Method: We developed a dynamic transmission microsimulation model that follows India’s population stratified by age, sex, TB, drug resistance, and treatment status. We calibrate the model to Indian demographic, epidemiologic, and TB healthcare patterns in the public and private sectors. Control interventions include: 1) improving treatment effectiveness in the public sector only; 2) improving the accuracy and rapidity of TB diagnosis and drug sensitivity testing in the public and/or the private sector; 3) increasing referrals from the private sector to the public sector through PPM; 4) reducing inappropriate medication use to prevent MDR in the private sector; 5) combinations of these efforts. Outcomes include incidence and prevalence of active non-MDR and MDR TB in 2023 relative to 2013 levels.
Result: Without interventions, the model projects declines in non-MDR TB incidence (12%) and prevalence (12%) and increases in MDR incidence (15%) and prevalence (19%). For non-MDR TB, increasing referrals from the private to the public sector (through PPM) alone or in combination with improved diagnostics yields 15-17% lower incidence and 34-47% lower prevalence. Synergies provided by combined public and private sector interventions are evident for MDR outcomes. Exclusively private sector interventions result in MDR incidence and prevalence increases of 13-16%, whereas exclusively public sector interventions result in 2-7% declines. Combinations of PPM and increases in non-MDR TB treatment effectiveness to avoid generating MDR reduce incidence by 13-19%. Likewise, although MDR prevalence increases 14-18% with PPM alone, PPM combined with rapid, accurate diagnostics results in MDR prevalence declines of 55-58%.
Conclusion: Combining public and private sector interventions to improve and link TB care and rapid, accurate diagnostics is a promising approach for reducing non-MDR and MDR TB in India and similar Asian countries.