Research in Progress (RIP): "Modeling Disease for Effective Control: Tuberculosis in India"

"Modeling Disease for Effective Control: Tuberculosis in India"

Please note: All research in progress seminars are off-the-record. Any information about methodology and/or results are embargoed until publication.

Abstract:

Simulation and optimization frameworks that incorporate individual heterogeneity can be powerful tools to inform health policy decisions, particularly decisions about how to efficiently control infectious diseases in resource-constrained settings.  We apply such models to assess policies for control of tuberculosis (TB) in India, where more than two million people have TB.

We first use a microsimulation model to uncover the changing dynamics of drug-resistant (DR) TB. We find that nearly half of new DR TB cases in India are transmission-generated, as opposed to treatment-generated, and we project this proportion to continue to rise, implying that strategies that disrupt DR transmission may provide greater DR prevalence reductions over time.  We then incorporate healthcare costs into the simulation and find that both new diagnostics and institutional reform policies that refer patients in informal, private TB clinics to public clinics using approved treatment regimens would both be cost-effective ways of combatting TB in India. However, these institutional reforms should be prioritized if insufficient resources are available to implement both types of policies nationally. Building on the microsimulation results, we use dynamic programming methods to design patient-specific DR TB testing algorithms that can reduce over-testing, reduce costs, and quickly identify DR TB patients. We estimate that the optimal DR TB testing algorithm identified by our analysis will decrease healthcare costs by an average of $4000 per patient by averting downstream transmission.