■欧洲各国都面临着类似的SARS-CoV-2变种的演变,包括阿尔法,Delta,和Omicron变体。
■我们使用了来自GISAID的数据,自动数学替代模型,以研究超过2年的欧洲COVID-19变体的动态,从2020年底到2023年初。该模型识别了变体替代模式,并区分了残差行为和显性行为。我们使用来自19个欧洲国家的每周测序数据来估计连续SARS-CoV-2变体之间的传播性(Δβ)的增加。此外,我们专注于具有独立区域爆发和多个竞争变种的复杂情景的大国。
■我们的模型准确地再现了观察到的Alpha之间的替代模式,Delta,和Omicron主要变体。我们估计了每日变异患病率,并计算了变异之间的Δβ,揭示:(i)Δβ从Alpha到Omicron变体逐渐增加;(ii)Δβ在Omicron变体中显示出高度的变异性;(iii)较高的Δβ与该变体在一个国家内的较晚出现有关;(iv)人群针对先前变体的较高免疫程度与Delta变体的较高Δβ有关;(v)较大的国家表现出较小的βΔ,建议同一国家内区域不同的疫情;最后(VI)该模型可靠地捕获了竞争变种的动态,即使在复杂的场景中。
■使用数学模型可以对每个变体的每日病例进行精确可靠的估计。通过量化Δβ,我们追踪了不同变体在欧洲的传播,突出了从Alpha到Omicron的传播性趋势的强劲增长。此外,我们已经表明,一个国家的地理特征,以及新的变体入口的时间,可以解释各国在变体替代动态方面观察到的一些差异。
UNASSIGNED: Countries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants.
UNASSIGNED: We used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in
transmissibility ( Δ β ) between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants.
UNASSIGNED: Our model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δ β between variants, revealing that: ( i ) Δ β increased progressively from the Alpha to the Omicron variant; ( i i ) Δ β showed a high degree of variability within Omicron variants; ( i i i ) a higher Δ β was associated with a later emergence of the variant within a country; ( i v ) a higher degree of immunization of the population against previous variants was associated with a higher Δ β for the Delta variant; ( v ) larger countries exhibited smaller Δ β , suggesting regionally diverse outbreaks within the same country; and finally ( v i ) the model reliably captures the dynamics of competing variants, even in complex scenarios.
UNASSIGNED: The use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δ β , we have tracked the spread of the different variants across Europe, highlighting a robust increase in
transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.