The impact of network clustering and assortativity on epidemic behaviour.
Epidemic models have successfully included many aspects of the complex contact structure apparent in real-world populations. However, it is difficult to accommodate variations in the number of contacts, clustering coefficient and assortativity. Investigations of the relationship between these properties and epidemic behaviour have led to inconsistent conclusions and have not accounted for their interrelationship. In this study, simulation is used to estimate the impact of social network structure on the probability of an SIR (susceptible-infective-removed) epidemic occurring and, if it does, the final size. Increases in assortativity and clustering coefficient are associated with smaller epidemics and the impact is cumulative. Derived values of the basic reproduction ratio (R(0)) over networks with the highest property values are more than 20% lower than those derived from simulations with zero values of these network properties.
Badham
Jennifer
J
School of Engineering and Information Technology, Australian Defence Force Academy, Northcott Drive, Canberra 2600, Australia. research@criticalconnections.com.au
Stocker
Rob
R
D000465:Algorithms; D001315:Australia; D050936:Basic Reproduction Number / Q000706:statistics & numerical data*; D016000:Cluster Analysis; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data; D014943:Global Health; D006801:Humans; D017053:Infection Control / Q000379:methods / Q000706:statistics & numerical data; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control; D008390:Markov Chains; D008954:Models, Biological; D015233:Models, Statistical; D012944:Social Support