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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

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, TD Hollingsworth
(2020)
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
– Proc Biol Sci
(2020)
287,
20201405
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 Infectious Diseases
(2020)
20,
1151
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, CCW group
(2020)
2020.04.23.20077024
How you can help with COVID-19 modelling
JR Gog
– Nature reviews. Physics
(2020)
2,
274
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
(2020)
17,
20190628
Contacts in context: large-scale setting-specific social mixing matrices from the BBC Pandemic project
P Klepac, AJ Kucharski, AJ Conlan, S Kissler, ML Tang, H Fry, JR Gog
(2020)
2020.02.16.20023754
Pease (1987): The evolutionary epidemiology of influenza A.
V Andreasen, JR Gog
– Theoretical population biology
(2020)
133,
29
A scale-free analysis of the HIV-1 genome demonstrates multiple conserved regions of structural and functional importance
J Skittrall, C Ingemarsdotter, J Gog, A Lever
– PLoS Comput Biol
(2019)
15,
e1007345
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
(2019)
19005710
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Research Group

Disease Dynamics

Room

G0.10

Telephone

01223 760429