PhD student secures Alan Turing Institute award
Ashleigh Myall, a PhD student on our National PhD Training Programme in AMR Research, has secured an Enrichment Community Award from the prestigious Alan Turing Institute.
Despite a large and expanding toolbox of epidemiological models, how we capture transmission of more complex spreading processes, like AMR, is still limited.Ash Myall
Ash is part of the ASPIRES consortium at Imperial College London, which is aiming to improve the use of antibiotics in surgical settings; specifically, he focuses on how pathogens (disease causing bugs) spread in nosocomial infection (these are infections which are picked up by patients when they are in the hospital).
The Alan Turing Institute is the leading institute for computational research in the UK, and its highly competitive Enrichment scheme gives PhD students the opportunity to support and enhance their current research, by accessing the facilities and opportunities available at the Institute and its partners.
For Ash, this award will allow him to collaborate with people across the Turing community, especially those with expertise in modelling antimicrobial resistance (AMR) in healthcare acquired infections. It will widen the scope of Ash's PhD, build his independence, and contribute to his development as a research leader in computational infection prevention.
AMR is recognised as an urgent threat to society, health systems and individuals across the world. However, while the mechanisms leading to AMR and drug resistant infections are biological, conditions which allow them to flourish are also social, cultural, political and economic. Research tackling AMR therefore requires a highly multidisciplinary approach and global collaboration.
Commenting on his award, Ash Myall said, "Despite a large and expanding toolbox of epidemiological models, how we capture transmission of more complex spreading processes, like AMR, is still limited. Through working with technical experts across the Turing Community, I will expand methodology and explore new theoretical classes of models to accurately capture AMR transmission in hospitals. Together, advances in this area have the potential to shed new light on transmission dynamics and improve control strategies with data-driven modelling."
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