Forecasting of COVID-19 Cases in Kurdistan Region Using Some Statistical Models

Shekhmous Hassan Hussen
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Shekhmous Hassan Hussen: Department of Animal Production, College of Agricultural Engineering Sciences, University of Duhok, KR, Iraq

Academic Journal of Applied Mathematical Sciences, 2020, vol. 6, issue 8, 172-180

Abstract: Nowadays the new universal disease of the coronavirus that is called the epidemic COVID-19 is spread as geometric progression among the people around the world, so, such pathogen considered the most dangerous threat facing humanity. This study aimed to derive the best forecasting models for the close future cases of infected, recovered, and deaths in the four provinces of Kurdistan Region-Iraq to avoid more loss of human lives by applying more health care in certain province. Two forecasting methods were used including Exponential Smoothing and ARIMA models. The results indicate that both ARIMA and Exponential Smoothing models were close to each other for predicting the infected cases of COVID-19 in Kurdistan Region provinces, and the predicting models show that the pandemic might not be under control unless the people apply the government instructions for health care and keep social distances.

Keywords: Forecast; COVID-19; Kurdistan region; Statistical models. (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:arp:ajoams:2020:p:172-180

DOI: 10.32861/ajams.68.172.180

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