Abstract
In the last decade, a large number of papers was devoted to studying probabilistic properties of epidemic models on graphs. In this paper we consider a generalization of the model proposed by Machado, Mashurian, and Matzinger. The Machado--Mashurian--Matzinger model serves as an interpretation of spread of viruses in a computer network. We assume that at each moment of time more than one node of the network can be infected. In this context we propose a more advanced model permitting jumps of several particles each time, while the number of such particles is random. We prove the optimal version of the law of large numbers for the number of infected particles in the epidemic model at hand.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
