There are two main methods for pandemic simulations:
the SEIR model and the MAS model. The SEIR model can deal with
simulations quickly for many homogeneous populations with simple
ordinary differential equations; however, the model cannot accommodate
many detailed conditions.
The MAS model, the multiagent simulation, can deal with detailed
simulations under the many kinds of initial and boundary conditions
with simple social network models. However, the computing cost
will grow exponentially as the population size becomes larger.
Thus, simulations in the largescale model would hardly be realized
unless supercomputers are available. By combining these two methods,
we may perform the pandemic simulations in the largescale model
with lower costs. That is, the MAS model is used in the early stage
of a pandemic simulation to determine the appropriate parameters
to be used in the SEIR model. With these obtained parameters, the
SEIR model may then be used. To investigate the validity of this
combined method, we first compare the simulation results between
the SEIR model and the MAS model. Simulation results of the MAS
model and the SEIR model that uses the parameters obtained by the
MAS model simulation are found to be close to each other.
