Digital Epidemiology and Beyond

Abstract

Respiratory and other close-contact infectious diseases, such as tuberculosis (TB), measles and pneumonia, are major killers in much of the developing world.Mathematical models are essential for understanding how these diseases spread, and for understanding how best to control them. Although central to modelling, few quantitative real-world data on relevant contact patterns are available. Capturing human interactions provides an empirical, quantitative measurement of social interaction patterns to informmathematical models of the spread of close-contact diseases.We have developed various systems to collect human contact/mobility data. The recent emergence ofwireless technology (e.g.mobile phones and sensors) makes it possible to collect real-world data on human proximity. Capturing human interactions with wireless sensors will allow us to understand complex patterns of human activities. For example, in one experiment people will carry tiny wireless sensors that record dynamic information about other devices nearby.