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Prediction of Daily Covid-19 Cases in European Countries Using Automatic Arima Model
Author(s) -
Tahir Mumtaz Awan,
Faheem Aslam
Publication year - 2020
Publication title -
deleted journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 13
ISSN - 2279-9028
DOI - 10.4081/jphr.2020.1765
Subject(s) - autoregressive integrated moving average , covid-19 , pandemic , sample (material) , china , geography , demography , econometrics , time series , statistics , economics , mathematics , medicine , virology , sociology , outbreak , chemistry , disease , archaeology , pathology , chromatography , infectious disease (medical specialty)
The recent pandemic (COVID-19) emerged in Wuhan city of China and after causing a lot of destruction there recently changed its epicenter to Europe. There are countless people affected and reported cases are increasing day by day. Predictive models need to consider previous reported cases and forecast the upcoming number of cases. Automatic ARIMA, one of the predictive models used for forecasting contagions, was used in this study to predict the number of confirmed cases for next 10 days in four top European countries through R package “forecast”. The study finds that Auto ARIMA applied on the sample satisfactorily forecasts the confirmed cases of coronavirus for next ten days. The confirmed cases for the four countries show an increasing trend for the next ten days with Spain with a highest number of expected new confirmed cases, followed by Germany and France. Italy is expected to have lowest number of new confirmed cases among the four countries.

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