Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
Department of Biology, McMaster University, Hamilton, Ontario, Canada.
J R Soc Interface. 2022 Jun;19(191):20220173. doi: 10.1098/rsif.2022.0173. Epub 2022 Jun 15.
Inferring the relative strength (i.e. the ratio of reproduction numbers) and relative speed (i.e. the difference between growth rates) of new SARS-CoV-2 variants is critical to predicting and controlling the course of the current pandemic. Analyses of new variants have primarily focused on characterizing changes in the proportion of new variants, implicitly or explicitly assuming that the relative speed remains fixed over the course of an invasion. We use a generation-interval-based framework to challenge this assumption and illustrate how relative strength and speed change over time under two idealized interventions: a constant-strength intervention like idealized vaccination or social distancing, which reduces transmission rates by a constant proportion, and a constant-speed intervention like idealized contact tracing, which isolates infected individuals at a constant rate. In general, constant-strength interventions change the relative speed of a new variant, while constant-speed interventions change its relative strength. Differences in the generation-interval distributions between variants can exaggerate these changes and modify the effectiveness of interventions. Finally, neglecting differences in generation-interval distributions can bias estimates of relative strength.
推断新型 SARS-CoV-2 变体的相对强度(即繁殖数之比)和相对速度(即增长率之差)对于预测和控制当前大流行的进程至关重要。对新变体的分析主要集中在表征新变体比例的变化上,隐含或明确地假设相对速度在入侵过程中保持不变。我们使用基于代间隔的框架来挑战这一假设,并说明在两种理想化干预措施下,相对强度和速度随时间的变化情况:一种是恒定强度干预,如理想化的疫苗接种或社交距离,它以恒定的比例降低传播率,另一种是恒定速度干预,如理想化的接触者追踪,它以恒定的速度隔离受感染的个体。一般来说,恒定强度的干预会改变新变体的相对速度,而恒定速度的干预会改变其相对强度。变体之间代间隔分布的差异会夸大这些变化,并改变干预措施的效果。最后,忽略代间隔分布的差异会导致对相对强度的估计产生偏差。