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Analysis and Forecasting COVID-19 Outbreak in Pakistan Using decomposition and ensemble model

Computers, Materials & Continua 2021年第7期68卷 841-856页

作者： Xiaoli Qiang Muhammad Aamir Muhammad Naeem Shaukat Ali Adnan Aslam Zehui Shao Institute of Computing Science and Technology Guangzhou UniversityGuangzhou510006China Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan Department of English University of MalakandChakdara188800Pakistan Department of Natural Sciences and Humanities University of Engineering and TechnologyLahore54000Pakistan

COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the *** the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new *** this study,we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases,deaths,and recoveries in Pakistan for the upcoming month until the end of *** the decomposition of data,the ensemble Empirical Mode decomposition(EEMD)technique is *** decomposes the data into small components,called Intrinsic Mode Functions(IMFs).For individual IMFs modelling,we use the Autoregressive Integrated Moving Average(ARIMA)*** data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily *** analyses reveal that the number of recoveries,new cases,and deaths are increasing in Pakistan *** on the selected EEMD-ARIMA model,the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020,which is an increase of almost 1.46 times with a 95%prediction interval of 246,529 to 376,*** 95%prediction interval for recovery is 162,414 to 224,579,with an increase of almost two times in total from 100802 to 193495 by 31 July *** the other hand,the deaths are expected to increase from 4395 to 6751,which is almost 1.54 times,with a 95%prediction interval of 5617 to ***,the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July *** also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19,and that it is capable of keeping track of the real COVID-19 data in nearly all *** decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.

关键词： Analysis ARIMA COVID-19 decomposition and ensemble model forecasting

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