Examining Drug Resistant Tuberculosis Screening

Patients with a drug-resistant disease may need different treatment than those with a drug-sensitive disease. However, identifying these patients may be difficult since tests to determine disease strain may be time-consuming or costly. In this project, we develop a model using the Partially Observable Markov Decision Process (POMDP) along with simulation techniques to identify when and which first-line tuberculosis patients are most likely at risk for drug resistance and should be screened to reduce costs and increase health outcomes.