Short-time human travel is dominated by local movements while longer journeys occur less frequently. Since human travel is an important driver of epidemic spread, such a power law of the traveled distance should enter models for the spread of human infectious diseases. This has now been established by Sebastian Meyer and Leonhard Held from EBPI’s Department of Biostatistics as part of the SNSF project “Statistical methods for spatio-temporal modelling and prediction of infectious diseases”. In a paper recently published in The Annals of Applied Statistics, they successfully modeled power laws of spatial interaction, which enabled better predictions of the spread of infectious diseases such as invasive meningococcal disease and seasonal influenza. To support the application of the methodology in other settings, the research findings are accompanied by a guide for the spatio-temporal analysis of epidemic phenomena using the open source R software package “surveillance”.