Additional file 1 of Global, regional, and national burden of HIV-negative tuberculosis, 1990–2021: findings from the Global Burden of Disease Study 2021
Creators: name: Zhang, Shun-Xian
name: Miao, Feng-Yu
name: Yang, Jian
name: Zhou, Wen-Ting
name: Lv, Shan
name: Wei, Fan-Na
name: Wang, Yu
name: Hu, Xiao-Jie
name: Yin, Ping
name: Zheng, Pei-Yong
name: Yang, Ming
name: Wang, Mei-Ti
name: Feng, Xin-Yu
name: Duan, Lei
name: Yang, Guo-Bing
name: Wang, Ji-Chun
name: Lu, Zhen-Hui
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 1: Table S1 The number of incidence cases of TB, DS-TB, MDR-TB, and XDR-TB in HIV-negative individuals in 2021, and percentage change of the number of incidence cases were analyzed across GBD regions. Table S2 The EAPC of ASRs for TB, DS-TB, MDR-TB, and XDR-TB in HIV-negative individuals were analyzed across five SDI regions. Table S3 ASRs of TB, DS-TB, MDR-TB, and XDR-TB in HIV-negative individuals in 2021, and percentage change of ASRs for 204 countries and territories. Table S4 The number of death cases of TB, DS-TB, MDR-TB, and XDR-TB in HIV-negative individuals in 2021, and percentage of change rates of death number for GBD regions. Table S5 The number of DALY cases of TB, DS-TB, MDR-TB, and XDR-TB in HIV-negative individuals in 2021, and percentage change of number of DALY cases were analyzed across GBD regions. Table S6 Predicted ASRs for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB from spanning 2022–2035, based on the Bayesian Age-Period-Cohort Model. Fig. S1 The specific mortality of TB, DS-TB, MDR-TB, and XDR-TB showed notable differences across age and gender distributions in 2021 year. Fig. S2 The specific DALY of TB, DS-TB, MDR-TB, and XDR-TB showed notable differences across age and gender distributions in 2021 year. Fig. S3 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of TB across 204 countries and territories in 2021 year. Fig. S4 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of DS-TB across 204 countries and territories in 2021 year. Fig. S5 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of MDR-TB across 204 countries and territories in 2021 year. Fig. S6 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of XDR-TB across 204 countries and territories in 2021. Fig. S7 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate from 1990 to 2021 year. Fig. S8 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of DS-TB from 1990 to 2021 year. Fig. S9 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of MDR-TB from 1990 to 2021 year. Fig. S10 The association between the SDI and the ASIR, ASMR, and age-standardized DALY rate of XDR-TB from 1990 to 2021 year. Fig. S11 The association between risk factors and the ASMR and age-standardized DALY rate of XDR-TB in 21 GBD regions from 1990 to 2021.