  As the understanding of the importance of social contact networks in the
spread of infectious diseases has increased, so has the interest in
understanding the feedback process of the disease altering the social network.
While many studies have explored the influence of individual epidemiological
parameters and/or underlying network topologies on the resulting disease
dynamics, we here provide a systematic overview of the interactions between
these two influences on population-level disease outcomes. We show that the
sensitivity of the population-level disease outcomes to the combination of
epidemiological parameters that describe the disease are critically dependent
on the topological structure of the population's contact network. We introduce
a new metric for assessing disease-driven structural damage to a network as a
population-level outcome. Lastly, we discuss how the expected individual-level
disease burden is influenced by the complete suite of epidemiological
characteristics for the circulating disease and the ongoing process of network
compromise. Our results have broad implications for prediction and mitigation
of outbreaks in both natural and human populations.
