385 / 2024-04-24 21:15:36

Ensuring fairness and efficiency in defibrillator deployment under uncertain transporting time

AED deployment,fairness,efficiency,uncertainty,exact algorithms

Cardiac arrest represents an urgent and critical public health emergency worldwide, characterized by exponentially decreasing survival rate with increasing time-to-treatment. Despite the efforts of the public access defibrillator programs and policies to ensure that automated external defibrillators (AEDs) are immediately available for use by lay bystanders, the utilization of AEDs still remains low. To enhance AED deployment strategies, we study an AED location problem under uncertain transporting times of bystanders. We formulate the problem as a maximal covering location problem under uncertain transporting times.  We minimize a novel maximum risk tolerance index to ensure that the time-to-treatment is within the ``Golden 4 Minutes'' as likely as possible, while the probability of exceeding the golden time decreases exponentially. To ensure fairness and efficiency concurrently, we employ a lexicographic minimization approach and develop binary search, cutting plane, and hill-climbing solution algorithms. Through simulation studies based on real data from Chengdu City, we demonstrate that our approach outperforms the traditional deterministic and probabilistic approaches in ensuring timely treatments and in mitigating unfairness, having the potential to help enhancing the survival rates of cardiac arrest victims.