Epidemic Spread Modeling with Time Variant Infective Population Using Pushdown Cellular Automata. (11th November 2014)

• Record Type: Journal Article
• Authors: Athithan, Senthil; Shukla, Vidya Prasad; Biradar, Sangappa Ramachandra
• Other Names: Liu Wen-Cheng Academic Editor.
• Is Part Of: Journal of computational environmental sciences. Volume 2014(2014)
• Publication Date: 2014-11-11
• Subjects: Environmental sciences -- Data processing -- Periodicals; Environmental sciences -- Data processing; Periodicals; 333.70285
• DOI: 10.1155/2014/769064
• Languages: English
• ISSNs: 2356-7279

Abstract

Abstract : The world without a disease is a dream of any human being. The disease spread if not controlled could cause an epidemic situation to spread and lead to pandemic. To control an epidemic we need to understand the nature of its spread and the epidemic spread model helps us in achieving this. Here we propose an epidemic spread model which considers not only the current infective population around the population but also the infective population which remain from the previous generations for computing the next generation infected individuals. A pushdown cellular automata model which is an enhanced version of cellular automata by adding a stack component is being used to model the epidemic spread and the model is validated by the real time data of H1N1 epidemic in Abu Dhabi.