PubMed · 14133222
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
V GOERISCH. 1964-01-01. [TOXICOLOGIC INFORMATION SERVICE].. https://pubmed.ncbi.nlm.nih.gov/14133222/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.
Explore the source record for details and available documents.
Explore the source record for details and available documents.