In addition, we had to pre-process all the data needed to feed the system (see processes P1 to P4 of the conceptual architecture in Figure 11 , section 4.1). We estimated the initial populations of Culex and crows at the beginning of the simulation. For the population of crows, we used the SAS statistical software and the MapInfo GIS to compute a specific density of birds per region (number of individuals by square kilometer). This done by estimating an average of the sighting mentions provided by professional or amateur ornithologists (from 1997 to 2005 and located inside the ecumene) using the ÉPOQ database [24] (Table 2) . We also processed the data relative to crows' roosts (obtained through an email survey involving expert birders or extracted from the ÉPOQ database [24] ). This data included the co-ordinates (latitude/longitude) as well as an approximate number of individuals for each mentioned roost. We computed an average of the number of individuals in the case of several records of the same roost (same latitude and same longitude). This data is used to characterise the roost agents (Table 3) . Moreover, we studied the literature and discussed with domain experts in order to collect relevant information about crows' behaviours. We used this information in order to specify some behavioural rules for the roost agent such as the way that particles spread around the roost to simulate the birds' daily search for food.