Alex Best

Dr. Alex Best is a Lecturer in Mathematical and Statistical Modelling at the School of Mathematical and Physical Sciences, University of Sheffield. He serves as the Student Voice Lead for Mathematics & Statistics and has been a faculty member since 2016. His academic journey includes a Leverhulme Early Career Research Fellowship at Sheffield (2013-2016), an Associate Research Fellowship at Exeter (2012), and postdoctoral work at Sheffield (2010-2011). He completed his PhD in Animal and Plant Sciences at the University of Sheffield (2006-2010).

Dr. Best's research focuses on mathematical biology, particularly using theoretical models to investigate infectious disease dynamics. His work spans multiple scales and incorporates:

• Models of host-parasite coevolution
• Spatial structure in epidemic and evolutionary models
• Immune processes in disease modeling
• Within-host models of bacteria-cell dynamics
• Seasonal effects on disease transmission
• Local vs. global interaction effects on epidemic spread

His publication record demonstrates consistent contributions to evolutionary epidemiology, with recent work examining how environmental fluctuations impact host-parasite coevolution, the dynamics of disease spread in university settings, and the evolution of host tolerance mechanisms. His research often combines mathematical modeling with biological insights to address fundamental questions in disease ecology and evolution.

Dr. Best has received recognition through the Leverhulme Early Career Research Fellowship and has made significant contributions to understanding the interplay between ecological dynamics and evolutionary processes in infectious disease systems.

As an educator, Dr. Best teaches multiple courses including MAS377 Mathematical Biology and MAS316 Mathematical Modelling of Natural Systems. He is actively involved in promoting equality, diversity, and inclusion in academia, having served as Director for Equality, Diversity and Inclusion in his department from 2018-2022 and currently serving on the London Mathematical Society's Good Practice Scheme steering committee.

His research group applies mathematical and computational tools to understand the ecology and evolution of infectious diseases, addressing questions about seasonal environments, local vs. global interactions, predator impacts on evolution, and optimal class sizes for epidemic control in university settings.