Impact of Transmission Dynamics and Treatment Uptake, Frequency and Timing on the Cost-effectiveness of Directly Acting Antivirals for Hepatitis C Virus Infection

TL;DR

This study develops an agent-based model to evaluate how transmission dynamics, treatment frequency, and timing influence the cost-effectiveness of hepatitis C treatments, revealing potential underestimations in traditional models.

Contribution

It introduces a comprehensive agent-based simulation model for HCV transmission in India and assesses the impact of transmission dynamics and treatment strategies on cost-effectiveness.

Findings

Transmission dynamics significantly affect cost-effectiveness estimates.

Higher treatment uptake rates increase the importance of considering transmission.

Timing and frequency of treatment influence economic evaluations.

Abstract

Cost-effectiveness analyses, based on decision-analytic models of disease progression and treatment, are routinely used to assess the economic value of a new intervention and consequently inform reimbursement decisions for the intervention. Many decision-analytic models developed to assess the economic value of highly effective directly acting antiviral (DAA) treatments for the hepatitis C virus (HCV) infection do not incorporate the transmission dynamics of HCV, accounting for which is required to estimate the number of downstream infections prevented by curing an infection. In this study, we develop and validate a comprehensive agent-based simulation (ABS) model of HCV transmission dynamics in the Indian context and use it to: (a) quantify the extent to which the cost-effectiveness of a DAA is underestimated - as a function of its uptake rate - if disease transmission dynamics are not considered in a cost-effectiveness analysis model; and (b) quantify the impact of the frequency and timing of treatment with DAAs, also as a function of their uptake rate, within a disease surveillance period on its cost-effectiveness.