An Operational View on Managing Mass Trauma Events

Problem definition: Mass trauma events (MTEs) present significant operational challenges. Affected populations require both immediate and prolonged mental health support, complicating response efforts. Posttraumatic stress disorder (PTSD) can have lasting effects and imposes a substantial economic burden, making early intervention critical to improving outcomes. The October 7, 2023, terror attack in southern Israel caused widespread trauma. Survivors, responders, and many others were exposed to extreme atrocities, placing an estimated 5.3% of the population at risk for developing PTSD and related conditions. This crisis underscores the urgent need for practical policies to deliver timely mental healthcare amid a surge in demand on an already-strained system. Methodology/results: We study the coordination of group and individual therapy channels in a multiserver queueing setting. Group therapy can alleviate immediate workload but may lead to increased follow-up demand for individual treatment. Our model captures this trade-off and the interdependence between therapy channels while accounting for key mental health system features, such as patient no-shows and dropouts. Using a fluid approximation, we derive index-based policies tailored to the surge, recovery, and long-term phases of MTEs, integrating time-varying, transient, and steady-state dynamics. Drawing on data from the attack and prior MTEs, we show that our policies can shorten the recovery phase by approximately six months, reduce queue lengths by 31%, and increase total cost savings by 52% relative to a benchmark policy that we adapted to incorporate group therapy, no-shows, and dropouts. These improvements result from embedded channel coordination in our policies. Managerial implications: Our results highlight the value of channel-specific coordination in mental health scheduling policies for traumatized populations. The index-based rules that we propose are simple to implement and offer actionable guidance for practitioners and policymakers managing care delivery after MTEs. Applying these policies can enhance support for at-risk populations, reduce system strain, and strengthen community recovery and resilience. Funding: This work was partially supported by the Israel Science Foundation [Grant No. 277/21] and by the Bernard M. Gordon Center for Systems Engineering at the Technion.