Epidemics is very important area of concern for most our living being family in the world. Any epidemic situation when properly not controlled could lead to a disaster when large amount of human population is involved. Here we propose a fundamental model of computation in terms of non-deterministic finite automata (NFA) for the Susceptible-Infectives-Recovered (SIR) model. Through this model we could prove there could be certain languages which are epidemic regular since it could be compared with the normal regular languages for which we can have NFA or regular grammar. If we could classify how the epidemic model could behave then we could better develop strategies that could tackle a similar epidemic situation in future. This model has been tested with the data of H1N1 obtained from CDC USA.
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