TY - JOUR

T1 - On analytical approaches to epidemics on networks

AU - Trapman, J.P.

N1 - Trap07a

PY - 2007

Y1 - 2007

N2 - One way to describe the spread of an infection on a network is by approximating the network by a random graph. However, the usual way of constructing a random graph does not give any control over the number of triangles in the graph, while these triangles will naturally arise in many networks (e.g. in social networks). In this paper, random graphs with a given degree distribution and a given expected number of triangles are constructed. By using these random graphs we analyze the spread of two types of infection on a network: infections with a fixed infectious period and infections for which an infective individual will infect all of its susceptible neighbors or none. These two types of infection can be used to give upper and lower bounds for R

AB - One way to describe the spread of an infection on a network is by approximating the network by a random graph. However, the usual way of constructing a random graph does not give any control over the number of triangles in the graph, while these triangles will naturally arise in many networks (e.g. in social networks). In this paper, random graphs with a given degree distribution and a given expected number of triangles are constructed. By using these random graphs we analyze the spread of two types of infection on a network: infections with a fixed infectious period and infections for which an infective individual will infect all of its susceptible neighbors or none. These two types of infection can be used to give upper and lower bounds for R

U2 - 10.1016/j.tpb.2006.11.002

DO - 10.1016/j.tpb.2006.11.002

M3 - Article

VL - 71

JO - Theoretical Population Biology

JF - Theoretical Population Biology

SN - 0040-5809

IS - 2

ER -