• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

新型冠状病毒(2019 - nCoV)感染的漏报率:利用日本撤离航班乘客数据进行的估计

The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights.

作者信息

Nishiura Hiroshi, Kobayashi Tetsuro, Yang Yichi, Hayashi Katsuma, Miyama Takeshi, Kinoshita Ryo, Linton Natalie M, Jung Sung-Mok, Yuan Baoyin, Suzuki Ayako, Akhmetzhanov Andrei R

机构信息

Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan.

Core Research for Evolutionary Science and Technology, Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan.

出版信息

J Clin Med. 2020 Feb 4;9(2):419. doi: 10.3390/jcm9020419.

DOI:10.3390/jcm9020419
PMID:32033064
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7074297/
Abstract

From 29 to 31 January 2020, a total of 565 Japanese citizens were evacuated from Wuhan, China on three chartered flights. All passengers were screened upon arrival in Japan for symptoms consistent with novel coronavirus (2019-nCoV) infection and tested for presence of the virus. Assuming that the mean detection window of the virus can be informed by the mean serial interval (estimated at 7.5 days), the ascertainment rate of infection was estimated at 9.2% (95% confidence interval: 5.0, 20.0). This indicates that the incidence of infection in Wuhan can be estimated at 20,767 infected individuals, including those with asymptomatic and mildly symptomatic infections. The infection fatality risk (IFR)-the actual risk of death among all infected individuals-is therefore 0.3% to 0.6%, which may be comparable to Asian influenza pandemic of 1957-1958.

摘要

2020年1月29日至31日,共有565名日本公民乘坐三架包机从中国武汉撤离。所有乘客抵达日本后均接受了新型冠状病毒(2019 - nCoV)感染相关症状筛查,并进行了病毒检测。假设病毒的平均检测窗口期可通过平均潜伏期(估计为7.5天)得知,感染确诊率估计为9.2%(95%置信区间:5.0,20.0)。这表明武汉的感染发生率估计为20767例感染者,包括无症状和轻症感染者。因此,感染致死风险(IFR)——所有感染者中实际的死亡风险——为0.3%至0.6%,这可能与1957 - 1958年的亚洲流感大流行相当。

相似文献

1
The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights.新型冠状病毒(2019 - nCoV)感染的漏报率:利用日本撤离航班乘客数据进行的估计
J Clin Med. 2020 Feb 4;9(2):419. doi: 10.3390/jcm9020419.
2
Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study.评估2020年1月至4月中国境内外新型冠状病毒的传播风险:一项基于旅行网络的建模研究
medRxiv. 2020 Mar 9:2020.02.04.20020479. doi: 10.1101/2020.02.04.20020479.
3
Effect of evacuation of Japanese residents from Wuhan, China, on preventing transmission of novel coronavirus infection: A modelling study.中国武汉日本居民撤离对预防新型冠状病毒感染传播的效果:建模研究。
J Infect Chemother. 2021 Mar;27(3):515-520. doi: 10.1016/j.jiac.2020.12.011. Epub 2020 Dec 16.
4
Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.国际旅行动态对 2019 年新型冠状病毒在印度国内传播的影响:基于起源的感染旅行者输入风险评估。
Global Health. 2020 May 12;16(1):45. doi: 10.1186/s12992-020-00575-2.
5
Estimating the prevalence and risk of COVID-19 among international travelers and evacuees of Wuhan through modeling and case reports.通过建模和病例报告估计武汉国际旅行者和撤离人员中的 COVID-19 流行率和风险。
PLoS One. 2020 Jun 23;15(6):e0234955. doi: 10.1371/journal.pone.0234955. eCollection 2020.
6
Nationwide Descriptive Epidemiological Study of Patients with COVID-19 Evacuated from Wuhan, China to Japan from January to February, 2020.2020 年 1 月至 2 月中国武汉撤侨至日本的 COVID-19 患者的全国描述性流行病学研究。
Jpn J Infect Dis. 2023 Jan 24;76(1):20-26. doi: 10.7883/yoken.JJID.2022.049. Epub 2022 Aug 31.
7
[Performance of screening of contacts of COVID-19 cases in same flight].[新冠病毒病病例同航班密切接触者筛查工作情况]
Zhonghua Liu Xing Bing Xue Za Zhi. 2023 May 10;44(5):713-719. doi: 10.3760/cma.j.cn112338-20230228-00112.
8
SARS-CoV-2 Screening Test for Japanese Returnees From Wuhan, China, January 2020.2020年1月针对从中国武汉返回日本人员的新型冠状病毒检测
Open Forum Infect Dis. 2020 Jun 20;7(7):ofaa243. doi: 10.1093/ofid/ofaa243. eCollection 2020 Jul.
9
Potential Maternal and Infant Outcomes from (Wuhan) Coronavirus 2019-nCoV Infecting Pregnant Women: Lessons from SARS, MERS, and Other Human Coronavirus Infections.新型冠状病毒(2019-nCoV)感染孕妇的母婴潜在结局:来自 SARS、MERS 和其他人类冠状病毒感染的教训。
Viruses. 2020 Feb 10;12(2):194. doi: 10.3390/v12020194.
10
Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.实时预测和预报源自中国武汉的 2019-nCoV 疫情在国内和国际的潜在传播:一项建模研究。
Lancet. 2020 Feb 29;395(10225):689-697. doi: 10.1016/S0140-6736(20)30260-9. Epub 2020 Jan 31.

引用本文的文献

1
Using meta-learning to recommend an appropriate time-series forecasting model.运用元学习为时间序列预测模型推荐合适的模型。
BMC Public Health. 2024 Jan 10;24(1):148. doi: 10.1186/s12889-023-17627-y.
2
Estimating infection fatality risk and ascertainment bias of COVID-19 in Osaka, Japan from February 2020 to January 2022.估算 2020 年 2 月至 2022 年 1 月日本大阪地区 COVID-19 的感染病死率和检出偏倚。
Sci Rep. 2023 Apr 4;13(1):5540. doi: 10.1038/s41598-023-32639-9.
3
Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor.新冠疫情封锁期间新德里化石燃料燃烧产生的空气污染代理指标二氧化氮:哨兵-5前体(5p)光谱仪传感器揭示的对天气的影响
Environ Dev Sustain. 2023 Feb 8:1-12. doi: 10.1007/s10668-023-02977-9.
4
Epidemiologic Parameters for COVID-19: A Systematic Review and Meta-Analysis.新型冠状病毒肺炎的流行病学参数:一项系统综述与荟萃分析
Med J Islam Repub Iran. 2022 Dec 19;36:155. doi: 10.47176/mjiri.36.155. eCollection 2022.
5
Machine learning based regional epidemic transmission risks precaution in digital society.基于机器学习的数字社会区域疫情传播风险防范。
Sci Rep. 2022 Nov 28;12(1):20499. doi: 10.1038/s41598-022-24670-z.
6
Zebrafish models of COVID-19.COVID-19 的斑马鱼模型。
FEMS Microbiol Rev. 2023 Jan 16;47(1). doi: 10.1093/femsre/fuac042.
7
Risk Factors Associated with Mental Health Outcomes during the Post-Quarantine Period of the COVID-19 in Saudi Population: A Cross-Sectional Study.沙特人群中COVID-19隔离期后心理健康结果的相关危险因素:一项横断面研究
Behav Sci (Basel). 2022 Oct 14;12(10):391. doi: 10.3390/bs12100391.
8
Artificial neural networks for prediction of COVID-19 in India by using backpropagation.使用反向传播的印度COVID-19预测人工神经网络
Expert Syst. 2022 Aug 2:e13105. doi: 10.1111/exsy.13105.
9
Anxiety, depression, stress, worry about COVID-19 and fear of loneliness during COVID-19 lockdown in Peru: A network analysis approach.秘鲁 COVID-19 封锁期间的焦虑、抑郁、压力、对 COVID-19 的担忧和对孤独的恐惧:网络分析方法。
Front Public Health. 2022 Sep 9;10:946697. doi: 10.3389/fpubh.2022.946697. eCollection 2022.
10
Agent Simulation Model of COVID-19 Epidemic Agent-Based on GIS: A Case Study of Huangpu District, Shanghai.基于 GIS 的 COVID-19 传染病agent 仿真模型:以上海市黄浦区为例。
Int J Environ Res Public Health. 2022 Aug 18;19(16):10242. doi: 10.3390/ijerph191610242.

本文引用的文献

1
Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates.新型冠状病毒 2019-nCoV (COVID-19):流行病学参数和疫情规模的早期估计。
Philos Trans R Soc Lond B Biol Sci. 2021 Jul 19;376(1829):20200265. doi: 10.1098/rstb.2020.0265. Epub 2021 May 31.
2
Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases.新型冠状病毒(COVID-19)感染死亡风险的实时估计:基于输出病例的推断
J Clin Med. 2020 Feb 14;9(2):523. doi: 10.3390/jcm9020523.
3
Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.新型冠状病毒感染肺炎在中国武汉的早期传播动力学。
N Engl J Med. 2020 Mar 26;382(13):1199-1207. doi: 10.1056/NEJMoa2001316. Epub 2020 Jan 29.
4
The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020.2020年中国武汉新型冠状病毒的传播范围
J Clin Med. 2020 Jan 24;9(2):330. doi: 10.3390/jcm9020330.
5
Infection fatality risk of the pandemic A(H1N1)2009 virus in Hong Kong.香港大流行 A(H1N1)2009 病毒的感染病死率风险。
Am J Epidemiol. 2013 Apr 15;177(8):834-40. doi: 10.1093/aje/kws314. Epub 2013 Mar 3.