Applying a system approach to forecast the total hepatitis C virus-infected population size: model validation using...

Area of Science:

• Epidemiology
• Public Health
• Mathematical Modeling

Background:

• Hepatitis C virus (HCV) infection causes chronic liver disease with an uncertain global epidemiology.
• The impact of HCV is projected to increase significantly in the coming decade.

Purpose of the Study:

• To develop a predictive tool for future Hepatitis C virus (HCV) prevalence globally.
• To understand the relationship between key assumptions and future disease trends.

Main Methods:

• A systems approach was employed to construct a simulation model.
• Population dynamics were modeled with inflows and outflows.
• Sensitivity analysis identified key drivers of future HCV prevalence.

Main Results:

• US HCV-infected population projected to decrease by 24% (3.15M in 2005 to 2.47M in 2021).
• HCV mortality rate forecasted to rise from 2.1% to 3.1% between 2005 and 2021.
• Only 50% of infections were diagnosed, and less than 2% were treated.

Conclusions:

• A framework for evaluating global HCV-infected populations has been developed.
• The model can assess policy impacts on future HCV challenges.
• This prediction tool can inform new public health strategies.