The daily swab test collection problem.

Area of Science:

• Health Logistics
• Operations Research
• Epidemiology

Background:

• Digital Contact Tracing (DCT) is effective against SARS-CoV-2 but strains local health logistics.
• The increasing demand for daily COVID-19 tests, especially during outbreaks, presents significant logistical challenges.

Purpose of the Study:

• Introduce the Daily Swab Test Collection (DSTC) problem to optimize home-based COVID-19 test collection.
• Formulate DSTC as a variant of the Team Orienteering Problem (TOP) and review its healthcare management applications.
• Develop efficient algorithms and realistic benchmarks for DSTC to ensure timely testing.

Main Methods:

• Formulation of the Daily Swab Test Collection (DSTC) problem as a variant of the Team Orienteering Problem (TOP).
• Creation of new, realistic benchmark instances for DSTC using data from Turin.
• Development and application of two novel hybrid algorithms to solve DSTC instances.

Main Results:

• The study demonstrates that optimizing health logistics can ensure timely COVID-19 testing for individuals identified by DCT.
• The proposed algorithms effectively handle realistic DSTC instances.
• Managerial insights highlight the feasibility and fairness of the optimized logistics approach.

Conclusions:

• The DSTC problem and its optimization are crucial for supporting effective Digital Contact Tracing (DCT).
• Efficient logistics planning is essential for timely diagnostic testing during public health crises.
• The developed methods provide a framework for improving healthcare system responsiveness and fairness.