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

贝叶斯概率 2019年冠状病毒病(COVID-19) 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 置信区间 区间(图论) 接种疫苗 传递率(结构动力学) 2019-20冠状病毒爆发 人口学 生物 统计 环境卫生 地理 医学 病毒学 数学 内科学 爆发 物理 疾病 社会学 组合数学 传染病(医学专业) 隔振 量子力学 振动
作者
Rui Dong,Taojun Hu,Yunjun Zhang,Li Yang,Xiao‐Hua Zhou
出处
期刊:Vaccines [MDPI AG]
卷期号:10 (4): 496-496 被引量:16
标识
DOI:10.3390/vaccines10040496
摘要

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 (R0) 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 R0. 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.

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
驿路梨花完成签到,获得积分10
刚刚
Twonej应助北北采纳,获得30
1秒前
禁止吃桃完成签到 ,获得积分10
1秒前
7秒前
光亮白山完成签到 ,获得积分10
9秒前
爆米花应助Eden采纳,获得10
9秒前
好大白发布了新的文献求助10
11秒前
14秒前
18秒前
19秒前
Eden发布了新的文献求助10
22秒前
Orange应助北北采纳,获得30
23秒前
我想当太空人完成签到,获得积分10
27秒前
kkk完成签到,获得积分10
33秒前
1234hai完成签到 ,获得积分10
33秒前
Li完成签到,获得积分10
33秒前
斯文的楷瑞完成签到,获得积分10
34秒前
sw123完成签到 ,获得积分10
44秒前
学吗完成签到,获得积分10
50秒前
郝雨竹郝雨竹完成签到 ,获得积分10
51秒前
果汁狸完成签到 ,获得积分10
54秒前
只会查文献完成签到,获得积分10
56秒前
北北完成签到,获得积分10
57秒前
59秒前
马龙完成签到,获得积分10
1分钟前
英姑应助Eden采纳,获得10
1分钟前
十七岁男高中生完成签到 ,获得积分10
1分钟前
自由溪灵完成签到,获得积分10
1分钟前
kiki完成签到,获得积分10
1分钟前
Olivia完成签到,获得积分10
1分钟前
zpz完成签到 ,获得积分10
1分钟前
grass完成签到,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
高分求助中
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 800
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
T/SNFSOC 0002—2025 独居石精矿碱法冶炼工艺技术标准 300
The Impact of Lease Accounting Standards on Lending and Investment Decisions 250
The Linearization Handbook for MILP Optimization: Modeling Tricks and Patterns for Practitioners (MILP Optimization Handbooks) 200
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5851979
求助须知:如何正确求助?哪些是违规求助? 6275055
关于积分的说明 15627539
捐赠科研通 4967924
什么是DOI,文献DOI怎么找? 2678842
邀请新用户注册赠送积分活动 1623057
关于科研通互助平台的介绍 1579488