Prioritizing Patients and Routes: A Mathematical Model for Pandemic Response

This research proposes a mathematical model to optimize the response time of ambulances during a pandemic like COVID-19. The model prioritizes suspected cases, determines the best routes for ambulances, and utilizes IoT for real-time monitoring. A new time-effective relief supply chain network is introduced to allocate ambulances to districts and patients. The model minimizes total response time while ensuring all patients are covered. Various optimization algorithms are employed to find optimal solutions, including SA, GA, PSO, and a hybrid PSO-VNS. The methodology is tested on a real case in Canada and demonstrates its effectiveness in identifying and treating COVID-19 cases efficiently. The study provides managerial insights for implementing efficient strategies to address pandemics using IoT.