Author: Demongeot, J.; Griette, Q.; magal, p.
Title: SI epidemic model applied to COVID-19 data in mainland China Cord-id: 2y6he9yz Document date: 2020_10_21
ID: 2y6he9yz
Snippet: The article is devoted the parameters identification in the SI model. We consider several method, starting from Liu et al. [17] to fit the early cumulative data of Sars-CoV2 in mainland China. This method provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result in the spirit of Hadeler [19]. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some result on the parameters identification.
Document: The article is devoted the parameters identification in the SI model. We consider several method, starting from Liu et al. [17] to fit the early cumulative data of Sars-CoV2 in mainland China. This method provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result in the spirit of Hadeler [19]. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some result on the parameters identification. The last part of the paper is devoted to some numerical Algorithms to fit a daily piecewise constant rate of transmission.
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