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Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model

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Published on: October 31, 2010

Doing Good with Good OR: Supporting Cost-effective Hepatitis B Interventions.

David W Hutton¹, Margaret L Brandeau, Samuel K So

¹Department of Management Science and Engineering, Stanford University, Stanford CA 94305.

Interfaces

|July 16, 2011

Summary

Mathematical models identified cost-effective hepatitis B interventions. This led to policy changes in the US for screening and free vaccination programs in China, improving public health.

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Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection

Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection

Published on: November 7, 2018

Area of Science:

Public Health
Health Economics
Mathematical Modeling

Background:

Hepatitis B is a vaccine-preventable disease causing cirrhosis and liver cancer, particularly affecting Asian populations.
Limited healthcare budgets necessitate cost-effective strategies for disease control.
The Asian Liver Center at Stanford University is a leader in hepatitis B and liver cancer advocacy.

Purpose of the Study:

To analyze the cost-effectiveness of hepatitis B interventions using mathematical models.
To inform policy decisions for hepatitis B control in the United States and China.

Main Methods:

Utilized novel combinations of decision analysis and Markov models.
Conducted OR-based analyses to evaluate intervention cost-effectiveness.

Main Results:

Influenced US public health policy, expanding hepatitis B screening for millions.
Encouraged Chinese policymakers to implement free catch-up hepatitis B vaccination for hundreds of millions of children.

Conclusions:

Mathematical modeling is crucial for identifying cost-effective public health programs.
Policy changes based on these models significantly advance hepatitis B prevention and treatment efforts.
These interventions contribute to reducing health disparities and discrimination.