Dataset on optimizing ambulance deployment and redeployment in Fez-Meknes region, Morocco.

Emergency Medical Services (EMS) are crucial for saving patients' life, attenuating disabilities, and improving patients' satisfaction. Optimal deployment and redeployment of ambulances over a territory reduce response times for serving emergencies. Thus, rapid interventions and transport to a hospital are guaranteed. Optimizing ambulance deployment and redeployment is achieved by conceptualizing and formulating mathematical programming models and simulation models. Mathematical models maximize the proportion of the population that can be reached by ambulance in a response time less than a threshold value. In contrast, simulation models assess a given ambulance deployment and redeployment configuration. The application of mathematical and simulation models require data related to demand areas (geographic territories), demand value at each demand area, locations of potential sites for ambulance bases, X and Y geographic coordinates of demand areas and potential sites, travel times between potential sites and demand areas, etc. All these data are essential in deciding which potential sites to choose for locating ambulance bases and how many ambulances to allocate to each base per period. Beside elaborating and constructing ambulance deployment and redeployment models, researchers in Operations Research (OR) are challenged when collecting data for executing, testing, and proving the performance of their proposed models. This paper provides data about medical transport in Morocco's Fez-Meknes region, which can be accessed at https://zenodo.org/record/6416058. They were collected from the field, estimated based on the population size, and obtained by computer programs. The dataset includes 199 demand areas and their respective demand value per ambulance type and per period, the travel times between 18, 22, 40 potential sites and the 199 demand areas per period, and the travel times between the potential sites. Also, the dataset comprises the minimum number of ambulances required by each demand area for -reliable coverage, which was computed using a MATLAB program. The number of ambulances required by each demand area is mandatory to apply reliability models such as the MALP and the Q-MALP models. These data would be used by the research community interested in EMS, especially pre-hospital emergency issues addressed by deploying mathematical programming and simulation tools.