埃博拉病毒差异性感染模型的数学分析

B. Onyango, G. O. Lawi, F. Tireito
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引用次数: 0

摘要

近年来,西非和刚果民主共和国是埃博拉病毒病(EVD)的主要流行区。埃博拉病毒造成的死亡每年都会发生,但在旱季自然会达到高峰。EVD 的平均致死率约为 50%。有关 EVD 传播动态的研究并未捕捉到该疾病的差异性感染方面。在这项研究中,我们建立了一个非线性差分传染性模型,该模型能捕捉到 EVD 的动态变化,以评估不同传染性对 EVD 的影响,并提出可能的干预措施。对模型的稳定性分析表明,该模型具有条件局部和全局稳定性。模型还显示出霍普夫分岔,这表明疾病的传播动态具有周期性。数值模拟结果表明,在疾病感染初期采取干预措施控制疾病,能更有效地减少疾病的传播。这些发现对设计旨在减少感染的干预措施具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Analysis of an Ebola Differential Infectivity Model
West Africa and the Democratic Republic of Congo have in the recent years experienced majority of the Ebola Virus Disease (EVD) burden. Deaths from EVD occur yearly but naturally peak during the dry season. The average EVD fatality rate is approximated at 50%. Studies done on the dynamics of EVD transmission have not captured the differential infectivity aspects of the disease. In this work, a nonlinear differential infectivity model with variation in infectiousness that captures the dynamics of EVD to assess the role of varied infectivity on EVD with possible intervention measures is formulated. Stability analysis of the model shows that the model is conditionally locally and globally stable. The model is also shown to exhibit hopf bifurcation, which shows that the transmission dynamics of the disease are periodic in nature. Numerical simulation results showed that intervention measures to control the disease is more efficient at the onset of the infection to reduce the spread of the disease. The findings are significant in designing intervention measures aimed at reducing infections.
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