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Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron

Rui Dong Yau Mathematical Sciences Center, Tsinghua University, Beijing, China; Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Beijing, China Taojun Hu Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China Yunjun Zhang Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China Yang Li Chongqing School, University of Chinese Academy of Sciences, Chongqing 400020, China Xiao-Hua Zhou Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Beijing International Center for Mathematical Research, Peking University, Beijing 100191, China

Data Analysis, Bio-Statistics, Bio-Mathematics mathscidoc:2204.42002

Vaccines, 10, (4), 496, 2022.3
Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R_0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high R_0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed.
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@inproceedings{rui2022assessing,
  title={Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron},
  author={Rui Dong, Taojun Hu, Yunjun Zhang, Yang Li, and Xiao-Hua Zhou},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20220428144145657908148},
  booktitle={Vaccines},
  volume={10},
  number={4},
  pages={496},
  year={2022},
}
Rui Dong, Taojun Hu, Yunjun Zhang, Yang Li, and Xiao-Hua Zhou. Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron. 2022. Vol. 10. In Vaccines. pp.496. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20220428144145657908148.
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