The Evolution & Genomics theme within CMMID unites genomic epidemiology, phylogenetics, experimental pathogen genetics, and infectious-disease modelling. Together, the group investigates how pathogens evolve under transmission pressures and how genomic data can be integrated with models to explain and forecast epidemic dynamics. Core interests include antimicrobial resistance, viral and bacterial phylodynamics, vaccine-driven strain change, and the design of genomic surveillance systems that inform policy. 

Examples of our work highlight the breadth of the theme. We advance HIV and TB drug-resistance genomics (Tully, Hué, Fuller). In parallel, we apply outbreak phylogenetics and genomic epidemiology to investigate transmission (Hué, Villabona-Arenas, Atkins, Tully). We also develop experimental and computational infection genetics, generating methods and data to probe pathogen function (Sanderson). Bacterial dynamics are studied from two angles: vaccine-driven serotype and strain change (Flasche, Davies, Atkins), and the emergence and control of antimicrobial resistance (Knight, Atkins, Davies, Barnsley). Finally, variant-aware transmission modelling supports real-time decision-making (Funk, Davies, Russell, Procter), while surveillance and population-level inference strengthen programme design across viruses and vaccines (O’Reilly, Brigitta, McCarthy, Fischer). 

People (alphabetical by surname)

Katherine Atkins, Gregory Barnsley, Clara Brigitta, Nick Davies, Natalie Fischer, Stefan Flasche, Naomi Fuller, Sebastian Funk, Stéphane Hué, Gwen Knight, Ciara McCarthy, Kath O’Reilly, Simon Procter, Tim Russell, Theo Sanderson, Damien Tully, Julian Villabona-Arenas. 

• Davies NG, Abbott S, Barnard RC, Jarvis CI, Kucharski AJ, Munday JD, Pearson CAB, Russell TW, Tully DC, Washburne AD, Wenseleers T, Gimma A, Waites W, Wong KLM, van Zandvoort K, Silverman JD, CMMID COVID-19 Working Group, COVID-19 Genomics UK (COG-UK) Consortium, Diaz-Ordaz K, Keogh R, Eggo RM, Funk S, Jit M, Atkins KE, Edmunds WJ. 2021. Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science 372: 149. doi: 10.1126/science.abg3055
• Leclerc QJ, Lindsay JA, Knight GM. 2022. Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution. PLoS Comput Biol. 18(11):e1010746. doi: 10.1371/journal.pcbi.1010746
• Villabona-Arenas CJ, Hall M, Lythgoe KA, Gaffney SG, Regoes RR, Hué S, Atkins KE. 2020. Number of HIV-1 Founder Variants Is Determined by the Recency of the Source Partner Infection. Science doi: 10.1126/science.aba5443
• Tully DC, Bean D, Sarette J, Ngo TL, Power K, Brook D, Cooper H, Feinberg J, Friedmann P, Hochstatter K, Havens J, Babalonis S, Hurt C, Jenkins W, Korthuis T, Miller W, Pho M, Smith G, Stopka T, Tsui J, Mixson S, Westergaard R, Young A, Allen TA. 2025. Genomic surveillance uncovers regional variation in HCV transmission networks in rural United States. Nature Communications In Press doi: 10.21203/rs.3.rs-6810633/v1
• Lindsey BB, Villabona-Arenas CJ, Campbell F, Keeley AJ, Parker MD, Shah DR, Parsons H, Zhang P, Kakkar N, Gallis M, Foulkes BH, Wolverson P, Louka SF, Christou S, State A, Johnson K, Raza M, Hsu S, Jombart T, Cori A, Sheffield COVID-19 Genomics Group, The COVID-19 Genomics UK (COG-UK) consortium, CMMID COVID-19 working group, Evans CM, Partridge DG, Atkins KE, Hué S, de Silva TI. 2021. Characterising within-hospital SARS-CoV-2 transmission events: a retrospective analysis integrating epidemiological and viral genomic data from a UK tertiary care setting across two pandemic waves. Nature Communications 13(671). doi: 10.1038/s41467-022-28291-y