A Prediction Model of PTSD in the Israeli Population in the Aftermath of October 7th, 2023, Terrorist Attack and the Israel-Hamas War

Abstract

ABSTRACTBackgroundOn October 7th, 2023, a mass terror attack was launched by Hamas militants, which was followed by the Israel-Hamas war. These events constitute a nationwide trauma with major ramifications for public mental health. This article presents an evidence-based model for the prediction of the prevalence of posttraumatic stress disorder (PTSD) related to the terrorist attack and the war.Main bodyThe creation of the model consisted of several steps. Firstly, the Israeli population was divided into six groups based on the intensity, context, and type of traumatic exposure (direct exposure to terror, close proximity to terror, soldiers in combat and support units, intense exposure to rocket attacks, moderate exposure to rocket attacks, and indirectly affected communities), and the population size of each group was assessed using official national databases. Secondly, an estimation of the expected prevalence of PTSD in each of the exposure groups was based on a review of the relevant literature. A random-effects meta-analysis of the prevalence rates was conducted separately per each exposure group. Finally, the predicted number of PTSD causalities in the population was calculated by multiplying the group size and the PTSD prevalence estimation. Based on population size and estimated PTSD prevalence within each exposure category, the model predicts that approximately 5.3% (N=519,923) of the Israeli population (95% prediction interval, 160,346-879,502), may develop PTSD as a result of the terrorist attack and the war.ConclusionsThe predicted number of individuals with PTSD following mass trauma is expected to be considerable. The presented model can assist policymakers, clinicians, and researchers in preparing and devising adequate interventions for the mental health needs of large populations. Moreover, this model can be applied in other instances of mass-trauma exposure.