Network Effects in Epidemiology

Preparing for the spread of infectious diseases is an important government function. The great influenza pandemic of 1918 killed about 100 million people, and in more recent times, SARS and avian influenza have affected several countries. Agent-based models can be used to predict the spread of new diseases within a population. However, the behaviour of such models is dependent on the topology of contacts between people. In this paper, we use rewiring and simulation techniques to investigate the spread of disease through a network, and highlight the network attributes which influence the spread of disease. We pay particular attention to three key disease characteristics: the peak number of infected individuals, the time to reach this peak infection, and the total number of individuals affected by the disease. Analysis of the results leads to a concept of “effective degree” for a network, which depends on the number of links in the network as well as the network “shape.” The three key characteristics are all strongly influenced by the effective degree.