Mathematical Modeling of COVID-19 with Periodic Transmission: The Case of South Africa

IF 0.9 Q3 MATHEMATICS, APPLIED Computational and Mathematical Methods Pub Date : 2023-02-15 DOI:10.1155/2023/9326843
Belthasara Assan, Farai Nyabadza
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Abstract

The data on SARS-CoV-2 (COVID-19) in South Africa show seasonal transmission patterns to date, with the peaks having occurred in winter and summer since the outbreaks began. The transmission dynamics have mainly been driven by variations in environmental factors and virus evolution, and the two are at the center of driving the different waves of the disease. It is thus important to understand the role of seasonality in the transmission dynamics of COVID-19. In this paper, a compartmental model with a time-dependent transmission rate is formulated and the stabilities of the steady states analyzed. We note that if R0 < 1, the disease-free equilibrium is globally asymptotically stable, and the disease completely dies out; and when R0 > 1, the system admits a positive periodic solution, and the disease is uniformly or periodically persistent. The model is fitted to data on new cases in South Africa for the first four waves. The model results indicate the need to consider seasonality in the transmission dynamics of COVID-19 and its importance in modeling fluctuations in the data for new cases. The potential impact of seasonality in the transmission patterns of COVID-19 and the public health implications is discussed.

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周期性传播COVID-19的数学模型:以南非为例
南非关于SARS-CoV-2 (COVID-19)的数据显示了迄今为止的季节性传播模式,自疫情开始以来,高峰发生在冬季和夏季。传播动态主要是由环境因素和病毒进化的变化驱动的,这两者是驱动疾病不同波的核心。因此,了解季节性在COVID-19传播动态中的作用非常重要。本文建立了具有时变传输速率的隔室模型,并分析了稳态的稳定性。我们注意到,当r0 = 1时,系统允许一个正周期解,并且疾病是均匀或周期性持续的。该模型适用于南非前四波新病例的数据。模型结果表明,需要考虑COVID-19传播动力学中的季节性及其在新病例数据波动建模中的重要性。讨论了季节性对COVID-19传播模式的潜在影响及其对公共卫生的影响。
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