title: Assessment of tuberculosis burden in China using a dynamic disease simulation model.
abstract: METHODS
  Although a preventable and treatable disease, tuberculosis (TB) is among the top 10 causes of death worldwide. A consequence of inadequately treated drug-susceptible TB (DS-TB) is multidrug-resistant TB (MDR-TB).
  
  
  OBJECTIVE
  To improve our understanding of the primary drivers of incidence and prevalence of DS- and MDR-TB in China.
  
  
  METHODS
  The Tuberculosis Disease Transmission Model (TBDTM) uses historical and current disease epidemiology and transmission trends and treatment effectiveness, and accounts for annual changes to these to estimate future DS-TB and MDR-TB burden.
  
  
  RESULTS
  The model shows that in China, by 2050, incidence, prevalence and mortality of DS-TB will decrease by 32%, 50% and 41%, respectively, whereas MDR-TB will increase by respectively 60%, 48% and 35%. Reduction in DS-TB is a result of high treatment and cure rates leading to a decrease in the prevalence of latent tuberculous infection (LTBI), while the increase in MDR-TB is attributed to inappropriate treatment, leading to high transmission of infection and increased LTBI prevalence.
  
  
  CONCLUSIONS
  These results demonstrate a reduction in DS-TB in China over the next 40 years, while MDR-TB will increase. Improvements in the diagnosis and treatment of MDR-TB are needed to counter this threat. The TBDTM tool has potential value in public health practice by demonstrating the impact of interventions and estimating their cost-effectiveness.
authors.affiliation: Janssen Global Services, Raritan, New Jersey 08869, USA. mmehra@its.jnj.com
authors.forename: M
authors.initials: M
authors.lastname: Mehra
authors.forename: N
authors.initials: N
authors.lastname: Cossrow
authors.forename: C
authors.initials: C
authors.lastname: Kambili
authors.forename: R
authors.initials: R
authors.lastname: Underwood
authors.forename: R
authors.initials: R
authors.lastname: Makkar
authors.forename: R
authors.initials: R
authors.lastname: Potluri
mesh_terms: D000995:Antitubercular Agents / Q000627:therapeutic use; D002681:China / Q000453:epidemiology; D003198:Computer Simulation; D024901:Drug Resistance, Multiple, Bacterial; D006801:Humans; D015994:Incidence; D008962:Models, Theoretical; D015995:Prevalence; D011379:Prognosis; D013997:Time Factors; D014376:Tuberculosis / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology* / Q000401:mortality / Q000635:transmission*; D018088:Tuberculosis, Multidrug-Resistant / Q000453:epidemiology / Q000635:transmission
chemical_list: D000995:Antitubercular Agents