Childbirth Mobilities: A Geo-Spatial Simulation Approach

While the literature has identified some predictors to childbirth hospital selection such as distance to facilities, ranking of hospitals and word-of-mouth, there is a lack of knowledge on how they interact. This contribution aims at filling this gap leveraging agent-based modeling as a method of collective artificial intelligence, modeling the decisional process of expectant women and social influence mechanisms. We initialize our model with a synthetic population extracted from integrated geo-data from the Tuscany region in Italy. We identify what combination of distance to hospital, opinion ranking and modes of social influence can replicate data and to what extent.