Mathematical modeling of COVID-19 pandemic in the context of sub-Saharan Africa: a short-term forecasting in Cameroon and Gabon.

IF 0.8 4区 数学 Q4 BIOLOGY
C H Nkwayep, S Bowong, B Tsanou, M A Aziz Alaoui, J Kurths
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引用次数: 3

Abstract

In this paper, we propose and analyse a compartmental model of COVID-19 to predict and control the outbreak. We first formulate a comprehensive mathematical model for the dynamical transmission of COVID-19 in the context of sub-Saharan Africa. We provide the basic properties of the model and compute the basic reproduction number $\mathcal {R}_0$ when the parameter values are constant. After, assuming continuous measurement of the weekly number of newly COVID-19 detected cases, newly deceased individuals and newly recovered individuals, the Ensemble of Kalman filter (EnKf) approach is used to estimate the unmeasured variables and unknown parameters, which are assumed to be time-dependent using real data of COVID-19. We calibrated the proposed model to fit the weekly data in Cameroon and Gabon before, during and after the lockdown. We present the forecasts of the current pandemic in these countries using the estimated parameter values and the estimated variables as initial conditions. During the estimation period, our findings suggest that $\mathcal {R}_0 \approx 1.8377 $ in Cameroon, while $\mathcal {R}_0 \approx 1.0379$ in Gabon meaning that the disease will not die out without any control measures in theses countries. Also, the number of undetected cases remains high in both countries, which could be the source of the new wave of COVID-19 pandemic. Short-term predictions firstly show that one can use the EnKf to predict the COVID-19 in Sub-Saharan Africa and that the second vague of the COVID-19 pandemic will still increase in the future in Gabon and in Cameroon. A comparison between the basic reproduction number from human individuals $\mathcal {R}_{0h}$ and from the SARS-CoV-2 in the environment $\mathcal {R}_{0v}$ has been done in Cameroon and Gabon. A comparative study during the estimation period shows that the transmissions from the free SARS-CoV-2 in the environment is greater than that from the infected individuals in Cameroon with $\mathcal {R}_{0h}$ = 0.05721 and $\mathcal {R}_{0v}$ = 1.78051. This imply that Cameroonian apply distancing measures between individual more than with the free SARS-CoV-2 in the environment. But, the opposite is observed in Gabon with $\mathcal {R}_{0h}$ = 0.63899 and $\mathcal {R}_{0v}$ = 0.39894. So, it is important to increase the awareness campaigns to reduce contacts from individual to individual in Gabon. However, long-term predictions reveal that the COVID-19 detected cases will play an important role in the spread of the disease. Further, we found that there is a necessity to increase timely the surveillance by using an awareness program and a detection process, and the eradication of the pandemic is highly dependent on the control measures taken by each government.

撒哈拉以南非洲地区COVID-19大流行的数学建模:喀麦隆和加蓬的短期预测。
在本文中,我们提出并分析了COVID-19的分区模型,以预测和控制疫情。我们首先建立了撒哈拉以南非洲地区COVID-19动态传播的综合数学模型。我们给出了模型的基本属性,并计算了参数值为常数时的基本再现数$\mathcal {R}_0$。然后,假设连续测量每周新发病例数、新发死亡病例数和新发康复病例数,使用集合卡尔曼滤波(EnKf)方法估计未测量变量和未知参数,假设这些变量和未知参数与COVID-19的真实数据具有时间依赖性。我们对提议的模型进行了校准,以适应喀麦隆和加蓬在封锁之前、期间和之后的每周数据。我们使用估计的参数值和估计的变量作为初始条件,提出了对这些国家当前大流行的预测。在估计期间,我们的研究结果表明,喀麦隆的$\mathcal {R}_0 \约为1.8377美元,而加蓬的$\mathcal {R}_0 \约为1.0379美元,这意味着如果这些国家不采取任何控制措施,该疾病将不会消失。此外,两国未被发现的病例数量仍然很高,这可能是新一波COVID-19大流行的根源。短期预测首先表明,人们可以使用EnKf预测撒哈拉以南非洲的COVID-19,并且未来在加蓬和喀麦隆,COVID-19大流行的第二个模糊值仍将增加。在喀麦隆和加蓬,对来自人类个体的基本繁殖数$\mathcal {R}_{0h}$和来自环境$\mathcal {R}_{0v}$的SARS-CoV-2进行了比较。估算期间的对比研究表明,喀麦隆环境中游离SARS-CoV-2的传播量大于感染个体的传播量,分别为$\mathcal {R}_{0h}$ = 0.05721和$\mathcal {R}_{0v}$ = 1.78051。这意味着喀麦隆人更多地采取个人之间的距离措施,而不是与环境中游离的SARS-CoV-2保持距离。但是,加蓬的情况正好相反,$\mathcal {R}_{0h}$ = 0.63899, $\mathcal {R}_{0v}$ = 0.39894。因此,在加蓬加强提高认识运动以减少人与人之间的接触是很重要的。然而,长期预测表明,COVID-19检测到的病例将在疾病的传播中发挥重要作用。此外,我们发现有必要通过使用意识计划和检测过程来增加及时的监测,并且根除大流行高度依赖于各国政府采取的控制措施。
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
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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