  In this work, we analyze and model the cholera epidemics that affected South
Sudan, the newest country in the world, during 2014 and 2015. South Sudan
possibly represents one of the most difficult context in which adapt the
deterministic mathematical cholera model, due to the unstable social and
political situation that clearly affects the fluxes of people and the sanitary
conditions, increasing the risk of large outbreaks. Despite the limitation of a
static gravity model in describing the chaotic human mobility of South Sudan,
the SIRB model, calibrated with a data assimilation technique (Ensemble Kalman
Filter), retrieves the epidemic dynamics in the counties with the largest
number of infected cases, showing the potentiality of the methodology in
forecasting future outbreaks.
