Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 720304, 13 pages
Research Article

System Identification and Prediction of Dengue Fever Incidence in Rio de Janeiro

1Escola de Engenharia, Universidade Presbiteriana Mackenzie, Rua da Consolação 896, 01302-907 São Paulo, SP, Brazil
2Departamento de Engenharia de Telecomunicações e Controle, Escola Politécnica, Universidade de São Paulo, Avenida Professor Luciano Gualberto, Travessa 3 380, 05508-900 São Paulo, SP, Brazil

Received 10 December 2010; Revised 17 April 2011; Accepted 15 May 2011

Academic Editor: J. Jiang

Copyright © 2011 D. O. Gerardi and L. H. A. Monteiro. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition 𝑆 𝐼 able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and nont-ime-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.