Voting Rule Based Cellular Automata Epidemic Spread Model for Leptospirosis

This paper is focused on a cellular automata based computational model for the spread of disease named Leptospirosis using voting rules. Leptospirosis is most commonly found in bovine rats and the humans get infected when they come into contact with them. The disease spread is modelled in terms of Susceptible-Infective-Recovered-Susceptible (SIRS) model through one of the efficient computational modeling tool-Cellular Automata (CA); and requires strategic change in the rule set of the traditional CA. An idea of voting based rule on the neighborhood environment is studied for modeling the Leptospirosis and compared with real data of such infection in Thailand during the year 2000 and 2001. The simulation of the model is done with real data of Leptospirosis infection in Thailand during 2000 and 2001 and the results yielded from this model were closely in match with the real time data.