School of Mathematics and Statistics, Jiangxi Normal University, Nanchang, 330000, China; Department of Mathematics, University of Florida, Gainesville, FL 32611, United States of America.
China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
J Theor Biol. 2023 May 21;565:111468. doi: 10.1016/j.jtbi.2023.111468. Epub 2023 Mar 20.
COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.
由 SARS-CoV-2 感染引起的 COVID-19 在全球范围内造成了前所未有的大流行。病毒的新变种已经出现并主导了病毒种群。在本文中，我们开发了一个具有无症状传播的多株模型，以研究无症状或症状前感染如何影响不同株之间的传播以及旨在减轻大流行的控制策略。分析和数值结果都表明，无症状传播的模型仍然符合竞争排斥原理。通过将模型拟合到美国的 COVID-19 病例和病毒变异数据，我们表明，奥密克戎变体比以前流行的变体更具传染性但致命性更低。奥密克戎变体的基本繁殖数估计为 11.15，大于以前的变体。我们以口罩令为例，展示了在流行高峰之前实施它可以显著降低和推迟高峰。取消口罩令的时间会影响后续波的出现和频率。在高峰之前取消限制将导致更早和更高的后续波。在很大一部分人口仍然易感的情况下，解除限制也应谨慎。这里获得的方法和结果可应用于使用其他控制措施研究具有无症状传播的其他传染病的动力学。
