Abstract

Modeling the propagation rate of diseases in a society via social interaction has continued to pose its many challenges. The recent spread of the covid-19 epidemic cannot be left out. Thus, social interactions heralds its many benefits and has becomes a vehicle for epidemic outbreaks –which has continually left the world puzzled as the disease itself has come to stay. The nature of its rapid propagation on exposure alongside its migration spread pattern of this contagion (with retrospect of other epidemics) on daily basis, has also left experts rethinking the set protocols. Our study models the spread propagation of the corona-virus contagion using the movement-interaction-return on a social graph. Thus, weseek to measure if the corona-virus (covid-19)spread propagation can be minimized alongside its death rate using movement pattern as a threshold feature and set of protocols. We design a Markovian block model to help minimize targeted propagation with the advent of seed-node(s) using the susceptible-infect structure on a time-varying graph. Study results showed that movement pattern must be employed as an imperative factors when modeling the propagation of contagion(s).

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