Mostrar el registro sencillo del ítem

dc.contributor.author
Ma, Jing  
dc.contributor.author
Valdez, Lucas Daniel  
dc.contributor.author
Braunstein, Lidia Adriana  
dc.date.available
2022-12-26T11:27:15Z  
dc.date.issued
2020-09  
dc.identifier.citation
Ma, Jing; Valdez, Lucas Daniel; Braunstein, Lidia Adriana; Role of bridge nodes in epidemic spreading: Different regimes and crossovers; American Physical Society; Physical Review E: Statistical, Nonlinear and Soft Matter Physics; 102; 3; 9-2020; 1-11  
dc.identifier.issn
2470-0045  
dc.identifier.uri
http://hdl.handle.net/11336/182285  
dc.description.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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Physical Society  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
MODULAR NETWORKS  
dc.subject
PERCOLATION  
dc.subject
CRITICAL EXPONENTS  
dc.subject.classification
Otras Ciencias Físicas  
dc.subject.classification
Ciencias Físicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Role of bridge nodes in epidemic spreading: Different regimes and crossovers  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-09-06T18:19:05Z  
dc.identifier.eissn
2470-0053  
dc.journal.volume
102  
dc.journal.number
3  
dc.journal.pagination
1-11  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Maryland  
dc.description.fil
Fil: Ma, Jing. Boston University; Estados Unidos  
dc.description.fil
Fil: Valdez, Lucas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina. Boston University; Estados Unidos  
dc.description.fil
Fil: Braunstein, Lidia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina. Universidad Nacional de Mar del Plata; Argentina  
dc.journal.title
Physical Review E: Statistical, Nonlinear and Soft Matter Physics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.032308  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1103/PhysRevE.102.032308