Intentional mass-casualty incidents (IMCIs) involving motor vehicles (MVs) as weapons represent a growing trend in Western countries. This method has resulted in the highest casualty rates per incident within the field of IMCIs. Consequently, there is an urgent requirement for a timely and accurate casualty estimation in MV-induced IMCIs to scale and adjust the necessary health care resources.

The objective of this study is to identify the factors associated with the number of casualties during the initial phase of MV-IMCIs.

This is a retrospective, observational, analytical study on MV-IMCIs world-wide, from 2000-2021. Data were obtained from three different sources: Targeted Automobile Ramming Mass-Casualty Attacks (TARMAC) Attack Database, Global Terrorism Database (GTD), and the vehicle-ramming attack page from the Wikipedia website. Jacobs’ formula was used to estimate the population density in the vehicle’s route. The primary outcome variables were the total number of casualties (injured and fatalities). Associations between variables were analyzed using Spearman’s correlation coefficient and simple linear regression.

Forty-six MV-IMCIs resulted in 1,636 casualties (1,430 injured and 206 fatalities), most of them caused by cars. The most frequent driving pattern was accelerating whilst approaching the target, with an average speed range between four to 130km/h and a distance traveled between ten to 2,260 meters. The people estimated in the MV-IMCI scenes ranged from 36-245,717. A significant positive association was found of the number affected with the estimated crowd in the scene (R2: 0.64; 95% CI, 0.61-0.67; P <.001) and the average vehicle speed (R2: 0.42; 95% CI, 0.40-0.44; P = .004).

The estimated number of people in the affected area and vehicle’s average speed are the most significant variables associated with the number of casualties in MV-IMCIs, helping to enable a timely estimation of the casualties.