  The epidemiology has recently witnessed great advances based on computational
models. Its scope and impact are getting wider thanks to the new data sources
feeding analytical frameworks and models. Besides traditional variables
considered in epidemiology, large-scale social patterns can be now integrated
in real time with multi-source data bridging the gap between different scales.
In a hyper-connected world, models and analysis of interactions and social
behaviors are key to understand and stop outbreaks. Big Data along with apps
are enabling for validating and refining models with real world data at scale,
as well as new applications and frameworks to map and track diseases in real
time or optimize the necessary resources and interventions such as testing and
vaccination strategies. Digital epidemiology is positioning as a discipline
necessary to control epidemics and implement actionable protocols and policies.
In this review we address the research areas configuring current digital
epidemiology: transmission and propagation models and descriptions based on
human networks and contact tracing, mobility analysis and spatio-temporal
propagation of infectious diseases and the emerging field of infodemics that
comprises the study of information and knowledge propagation related to
epidemics. Digital epidemiology has the potential to create new operational
mechanisms for prevention and mitigation, monitoring of the evolution of
epidemics, assessing their impact and evaluating the pharmaceutical and
non-pharmaceutical measures to fight the outbreaks.
