  Outbreaks are complex multi-scale processes that are impacted not only by
cellular dynamics and the ability of pathogens to effectively reproduce and
spread, but also by population-level dynamics and the effectiveness of
mitigation measures. A timely exchange of information related to the spread of
novel pathogens, stay-at-home orders, and other containment measures can be
effective at containing an infectious disease, particularly during in the early
stages when testing infrastructure, vaccines, and other medical interventions
may not be available at scale. Using a multiplex epidemic model that consists
of an information layer (modeling information exchange between individuals) and
a spatially embedded epidemic layer (representing a human contact network), we
study how random and targeted disruptions in the information layer (\eg, errors
and intentional attacks on communication infrastructure) impact outbreak
dynamics. We calibrate our model to the early outbreak stages of the SARS-CoV-2
pandemic in 2020. Mitigation campaign can still be effective under random
disruptions, such as failure of information channels between a few individuals.
However, targeted disruptions or sabotage of hub nodes that exchange
information with a large number of individuals can abruptly change outbreak
characteristics such as the time to reach the peak infection. Our results
emphasize the importance of using a robust communication infrastructure that
can withstand both random and targeted disruptions.
