Based on DRG’s gold-standard Epidemiology data, the Interactive Patient Flow Model provides insight into the epidemiology of HCV for five different treatment scenarios.

With the introduction of DAAs, an effective cure for HCV, the epidemiology and consequent future size of the HCV drug market will be radically transformed. The more patients with HCV who get treated with DAAs, the fewer people will have HCV. But the situation is more complex than this simple piece of logic. For, the fewer people that have the HCV circulating in their blood, the lower the risk of anyone without HCV of being infected. Meanwhile, as time passes for those older people living with undiagnosed HCV, the more likely that they will become diagnosed as the disease progresses.

While DRG Epidemiology’s HCV forecast models these factors into a global HCV forecast, there are other scenarios that can be examined. With DRG Epidemiology’s interactive patient flow model for HCV, each of these scenarios can be played out across 45 countries worldwide. Each scenario comprises more than 50 patient populations, forecast to 2030. The scenarios are depicted via interactive graphical patient flow diagrams, each one showing the patient flow between different disease states from a different perspective.

The model comes with extensive tabulation of data, description of methods and data sources used, and full support from our infectious disease epidemiology team. The model is available as an MS Excel deliverable, downloadable from the top right.

One of the most informative of these counterfactual scenarios is if DAAs were not launched, thus enabling to see their true impact on HCV epidemiology apart from demographic factors such as the aging of the older generation who were exposed to the virus prior to its characterization and public health prevention policies.

Other interesting scenarios to play out are those where treatment is restricted to only those high-risk HCV cases. Namely, those with liver cirrhosis. This allows players in the HCV space to estimate – at a global level – the minimum eligible market size on the assumption that there will be strong advocacy for treatment of these high-risk cases. On the flip side of this is where constraints on healthcare providers’ budgets are loosened worldwide, so that even more resource-constrained countries in the developing world have the same treatment patterns as high-income western European countries.

Finally, the WHO development goals for both the diagnosis and treatment of HCV also effectively specify a counterfactual scenario. Namely: if these goals were to be achieved, what would be the result in terms of the prevalence of HCV worldwide?

Questions Answered

  • How will different treatment patterns affect the size of the eligible and treated HCV patient population in 45 countries over the next decade and beyond?
  • How will the commercial objectives for your HCV assets need to change in response to unanticipated reimbursement and policy shifts among payers?
  • In which countries should I focus my commercial strategy to maximize revenues from a shrinking eligible population?
  • Under what national or international set of policy objectives would the RoI on my HCV assets be maximized over the coming decade and beyond?
  • How does restricting HCV treatment based on disease severity affect the commercial viability of your HCV asset?

Key Benefits and Uses

  • Compare five different treatment scenarios and the effect of these scenarios on the epidemiology of HCV in 45 countries.
  • Understand how different treatment scenarios impact the HCV epidemic over a 15-year forecast
  • Make assumptions about the viability of HCV assets across 45 different countries.
  • Understand changes in the diagnosis and drug-treatment of HCV populations, defined by viremia, genotype and cirrhosis status, related to different treatment scenarios.

Table of contents

  • Hepatitis C Virus - Epidemiology - Interactive Patient Flow Model - Global
    • Introduction

Author(s): Ruchika Sharma, MPH; Mike Hughes, MSc, PhD

Ruchika Sharma joined Decision Resources Group as Associate Epidemiologist in May 2016. She performs fully documented systematic reviews of both published and grey literature on the epidemiology of assigned diseases and their risk factors to estimate incidence/prevalence over a 10-30 year period. She produces analyses for pharmaceutical drug developers on the descriptive epidemiology of major drug indications in mature and developing markets.

She holds a Master of Public Health degree from School of Public Health, Post-Graduate Institute of Medical Education and Research, and a Bachelor of Dental Surgery from MN DAV Dental College & Hospital.She has previously worked as a dental surgeon and as a Fellow at the National Health Systems Resource Centre, where she supported the preparation of National Health Accounts - Guidelines for India 2016.

Mike joined Decision Resources as an epidemiologist in 2006. He has many years’ experience in the mathematical modeling of healthcare service delivery, cardiovascular and cancer epidemiology, biostatistics, meta-analysis and systematic reviewing.

He has been principal author on many published articles in leading international journals in the areas of risk modeling in intensive care and cardiovascular medicine. He has also been responsible for developing national guidelines on behalf of NICE and the American College of Chest Physicians for the treatment of atrial fibrillation, stroke and hypertension. He is particularly interested in modeling patient flows in cancer and methods for forecasting disease burden in non-communicable epidemiology.

Dr. Hughes received his Ph.D. in risk modeling in intensive care in 2003 from City University, London and is currently enrolled in a Ph.D. program in statistical causation and foundations of probability theory at the University of Nottingham.