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

Soham Das, Ajit Sood, Vandana Midha, Arshdeep Singh, Pranjl Sharma, Varun Ramamohan

TL;DR

This study develops and validate a comprehensive agent-based simulation (ABS) model of HCV transmission dynamics in the Indian context and uses it to quantify the extent to which the cost-effectiveness of a DAA is underestimated.

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.

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 and validate a comprehensive agent-based simulation (ABS) model of HCV transmission dynamics in the Indian context and uses it to quantify the extent to which the cost-effectiveness of a DAA is underestimated.

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.
Paper Structure (19 sections, 21 equations, 5 figures, 10 tables, 3 algorithms)

This paper contains 19 sections, 21 equations, 5 figures, 10 tables, 3 algorithms.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Literature Pertaining to RO1: Model-based Cost-effectiveness Analyses of HCV Treatment
  4. Literature Pertaining to RO2: Impact of Intervention Frequency and Timing
  5. Agent-Based Simulation Model Development
  6. Agent Interaction Environments and Ancillary Dynamics
  7. Medical environment for HCV transmission.
  8. Social interaction environment.
  9. Treatment Module for Infected Agents
  10. Outcomes Estimation Module
  11. Outcomes of interest.
  12. Computational Experiments for Research Objectives 1 and 2
  13. Research Objective 1: Quantifying the Impact of Treatment Uptake and Incorporating Transmissions on DAA Cost-effectiveness
  14. Research Objective 2 Outcomes: Impact of Timing and Frequency of Treatment
  15. Discussion
  16. ...and 4 more sections

Figures (5)

  • Figure 1: Agent interaction models in the HCV dynamic transmission model.
  • Figure 2: Incremental net monetary benefit at each applicable treatment uptake rate, calculated with respect to the previous uptake rate.
  • Figure 3: Ratios of outcomes - net monetary benefits (NMBs), costs and the QALY terms within the NMB equation - for the with transmission (WT) and the without transmission (WoT) analyses.
  • Figure 4: Epidemiological outcomes and NMBs associated with multiple treatment models as a function of treatment uptake rate
  • Figure A.5: The discrete-time Markov chain used to model the natural history of chronic HCV in an infected agent.