Through this project, we aim to develop models of human mobility leveraging multiple types of data (mobile phone data, survey data, GPS loggers, airline data, etc.) globally. We investigate how mobility patterns change across a wide range of socio-demographic and geographic settings, with a particular focus on mobility in low- and middle-income settings. We use these data to fit novel models of mobility that take into account the multi-dimensional aspects of travel (who is traveling? When? Where? For how long? At what frequency?). We then investigate how travel impacts infectious disease dynamics focusing on a wide range of pathogens (including malaria, dengue, measles, rubella, SARS-CoV-2, influenza). We hope this work will help us better understand how human mobility impacts disease transmission and ultimately allow models to better capture travel.