Estimation of COVID-19 prevalence in Italy, Spain, and France
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Abstract
At the end of December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan city, China. As of April
15, 2020, N1.9 million COVID-19 cases were confirmed worldwide, including N120,000 deaths. There is an urgent
need to monitor and predict COVID-19 prevalence to control this spread more effectively. Time series models are
significant in predicting the impact of the COVID-19 outbreak and taking the necessary measures to respond to
this crisis. In this study, Auto-Regressive Integrated Moving Average (ARIMA) models were developed to predict
the epidemiological trend of COVID-19 prevalence of Italy, Spain, and France, the most affected countries of
Europe. The prevalence data of COVID-19 from 21 February 2020 to 15 April 2020 were collected from the
World Health Organization website. Several ARIMA models were formulated with different ARIMA parameters.
ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) models with the lowest MAPE values (4.7520, 5.8486, and
5.6335) were selected as the best models for Italy, Spain, and France, respectively. This study shows that
ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis
can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of
these regions. Besides, the prediction of COVID-19 prevalence trends of Italy, Spain, and France can help take precautions and policy formulation for this epidemic in other countries.
Link to resource
https://doi.org/10.1016/j.scitotenv.2020.138817Collections
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