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Cambridge Infectious Diseases

An Interdisciplinary Research Centre at the University of Cambridge

Studying at Cambridge


Professor Julia Gog

Professor Julia Gog

Department of Applied Mathematics and Theoretical Physics (DAMTP)

Mathematics of infectious diseases,viral bioinformatics,influenza modelling


Professor Julia Gog is a British mathematician, David N. Moore Fellow and Director of Studies in Mathematics at Queens' College, Cambridge and Professor of mathematical biology in the University of Cambridge Department of Applied Mathematics and Theoretical Physics. She is also a member of the Cambridge Immunology Network and the Cambridge Infectious Diseases Interdisciplinary Research Centre.Her research specialises in using mathematical techniques to study infectious diseases, particularly influenza. Current 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


  • Evolution
  • Strain dynamics
  • Epidemic control
  • Pathogen Evolution
  • Epidemiology
  • Bioinformatics
  • Genome Packaging


  • Salmonella
  • Influenza (Flu)


  • Mathematical modelling
  • Computational modelling

Key Publications

Geographic transmission hubs of the 2009 influenza pandemic in the United States. SM Kissler, JR Gog, C Viboud, V Charu, ON Bjørnstad, L Simonsen, ...
Epidemics 26, 86-94 4 2019

Urbanization and humidity shape the intensity of influenza epidemics in US cities
BD Dalziel, S Kissler, JR Gog, C Viboud, ON Bjørnstad, CJE Metcalf, ...
Science 362 (6410), 75-79 13 2018

Contagion! The BBC Four Pandemic–The model behind the documentary
P Klepac, S Kissler, J Gog Epidemics 24, 49-59 4 2018

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 13 (4), e0195763 2018

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 bioRxiv, 479154