Friday, April 19, 2024
4/19/2024
Project Summary/Abstract People who inject drugs (PWID) account for the majority of hepatitis C virus (HCV) infections in the U.S. Improving the HCV care continuum, with particular attention to the complication of HIV-coinfection, is critical to achieving HCV elimination. Heterogeneous injection and sexual networks among PWID can significantly affect HCV and HIV transmission and intervention outcomes. Although empirical studies on the efficacy of interventions to improve the HCV care continuum in the direct-acting antiviral (DAA) era have begun to accumulate, there remains a lack of understanding of the population level impact and cost-effectiveness of these interventions to inform policymaking. My long-term goal is to develop mathematical and statistical simulation models to inform health policies relating to infectious disease control. The overall objective for this application, which is a critical step toward attaining my long-term goal, is to develop a dynamic agent- based network model of HCV and HIV transmission among PWID, to determine the population-level impact and cost-effectiveness of interventions to improve the HCV care continuum. My central hypothesis is that interventions that target multiple stages of the care continuum, taking account of individual characteristics, service environment, and meso/macro-level contexts, will have significant population-level impact in decreasing HCV and HIV infections and associated complications while being cost-effective. The central hypothesis will be tested by pursuing three specific aims: 1) Identify social determinants of the HCV care continuum outcomes among PWID, and effective interventions to improve these outcomes in the DAA era; 2) Determine the population-level impact and cost-effectiveness of different interventions to improve the HCV care continuum among PWID; 3) Identify the determinants of differences in population-level impact of interventions to improve the HCV care continuum based on specific features of PWID networks. I will pursue these aims using systematic review and meta-analysis (Aim 1), expanding our model of HCV transmission via injection network to incorporate sexual network and HIV transmission (Aim 2), and fitting the model to different PWID networks and evaluate impact across the networks (Aim 3). To complete the research and advance my career, I will obtain research training in evidence synthesis, Bayesian methods for model calibration, and health economics, and professional training in scientific communication, leadership, and collaboration, in the interdisciplinary environment of the Department of Health Policy at the Stanford School of Medicine. The expected outcome is a novel model platform to evaluate complex HIV/HCV intervention strategies for improving the health of PWID. The proposed research is significant because the results will provide systematic understanding of social determinants of HCV care in PWID and essential evidence on the population-level impact and cost-effectiveness of interventions to improve the HCV care continuum in different PWID populations to inform policymaking on HCV elimination.
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