Grant: Operating Grant

The combined epidemics of HIV and tuberculosis (TB) have had a huge negative impact in both the developing and developed world. Early diagnosis and rapid initiation of treatment are essential to control both infections. Although there are many accurate rapid tests to diagnose HIV, an unacceptably large proportion of HIV infections are still undiagnosed, and therefore untreated, which fuels the epidemic. For TB, less than perfect tools and diagnostic delays are to blame for the ongoing transmission in at risk regions. Unlike HIV, a simple handheld test for TB is currently not available, but the landscape is looking more promising for affordable easy to use molecular tests, which can be used at the point-of-care to reduce diagnostic delays. Such tests, including the widely-publicized Xpert MTB/RIF test, have the potential to transform TB control, but they must be scaled up and adapted to local conditions. In the rapidly changing world of diagnostics, we need to know: Which technologies, implemented at which level of the health system, with which performance characteristics, will have greatest impact on the TB and HIV epidemics? Combined epidemic-economic models are important tools for answering these questions, as they have the unique ability to project the costs, cost-effectiveness and public health impact of alternative diagnostic strategies in a single unified platform. We propose to construct a dynamic model of a TB and HIV epidemic, and to compare our results for India, where HIV and TB are important health problems, and Canada, a low risk region. We will use the model to estimate the public health impact, cost and cost-effectiveness of using the Xpert test routinely for TB diagnosis, and the impacts of using a rapid handheld test for HIV screening. Our model and the data we generate will help inform and guide policymakers on TB and HIV diagnostic issues.