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Localized Economic Modeling To Optimize Public Health Strategies For HIV Treatment And Prevention
The North American HIV epidemic is a diverse set of microepidemics, dispersed primarily across large urban centers with different underlying epidemiological and structural conditions. These disparate underlying conditions require localized strategies to optimize the HIV care cascade. Changes over time in these microepidemics, as well as in evidence on how to improve HIV testing and care, challenges our ability to make informed and timely decisions that result in the greatest health benefits for the resources invested in treating and preventing HIV.
We describe progress on a novel economic modeling framework to augment HIV surveillance efforts. This framework would ensure scarce resources are focused on interventions that can provide the greatest value for money in a given microepidemic. We will build upon a validated economic model to produce rapid, automated evidence synthesis, focusing on minimal data requirements to update the model, and integrate findings from emerging results of public health interventions into near real-time disease surveillance systems for 6 US cities. Learning objectives from this work-in-progress presentation include discussion on methods for calibration and validation of dynamic transmission models, as well as approaches to executing evidence syntheses for high-dimensional models.