First responders including firefighters, paramedics, and police officers are among the first to respond to vehicle collisions on roads and highways. Police officers conduct regular roadside Please check if the country name is correct traffic controls and checks on urban and rural roads, and highways. Once first responders begin such operations, they are vulnerable to motor vehicle collisions by oncoming traffic, a circumstance that calls for a better understanding of contributing factors and the extent to which they affect tragic outcomes. In light of factors identified in the literature, this paper applies machine learning methods including decision tree and random forest to a subset of the National Collision Database (NCDB) of Canada that includes information on collisions between two vehicles (one in parked position) and the severity of these collisions as measured by having or not having injuries. Findings reveal that key measurable, predictable, and sensible factors such as time, location, and weather conditions, as well as the interconnections among them, can explain the severity of collisions that may happen between motor vehicles and first responders who are working alongside the roads. Analysis from longitudinal data is rich and the use of automated methods can be used to predict and assess the risk and vulnerability of first responders while responding to or operating on different roads and conditions.

Mass vaccination is proving to be the most effective method of disease control, and several methods have been developed for the operation of mass vaccination clinics to administer vaccines safely and quickly. One such method is known as the hockey hub model, a relatively new method that involves isolating vaccine recipients in individual cubicles for the entire duration of the vaccination process. Healthcare staff move between the cubicles and administer vaccines. This allows for faster vaccine delivery and less recipient contact. In this paper we present a simulation tool which has been created to model the operation of a hockey hub clinic. This tool was developed using AnyLogic and simulates the process of individuals moving through a hockey hub vaccination clinic. To demonstrate this model, we simulate six scenarios comprising three different arrival rates with and without physical distancing. Findings demonstrate that the hockey hub method of vaccination clinic can function at a large capacity with minimal impact on wait times.