ARIMA MODEL IN PREDICTING OF COVID-19 EPIDEMIC FOR THE SOUTHERN AFRICA REGION.

Q4 Medicine
Shoko Claris, Njuho Peter
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引用次数: 2

Abstract

Background: Coronavirus pandemic, a serious global public health threat, affects the Southern African countries more than any other country on the continent. The region has become the epicenter of the coronavirus with South Africa accounting for the most cases. To cap the deadly effect caused by the pandemic, we apply a statistical modelling approach to investigate and predict COVID-19 incidence.

Methods: Using secondary data on the daily confirmed COVID-19 cases per million for Southern Africa Development Community (SADC) member states from March 5, 2020, to July 15, 2021, we model and forecast the spread of coronavirus in the region. We select the best ARIMA model based on the log-likelihood, AIC, and BIC of the fitted models.

Results: The ARIMA (11,1,11) model for the complete data set was finally selected among ARIMA models based upon the parameter test and the Box-Ljung test. The ARIMA(11,1,9) was the best candidate for the training set. A 15-day forecast was also made from the model, which shows a perfect fit with the testing set.

Conclusion: The number of new COVID-19 cases per million for the SADC shows a downward trend, but the trend is characterized by peaks from time to time. Tightening up of the preventive measures continuously needs to be adapted in order to eradicate the coronavirus epidemic from the population.

Abstract Image

Abstract Image

Abstract Image

Arima模型在南部非洲地区COVID-19流行预测中的应用
背景:冠状病毒大流行是严重的全球公共卫生威胁,对南部非洲国家的影响超过非洲大陆任何其他国家。该地区已成为冠状病毒的中心,南非的病例最多。为了限制大流行造成的致命影响,我们采用统计建模方法来调查和预测COVID-19的发病率。方法:利用南部非洲发展共同体(SADC)成员国2020年3月5日至2021年7月15日每日每百万确诊病例的二手数据,对该地区冠状病毒的传播进行建模和预测。我们根据拟合模型的对数似然、AIC和BIC选择最佳的ARIMA模型。结果:经过参数检验和Box-Ljung检验,最终在ARIMA模型中选择了完整数据集的ARIMA(11,1,11)模型。ARIMA(11,1,9)是训练集的最佳候选。该模型还进行了15天的预测,与测试集完美吻合。结论:南共体新发病例数呈下降趋势,但呈阶段性高峰。为了从人群中根除冠状病毒的流行,需要不断加强预防措施。
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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来源期刊
African Journal of Infectious Diseases
African Journal of Infectious Diseases Medicine-Infectious Diseases
CiteScore
1.60
自引率
0.00%
发文量
32
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