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Department of Applied Mathematics and Theoretical Physics

Professor Julia Rose Gog

Professor of Mathematical Biology, DAMTP, University of Cambridge

David N. Moore Fellow in Mathematics, Queens' College

Current roles:

Honours and awards:

Career:

  • 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

Research:

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

Publications

Epidemic interventions: insights from classic results
JR Gog, TD Hollingsworth
– Philosophical Transactions of the Royal Society B: Biological Sciences
(2021)
376,
20200263
(doi: 10.1098/rstb.2020.0263)
SARS-CoV-2 incidence and vaccine escape
RN Thompson, EM Hill, JR Gog
– The Lancet Infectious Diseases
(2021)
21,
913
(doi: 10.1016/s1473-3099(21)00202-4)
Coughs, Colds and “Freshers’ Flu” Survey in the University of Cambridge, 2007-2008
KTD Eames, M Tang, E Hill, M Tildesley, J Read, M Keeling, J Gog
(2021)
2021.03.31.21251220
(doi: 10.1101/2021.03.31.21251220)
Vaccine escape in a heterogeneous population: insights for SARS-CoV-2 from a simple model
J Gog, E Hill, L Danon, R Thompson
(2021)
2021.03.14.21253544
(doi: 10.1101/2021.03.14.21253544)
Human mobility data from the BBC Pandemic project
AJK Conlan, P Klepac, A Kucharski, S Kissler, M Tang, H Fry, J Gog
(2021)
2021.02.19.21252079
(doi: 10.1101/2021.02.19.21252079)
Engagement and adherence trade-offs for SARS-CoV-2 contact tracing
T Lucas, E Davis, D Ayabina, A Borlase, T Crellen, L Pi, G Medley, L Yardley, P Klepac, J Gog, D Hollingsworth
(2020)
2020.08.20.20178558
(doi: 10.1101/2020.08.20.20178558)
Key questions for modelling 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: Biological Sciences
(2020)
287,
20201405
(doi: 10.1098/rspb.2020.1405)
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
– The Lancet. Infectious diseases
(2020)
20,
1151
(doi: 10.1016/s1473-3099(20)30457-6)
Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings
A Kucharski, P Klepac, A Conlan, S Kissler, M Tang, H Fry, J Gog, J Edmunds, CMMID COVID-19 working group
(2020)
2020.04.23.20077024
(doi: 10.1101/2020.04.23.20077024)
How you can help with COVID-19 modelling
JR Gog
– Nature Reviews Physics
(2020)
2,
274
(doi: 10.1038/s42254-020-0175-7)
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Research Group

Disease Dynamics

Email

jrg20@cam.ac.uk

Room

G0.10

Telephone

01223 760429

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