Simulation of Swine and Avian Influenza Viruses Recombination Based on Genetic Algorithm

Abstract

This paper describes analysis, design and development of simulation software for Swine (H1N1) and Avian Influenza (H5N1) viruses recombination process. Influenza Pandemics have occurred several times, caused by mutation and recombination of Influenza viruses. Recombination is a sudden change of viruses enabling two different Influenza virus strains combined to become a new virus subtype. The H1N1 recombination has caused Spanish Flu Pandemic in 1918, and the recombination of swine virus, human virus and bird virus has caused Swine Flu Pandemic started in Mexico during April 2009. The main concern raised by WHO is the possibility of recombination between Swine Flu (H1N1), Avian Flu (H5N1) and Human Flu Virus (H3N2) which could trigger Swine Flu becomes more contagious, and have a higher CFR (Case Fatality Rate) causing more people to die. This research's purpose is to define modeling for virus recombination causing Influenza Pandemic phenomena. This research defines several different virus variants which can potentially trigger the Influenza Pandemic. Additionally, this simulation objective is to obtain most possible virus strains formed from the recombination, the scope within this article, which can potentially trigger Influenza Pandemic. New strains could be utilized to support the vaccine planning process. This simulation program was developed based on Genetic Algorithm method, for solving this multi-objective optimization problem. By utilizing Genetic Algorithm approach, the chromosome solution and fitness values/functions of Influenza Pandemic stages are defined and the maximum fitness values are to be searched. The simulation result of H1N1 and H5N1 recombination gave 2 best fitness values as static result and dynamic mean fitness values. Better and more fitness values could be obtained once the database of recombination and mutation virus strains is enhanced.