A study of the infectious disease with incubation period model based on cellular automata
Abstract
Considering the two measures of vaccination to susceptible population and isolation treatment to infectious population, this study builds a SEIQR -V infectious disease model with incubation period, which is based on the principle of cellular automata. According to the random walking principle, it gets an expanded Moore neighbor. For influenza A (H1N1), BP neural network is used to recognize the quarantine intensity parameters of some countries. Furthermore, according to Cellular Automata’s simulation to the number of infections under the different vaccination proportion, the article studies the factors about spreading regularity of infectious diseases. Simultaneously, for different countries, the study proposes a better control strategy suited to the country’s vaccination.
- Published
- 4 December 2015
- Volume
- 2015 (2015)
- License
- CC BY 3.0
Copyright © 2015 Jiatai Gang, Sisi Liu, Shujuan Li, Zhiwei Zhao. 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.
Cite this article
J. Gang, S. Liu, S. Li, Z. Zhao, A study of the infectious disease with incubation period model based on cellular automata, Commun. Math. Biol. Neurosci. 2015 (2015), 35.
BibTeX
@article{Gang2015,
author = {Gang, Jiatai and Liu, Sisi and Li, Shujuan and Zhao, Zhiwei},
title = {A study of the infectious disease with incubation period model based on cellular automata},
journal = {Commun. Math. Biol. Neurosci.},
volume = {2015},
year = {2015},
pages = {35},
doi = {}
}