通过重复联合检测监测 SARS-CoV-2 流行情况:应用于瑞士常规数据。

IF 2.5 4区 医学 Q3 INFECTIOUS DISEASES Epidemiology and Infection Pub Date : 2024-08-22 DOI:10.1017/S0950268824000876
Julien Riou, Erik Studer, Anna Fesser, Tobias Magnus Schuster, Nicola Low, Matthias Egger, Anthony Hauser
{"title":"通过重复联合检测监测 SARS-CoV-2 流行情况:应用于瑞士常规数据。","authors":"Julien Riou, Erik Studer, Anna Fesser, Tobias Magnus Schuster, Nicola Low, Matthias Egger, Anthony Hauser","doi":"10.1017/S0950268824000876","DOIUrl":null,"url":null,"abstract":"<p><p>Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021-2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4-5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.</p>","PeriodicalId":11721,"journal":{"name":"Epidemiology and Infection","volume":"152 ","pages":"e100"},"PeriodicalIF":2.5000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Surveillance of SARS-CoV-2 prevalence from repeated pooled testing: application to Swiss routine data.\",\"authors\":\"Julien Riou, Erik Studer, Anna Fesser, Tobias Magnus Schuster, Nicola Low, Matthias Egger, Anthony Hauser\",\"doi\":\"10.1017/S0950268824000876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021-2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4-5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.</p>\",\"PeriodicalId\":11721,\"journal\":{\"name\":\"Epidemiology and Infection\",\"volume\":\"152 \",\"pages\":\"e100\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epidemiology and Infection\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1017/S0950268824000876\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiology and Infection","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1017/S0950268824000876","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0

摘要

通过报告的 RT-PCR 阳性检测对 SARS-CoV-2 进行监测,由于检测不是随机的,因此存在偏差。基于人群样本的流行率估计可以纠正这种偏差。在这种情况下,集合检测设计具有许多优势,但在分析此类数据方面仍存在一些挑战。我们开发了一个贝叶斯模型,旨在从重复集中检测数据中估算感染率,同时(i) 校正检测灵敏度;(ii) 传播检测灵敏度的不确定性;(iii) 包括时间和空间上的相关性。我们在模拟场景中对模型进行了验证,结果表明,当样本量至少为 500 个、集合规模低于 20 个、真实感染率低于 5%时,模型是可靠的。我们将该模型应用于 2021-2022 年在瑞士的学校、护理中心和工作场所收集的 149 万个集合测试。我们在这三种环境中发现了类似的动态变化,流行率在 2022 年冬季达到峰值,为 4-5%。我们还发现了不同地区的差异。学校中的流行率估计值与报告病例、住院人数和死亡人数相关(系数为 0.84 至 0.90)。我们的结论是,在许多实际情况下,集合测试设计是监测 SARS-CoV-2 和其他病毒的可靠且经济实惠的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Surveillance of SARS-CoV-2 prevalence from repeated pooled testing: application to Swiss routine data.

Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021-2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4-5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Epidemiology and Infection
Epidemiology and Infection 医学-传染病学
CiteScore
4.10
自引率
2.40%
发文量
366
审稿时长
3-6 weeks
期刊介绍: Epidemiology & Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope covers the zoonoses, outbreaks, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease, as well as some tropical infections. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections are of particular value.
期刊最新文献
A self-driven ESN-DSS approach for effective COVID-19 time series prediction and modelling. Identifying risk factors for clinical Lassa fever in Sierra Leone, 2019-2021. Association between age of paediatric index cases and household SARS-CoV-2 transmission. Analysis of Foodborne Outbreaks in Wenzhou City, China, 2012-2022. The health and demographic impacts of the "Russian flu" pandemic in Switzerland in 1889/1890 and in the years thereafter.
×
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