  One of the famous results of network science states that networks with
heterogeneous connectivity are more susceptible to epidemic spreading than
their more homogeneous counterparts. In particular, in networks of identical
nodes it has been shown that heterogeneity can lower the epidemic threshold at
which epidemics can invade the system. Network heterogeneity can thus allow
diseases with lower transmission probabilities to persist and spread. Here, we
point out that for real world applications, this result should not be regarded
independently of the intra-individual heterogeneity between people. Our results
show that, if heterogeneity among people is taken into account, networks that
are more heterogeneous in connectivity can be more resistant to epidemic
spreading. We study a susceptible-infected-susceptible model with adaptive
disease avoidance. Results from this model suggest that this reversal of the
effect of network heterogeneity is likely to occur in populations in which the
individuals are aware of their subjective disease risk. For epidemiology, this
implies that network heterogeneity should not be studied in isolation.
