Unknown

Dataset Information

0

SI epidemic model applied to COVID-19 data in mainland China.


ABSTRACT: The article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit to the early cumulative data of SARS-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some results 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.

SUBMITTER: Demongeot J 

PROVIDER: S-EPMC7813244 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

SI epidemic model applied to COVID-19 data in mainland China.

Demongeot J J   Griette Q Q   Magal P P  

Royal Society open science 20201202 12


The article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit to the early cumulative data of SARS-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some results on the parameters identification. The last part  ...[more]

Similar Datasets

| S-EPMC8056483 | biostudies-literature
| S-EPMC7669363 | biostudies-literature
| S-EPMC8024219 | biostudies-literature
| S-EPMC7603985 | biostudies-literature
| S-EPMC8796085 | biostudies-literature
| S-EPMC8464399 | biostudies-literature
| S-EPMC7256610 | biostudies-literature
| S-EPMC7565247 | biostudies-literature