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Unraveling the epidemiology of Mycobacterium bovis using whole-genome sequencing combined with environmental and demographic data
1. Introduction In the last two decades, the increased availability, efficiency, and reliability of genomic reading techniques, such as whole-genome sequencing (WGS) techniques, have ignited a profound transformation in understanding disease ecology and epidemiology. This, coupled with improved statistical methodologies and high-performance computing, has enhanced our understanding of pathogen dynamics and evolution (1).
Unravelling the epidemiology of Mycobacterium bovis using whole genome sequencing combined with environmental and demographic data
Gianluigi Rossi1, 2*, Barbara B. Shih1, Franklyn N. Egbe3, Paolo Motta4, Florian Duchatel1, Robert F. Kelly5, Lucy M. Ndip6, 7, Melissa Sander8, Vincent N. Tanya9, Samatha J. Lycett1, 2, Barend M.
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