PIERRE MAGAL

Webinar (Europe-America)

• Infectious Disease Outbreaks 2019-2020

Webinar (Europe-Asia)

• Infectious Disease Outbreaks 2021-2022

Special volume co-organized

• Theories and Models on COVID-19 Epidemics in Biology

• Data Driven Modeling in Mathematical Biology in Frontiers in Applied Mathematics and Statistics

• Mathematical Modelling of Horizontally Transmitted Seasonal Diseases in Infectious Disease Reports

• Modeling Infectious Diseases in the light of COVID-19 pandemic in Mathematical Biosciences and Engineering

Papers on COVID-19

• 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

• Video of my talk at the Fields Institute for Research in Mathematical Sciences Toronto Canada on March 31 2020
• Video de mon exposé en Francais au Laboratoire Jacques-Louis Lions le 22 Avril 2020
• Slide of my talk at the EHESS: Workshop: Modeling the propagation of Covid-19 Monday May 18 2020
• Vidéo en Français de mon exposé aux Journées Pandémia Jeudi 18 Mars 2021