期刊
VIRUS EVOLUTION
卷 9, 期 2, 页码 -出版社
OXFORD UNIV PRESS
DOI: 10.1093/ve/vead070
关键词
Bayesian phylodynamics; birth-death; simulations; SARS-CoV-2; transmission advantage; reproductive number
类别
Phylodynamic methods are crucial for understanding the spread of infectious diseases, and large-scale genomic surveillance during the COVID-19 pandemic has increased the potential for dynamic inference from viral genomes. In this study, a new extension to the BEAST2 package called BDSKYλ is introduced and validated, which allows for the quantification of transmission rate differences between circulating variants. Using this method, the transmission advantage of the Omicron variant over the Delta variant in Berlin, Germany is quantified, highlighting the importance of incorporating lineage-specific transmission differences in phylodynamic inference.
Phylodynamic methods have lately played a key role in understanding the spread of infectious diseases. During the coronavirus disease (COVID-19) pandemic, large scale genomic surveillance has further increased the potential of dynamic inference from viral genomes. With the continual emergence of novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, explicitly allowing transmission rate differences between simultaneously circulating variants in phylodynamic inference is crucial. In this study, we present and empirically validate an extension to the BEAST2 package birth-death skyline model (BDSKY), BDSKY$\lambda $, which introduces a scaling factor for the transmission rate between independent, jointly inferred trees. In an extensive simulation study, we show that BDSKY$\lambda $ robustly infers the relative transmission rates under different epidemic scenarios. Using publicly available genome data of SARS-CoV-2, we apply BDSKY$\lambda $ to quantify the transmission advantage of the Omicron over the Delta variant in Berlin, Germany. We find the overall transmission rate of Omicron to be scaled by a factor of two with pronounced variation between the individual clusters of each variant. These results quantify the transmission advantage of Omicron over the previously circulating Delta variant, in a crucial period of pre-established non-pharmaceutical interventions. By inferring variant- as well as cluster-specific transmission rate scaling factors, we show the differences in transmission dynamics for each variant. This highlights the importance of incorporating lineage-specific transmission differences in phylodynamic inference.
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