Short-term prediction model for daily COVID-19 reported positive cases in Senegal

A. Diop, Abdourahmane Ndao, C. Seck, I. Faye
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引用次数: 2

Abstract

In this work, we use an Auto-Regressive Integrated Moving Average (ARIMA) model to study the evolution of COVID-19 disease in Senegal and then make short-term predictions about the number of people likely to be infected by the coronavirus. We are dealing with daily data provided by the Senegalese Ministry of Health during the period from March 2, 2020 to March 2, 2021.Our results show that the peak of the disease appearsduring the second wave seems to be reached on February 12 2021. But they also show that the number of COVID-19 infections will be around 200 cases per day during the next 30 days if the trend of the total number of tests performed is maintained.
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塞内加尔每日COVID-19报告阳性病例的短期预测模型
在这项工作中,我们使用自回归综合移动平均(ARIMA)模型研究了塞内加尔COVID-19疾病的演变,然后对可能感染冠状病毒的人数进行了短期预测。我们正在处理塞内加尔卫生部在2020年3月2日至2021年3月2日期间提供的每日数据。我们的结果表明,在第二波期间出现的疾病高峰似乎在2021年2月12日达到。但它们也表明,如果保持检测总数的趋势,未来30天内COVID-19感染人数将达到每天200例左右。
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