  Traditional epidemic models consider that individual processes occur at
constant rates. That is, an infected individual has a constant probability per
unit time of recovering from infection after contagion. This assumption
certainly fails for almost all infectious diseases, in which the infection time
usually follows a probability distribution more or less spread around a mean
value. We show a general treatment for an SIRS model in which both the infected
and the immune phases admit such a description. The general behavior of the
system shows transitions between endemic and oscillating situations that could
be relevant in many real scenarios. The interaction with the other main source
of oscillations, seasonality, is also discussed.
