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Faculty of Mathematics

 

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

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 et al.
– 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, CCW 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,
1
(doi: 10.17863/CAM.52467)
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
– J R Soc Interface
(2020)
17,
20190628
(doi: 10.1098/rsif.2019.0628)
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
(doi: 10.1101/2020.02.16.20023754)
Pease (1987): The evolutionary epidemiology of influenza A.
V Andreasen, JR Gog
– Theoretical Population Biology
(2020)
133,
29
(doi: 10.1016/j.tpb.2019.12.006)
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
(doi: 10.1371/journal.pcbi.1007345)
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
(doi: 10.1101/19005710)
Sparking “The BBC Four Pandemic”: Leveraging citizen science and mobile phones to model the spread of disease
SM Kissler, P Klepac, M Tang, AJK Conlan, JR Gog
(2018)
479154
(doi: 10.1101/479154)
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Research Group

Disease Dynamics

Email

jrg20@cam.ac.uk

Room

G0.10

Telephone

01223 760429

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