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A Regression Model for Short-Term COVID-19 Pandemic Assessment
Communications in Computer and Information Science ; 1303:511-518, 2020.
Article in English | Scopus | ID: covidwho-1114285
ABSTRACT
COVID-19 has rapidly spread around the world in the past few months, researchers around the world are working around the clock to closely monitor and assess the development of this pandemic. In this paper, a time series regression model is built to assess the short-term progression of COVID-19 pandemic. The model structure and parameters are identified using COVID-19 pandemic data released by China within the time window from 22 January to 09 April 2020. The same model structure and parameters are applied to a few other countries for day ahead forecasting, showing a good fit of the model. This modeling exercise confirms that the underlying internal dynamics of this disease progression is quite similar. The differences in the impact of this pandemic on different countries are largely attributed to different eternal factors. © 2020, Springer Nature Singapore Pte Ltd.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Communications in Computer and Information Science Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Communications in Computer and Information Science Year: 2020 Document Type: Article