Disease Progression Mathematical Modeling With a Case Study on Hepatitis B Virus Infection

Area of Science:

• Virology
• Mathematical Modeling
• Hepatology

Background:

• Chronic Hepatitis B (HBV) poses a significant global health and economic challenge.
• Hepatocellular carcinoma (HCC) risk persists despite available HBV treatments.
• Optimal HBV treatment requires understanding complex virus-host dynamics.

Purpose of the Study:

• To outline considerations for developing a disease modeling platform for HBV treatment decision-making.
• To review existing HBV models, their structures, and underlying assumptions.
• To provide interactive tools for exploring model behavior and parameter sensitivity.

Main Methods:

• Review of published mathematical models for Hepatitis B.
• Analysis of model structures, assumptions, and motivating contexts.
• Development of an interactive RShiny application showcasing selected models.

Main Results:

• Demonstration of how model choice impacts outcomes in Hepatitis B treatment scenarios.
• Illustration of parameter sensitivity analysis within interactive HBV models.
• Availability of practical tools for exploring HBV disease dynamics.

Conclusions:

• Disease modeling is crucial for informed decision-making in chronic Hepatitis B management.
• Interactive platforms enhance understanding of model utility and limitations.
• Further development of HBV models can refine personalized treatment strategies.