Cost-Optimal Intervention Strategies for Infectious Diseases

This dashboard supports evidence-based policymaking during infectious disease outbreaks. It integrates mathematical modeling, multi-objective optimization, and cost-benefit analysis to suggest cost-optimal transmission reduction strategies.

📌 Research Framework

  • 1. Mathematical Modeling
  • 2. Parameter Estimation
  • 3. Multi-Objective Optimization
  • 4. Cost-Benefit Analysis
  • 5. Interactive Dashboard

🧪 Dashboard Features

  • Adjust cost-related parameters; GDP, VSL, fatality rate, etc.
  • Visualize Pareto-optimal and cost-optimal intervention strategies
  • Compare infection and intervention costs
  • Explore cost-optimal patterns across different assumptions

⚙️ Model Assumptions

The dashboard uses a SEIQRD compartmental model fitted to early COVID-19 epidemic of the Republic of Korea. Intervention policies are estimated using IMODE and MCMC. Cost functions assume proportional or nonlinear relationships between intervention intensity and societal costs.


📊 Default Parameters; Korea

Parameter Default
GDP per capita 31,902 USD
GDP reduction 4.26%
VSL 1,751,311 USD
Fatality rate 1.73%

🛠️ How to Use

  1. Adjust parameters in the left panel.
  2. View cost and intervention results in the right panel.
  3. Identify cost-optimal policies; marked with green square.

🔗 External Links


🎓 Acknowledgements

This research is supported by the Bio\&Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) {RS-2023-00227944}. This paper is supported by the Korea National Research Foundation (NRF) grant funded by the Korean government (MEST) {NRF-2021R1A2C100448711}. The dashboard is developed by researchers at Konkuk University and University of the Philippines, Diliman.

👥 Demography-related parameters

🦠 Disease-related parameters

🏛️ Policy-related parameters

💰 Cost-related parameters

Parameters in this model are classified by 4 group.

  1. demograpy-related parameter
  2. disease-related parameter
  3. policy-related parameter
  4. Economy-related parameter

Demograpy is a population of the country

Disease-related parameters are the chracteristics of the disease. For example, reproduction number $R_0$, latent period $\kappa$, infectious period $\alpha$, recovery period $\gamma$, and fatality rate $f$.

Policy-related parameters are the effect of intervention policy. For example, imported cases $\xi$ and transmission reduction $\mu$ are changed by the intervention policy.

Economy-related parameters determine the intervention cost and infection cost. For example, GDP determines the intervention cost and VSL determines the infection cost.

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