利用logistic增长和多项式回归模型预测阿尔及利亚COVID-19病例

M. Lounis, B. Malavika
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引用次数: 0

摘要

新型冠状病毒呼吸系统疾病2019 (COVID-19)自2019年12月在中国武汉爆发以来,仍在全球蔓延,截至2021年1月3日,报告病例超过8440万例,死亡人数超过180万例。在这项工作中,我们利用阿尔及利亚卫生部2020年2月25日至12月2日报告的COVID-19病例数据,使用了logistic增长模型和多项式回归模型两种模型来预测阿尔及利亚的COVID-19病例。结果表明,多项式回归模型与Logistic模型拟合较好。第一种模型估计2021年1月19日的病例数为387673例。这种模式可以帮助阿尔及利亚当局防治这种疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models
The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.
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