An exact relationship between invasion probability and endemic prevalence for Markovian SIS dynamics on networks.

ABSTRACT: Understanding models which represent the invasion of network-based systems by infectious agents can give important insights into many real-world situations, including the prevention and control of infectious diseases and computer viruses. Here we consider Markovian susceptible-infectious-susceptible (SIS) dynamics on finite strongly connected networks, applicable to several sexually transmitted diseases and computer viruses. In this context, a theoretical definition of endemic prevalence is easily obtained via the quasi-stationary distribution (QSD). By representing the model as a percolation process and utilising the property of duality, we also provide a theoretical definition of invasion probability. We then show that, for undirected networks, the probability of invasion from any given

SUBMITTER: Wilkinson RR 

PROVIDER: S-EPMC3728314 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature