IJPAM: Volume 52, No. 2 (2009)


W. Jumpen$^1$, B. Wiwatanapataphee$^2$, Y.H. Wu$^3$, I.M. Tang$^4$
$^{1,2}$Department of Mathematics
Faculty of Science
Mahidol University
Bangkok, 10400, THAILAND
$^2$e-mail: [email protected]
$^3$Department of Mathematics and Statistics
Curtin University of Technology
Perth, WA6845, AUSTRALIA
e-mail: [email protected]
$^4$Department of Physics
Faculty of Science
Mahidol University
Bangkok, 10400, THAILAND
e-mail: [email protected]

Abstract.In this paper, we first propose a pandemic influenza susceptib-le-exposed-infected-quarantined-recovered ($SEIQR$) model and analyze the model properties. We then introduce a differential evolution (DE) algorithm for determining the numerical values of the parameters in the model. For a given set of measured data, e.g. from the first outbreak, all the values of the model parameters can be determined by the algorithm. We have also shown from numerical simulations that the DE algorithm yields the same parameter values for different sets of initial guesses. With the values of the parameters determined, the model can then be used to capture the behavior of the next outbreaks of the disease. The work provides an effective tool for predicting the spread of the disease.

Received: March 10, 2009

AMS Subject Classification: 03C98

Key Words and Phrases: $SEIQR$ model, influenza pandemic, stability, differential evolution algorithm

Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2009
Volume: 52
Issue: 2