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Fig. 18.1. In an adaptive network the evolution of the topology depends on the dynamics of the
nodes. Thus a feedback loop is created in which a dynamical exchange of information is possible.
Figure reprinted from Gross and Blasius (2008).
this \epidemic of epidemics" (Karlen, 1995). Today the world's population density
is higher than ever, which means that epidemics can spread at a higher rate. We
also change our environment faster than ever, which promotes epidemics on many
scales: Global change drives host populations of pathogens into more densely pop-
ulated areas; New farming methods and transport of livestock entail an increased
probability of the transmission of animal diseases to humans (zoonoses); Finally,
articial environments, such as air-conditioning systems and cooling towers provide
new ecological niches in which pathogens (in this example Legionella) can survive.
As we will see below another reason for the emergence and reemergence of dis-
eases lies in the nature of human contact networks. Since neither ecological change,
population growth, or the contact networks are likely to change signicantly over
the next decades, more ecient methods to combat epidemics have to be found. In
this context networks appear on two levels. On the molecular level, the study of
gene regulatory, metabolic or signaling networks can lead to the development of new
medicines and pesticides that target pathogens and disease vectors. On the popula-
tion level the study of contact networks can lead to new insights into the spreading
of epidemics across social networks and to the improvement of vaccination schemes.
In the present chapter I focus on this latter level.
One idea that has recently attracted considerable attention is to use insights
from network research to optimize vaccination campaigns. Previous research has
shown that the amount of vaccine that is necessary to stop an epidemic can be
signicantly reduced by targeted vaccination (Albert et al., 2000; Holme, 2004).
However, the success of targeted vaccination schemes depends strongly on certain
network properties. Currently, attempts are made to measure these properties in
