Professor Julia Rose Gog

Professor of Mathematical Biology, DAMTP, University of Cambridge

David N. Moore Fellow in Mathematics, Queens' College

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

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)

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. Biological sciences

(2020)

287,

20201405

(DOI: 10.1098/rspb.2020.1405rspb20201405)

Pease (1987): The evolutionary epidemiology of influenza A

V Andreasen, JR Gog

– Theoretical Population Biology

(2020)

133,

(DOI: 10.1016/j.tpb.2019.12.006)

How you can help with COVID-19 modelling

JR Gog

– Nature Reviews Physics

(2020)

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

– Journal of the Royal Society, Interface

(2020)

17,

20190628

(DOI: 10.1098/rsif.2019.0628)

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 Computational Biology

(2019)

15,

e1007345

(DOI: 10.1371/journal.pcbi.1007345)

Geographic transmission hubs of the 2009 influenza pandemic in the United States

SM Kissler, JR Gog, C Viboud, V Charu, ON Bjørnstad, L Simonsen, BT Grenfell

– Epidemics

(2019)

26,

(DOI: 10.1016/j.epidem.2018.10.002)

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 US cities

BD Dalziel, S Kissler, JR Gog, C Viboud, ON Bjørnstad, CJE Metcalf, BT Grenfell

– Science

(2018)

362,

(DOI: 10.1126/science.aat6030)

Contagion! The BBC Four Pandemic - The model behind the documentary.

P Klepac, S Kissler, J Gog

– Epidemics

(2018)

24,

(DOI: 10.1016/j.epidem.2018.03.003)

Department of Applied Mathematics and Theoretical Physics

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