This dissertation is related to mathematical modelling of the spread of respiratory syncytial virus (RSV) in Valencia and is still causing a large number of hospitalizations of children in this community.
A mathematical model based on a system of nonlinear differential equations of first order has been built. This model considers the population divided into two age groups to pay particular attention to children under one year who are the most affected by this disease.
This model has been fitted with hospitalizations data of Valencia and has been used to perform a cost analysis of a potential vaccination strategy.
We also propose a complete network model to study the seasonal evolution of RSV epidemics in which seasonal parameters were fitted with the previous continuous model. Both developments are contrasted.
On the complete network model we propose a strategy for vaccination of children based on the administration of three doses, and develop a cost-effectiveness study for different vaccination rates.
Finally we have defined a SIRS model for RSV epidemics on a random social network of contacts among individuals. In this model has not forced the seasonality. The seasonality arises naturally for certain values of the duration of immunity of a patient recovered, the number of contacts and the likelihood of infection from a contact in a day. In this social network model only a narrow range of parameters can support RSV epidemic seasons.