TB Research

Evolving dynamics of tuberculosis and emerging HIV Co-infection in China: Age-period-cohort analysis and projections to 2035

Yang Zhu, Wenxi Wang, Tinglong Chen, Ruiwen Liu, Jialiang Yao, Yuqi Cai, Vivian Yawei Guo, Jing Gu, et al. (12 authors)

Journal of Infection and Public Health · 2026-04

Abstract

BACKGROUND: Despite significant progress in tuberculosis (TB) prevention, China remains the third-highest TB burdened country globally, with ongoing concerns about drug-resistant tuberculosis (DR-TB) and HIV/TB co-infection. METHOD: The study utilized data from the Global Burden of Disease (GBD) 2021, applying the Age-Period-Cohort (APC) model to analyze age, period, and cohort effects on the incidence and mortality of TB, DR-TB, and HIV/TB co-infection. The Bayesian Age-Period-Cohort (BAPC) model projected future trends from 2022 to 2035. RESULT: Age effects indicated an increased incidence and mortality risk for TB and DR-TB with age, while younger and middle-aged groups were more affected by HIV/TB co-infection. Period effects demonstrated decreasing risks for TB and DR-TB, but an increasing trend for HIV/TB co-infection. Cohort effects similarly indicated a decline for TB and DR-TB, with a slight rise for HIV/TB co-infection among individuals born between 1990 and 2006. BAPC projections indicate that by 2035, the age-standardized incidence rate (ASIR) for TB, DR-TB, and HIV/TB co-infection will be 21.86, 1.04, and 1.21 per 100,000 person-years, respectively, while the age-standardized mortality rate (ASMR) will be 0.90, 0.09, and 0.12 per 100,000 person-years, respectively. None of these projections fulfill the End TB targets. CONCLUSION: Current strategies are unlikely to meet the End TB targets by 2035 in China, suggesting a need for preventive treatment for latent tuberculosis infection (LTBI) and improved screening for HIV and TB in high-risk populations.

MeSH terms

  • Human immunodeficiency virus (HIV)
  • Tuberculosis
  • Dynamics (music)
  • Medicine
  • Antiretroviral therapy
  • Evolutionary biology