  It is often necessary to introduce the main characteristics of population
mobility dynamics to model critical social phenomena such as the economy,
violence, transmission of information, or infectious diseases. In this work, we
focus on modeling and inferring urban population mobility using the geospatial
data of its inhabitants. The objective is to estimate mobility and times
inhabitants spend in the areas of interest, such as zip codes and census
geographical areas. The proposed method uses the Brownian bridge model for
animal movement in ecology. We illustrate its possible applications using
mobile phone GPS data in 2020 from the city of Hermosillo, Sonora, in Mexico.
We incorporate the estimated residence-mobility matrix into a multi-patch
compartmental SEIR model to assess the effect of mobility changes due to
governmental interventions
