The fastest spreader in SIS epidemics on networks

The fastest spreader in SIS epidemics on networks

Identifying the fastest spreaders in epidemics on a network helps to ensure an efficient spreading. By ranking the average spreading time for different spreaders, we show that the fastest spreader may change with the effective infection rate of a SIS epidemic process, which means that the time-dependent influence of a node is usually strongly coupled to the dynamic process and the underlying ne...

The spreading time in SIS epidemics on networks

In a Susceptible–Infected–Susceptible (SIS) process, we investigate the spreading time Tm, which is the time when the number of infected nodes in the metastable state is first reached, starting from the outbreak of the epidemics. We observe that the spreading time Tm resembles a lognormal-like distribution, though with different deep tails, both for the Markovian and the non-Markovian infection...

Learning to Suppress SIS Epidemics in Networks

In this paper, we introduce the class of priority planning strategies for suppressing SIS epidemics taking place in a network. This is performed via dynamic allocation of treatment resources with limited efficiency to the infected nodes, according to a precomputed priority-order. Using recent theoretical results that highlight the role of the maxcut of a node ordering and the extinction time of...

Resilience of epidemics for SIS model on networks.

Epidemic propagation on complex networks has been widely investigated, mostly with invariant parameters. However, the process of epidemic propagation is not always constant. Epidemics can be affected by various perturbations and may bounce back to its original state, which is considered resilient. Here, we study the resilience of epidemics on networks, by introducing a different infection rate ...

in stochastic SIS epidemics