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Department of Applied Mathematics and Theoretical Physics

Professor of Mathematical Biology, DAMTP, University of Cambridge

David N. Moore Fellow in Mathematics, Queens' College

Honours and awards


  • 2017-present  Professor of Mathematical Biology 
  • 2013-2017 Reader in Mathematical Biology
  • 2010-2012  Visiting Fellow, Ecology and Evolutionary Biology, Princeton University
  • 2006-2013 University Lecturer, DAMTP, University of Cambridge
  • 2006-2012 Royal Society University Research Fellowship, DAMTP, University of Cambridge
  • 2004-present Official Fellow, Queens' College
  • 2004-2006 Royal Society University Research Fellowship, Department of Zoology, University of Cambridge
  • 2002-2004 Research Fellowship, Queens' College


Julia Gog's research is in the mathematics of infectious diseases. Recent projects include:

  • Models of influenza strain dynamics
  • Spatial spread of influenza
  • Within-host dynamics of influenza
  • In vitro dynamics of Salmonella
  • Bioinformatic methods to detect RNA signals in viruses

University news items on our work

For list of publications, please try Julia's profile on Google Scholar.

Photo credit: Marisa Sutherland-Brown


SARS-CoV-2 infection in UK university students: lessons from September–December 2020 and modelling insights for future student return
J Enright, EM Hill, HB Stage, KJ Bolton, EJ Nixon, EL Fairbanks, ML Tang, E Brooks-Pollock, L Dyson, CJ Budd, RB Hoyle, L Schewe, JR Gog, MJ Tildesley
– Royal Society Open Science
Vaccine escape in a heterogeneous population: insights for SARS-CoV-2 from a simple model.
JR Gog, EM Hill, L Danon, RN Thompson
– Royal Society Open Science
SARS-CoV-2 incidence and vaccine escape.
RN Thompson, EM Hill, JR Gog
– Lancet Infect Dis
Engagement and adherence trade-offs for SARS-CoV-2 contact tracing.
TCD Lucas, EL Davis, D Ayabina, A Borlase, T Crellen, L Pi, GF Medley, L Yardley, P Klepac, J Gog, T Déirdre Hollingsworth
– Philosophical Transactions of the Royal Society B: Biological Sciences
Epidemic interventions: insights from classic results.
JR Gog, TD Hollingsworth
– Philosophical Transactions of the Royal Society B: Biological Sciences
Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study
AJ Kucharski, P Klepac, AJK Conlan, SM Kissler, ML Tang, H Fry, JR Gog, WJ Edmunds, CMMID COVID-19 working group
– Lancet Infect Dis
Key questions for modelling COVID-19 exit strategies: COVID-19 Exit Strategies
RN Thompson, TD Hollingsworth, V Isham, D Arribas-Bel, B Ashby, T Britton, P Challenor, LHK Chappell, H Clapham, NJ Cunniffe, AP Dawid, CA Donnelly, RM Eggo, S Funk, N Gilbert, P Glendinning, JR Gog, WS Hart, H Heesterbeek, T House, M Keeling, IZ Kiss, ME Kretzschmar, AL Lloyd, ES McBryde, JM McCaw, TJ McKinley, JC Miller, M Morris, PD O'Neill, KV Parag, CAB Pearson, L Pellis, JRC Pulliam, JV Ross, GS Tomba, BW Silverman, CJ Struchiner, MJ Tildesley, P Trapman, CR Webb, D Mollison, O Restif
– Proceedings of the Royal Society B
Pease (1987): The evolutionary epidemiology of influenza A.
V Andreasen, JR Gog
– Theor Popul Biol
How you can help with COVID-19 modelling.
JR Gog
– Nature Reviews Physics
Symbolic transfer entropy reveals the age structure of pandemic influenza transmission from high-volume influenza-like illness data
SM Kissler, C Viboud, BT Grenfell, JR Gog
– Journal of The Royal Society Interface
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Research Group

Disease Dynamics




01223 760429