Biography:Christophe Fraser

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Short description: British epidemiologist


Professor

Christophe Fraser
Born1973 (age 50–51)
Academic background
EducationEdinburgh University BSc,
Swansea University PhD
ThesisSupersymmetric Monopoles and Duality in Non-Abelian Gauge Theories (1997)
Academic work
DisciplineEpidemiology
Infectious diseases
InstitutionsBig Data Institute
Main interestsMathematical modelling of infectious diseases, Viral evolution, Antimicrobial resistance, Emerging infectious disease
Websitehttps://www.bdi.ox.ac.uk/Team/christophe-fraser


Christophe Fraser is a professor of Infectious Disease Epidemiology in the Big Data Institute, part of the Nuffield Department of Medicine at the University of Oxford.[1]

Fraser's PhD and initial postdoctoral research were in theoretical particle physics. He converted to infectious disease epidemiology in 1998, based first at the University of Oxford then at Imperial College London, where he became Chair of Theoretical Epidemiology and served as deputy director of the MRC Centre for Outbreak Analysis and Modelling.[2] He returned to the University of Oxford in 2016 as Senior Group Leader in Pathogen Dynamics at the Big Data Institute.[1] In 2022 he was appointed Moh Family Foundation Professor of Infectious Disease Epidemiology as part of the University of Oxford's newly created Pandemic Sciences Institute.[3]

Research on HIV

Fraser and colleagues were among the first to hypothesise that the large variability in virulence observed between individuals living with HIV could be partly due to genetic variation in the virus.[4] In other words they hypothesised that virulence, considered as a phenotype of the virus, has appreciable heritability. They[5][6][7] and others[8][9][10][11] later provided evidence for this. Fraser was principal investigator of the BEEHIVE project to investigate the mechanism of this heritability,[12] which discovered the 'VB variant': a highly virulent strain within the B subtype of HIV found in 107 individuals living with HIV in the Netherlands.[13][14] UNAIDS stated that the discovery "provides evidence of urgency to halt the pandemic and reach all with testing and treatment".[15]

Research on the COVID-19 pandemic

In March 2020 Fraser and his research group published epidemiological modelling supporting 'digital contact tracing' using COVID-19 apps to reduce the spread of SARS-CoV-2.[16] Fraser provided advice to the British government[17] and more broadly[18] about implementing such apps, including designing a risk evaluation algorithm with Anthony Finkelstein and others.[19] Fraser's team developed the OpenABM-Covid-19 agent-based model,[20] used by the NHS to model the pandemic, winning the 2021 Analysis in Government award for Innovative methods.[21]

Research on other outbreaks

Fraser worked on the 2002–2004 SARS outbreak,[22] the 2009 swine flu pandemic,[23] the 2012 MERS outbreak[24] and the Western African Ebola virus epidemic.[25]

Methodological research

Fraser's publications[26] include "Factors that make an infectious disease outbreak controllable",[27] 2004, which argued that in addition to the basic reproduction number [math]\displaystyle{ R_0 }[/math] a second key parameter of an infectious disease is the proportion of transmission that occurs before the onset of symptoms. This proportion being large for SARS-CoV-2 was a key difficulty in infection control for the COVID-19 pandemic.

Fraser's 2007 analysis "Estimating Individual and Household Reproduction Numbers in an Emerging Epidemic"[28] first defined an estimator for the instantaneous (time-varying) reproduction number [math]\displaystyle{ R(t) }[/math] that was subsequently widely used.[29] The definition was obtained by inverting the standard relationship between the reproduction number, the generation time distribution and the parameter [math]\displaystyle{ r }[/math] of the Malthusian growth model that is implied by the renewal equation for epidemic dynamics[30] (or the Euler-Lotka equation as it is known in demography; the two are equivalent due to actual births being analogous to infectious disease transmissions as 'epidemiological births', giving rise to a new infected individual).

References

  1. ↑ 1.0 1.1 "Christophe Fraser, Oxford Big Data Institute". https://www.bdi.ox.ac.uk/Team/christophe-fraser. 
  2. ↑ "Christophe Fraser, Imperial College London". https://www.imperial.ac.uk/people/c.fraser. 
  3. ↑ "University of Oxford News". https://www.ox.ac.uk/news/2022-05-19-major-boost-oxford-s-mission-counter-future-pandemic-threats. 
  4. ↑ Fraser, Christophe; Hollingsworth, T. Déirdre; Chapman, Ruth; De Wolf, Frank; Hanage, William P. (2007). "Variation in HIV-1 set-point viral load: epidemiological analysis and an evolutionary hypothesis". Proceedings of the National Academy of Sciences 104 (44): 17441–17446. doi:10.1073/pnas.0708559104. PMID 17954909. 
  5. ↑ HIV-1 Transmitting Couples Have Similar Viral Load Set-Points in Rakai, Uganda. 2010. doi:10.1371/journal.ppat.1000876. 
  6. ↑ Fraser, Christophe; Lythgoe, Katrina; Leventhal, Gabriel E.; Shirreff, George; Hollingsworth, T. Déirdre; Alizon, Samuel; Bonhoeffer, Sebastian (2014). "Virulence and pathogenesis of HIV-1 infection: an evolutionary perspective". Science 343 (6177). doi:10.1126/science.1243727. PMID 24653038. 
  7. ↑ Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe. 2017. doi:10.1371/journal.pbio.2001855. 
  8. ↑ Bertels, Frederic; Marzel, Alex; Leventhal, Gabriel; Mitov, Venelin; Fellay, Jacques; Günthard, Huldrych F.; Böni, Jürg; Yerly, Sabine et al. (2018). "Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity". Molecular Biology and Evolution 35: 27–37. doi:10.1093/molbev/msx246. PMID 29029206. 
  9. ↑ Mitov, Venelin; Stadler, Tanja (2018). "A Practical Guide to Estimating the Heritability of Pathogen Traits". Molecular Biology and Evolution 35 (3): 756–772. doi:10.1093/molbev/msx328. PMID 29329426. 
  10. ↑ Potential Pitfalls in Estimating Viral Load Heritability. 2016. doi:10.1016/j.tim.2016.04.008. 
  11. ↑ Estimating the Respective Contributions of Human and Viral Genetic Variation to HIV Control. 2017. doi:10.1371/journal.pcbi.1005339. 
  12. ↑ "BEEHIVE". https://cordis.europa.eu/article/id/418109-hiv-analysis-shines-light-on-viral-process. 
  13. ↑ AP (February 3, 2022). "Study identifies virulent HIV variant unrecognized for years". https://apnews.com/article/science-health-europe-netherlands-western-europe-176156e8d785f10b53224c856c671aba. 
  14. ↑ Wymant, Chris et al. (2022). "A highly virulent variant of HIV-1 circulating in the Netherlands". Science 375 (6580): 540–545. doi:10.1126/science.abk1688. PMID 35113714. Bibcode: 2022Sci...375..540T. 
  15. ↑ UNAIDS (7 February 2022). "Identification of fast-spreading HIV variant provides evidence of urgency to halt the pandemic and reach all with testing and treatment". https://www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2022/february/20220207_hiv-variant. 
  16. ↑ Ferretti, Luca; Wymant, Chris; Kendall, Michelle; Zhao, Lele; Nurtay, Anel; Abeler-Dörner, Lucie; Parker, Michael; Bonsall, David et al. (March 31, 2020). "Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing". Science 368 (6491): eabb6936. doi:10.1126/science.abb6936. PMID 32234805. 
  17. ↑ "Coronavirus: NHS contact tracing app to target 80% of smartphone users". BBC News. April 16, 2020. https://www.bbc.co.uk/news/technology-52294896. 
  18. ↑ "REF 2021 Impact Case Study". https://results2021.ref.ac.uk/impact/d3d20ce5-b625-4da5-9e0e-8e4bf87ef238?page=1. 
  19. ↑ "Defining an epidemiologically meaningful contact from phone proximity events: uses for digital contact tracing". https://github.com/BDI-pathogens/covid-19_instant_tracing/blob/master/Epidemiologically%20meaningful%20contact%20from%20phone%20proximity%20events%20-%20uses%20for%20digital%20contact%20tracing.pdf. 
  20. ↑ Hinch, Robert; Probert, William J. M.; Nurtay, Anel; Kendall, Michelle; Wymant, Chris; Hall, Matthew; Lythgoe, Katrina; Bulas Cruz, Ana et al. (2021). "OpenABM-Covid19—An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing". PLOS Computational Biology 17 (7): e1009146. doi:10.1371/journal.pcbi.1009146. PMID 34252083. Bibcode: 2021PLSCB..17E9146H. 
  21. ↑ "2021 Analysis in Government awards". https://www.gov.uk/government/news/analysis-in-government-award-winners-2021. 
  22. ↑ Riley, Steven; Fraser, Christophe; Donnelly, Christl A.; Ghani, Azra C.; Abu-Raddad, Laith J.; Hedley, Anthony J.; Leung, Gabriel M.; Ho, Lai-Ming et al. (2003). "Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions". Science 300 (5627): 1961–1966. doi:10.1126/science.1086478. PMID 12766206. Bibcode: 2003Sci...300.1961R. 
  23. ↑ Fraser, Christophe; Donnelly, Christl A.; Cauchemez, Simon; Hanage, William P.; Van Kerkhove, Maria D.; Hollingsworth, T. Déirdre; Griffin, Jamie; Baggaley, Rebecca F. et al. (2009). "Pandemic potential of a strain of influenza A (H1N1): early findings". Science 324 (5934): 1557–1561. doi:10.1126/science.1176062. PMID 19433588. Bibcode: 2009Sci...324.1557F. 
  24. ↑ Cauchemez, Simon; Fraser, Christophe; Van Kerkhove, Maria D.; Donnelly, Christl A.; Riley, Steven; Rambaut, Andrew; Enouf, Vincent; Van Der Werf, Sylvie et al. (2014). "Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility". The Lancet Infectious Diseases 14 (1): 50–56. doi:10.1016/S1473-3099(13)70304-9. PMID 24239323. 
  25. ↑ Agua-Agum, Junerlyn et al. (2016). "Exposure Patterns Driving Ebola Transmission in West Africa: A Retrospective Observational Study". PLOS Medicine 13 (11): e1002170. doi:10.1371/journal.pmed.1002170. PMID 27846234. 
  26. ↑ {{Google Scholar id}} template missing ID and not present in Wikidata.
  27. ↑ Fraser, Christophe; Riley, Steven; Anderson, Roy M.; Ferguson, Neil M. (2004). "Factors that make an infectious disease outbreak controllable". Proceedings of the National Academy of Sciences 101 (16): 6146–6151. doi:10.1073/pnas.0307506101. PMID 15071187. Bibcode: 2004PNAS..101.6146F. 
  28. ↑ Fraser, Christophe (2007). "Estimating Individual and Household Reproduction Numbers in an Emerging Epidemic". PLOS ONE 2 (8): e758. doi:10.1371/journal.pone.0000758. PMID 17712406. Bibcode: 2007PLoSO...2..758F. 
  29. ↑ Cori, Anne; Ferguson, Neil M.; Fraser, Christophe; Cauchemez, Simon (2013). "A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics". American Journal of Epidemiology 178 (9): 1505–1512. doi:10.1093/aje/kwt133. PMID 24043437. 
  30. ↑ Wallinga, J.; Lipsitch, M. (2007). "How generation intervals shape the relationship between growth rates and reproductive numbers". Proceedings of the Royal Society B: Biological Sciences 274 (1609): 599–604. doi:10.1098/rspb.2006.3754. PMID 17476782. 



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