Designing a Digital Twin for Equitable Blood Donation Logistics in Geneva

Area of Science:

• Operations Research
• Geographic Information Systems (GIS)

Background:

• Mobile blood drives are crucial for reaching diverse donor populations.
• Current planning for mobile blood drives often lacks data-driven optimization strategies.

Purpose of the Study:

• To develop and demonstrate a novel digital twin approach for optimizing mobile blood drive logistics.
• To enhance the efficiency and equity of blood collection through spatial analysis and mathematical optimization.

Main Methods:

• A four-layer digital twin architecture was developed, integrating GIS analysis with Mixed-Integer Linear Programming (MILP).
• Six accessibility indicators were used to inform an objective function aimed at maximizing expected donations.
• Operational constraints were incorporated into the optimization model.

Main Results:

• An illustrative scenario indicated that evening donation slots could yield approximately 25% more donations compared to midday slots.
• Specific time slots, such as Thursday evenings, showed potential for peaking at 33-34 expected donations.
• The model demonstrated the impact of timing and location on donation volumes.

Conclusions:

• This proof-of-concept validates the integration of spatial analysis and mathematical optimization for mobile blood collection planning.
• The digital twin approach offers a feasible method for improving equitable blood collection strategies in urban settings like Geneva.
• The findings highlight the potential for significant increases in donation efficiency through optimized scheduling.