An adaptive resource allocation mechanism based on patch cluster structures: Coupling resource flow and epidemic...

Area of Science:

• Epidemiology
• Network Science
• Mathematical Modeling

Background:

• Epidemic outbreaks pose significant global health risks.
• Existing resource allocation models lack dynamic regional risk adjustments and cluster-based coordination.

Purpose of the Study:

• To develop an adaptive resource allocation mechanism for epidemic control.
• To integrate resource flow with epidemic spreading in a metapopulation network using patch cluster structures.

Main Methods:

• Developed a coupled dynamics model incorporating migration-interaction-return processes.
• Designed an adaptive resource allocation mechanism adjusting donation and intra-cluster schemes based on evolving risk levels.
• Utilized the micro Markov chain approach to derive epidemic evolution equations and infection thresholds.

Main Results:

• Increased patch cluster numbers, inter-cluster connectivity, and cluster efficiency raise epidemic thresholds and reduce infection scale.
• Adaptive resource allocation models improve resource efficiency and decrease infection scale compared to traditional models.
• Targeted assistance from high-risk to low-risk patches effectively lowers overall prevalence.

Conclusions:

• The proposed model offers a theoretical framework for dynamic group resource optimization in heterogeneous risk environments.
• Adaptive resource allocation strategies are crucial for efficient epidemic prevention and control.
• Network structure, particularly triangular motifs, significantly impacts epidemic containment.