Self-isolation vs frontiers closing: What prevents better of epidemic spread?

Valba, O.; Avetisov, V.; Gorsky, A.; Nechaev, S.

We discuss combined effects of network clustering and adaptivity on epidemic spread. We address the question which mechanism is more effective for prohibiting disease propagation in a connected network: adaptive clustering, which mimics self-isolation (SI) in local communities, or sharp instant clustering, which looks like frontiers closing (FC) between cities and countries? Since in reality cross-community connections always survive, we can wonder how efficient is the excitation (illness) propagation through the entire clustered network which has some density of inter-cluster connections. Crucial difference between SI- and FC-networks is as follows: SI-networks are"adaptively grown"under condition of maximization of small cliques in the entire network, while FC-networks are"instantly created"by \emph{ad hoc} imposed borders. We found that SI model has scale-free property for degree distribution $P(k)\sim k^{\eta}$ with surprisingly small critical exponent $-2<\eta<-1$. Running the standard SIR model on clustered SI- and FC-networks, we demonstrate that the adaptive network clustering caused by self-isolation in communities prohibits the epidemic spread better than the clustering due to instant boundaries closing.