TITLE:
Analysis of SDEs Applied to SEIR Epidemic Models by Extended Kalman Filter Method
AUTHORS:
D. Ndanguza, I. S. Mbalawata, J. P. Nsabimana
KEYWORDS:
Epidemic Model, Estimation of Parameters, Extended Kalman Filter, Markov Chain Monte Carlo
JOURNAL NAME:
Applied Mathematics,
Vol.7 No.17,
November
23,
2016
ABSTRACT: A disease transmission model of SEIR type
is discussed in a stochastic point of view. We start by formulating the SEIR
epidemic model in form of a system of nonlinear differential equations and then
change it to a system of nonlinear stochastic differential equations (SDEs).
The numerical simulation of the resulting SDEs is done by Euler-Maruyama scheme
and the parameters are estimated by adaptive Markov chain Monte Carlo and
extended Kalman filter methods. The stochastic results are discussed and it is
observed that with the SDE type of modeling, the parameters are also
identifiable.