TY - JOUR
T1 - Dangerous connections
T2 - on binding site models of infectious disease dynamics
AU - Leung, Ka Yin
AU - Diekmann, Odo
PY - 2017
Y1 - 2017
N2 - We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the ‘outside world’ on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of ‘binding sites’ for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as (Formula presented.), r, the final size, and the endemic equilibrium, in terms of the corresponding variables.
AB - We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the ‘outside world’ on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of ‘binding sites’ for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as (Formula presented.), r, the final size, and the endemic equilibrium, in terms of the corresponding variables.
KW - Binding site models
KW - Configuration model
KW - Dynamic networks
KW - Infectious disease dynamics
UR - http://www.scopus.com/inward/record.url?scp=84975303668&partnerID=8YFLogxK
U2 - 10.1007/s00285-016-1037-x
DO - 10.1007/s00285-016-1037-x
M3 - Article
AN - SCOPUS:84975303668
SN - 0303-6812
VL - 74
SP - 619
EP - 671
JO - Journal of Mathematical Biology
JF - Journal of Mathematical Biology
ER -