L-2 DYNAMIC TRANSMISSION MICROSIMULATION OF TUBERCULOSIS IN INDIA TO ASSESS THE FUTURE IMPACT OF TREATMENT PROGRAMS

Friday, October 19, 2012: 4:15 PM
Regency Ballroom D (Hyatt Regency)
Health Services, and Policy Research (HSP)
Candidate for the Lee B. Lusted Student Prize Competition

Sze-chuan Suen, BS, BA, Stanford University, Palo Alto, CA, Eran Bendavid, MD, MS, Stanford University, Stanford, CA and Jeremy D. Goldhaber-Fiebert, PhD, Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University, Stanford, CA

Purpose: Tuberculosis (TB) continues to be a public health challenge in India, which accounts for a quarter of global incident cases.  Disease control is complicated by a growing burden of multi-drug resistant (MDR) TB. Understanding the drivers of India’s future TB and MDR-TB epidemic is crucial to disease control.  We used simulation modeling to assess India’s future TB trends and the potential impacts of treatment programs.

Method: We developed a dynamic transmission microsimulation model of TB in India. Individuals were characterized by age, sex, smoking status, TB infection and disease, and whether they had drug-sensitive (DS) or MDR-TB. The model incorporated DOTS and DOTS+ treatment algorithms for DS-TB and MDR-TB respectively and empirically-observed patterns of coverage and treatment uptake. Data sources included: the United Nations Population Division, India’s National Family and Health Survey and Revised National Tuberculosis Control Program, and the published literature. We calibrated the model to India’s demographic patterns, age- and sex-specific smoking prevalence rates, overall force of TB infection, and annual estimates of TB prevalence and incidence both before and during DOTS and DOTS+ ramp-up. We examined the role played by the coverage and quality of DOTS and DOTS+ on future prevalence and incidence of MDR-TB.

Result: The model achieved good calibration for 1996-2011. Compared to a counterfactual without any DOTS, we estimated that DOTS has averted 100 million latent DS-TB infections and 3 million active TB cases in India to date. These effects differed by smoking, age, and sex.  DOTS was also associated with 7 million latent MDR-TB infections and 800,000 active MDR-TB cases through treatment default and incomplete treatment.  We estimate that MDR-TB prevalence will increase by 150% by 2036 without any changes to DOTS or DOTS+. Improving DOTS quality now could avert >80% of incident MDR-TB cases. The timing of quality improvement is influential, because over time a decreasing number of new MDR-TB cases are due to incomplete treatment and more cases result directly from transmission.

Conclusion: In India, DOTS has been associated with reducing overall TB incidence but increasing MDR-TB incidence.  At the current quality of treatment programs, MDR-TB is expected to increase in India.  Dynamic simulation models stratified by demographic and risks factors can provide timely insights to inform policymaking.