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Technological advances have revolutionized our ability to observe the evolution of infections that are posing major global health challenges. However, using these new and high-resolution sources of data to improve health requires new theory -- new mathematical structures to understand patterns of ancestry and evolution in infectious diseases, new ways to map how antibiotic resistance emerges and spreads and new methods to combine data, modelling, inference and machine learning. This workshop will bring together mathematicians and statisticians, methods developers and biologists gathering state-of-the-art large datasets in pathogen genomics. The aims are to share not only mathematics and methods, but upcoming challenges and aims, and to ensure that large genomic datasets and the people that gather them have a voice in shaping methods and models towards the questions of the highest importance for pathogen evolution and ultimately for health.