School of Mathematics, Hefei University of Technology, Hefei, Anhui 230009, China.
School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China.
J Theor Biol. 2023 Oct 7;574:111611. doi: 10.1016/j.jtbi.2023.111611. Epub 2023 Aug 26.
XBB, an Omicron subvariant of SARS-CoV-2 that began to circulate in late 2022, has been dominant in the US since early 2023. To quantify the impact of XBB on the progression of COVID-19, we propose a new mathematical model which describes the interplay between XBB and other SARS-CoV-2 variants at the population level and which incorporates the effects of reinfection. We apply the model to COVID-19 data in the US that include surveillance data on the cases and variant proportions from the New York City, the State of New York, and the State of Washington. Our fitting and simulation results show that the transmission rate of XBB is significantly higher than that of other variants and the reinfection from XBB may play an important role in shaping the pandemic/epidemic pattern in the US.
XBB,一种奥密克戎的 SARS-CoV-2 亚变种,于 2022 年末开始传播,自 2023 年初以来已成为美国的主要流行株。为了量化 XBB 对 COVID-19 进展的影响,我们提出了一个新的数学模型,该模型描述了 XBB 与其他 SARS-CoV-2 变体在人群水平上的相互作用,并纳入了再感染的影响。我们将该模型应用于美国的 COVID-19 数据,其中包括来自纽约市、纽约州和华盛顿州的病例和变体比例的监测数据。我们的拟合和模拟结果表明,XBB 的传播率明显高于其他变体,而 XBB 的再感染可能在美国大流行/疫情模式中发挥重要作用。