Impact of vaccination on Omicron's escape variants: Insights from fine-scale modelling of waning immunity in Hong Kong

IF 8.8 3区 医学 Q1 Medicine Infectious Disease Modelling Pub Date : 2024-09-16 DOI:10.1016/j.idm.2024.09.006
Yuling Zou , Wing-Cheong Lo , Wai-Kit Ming , Hsiang-Yu Yuan
{"title":"Impact of vaccination on Omicron's escape variants: Insights from fine-scale modelling of waning immunity in Hong Kong","authors":"Yuling Zou ,&nbsp;Wing-Cheong Lo ,&nbsp;Wai-Kit Ming ,&nbsp;Hsiang-Yu Yuan","doi":"10.1016/j.idm.2024.09.006","DOIUrl":null,"url":null,"abstract":"<div><div>COVID-19 vaccine-induced protection declines over time. This waning of immunity has been described in modelling as a lower level of protection. This study incorporated fine-scale vaccine waning into modelling to predict the next surge of the Omicron variant of the SARS-CoV-2 virus. In Hong Kong, the Omicron subvariant BA.2 caused a significant epidemic wave between February and April 2022, which triggered high vaccination rates. About half a year later, a second outbreak, dominated by a combination of BA.2, BA.4 and BA.5 subvariants, began to spread. We developed mathematical equations to formulate continuous changes in vaccine boosting and waning based on empirical serological data. These equations were incorporated into a multi-strain discrete-time Susceptible-Exposed-Infectious-Removed model. The daily number of reported cases during the first Omicron outbreak, with daily vaccination rates, the population mobility index and daily average temperature, were used to train the model. The model successfully predicted the size and timing of the second surge and the variant replacement by BA.4/5. It estimated 655,893 cumulative reported cases from June 1, 2022 to 31 October 2022, which was only 2.69% fewer than the observed cumulative number of 674,008. The model projected that increased vaccine protection (by larger vaccine coverage or no vaccine waning) would reduce the size of the second surge of BA.2 infections substantially but would allow more subsequent BA.4/5 infections. Increased vaccine coverage or greater vaccine protection can reduce the infection rate during certain periods when the immune-escape variants co-circulate; however, new immune-escape variants spread more by out-competing the previous strain.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 1","pages":"Pages 129-138"},"PeriodicalIF":8.8000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468042724001118/pdfft?md5=2e0c58621546ee3ac3d0fbd14dfae520&pid=1-s2.0-S2468042724001118-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042724001118","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

COVID-19 vaccine-induced protection declines over time. This waning of immunity has been described in modelling as a lower level of protection. This study incorporated fine-scale vaccine waning into modelling to predict the next surge of the Omicron variant of the SARS-CoV-2 virus. In Hong Kong, the Omicron subvariant BA.2 caused a significant epidemic wave between February and April 2022, which triggered high vaccination rates. About half a year later, a second outbreak, dominated by a combination of BA.2, BA.4 and BA.5 subvariants, began to spread. We developed mathematical equations to formulate continuous changes in vaccine boosting and waning based on empirical serological data. These equations were incorporated into a multi-strain discrete-time Susceptible-Exposed-Infectious-Removed model. The daily number of reported cases during the first Omicron outbreak, with daily vaccination rates, the population mobility index and daily average temperature, were used to train the model. The model successfully predicted the size and timing of the second surge and the variant replacement by BA.4/5. It estimated 655,893 cumulative reported cases from June 1, 2022 to 31 October 2022, which was only 2.69% fewer than the observed cumulative number of 674,008. The model projected that increased vaccine protection (by larger vaccine coverage or no vaccine waning) would reduce the size of the second surge of BA.2 infections substantially but would allow more subsequent BA.4/5 infections. Increased vaccine coverage or greater vaccine protection can reduce the infection rate during certain periods when the immune-escape variants co-circulate; however, new immune-escape variants spread more by out-competing the previous strain.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
疫苗接种对 Omicron 逃逸变种的影响:从香港免疫力下降的精细模型中获得的启示
COVID-19 疫苗诱导的保护作用会随着时间的推移而减弱。这种免疫力的减弱在建模中被描述为较低水平的保护。这项研究将细微的疫苗减弱纳入建模,以预测下一次 SARS-CoV-2 病毒的 Omicron 变体的飙升。在 2022 年 2 月至 4 月期间,香港的 Omicron 亚变异体 BA.2 引发了严重的疫潮,导致疫苗接种率居高不下。大约半年后,以 BA.2、BA.4 和 BA.5 亚变体组合为主的第二次疫情开始蔓延。我们根据经验性血清学数据建立了数学方程,用于计算疫苗增强和减弱的连续变化。这些方程被纳入一个多菌株离散时间易感-暴露-感染-清除模型。第一次 Omicron 疫情爆发期间报告的每日病例数、每日疫苗接种率、人口流动指数和日平均气温被用来训练模型。该模型成功预测了第二次疫情激增的规模和时间,以及 BA.4/5 的变异替换。它估计从 2022 年 6 月 1 日到 2022 年 10 月 31 日,累计报告病例数为 655,893 例,仅比观测到的累计病例数 674,008 例少 2.69%。该模型预测,加强疫苗保护(扩大疫苗覆盖范围或不减弱疫苗保护)将大大减少 BA.2 感染病例第二次激增的规模,但会使随后出现更多的 BA.4/5 感染病例。在免疫逃逸变异株共同流行的某些时期,增加疫苗覆盖率或加强疫苗保护可降低感染率;然而,新的免疫逃逸变异株通过竞争先前的毒株而传播得更广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
期刊最新文献
Evaluation of wastewater percent positive for assessing epidemic trends - A case study of COVID-19 in Shangrao, China Behavioural Change Piecewise Constant Spatial Epidemic Models Application of multiple linear regression model and long short-term memory with compartmental model to forecast dengue cases in Selangor, Malaysia based on climate variables Conditional logistic individual-level models of spatial infectious disease dynamics Information-guided adaptive learning approach for active surveillance of infectious diseases
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1