Vaccination and Complex Social Dynamics
  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. 
Enys Mones, Arkadiusz Stopczynski, Alex Pentland, Nathaniel Hupert and   Sune Lehmann
physics.soc-ph cs.SI