College of Mathematical Sciences, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
Int J Infect Dis. 2022 Aug;121:195-202. doi: 10.1016/j.ijid.2022.05.031. Epub 2022 May 15.
Because of the spread of the Omicron variant, many countries have experienced COVID-19 case numbers unseen since the start of the pandemic. We aimed to compare the epidemiological characteristics of Omicron with previous variants and different strains of influenza to provide context for public health responses.
We developed transmission models for SARS-CoV-2 variants and influenza, in which transmission, death, and vaccination rates were taken to be time-varying. We fit our model based on publicly available data in South Africa, the United States, and Canada. We used this model to evaluate the relative transmissibility and mortality of Omicron compared with previous variants and influenza.
We found that Omicron is more transmissible and less fatal than both seasonal and 2009 H1N1 influenza and the Delta variant; these characteristics make Omicron epidemiologically more similar to influenza than it is to Delta. We estimate that as of February 7, 2022, booster doses have prevented 4.29×10 and 1.14×10 Omicron infections in the United States and Canada, respectively.
Our findings indicate that the high infectivity of Omicron will keep COVID-19 endemic, similar to influenza. However, because of Omicron's lower fatality rate, our work suggests that human populations living with SARS-CoV-2 are most likely.
由于奥密克戎变异株的传播,许多国家的 COVID-19 病例数达到了大流行开始以来从未见过的水平。我们旨在比较奥密克戎与之前的变异株和不同流感株的流行病学特征,为公共卫生应对措施提供背景信息。
我们开发了 SARS-CoV-2 变异株和流感的传播模型,其中传播、死亡和疫苗接种率被视为时变的。我们根据南非、美国和加拿大的公开数据对模型进行了拟合。我们使用该模型评估了奥密克戎与之前的变异株和流感相比的相对传染性和死亡率。
我们发现,奥密克戎比季节性和 2009 年 H1N1 流感以及德尔塔变异株更具传染性和致命性;这些特征使奥密克戎在流行病学上与流感更为相似,而不是与德尔塔相似。我们估计,截至 2022 年 2 月 7 日,在美国和加拿大,加强针分别预防了 4.29×10 和 1.14×10 例奥密克戎感染。
我们的研究结果表明,奥密克戎的高传染性将使 COVID-19 继续流行,类似于流感。然而,由于奥密克戎的死亡率较低,我们的研究表明,与 SARS-CoV-2 共存的人群很可能。