Power-law behaviors are common in many disciplines, especially in network science. Real-world networks, like disease spreading among people, are more likely to be interconnected communities, and show richer power-law behaviors than isolated networks. In this paper, we look at the system of two communities which are connected by bridge links between a fraction r of bridge nodes, and study the effect of bridge nodes to the final state of the Susceptible-Infected-Recovered model by mapping it to link percolation. By keeping a fixed average connectivity, but allowing different transmissibilities along internal and bridge links, we theoretically derive different power-law asymptotic behaviors of the total fraction of the recovered R in the final state as r goes to zero, for different combinations of internal and bridge link transmissibilities. We also find crossover points where R follows different power-law behaviors with r on both sides when the internal transmissibility is below but close to its critical value for different bridge link transmissibilities. All of these power-law behaviors can be explained through different mechanisms of how finite clusters in each community are connected into the giant component of the whole system, and enable us to pick effective epidemic strategies and to better predict their impacts.

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network science susceptibleinfectedrecovered model r internal transmissibility giant component of the whole system bridge nodes impacts link percolation powerlaw asymptotic disease finite clusters average epidemic

Ma, Jing, Valdez, Lucas D., Braunstein, Lidia A.,.Role of bridge nodes in epidemic spreading: Different regimes and crossovers. 102 (3),.

Ma, Jing, Valdez, Lucas D., Braunstein, Lidia A.,"Role of bridge nodes in epidemic spreading: Different regimes and crossovers" 102

Ma, Jing, Valdez, Lucas D., Braunstein, Lidia A.,"Role of bridge nodes in epidemic spreading: Different regimes and crossovers"