The system of equations given by Eqs. ͑20a͒ and ͑21c͒ is an exact transformation of the system of equations given by Eqs. ͑1a͒-͑1c͒. We numerically integrate the original stochastic system of the SEIR model ͓Eqs. ͑1a͒-͑1c͔͒ along with the transformed stochastic system ͓Eqs. ͑20a͒-͑20c͔͒ using a stochastic fourth-order Runge-Kutta scheme with a constant time step size. The original system is solved for S, E, and I, while the transformed system is solved for U, V, and W. In the latter case, once the values of U, V, and W are known, we compute the values of S, Ē , and Ī using the transformation given by Eqs. ͑7a͒-͑7c͒. We shift S, Ē , and Ī, respectively, by S 0 , E 0 , and I 0 to find the values of S, E, and I. Figure 2 compares the time series of the fraction of the population that is infected with a disease I, computed using the original stochastic system of equations of the SEIR model with the time series of I computed using the transformed stochastic system of equations of the SEIR model. Although the two time series shown in Fig. 2 generally agree very well, there is some discrepancy. This discrepancy is due to the fact that the noise processes 4 4 , 5 5 , and