Analyzing techniques used to detect disjoint community in epidemics

The infectious diseases are common now days. We catch these infections easily because of unbalanced diets that human being takes. Once person catches infectionthere are several ways by which that infection is spread to multiple persons. When infection is considered then there must be some infection agent and population. The infection agent will be responsible for passing the infection to the population. The infection separations will also depend upon the immune system of the human within the population. In the proposed paper we will study the rate at which the recovery of the human from the infection takes place and also the rate at which infection spread.If the rate of infection spreading is higher than whole of the population will be infected. So the proposed paper studies the rate at which recovery must happen so that population can recover from the infection. This paper present the comparison among various techniques used to detect the disjoint communities in epidemic networks.