Lukman Adewale F, Rauf Rauf I, Abiodun Oluwakemi, Oludoun Olajumoke, Ayinde Kayode, Ogundokun Roseline O
Department of Mathematics and Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
Department of Statistics, University of Abuja, Abuja, Nigeria.
Infect Dis Model. 2020;5:827-838. doi: 10.1016/j.idm.2020.10.002. Epub 2020 Oct 12.
The world at large has been confronted with several disease outbreak which has posed and still posing a serious menace to public health globally. Recently, COVID-19 a new kind of coronavirus emerge from Wuhan city in China and was declared a pandemic by the World Health Organization. There has been a reported case of about 8622985 with global death of 457,355 as of 15.05 GMT, June 19, 2020. South-Africa, Egypt, Nigeria and Ghana are the most affected African countries with this outbreak. Thus, there is a need to monitor and predict COVID-19 prevalence in this region for effective control and management. Different statistical tools and time series model such as the linear regression model and autoregressive integrated moving average (ARIMA) models have been applied for disease prevalence/incidence prediction in different diseases outbreak. However, in this study, we adopted the ARIMA model to forecast the trend of COVID-19 prevalence in the aforementioned African countries. The datasets examined in this analysis spanned from February 21, 2020, to June 16, 2020, and was extracted from the World Health Organization website. ARIMA models with minimum Akaike information criterion correction (AICc) and statistically significant parameters were selected as the best models. Accordingly, the ARIMA (0,2,3), ARIMA (0,1,1), ARIMA (3,1,0) and ARIMA (0,1,2) models were chosen as the best models for SA, Nigeria, and Ghana and Egypt, respectively. Forecasting was made based on the best models. It is noteworthy to claim that the ARIMA models are appropriate for predicting the prevalence of COVID-19. We noticed a form of exponential growth in the trend of this virus in Africa in the days to come. Thus, the government and health authorities should pay attention to the pattern of COVID-19 in Africa. Necessary plans and precautions should be put in place to curb this pandemic in Africa.
整个世界面临着几次疾病爆发,这些爆发已经并仍在对全球公共卫生构成严重威胁。最近,新型冠状病毒COVID-19在中国武汉市出现,并被世界卫生组织宣布为大流行病。截至2020年6月19日格林威治标准时间15:00,报告病例约8622985例,全球死亡457355例。南非、埃及、尼日利亚和加纳是受此次疫情影响最严重的非洲国家。因此,有必要监测和预测该地区COVID-19的流行情况,以便进行有效的控制和管理。不同的统计工具和时间序列模型,如线性回归模型和自回归积分滑动平均(ARIMA)模型,已被应用于不同疾病爆发中的疾病流行率/发病率预测。然而,在本研究中,我们采用ARIMA模型来预测上述非洲国家COVID-19的流行趋势。本分析中检验的数据集涵盖2020年2月21日至2020年6月16日,数据取自世界卫生组织网站。选择具有最小赤池信息准则校正(AICc)和统计显著参数的ARIMA模型作为最佳模型。因此,ARIMA(0,2,3)、ARIMA(0,1,1)、ARIMA(3,1,0)和ARIMA(0,1,2)模型分别被选为南非、尼日利亚、加纳和埃及的最佳模型。基于最佳模型进行预测。值得一提的是,ARIMA模型适用于预测COVID-19的流行情况。我们注意到在未来几天,这种病毒在非洲的趋势呈现出一种指数增长形式。因此,政府和卫生当局应关注非洲COVID-19的模式。应制定必要的计划和预防措施来遏制非洲的这一流行病。