in BRICS and the data from high resource settings heavily informed GBD models. However, it is also a strength of the GBD 2019 approach to leverage all available data to estimate disease burden. Details of the methods and processing for quantifying the burden of tuberculosis have been published before.5 We used an age-period-cohort model to develop independent effect estimates of age, period and birth cohort on tuberculosis mortality.9,10 In the age-period-cohort model, net drift represents the log-linear trend by period and cohort for the whole population and local drift represents the log-linear trend by period and cohort for each age group.11 The model results showed longitudinal age curve, period relative risks and cohort relative risks. To avoid the problem of reading a graph with too many lines, we calculated the mortality and population data into consecutive 5-year periods from 1990 to 2019. The longitudinal age curve used successive 5-year age intervals from 15 to 19 years old to 75 to 79 years old among HIV-negative individuals and from 15 to 19 years old to 65 to 69 years old among HIV-positive individuals due to the small number of HIV-TB patients aged over 70. The period relative risks are the ratio of age-specific rates in each period, with the 2000 to 2004 survey year as the reference period group. The cohort relative risks are the ratio of the age-specific rate in 18 consecutive cohorts among HIV-negative individuals including those born from 1913 to 1917 (median, 1915) to 1998 to 2002 (median, 2000), with the birth cohort of 1953 to 1957 (median, 1955) as the reference group, and 16 consecutive cohorts among HIV-positive individuals including those born from 1913 to 1917 (median, 1915) to 1988 to 1992 (median, 1990), with the birth cohort of 1948 to 1952 (median, 1950) as the reference group. We obtained the estimated parameters from the age-period-cohort Web Tool designed by the National Cancer Institute of the United States.11 To examine the significance of the estimable parameters and functions, the Wald χ2 test was used and all statistical tests were two sided. As BRICS countries were all listed as the top 30 high TB burden countries, we chose high-income Asia Pacific countries (including Japan, the Republic of Korea, Singapore and Brunei Darussalam) as the reference group, which had more comparable tuberculosis burden and ASMR with BRICS. The funders of this study had no role in study design, data collection, data analysis, data interpretation, and writing of the manuscript. ZZ and CJLM had access to GBD 2019 public datasets. All authors agreed to submit this study for publication.