About: The role of bridge nodes in epidemic spreading: different regimes and crossovers

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The role of bridge nodes in epidemic spreading: different regimes and crossovers
Creator	Ma, Jing Braunstein, Lidia Valdez, Lucas
Source	ArXiv
abstract	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.
has issue date	2020-05-28(xsd:dateTime)
has license	arxiv
sha1sum (hex)	20b0f72c1a2036ff097b62cb8d1f81b6f0935b8a
resource representing a document's title	The role of bridge nodes in epidemic spreading: different regimes and crossovers
resource representing a document's body	covid:20b0f72c1a2036ff097b62cb8d1f81b6f0935b8a#body_text
is schema:about of	named entity 'EXPLAINED' named entity 'FOLLOWS' named entity 'COMPONENT' named entity 'PEOPLE' named entity 'VALUE' named entity 'FINAL' named entity 'HOW' named entity 'ENABLE' named entity 'BRIDGE' named entity 'TOTAL' named entity 'COMMUNITIES' named entity 'DISEASE' named entity 'FINITE' named entity 'INFECTED' named entity 'BEHAVIORS' named entity 'epidemic' named entity 'power-law' named entity 'transmissibility' named entity 'giant component' named entity 'epidemic' named entity 'physical quantities' named entity 'T b' named entity 'generating functions' named entity 'susceptible individual' named entity 'degree distribution' named entity 'epidemic' named entity 'percolation' named entity 'T b' named entity 'order parameter' named entity 'complex networks' named entity 'percolation' named entity '1/2' named entity 'probability 1' named entity 'degree distribution' named entity 'SIR model' named entity '0.01' named entity 'probability' named entity 'dashed' named entity 'power laws' named entity 'infection' named entity 'branching factor' named entity '1/2' named entity 'probability' named entity 'SIR model' named entity 'epidemic' named entity 'SIR model' named entity 'degree distribution' named entity 'thermodynamic limit' named entity 'percolation' named entity 'dashed' named entity 'infection' named entity 'epidemic' named entity 'consistent equations' named entity 'topology' named entity 'SIR model' named entity 'probability' named entity 'probability' named entity 'epidemic' named entity 'asymptotic behavior' named entity 'power laws' named entity 'percolation' named entity 'percolation' named entity 'giant component' named entity 'Jacobian matrix' named entity 'probability' named entity 'power law' named entity 'probability' named entity 'epidemic' named entity 'probability' named entity 'power law' named entity 'COVID-19' named entity 'power-law' named entity 'T b' named entity 'macroscopic' named entity 'generating function' named entity 'network theory' named entity 'generating function' named entity 'T b' named entity 'probability' named entity 'epidemic' named entity 'percolation' named entity 'probability' named entity 'percolation' named entity 'epidemic' named entity 'transportation network'

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