Bifurcation, stability, and cluster formation of multi-strain infection models.
Clustering behaviours have been found in numerous multi-strain transmission models. Numerical solutions of these models have shown that steady-states, periodic, or even chaotic motions can be self-organized into clusters. Such clustering behaviours are not a priori expected. It has been proposed that the cross-protection from multiple strains of pathogens is responsible for the clustering phenomenon. In this paper, we show that the steady-state clusterings in existing models can be analytically predicted. The clusterings occur via semi-simple double zero bifurcation from the quotient networks of the models and the patterns which follow can be predicted through the stability analysis of the bifurcation. We calculate the stability criteria for the clustering patterns and show that some patterns are inherently unstable. Finally, the biological implications of these results are discussed.
Department of Applied Mathematics, The University of Western Ontario, London, ON, N6A 5B7, Canada, chan.bernard@gmail.com.
Bernard S
BS
Chan
Pei
P
Yu
D016000:Cluster Analysis; D003141:Communicable Diseases / Q000276:immunology* / Q000635:transmission; D018448:Models, Immunological