To provide an integrative overview of mathematical modeling approaches in infectious disease dynamics, emphasizing their application in public health decision-making.
Key Findings:
Mathematical modeling is crucial for understanding and controlling infectious diseases.
Hybrid modeling pipelines enhance real-time outbreak monitoring and intervention design.
An integrative approach provides a coherent roadmap for selecting and combining modeling strategies.
Interpretation:
The study emphasizes the importance of integrating diverse modeling approaches to improve public health responses to infectious diseases.
Limitations:
The review may not cover all emerging modeling techniques due to the rapid evolution of the field.
Focus on translational relevance may overlook some theoretical advancements.
Conclusion:
The manuscript offers a structured decision-support perspective that bridges theory, computation, and policy implementation in infectious disease modeling.
