The paper investigates the impact of multiscale mobility networks on the large-scale spreading of infectious diseases. The authors analyze mobility data from 29 countries to develop a gravity model that describes commuting patterns up to 300 kilometers. They integrate this model into a worldwide structured metapopulation epidemic model, using a time-scale separation technique to evaluate the force of infection due to multiscale mobility processes. Commuting flows are found to be one order of magnitude larger than airline flows, but their inclusion in the model shows only small variations in the simulated epidemic patterns. However, short-range mobility increases the synchronization of subpopulations and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The study highlights the importance of considering both long-range and short-range mobility in epidemic models to better understand and predict disease spread.The paper investigates the impact of multiscale mobility networks on the large-scale spreading of infectious diseases. The authors analyze mobility data from 29 countries to develop a gravity model that describes commuting patterns up to 300 kilometers. They integrate this model into a worldwide structured metapopulation epidemic model, using a time-scale separation technique to evaluate the force of infection due to multiscale mobility processes. Commuting flows are found to be one order of magnitude larger than airline flows, but their inclusion in the model shows only small variations in the simulated epidemic patterns. However, short-range mobility increases the synchronization of subpopulations and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The study highlights the importance of considering both long-range and short-range mobility in epidemic models to better understand and predict disease spread.