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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

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

Honours and awards

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, 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
(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)
How you can help with COVID-19 modelling
JR Gog
– Nature Reviews Physics
(2020)
2,
274
(DOI: 10.1038/s42254-020-0175-7)
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)
Pease (1987): The evolutionary epidemiology of influenza A
V Andreasen, JR Gog
– Theor Popul Biol
(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
JP Skittrall, CK Ingemarsdotter, JR Gog, AML Lever
– PLoS Comput. Biol.
(2019)
15,
e1007345
(DOI: 10.1371/journal.pcbi.1007345)
Sparking “The BBC Four Pandemic”: Leveraging citizen science and mobile phones to model the spread of disease
S Kissler, P Klepac, M Tang, AJK Conlan, J Gog
(2018)
(DOI: 10.1101/479154)
Urbanization and humidity shape the intensity of influenza epidemics in U.S. cities.
BD Dalziel, S Kissler, JR Gog, C Viboud, ON Bjørnstad, CJE Metcalf, BT Grenfell
– Science
(2018)
362,
75
(DOI: 10.1126/science.aat6030)
Contagion! The BBC Four Pandemic - The model behind the documentary
P Klepac, S Kissler, J Gog
– Epidemics
(2018)
24,
49
(DOI: 10.1016/j.epidem.2018.03.003)
A new method for detecting signal regions in ordered sequences of real numbers, and application to viral genomic data
JR Gog, AML Lever, JP Skittrall
– PloS one
(2018)
13,
e0195763
(DOI: 10.1371/journal.pone.0195763)
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Research Group

Disease Dynamics

Email

jrg20@cam.ac.uk

Room

G0.10

Telephone

01223 760429

Study at Cambridge

About the University

Research at Cambridge