Reem Razzaq Abdul Hussein 1 , Zainab Falih Hamza2 , and Bassam Talib Sabri3
1Department of Business Information Technology, College of Business Informatics, University of Information Technology and Communications, Baghdad, Iraq
Received: December 27, 2020 Accepted: January 28, 2021 Publication Date: October 1, 2021
In November 2019, cases of a new virus called coronavirus disease 2019 (COVID-19) were recorded in Wuhan City, China. The outbreak of such disease became a global health crisis after the World Health Organization declared it as a pandemic in March 2020. Syndrome severe acute respiratory system (2002/2003) and respiratory syndrome in the Middle East (2012/2013) are examples of pandemics that affected the whole world. They spread rapidly in different countries, including the Middle East, wherein Iraq was almost one of the last countries to be affected. The first case of COVID-19, which was an Iranian student, occurred in the city of Najaf on 24 February 2020. Afterward, other infected cases were detected, and Iraq recorded a total of 1,387 infected individuals and 195 related deaths up to 14 April 2020. This study aims to predict the number of infections caused by a temperature increase factor in Iraq. In this study, a time series algorithm called autoregressive integrated moving average is used. From 24 February 2020 to 14 April 2020 and 10 September 2020 to 30 October 2020, knowledge about expected confirmed cases is extracted. The examined cases have increased from 2,407,183 to 2,724,328 within the study period (September to October 2020).
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