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

S. Hussen
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引用次数: 1

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.
基于几种统计模型的库尔德斯坦地区新冠肺炎病例预测
如今,被称为COVID-19的新型普遍疾病冠状病毒在全球范围内以几何级数传播,因此这种病原体被认为是人类面临的最危险的威胁。本研究旨在为伊拉克库尔德斯坦地区四个省近期的感染病例、康复病例和死亡病例建立最佳预测模型,从而通过在某些省实施更多的医疗保健措施来避免更多的生命损失。采用了指数平滑和ARIMA模型两种预测方法。结果表明,ARIMA模型和指数平滑模型对库尔德斯坦地区各省新冠肺炎感染病例的预测结果非常接近,预测模型显示,除非人们遵守政府的卫生保健指示并保持社交距离,否则疫情可能无法得到控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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