Ben Hassen Hanen, Elaoud Anis, Ben Salah Nahla, Masmoudi Afif
Laboratory of Probability and Statistics, Faculty of Sciences of Sfax, Sfax University, Sfax, Tunisia.
Laboratory of Environmental Sciences and Technologies, Higher Institute of Sciences and Technologies of Environment, Carthage University, Tunis, Tunisia.
Arab J Sci Eng. 2021;46(1):93-102. doi: 10.1007/s13369-020-04792-0. Epub 2020 Jul 23.
2019-nCoV is a virulent virus belonging to the coronavirus family that caused the new pneumonia (COVID-19) which has spread internationally very rapidly and has become pandemic. In this research paper, we set forward a statistical model called SIR-Poisson that predicts the evolution and the global spread of infectious diseases. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. More precisely, it is used to infer the transmission of the COVID-19 in the three Maghreb Central countries (Tunisia, Algeria, and Morocco). Using the SIR-Poisson model and based on daily reported disease data, since its emergence until end April 2020, we attempted to predict the future disease period over 60 days. The estimated average number of contacts by an infected individual with others was around 2 for Tunisia and 3 for Algeria and Morocco. Relying on inferred scenarios, although the pandemic situation would tend to decline, it has not ended. From this perspective, the risk of COVID-19 spreading still exists after the deconfinement act. It is necessary, therefore, to carry on the containment until the estimated infected number achieves 0.
2019新型冠状病毒是一种属于冠状病毒科的高致病性病毒，它引发了新型肺炎（COVID-19），该肺炎在国际上传播速度极快，已成为大流行病。在本研究论文中，我们提出了一种名为SIR-泊松的统计模型，用于预测传染病的演变和全球传播情况。所提出的SIR-泊松模型能够预测未来一段时间内的感染病例范围。更确切地说，它被用于推断COVID-19在马格里布中部三个国家（突尼斯、阿尔及利亚和摩洛哥）的传播情况。利用SIR-泊松模型并基于每日报告的疾病数据，自COVID-19出现至2020年4月底，我们试图预测未来60天的疾病情况。突尼斯一名感染者与他人的估计平均接触次数约为2次，阿尔及利亚和摩洛哥为3次。根据推断的情景，尽管大流行情况趋于下降，但尚未结束。从这个角度来看，解封后COVID-19传播的风险仍然存在。因此，有必要继续实施隔离措施，直到估计感染人数达到0。
