  This article presents a new model to predict the evolution of infective
diseases under uncertainty or low-quality information, just as it has happened
in the initial scenario during the CoVid-19 spread in China and Europe. The
model has been used to predict the death rate in Spain but can be used to
predict the demand of ICUs or mechanical ventilators under different restraint
policies. The main novelty of the model is that it keeps track of the date of
infection of a single individual and uses stochastic distributions to aggregate
individuals who share the same date of infection. In addition, it uses two
types of infections, mild and serious, with a different recovery time. These
features are implemented in a set of differential equations which determine the
number of Carriers, Infections, Recoveries, Hospitalized and Deaths. Comparison
with real data shows good agreement.
