Special volume co-organized
Please send an email to one the co-organizing editors to let us know when you submit an article in these special volumes
Papers on COVID-19
- J. Demongeot and P. Magal, (2022) Spectral method in epidemic time series Biology (To appear)
- J. Demongeot, Q. Griette, Y. Maday, P. Magal, (2022) A Kermack-McKendrick model with age of infection starting from a single or multiple cohorts of infected patients Proceedings of the Royal Society A (To appear) Supplementary material
- Jacques Demongeot, Quentin Griette, Pierre Magal, and Glenn Webb (2022) Vaccine efficacy for COVID-19 outbreak in New York City Biology 2022, 11(3), 345.
- Q. Griette, Z. Liu, P. Magal and R. N. Thompson (2022) Real-time prediction of the end of an epidemic wave: COVID-19 in China as a case-study, (V. Kumar Murty, Jianhong Wu editors) Mathematics of Public Health, Fields Institute Communications, Springer International Publishing
- Q. Griette, J. Demongeot and P. Magal (2021) What can we learn from COVID-19 data by using epidemic models with unidentified infectious cases? Mathematical Biosciences and Engineering, 19(1): 537–594.
- Q. Griette, J. Demongeot and P. Magal (2021) A robust phenomenological approach to investigate COVID-19 data for France Mathematics in Applied Sciences and Engineering, Vol. 2 No. 3 (2021): pp. 149-218.
- Q. Griette and P. Magal (2021) Clarifying predictions for COVID-19 from testing data: the example of New York State, Infectious Disease Modelling, Volume 6, Pages 273-283.
- Z. Liu, P. Magal, G. Webb (2021) Predicting the number of reported and unreported cases for the COVID-19 epidemics in China, South Korea, Italy, France, Germany and United Kingdom Journal of Theoretical Biology Volume 509, 21.
- J. Demongeot, Q. Griette and P. Magal (2020) SI epidemic model applied to COVID-19 data in mainland China Royal Society Open Science 7:201878. doi
- Q. Griette, P. Magal and O. Seydi (2020), Unreported cases for Age Dependent COVID-19 Outbreak in Japan, Biology 9, 132.
- R.M. Cotta, C.P. Naveira-Cotta and P. Magal (2020), Modelling the COVID-19 epidemics in Brasil: Parametric identification and public health measures influence, Biology 2020, 9(8), 220.
- P. Magal and G. Webb, Predicting the number of reported and unreported cases for the COVID-19 epidemic in South Korea, Italy, France and Germany, medRxiv
- Z. Liu, P. Magal, O. Seydi, and G. Webb (2020), A model to predict COVID-19 epidemics with applications to South Korea, Italy, and Spain, SIAM News May 01 2020.
- Z. Liu, P. Magal, O. Seydi, and G. Webb (2020), A COVID-19 epidemic model with latency period, Infectious Disease Modelling 5, Pages 323-337.
- Z. Liu, P. Magal, O. Seydi, and G. Webb (2020), Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data, Mathematical Biosciences and Engineering 17(4), 3040-3051.
- Z. Liu, P. Magal, O. Seydi, and G. Webb (2020), Understanding unreported cases in the 2019-nCov epidemic outbreak in Wuhan, China, and the importance of major public health interventions, Biology, 9(3), 50.
Talks on COVID-19
Institut de Mathématiques de Bordeaux,
Université de Bordeaux,
351 cours de la libération
33400 Talence, France
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