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Cécile Viboud

From Wikipedia, the free encyclopedia
Cécile Viboud
Alma materPierre and Marie Curie University
University of Lyon
Scientific career
InstitutionsNational Institutes of Health
ThesisPrédictions épidémiologiques de la grippe en zones tempérées (2003)

Cécile Viboud is a Staff Scientist based in the Fogarty International Center at the National Institutes of Health, where she is part of the Multinational Influenza Seasonal Mortality Study (MISMS). Viboud specialises in the mortality of infectious disease. Viboud was involved with epidemiological analysis during the COVID-19 pandemic.

Early life and education

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Viboud is from France. She earned her undergraduate degree in biomedical engineering at the University of Lyon.[1] She moved to Pierre and Marie Curie University (UPMC) for her graduate studies, where she specialised in public health. Viboud completed her doctoral degree at UPMC, where she worked under the supervision of Antoine Flahault. She studied the spread of influenza epidemics through the use of a method of analogues.[2] The method of analogues is a model borrowed from meteorology, using vectors from historical influenza epidemics that matches current activity.[2][3]

Research and career

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Viboud is a member of the Fogarty International Center at the National Institutes of Health. She is part of the Multinational Influenza Seasonal Mortality Study (MISMS). Here she studies the mortality burden and transmission dynamics of infectious diseases.[4]

She has extensively investigated the epidemiology of influenza. In 2016, Viboud demonstrated that a person's first case of influenza influenced their later likelihood to become infected.[5][6] For example, if people were exposed to a particular strain of influenza as a child, they would be to 75% less likely to contract it in the future.[6] Viboud has also studied how urbanisation impacts the intensity of influenza epidemics.[7] She showed that more diffuse epidemics occur in large cities, which were less sensitive to changes in climate.[8] In these cities people live so close together that the virus can spread easily from person to person.[7] In an effort to better predict influenza-like illness activity, Viboud has examined whether they can be forecast using heart rate information from activity trackers.[9]

During the COVID-19 pandemic, Viboud was part of international efforts to collect, curate and disseminate epidemiological information about SARS-CoV-2.[10][11] As part of this effort, she monitored the time between onset of symptoms and visiting a medical facility. She found that people in the Hubei province who experienced SARS-CoV-2 symptoms waited longer before seeking help than in other parts of China, or even those overseas.[10] The delay between symptom onset and visiting a clinic was found to decrease throughout January, which Viboud associated with and increase in news reports and content sharing on social media. She believed that a crowd-sourced, collaborative, physician-oriented social network helped to compile early SARS-CoV-2 data, as well as helping to track the progression of the outbreak.[10] These efforts helped to disseminate up-to-date and correct information when limited data was available.[10] She has also investigated why there are so few cases of COVID-19 in younger populations.[12]

Throughout February and March 2020 Viboud continued to monitor the evolving epidemic, looking to describe the epidemiology and transmission dynamics of SARS-CoV-2 as it spread beyond Hubei province.[13][14][15] Her findings identified that infectiousness peaked early in the disease and that transmission may occur before symptoms even manifest. She believes that as the pandemic progressed around the world, social distancing reduced the time for community transmission.[13]

Viboud evaluated the impact of travel restrictions on the spread of SARS-CoV-2, starting from the travel restrictions out of Wuhan from January 23.[16] She identified that the Wuhan travel ban only delayed the spread to mainland China by 5 days, but prevented international spread until the middle of February.[17] In April 2020, Viboud commented that the number of Americans who had lost their lives to SARS-CoV-2 was likely to be considerably higher than was officially reported.[18][19] Throughout the COVID-19 pandemic, Viboud was involved with regular conference calls with Centers for Disease Control and Prevention to provide expert advice on the ongoing pandemic.[20] She has documented her work on COVID-19 with the Center for Disease Dynamics, Economics & Policy.[21]

Selected publications

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  • Goodwin, K; Viboud, C; Simonsen, L (2006-02-20). "Antibody response to influenza vaccination in the elderly: A quantitative review". Vaccine. 24 (8): 1159–1169. doi:10.1016/j.vaccine.2005.08.105. ISSN 0264-410X. PMID 16213065.
  • Mockenhaupt, Maja; Viboud, Cécile; Dunant, Ariane; Naldi, Luigi; Halevy, Sima; Bavinck, Jan Nico Bouwes; Sidoroff, Alexis; Schneck, Jürgen; Roujeau, Jean-Claude; Flahault, Antoine (January 2008). "Stevens–Johnson Syndrome and Toxic Epidermal Necrolysis: Assessment of Medication Risks with Emphasis on Recently Marketed Drugs. The EuroSCAR-Study". Journal of Investigative Dermatology. 128 (1): 35–44. doi:10.1038/sj.jid.5701033. ISSN 0022-202X. PMID 17805350.
  • Viboud, Cécile; Bjørnstad, Ottar N.; Smith, David L. (2006-04-21). "Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza". Science. 312 (5772): 447–451. Bibcode:2006Sci...312..447V. doi:10.1126/science.1125237. PMID 16574822.

References

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  1. ^ "Cecile Viboud". The Conversation. 20 February 2018. Retrieved 2020-04-09.
  2. ^ a b Viboud, Cécile; Boëlle, Pierre-Yves; Carrat, Fabrice; Valleron, Alain-Jacques; Flahault, Antoine (2003-11-15). "Prediction of the Spread of Influenza Epidemics by the Method of Analogues". American Journal of Epidemiology. 158 (10): 996–1006. doi:10.1093/aje/kwg239. ISSN 0002-9262. PMID 14607808.
  3. ^ Viboud, Cecile; Chowell, Gerardo; Simonsen, Lone (5 March 2018). "How historical disease detectives are solving mysteries of the 1918 flu". The Conversation. Retrieved 2020-04-09.
  4. ^ "Cécile Viboud – MISMS". misms.net. Archived from the original on 2020-04-02. Retrieved 2020-04-09.
  5. ^ Viboud, Cécile; Epstein, Suzanne L. (2016-11-11). "First flu is forever". Science. 354 (6313): 706–707. Bibcode:2016Sci...354..706V. doi:10.1126/science.aak9816. ISSN 0036-8075. PMID 27846592. S2CID 3050246.
  6. ^ a b Howard, Jacqueline (10 November 2016). "Your flu risk may be linked to when you were born". CNN. Retrieved 2020-04-09.
  7. ^ a b Letzter, Rafi (5 October 2018). "Why Flu Epidemics Work Differently in Big American Cities". livescience.com. Retrieved 2020-04-09.
  8. ^ Dalziel, Benjamin D.; Kissler, Stephen; Gog, Julia R.; Viboud, Cecile; Bjørnstad, Ottar N.; Metcalf, C. Jessica E.; Grenfell, Bryan T. (2018-10-05). "Urbanization and humidity shape the intensity of influenza epidemics in U.S. cities". Science. 362 (6410): 75–79. Bibcode:2018Sci...362...75D. doi:10.1126/science.aat6030. ISSN 0036-8075. PMC 6510303. PMID 30287659.
  9. ^ Viboud, Cecile; Santillana, Mauricio (2020-02-01). "Fitbit-informed influenza forecasts". The Lancet Digital Health. 2 (2): e54–e55. doi:10.1016/S2589-7500(19)30241-9. ISSN 2589-7500. PMID 33334559.
  10. ^ a b c d Sun, Kaiyuan; Chen, Jenny; Viboud, Cécile (2020-04-01). "Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study". The Lancet Digital Health. 2 (4): e201–e208. doi:10.1016/S2589-7500(20)30026-1. ISSN 2589-7500. PMC 7158945. PMID 32309796.
  11. ^ "Le coronavirus Covid-19 se propagera-t-il plus que la grippe ?". Sciences et Avenir (in French). 28 February 2020. Retrieved 2020-04-09.
  12. ^ "Coronavirus: Who is most at risk?". www.thelocal.com. March 2020. Retrieved 2020-04-09.
  13. ^ a b Zhang, Juanjuan; Litvinova, Maria; Wang, Wei; Wang, Yan; Deng, Xiaowei; Chen, Xinghui; Li, Mei; Zheng, Wen; Yi, Lan; Chen, Xinhua; Wu, Qianhui (2020-04-02). "Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study". The Lancet Infectious Diseases. 20 (7): 793–802. doi:10.1016/S1473-3099(20)30230-9. ISSN 1473-3099. PMC 7269887. PMID 32247326.
  14. ^ Backer, Jantien A.; Klinkenberg, Don; Wallinga, Jacco (2020-02-06). "Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020". Eurosurveillance. 25 (5): 2000062. doi:10.2807/1560-7917.ES.2020.25.5.2000062. ISSN 1560-7917. PMC 7014672. PMID 32046819.
  15. ^ "New Analysis Suggests Months Of Social Distancing May Be Needed To Stop Virus". NPR.org. Retrieved 2020-04-09.
  16. ^ "Cecile Viboud". midasnetwork.us. Retrieved 2020-04-09.
  17. ^ Chinazzi, Matteo; Davis, Jessica T.; Ajelli, Marco; Gioannini, Corrado; Litvinova, Maria; Merler, Stefano; Piontti, Ana Pastore y; Mu, Kunpeng; Rossi, Luca; Sun, Kaiyuan; Viboud, Cécile (2020-03-06). "The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak". Science. 368 (6489): 395–400. Bibcode:2020Sci...368..395C. doi:10.1126/science.aba9757. ISSN 0036-8075. PMC 7164386. PMID 32144116.
  18. ^ Brown, Emma. "Coronavirus death toll: Americans are almost certainly dying of covid-19 but being left out of the official count". Washington Post. Retrieved 2020-04-09.
  19. ^ Henriques, Martha. "Coronavirus: Why death and mortality rates differ". www.bbc.com. Retrieved 2020-04-09.
  20. ^ Greenfieldboyce, Nell (4 March 2020). "How Computer Modeling Of COVID-19's Spread Could Help Fight The Virus". www.kcur.org. Retrieved 2020-04-09.
  21. ^ "Cecile Viboud". Center for Disease Dynamics, Economics & Policy (CDDEP). Archived from the original on 2020-05-25. Retrieved 2020-04-09.