Epidemic model with isolation in multilayer networks

• Autores: Alvarez Zuzek, Lucila Gisele; Stanley, H. E.; Braunstein, L. A.
• Año de publicación: 2015
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Complex Netorks; Multilayer Networks; Epidemic Models; Percolation
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

The Susceptible-Infected-Recovered ($SIR$) model has successfully mimicked the propagation of such airborne diseases as influenza A (H1N1). Although the $SIR$ model has recently been studied in a multilayer networks configuration, in almost all the research the isolation of infected individuals is disregarded. Hence we focus our study in an epidemic model in a two-layer network, and we use an isolation parameter $w$ to measure the effect of quarantining infected individuals from both layers during an isolation period $t_w$. We call this process the Susceptible-Infected-Isolated-Recovered ($SI_IR$) model. Using the framework of link percolation we find that isolation reduces the critical epidemic threshold of the disease because} the time in which infection can spread is reduced. In this scenario we find that this threshold increases with w and t_w. When the isolation period is maximum there is a critical threshold for $w$ above which the disease never becomes an epidemic. We also find that epidemic models, like $SIR$ overestimate the critical epidemic threshold. We simulate the process and found an excellent agreement with the theoretical results.
Fil: Alvarez Zuzek, Lucila Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata; Argentina
Fil: Stanley, H. E.. Boston University; Estados Unidos
Fil: Braunstein, L. A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata; Argentina. Boston University; Estados Unidos