DOI: 10.5281/zenodo.6416057
title: Dataset on ambulance deployment and redeployment

description: These data consist of a network of demand areas and ambulance potential sites for research on optimizing ambulance deployment and redeployment. The reported data are helpful for researchers interested in developing and comparing ambulance deployment and redeployment models, such as mathematical programming models and simulation models. They contain 199 demand areas and 3 cases related to ambulance potential sites (18, 22, and 40 potential sites). All data are gathered from the Moroccan context (Fez-Meknes region) and are presented in 16 tables: <strong>Table 1</strong> defines the 199 demand areas with their indexes. It classifies the demand areas by prefectures and provinces of the Fez-Meknes region. <strong>Table 2</strong> gives the geographical coordinates (X, Y) of the 199 demand areas. This data is essential to determine the location of demand areas. <strong>Table 3</strong> provides the population size in each of the 199 demand areas. This information is vital for calculating demand values and arrival rates in each demand area. <strong>Table 4</strong> presents the demand value in each of the 199 demand areas by type of ambulance and time period. <strong>Table 5</strong> displays the arrival rates for demands requesting ALS ambulances and BLS ambulances by demand area and time period. <strong>Table 6</strong> shows the service time in each demand area. It is the sum of the time the ambulance spends going from its base to the demand area, the time for the on-site care, transporting the patient to a hospital, and returning the ambulance to its base. <strong>Table 7</strong> defines the potential ambulance base sites with their indexes. The table considers three cases: Case 1 defines 18 potential sites that are the current Civil Protection bases in the Fez-Meknes region; Case 2 defines 22 sites corresponding to the 18 sites in Case 1 and 4 hospitals; Case 3 defines 40 potential sites corresponding to the 22 sites in Case 2 and 18 sites that are urban communes. <strong>Table 8</strong> presents scenarios for the number of ambulances to be deployed. It gives increasing numbers of ambulances to evaluate the behavior and performance of the optimization models. <strong>Table 9</strong> provides the travel times between the 18 potential sites of ambulance bases corresponding to Case 1 and the 199 demand areas. <strong>Table 10</strong> displays the travel times between the 22 potential sites of ambulance bases corresponding to Case 2 and the 199 demand areas. <strong>Table 11</strong> gives the travel times between the 40 potential sites of ambulance bases corresponding to Case 3 and the 199 demand areas. <strong>Table 12</strong> shows the travel time between the 18 potential sites of ambulance bases. It is the travel time between each potential site and the other potential sites. <strong>Table 13</strong> indicates the travel time between the 22 potential sites of ambulance bases. It is the travel time between each potential site and the other potential sites. <strong>Table 14</strong> contains the travel time between the 40 potential sites of ambulance bases. It is the travel time between each potential site and the other potential sites. <strong>Table 15</strong> gives the values of the minimum number <em>b</em> of ambulances that must cover a demand area for α-reliability coverage. The table gives the values of the number b for <em>α</em> = 90%. In other words, for the probability that a demand area can find an available ambulance to be greater than 0.9, the demand area must be covered by at least <em>b</em> ambulances. <strong>Table 16</strong> reports the values of the minimum number <em>b</em> of ambulances that must cover a demand area for variable α-reliability coverage. The table considers different values of the reliability α ranging from 1% to 90%. For each value of <em>α,</em> the table gives the minimum number of ambulances that must cover a demand area to be considered as covered with reliability <em>α</em>.