Understanding unreported cases in the 2019 n-Cov epidemic outbreak and the importance of major public health interventions
We develop a mathematical model to provide epidemic predictions for the 2019-nCov epidemic in China. We use reported case data from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model we identify the number of unreported cases. We then use the model to project the epidemic forward with varying level of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling 2019-nCov epidemics. Next we will apply it to the data from South Korea, Italy, France and Germany.
Speaker:
Pierre Magal received his PhD degree from University of Pau (France) in 1996. He is a Full Professor at the Department of Life Sciences at the University of Bordeaux (France) from 1999. He is an expert in Differential Equations, Dynamical Systems and Mathematical Biology and is currently working on understanding and predicting COVID-19 spread through mathematical models.
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