Optimal Investment in Prevention and Recovery for Mitigating Epidemic Risks

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health Economics

Background:

• The COVID-19 pandemic underscored the need for effective epidemic risk mitigation strategies.
• Existing models often overlook the critical role of social network structures in disease spread.

Purpose of the Study:

• To develop and analyze a mathematical model for optimizing investments in epidemic risk mitigation.
• To investigate the impact of network characteristics and investment limits on mitigation strategies.

Main Methods:

• Construction of a mathematical model to optimize investments in prevention/containment and treatment/recovery measures.
• Explicit incorporation of individual network characteristics into the propagation model.
• Analysis of investment optimization under varying connectivity and loss parameters.

Main Results:

• Optimal investment in either mitigation category increases with network connectivity and intrinsic loss, capped at a fraction of potential loss.
• When allocating a fixed budget, the optimal proportion for prevention/containment rises with increased investment limits and decreased network connectivity.

Conclusions:

• The model provides a framework for understanding optimal resource allocation in epidemic mitigation.
• Findings offer insights into past pandemic responses and inform strategies for future events, including COVID-19.