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[Research] Real-time bioinformatics platform to predict COVID-19 vaccine effectiveness

Updated: Jul 19


CU Medicine develops a computational approach to rapidly predict the protective effects of COVID-19 vaccines by analysing genetic distance.  (From left) Ms. Lirong CAO, PhD student; Professor Benny ZEE, Director of the Centre for Clinical Research and Biostatistics; and Professor Maggie WANG, Associate Professor, The Jockey Club School of Public Health and Primary Care, CU Medicine.
CU Medicine develops a computational approach to rapidly predict the protective effects of COVID-19 vaccines by analysing genetic distance. (From left) Ms. Lirong CAO, PhD student; Professor Benny ZEE, Director of the Centre for Clinical Research and Biostatistics; and Professor Maggie WANG, Associate Professor, The Jockey Club School of Public Health and Primary Care, CU Medicine.


Timely evaluation of COVID-19 vaccine effectiveness (VE) is desperately needed to inform and update vaccine design as novel genetic variants continually emerge. A research team led by Professor Maggie Haitian WANG and Professor Benny Chung Ying ZEE, both from The Jockey Club School of Public Health and Primary Care at The Chinese University of Hong Kong’s (CUHK) Faculty of Medicine (CU Medicine), has developed a computational approach that can rapidly predict the protective effects of COVID-19 vaccines by analysing genetic distance (GD). The research findings have been published in the renowned journal Nature Medicine.


Details: https://bit.ly/3IA018Q

Full article of the study: https://go.nature.com/3aFWfOx


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