We have considered the dynamics of a SEIR epidemiological model with stochastic forcing in the form of additive Gaussian noise. We have presented two methods of model reduction, whereby the goal is to project both the noise and the dynamics onto the stochastic center manifold. The first method uses the deterministic center manifold found by neglecting the stochastic terms in the governing equations, while the second method uses a stochastic normal form coordinate transform.