  Vaccination and outbreak monitoring are essential tools for preventing and
minimizing outbreaks of infectious diseases. Targeted strategies, where the
individuals most important for monitoring or preventing outbreaks are selected
for intervention, offer a possibility to significantly improve these measures.
Although targeted strategies carry a strong potential, identifying optimal
target groups remains a challenge. Here we consider the problem of identifying
target groups based on digital communication networks (telecommunication,
online social media) in order to predict and contain an infectious disease
spreading on a real-world person-to-person network of more than 500
individuals. We show that target groups for efficient outbreak monitoring can
be determined based on both telecommunication and online social network
information. In case of vaccination the information regarding the digital
communication networks improves the efficacy for short-range disease
transmissions but, surprisingly, performance is severely reduced in the case of
long-range transmission. These results are robust with respect to the strategy
used to identify targeted individuals and time-gap between identification of
targets and the intervention. Thus, we demonstrate that data available from
telecommunication and online social networks can greatly improve epidemic
control measures, but it is important to consider the details of the pathogen
spreading mechanism when such policies are applied.
