Zusammenfassung
Current modeling of infectious diseases allows for the study of complex and
realistic scenarios that go from the population to the individual level of
description. However, most epidemic models assume that the spreading process
takes place on a single level (be it a single population, a meta-population
system or a network of contacts). In particular, interdependent contagion
phenomena can only be addressed if we go beyond the scheme one pathogen-one
network. In this paper, we propose a framework that allows describing the
spreading dynamics of two concurrent diseases. Specifically, we characterize
analytically the epidemic thresholds of the two diseases for different
scenarios and also compute the temporal evolution characterizing the unfolding
dynamics. Results show that there are regions of the parameter space in which
the onset of a disease's outbreak is conditioned to the prevalence levels of
the other disease. Moreover, we show, for the SIS scheme, that under certain
circumstances, finite and not vanishing epidemic thresholds are found even at
the thermodynamic limit for scale-free networks. For the SIR scenario, the
phenomenology is richer and additional interdependencies show up. We also find
that the secondary thresholds for the SIS and SIR models are different, which
results directly from the interaction between both diseases. Our work thus
solve an important problem and pave the way towards a more comprehensive
description of the dynamics of interacting diseases.
Nutzer