Logistics of temporary testing centers for coronavirus disease

Area of Science:

• Operations Research
• Public Health
• Epidemiology

Background:

• The COVID-19 pandemic highlighted the need for efficient testing strategies.
• Current testing methods vary globally, with diverse approaches like drive-through and mobile centers.
• Optimizing the logistics of Polymerase Chain Reaction (PCR) testing is crucial for pandemic control.

Purpose of the Study:

• To propose a generic model for temporary pandemic testing logistics systems.
• To maximize total sample collection while minimizing walking distances for convenient sample collection.
• To present a case study on implementing vital procedures in Turkey based on best practices from South Korea and the UK.

Main Methods:

• Developed a mathematical model extending the Selective Vehicle Routing Problem and Covering Tour Problem.
• Proposed four two-stage math-heuristic algorithms for locating and routing temporary testing centers.
• Considered diminishing sample potentials and coverage over time to model non-linear pandemic progression.

Main Results:

• Generated Pareto sets of optimal solutions balancing total sample collection and maximum walking distance.
• Tested the model's performance on datasets from Seoul, South Korea, and Istanbul, Turkey.
• Conducted sensitivity analyses on key design parameters.

Conclusions:

• The proposed logistics model effectively enhances PCR testing availability and accessibility during pandemics.
• The mathematical framework and algorithms provide a robust solution for optimizing temporary testing center operations.
• Findings offer valuable insights for public health policy and pandemic preparedness planning.