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Brief Analysis of the ARIMA model on the COVID-19 in Italy
Guorong Ding; Xinru Li; Yang Shen; Jiao Fan.
Afiliação
  • Guorong Ding; Wuhan University of Science and Technology
  • Xinru Li; Wuhan University of Science and Technology
  • Yang Shen; Wuhan University of Science and Technology
  • Jiao Fan; Wuhan University of Science and Technology
Preprint em En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20058636
ABSTRACT
Coronavirus disease 2019 (COVID-19) has been considered as a global threat infectious disease, and various mathematical models are being used to conduct multiple studies to analyze and predict the evolution of this epidemic. We statistically analyze the epidemic data from February 24 to March 30, 2020 in Italy, and proposes a simple time series analysis model based on the Auto Regressive Integrated Moving Average (ARIMA). The cumulative number of newly diagnosed and newly diagnosed patients in Italy is preprocessed and can be used to predict the spread of the Italian COVID-19 epidemic. The conclusion is that an inflection point is expected to occur in Italy in early April, and some reliable points are put forward for the inflection point of the epidemic strengthen regional isolation and protection, do a good job of personal hygiene, and quickly treat the team leaders existing medical forces. It is hoped that the "City Closure" decree issued by the Italian government will go in the right direction, because this is the only way to curb the epidemic.
Licença
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Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Experimental_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Experimental_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint