Suppr超能文献

全貌:根据重症病例数估算黄热病病毒感染发病率

The whole iceberg: estimating the incidence of yellow fever virus infection from the number of severe cases.

作者信息

Johansson Michael A, Vasconcelos Pedro F C, Staples J Erin

机构信息

Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, Fort Collins, Colorado, USA

Instituto Evandro Chagas, Department of Arbovirology and Hemorrhagic Fevers, Ministry of Health, Ananindeua, Pará State, Brazil.

出版信息

Trans R Soc Trop Med Hyg. 2014 Aug;108(8):482-7. doi: 10.1093/trstmh/tru092. Epub 2014 Jun 30.

Abstract

BACKGROUND

Like many infectious agents, yellow fever (YF) virus only causes disease in a proportion of individuals it infects and severe illness only represents the tip of the iceberg relative to the total number of infections, the more critical factor for virus transmission.

METHODS

We compiled data on asymptomatic infections, mild disease, severe disease (fever with jaundice or hemorrhagic symptoms) and fatalities from 11 studies in Africa and South America between 1969 and 2011. We used a Bayesian model to estimate the probability of each infection outcome.

RESULTS

For YF virus infections, the probability of being asymptomatic was 0.55 (95% credible interval [CI] 0.37-0.74), mild disease 0.33 (95% CI 0.13-0.52) and severe disease 0.12 (95% CI 0.05-0.26). The probability of death for people experiencing severe disease was 0.47 (95% CI 0.31-0.62).

CONCLUSIONS

In outbreak situations where only severe cases may initially be detected, we estimated that there may be between one and seventy infections that are either asymptomatic or cause mild disease for every severe case identified. As it is generally only the most severe cases that are recognized and reported, these estimates will help improve the understanding of the burden of disease and the estimation of the potential risk of spread during YF outbreaks.

摘要

背景

与许多感染源一样,黄热病(YF)病毒仅在其感染的一部分个体中引发疾病,相对于总感染数而言,严重疾病仅占冰山一角,而这对病毒传播更为关键。

方法

我们汇总了1969年至2011年间在非洲和南美洲开展的11项研究中关于无症状感染、轻症疾病、重症疾病(伴有黄疸或出血症状的发热)及死亡的数据。我们使用贝叶斯模型来估计每种感染结果的概率。

结果

对于黄热病病毒感染,无症状的概率为0.55(95%可信区间[CI] 0.37 - 0.74),轻症疾病为0.33(95% CI 0.13 - 0.52),重症疾病为0.12(95% CI 0.05 - 0.26)。重症患者的死亡概率为0.47(95% CI 0.31 - 0.62)。

结论

在最初可能仅检测到重症病例的疫情形势下,我们估计,每发现一例重症病例,可能存在1至70例无症状或导致轻症疾病的感染。由于通常只有最严重的病例才会被识别和报告,这些估计将有助于提高对疾病负担的认识以及对黄热病疫情期间潜在传播风险的评估。

相似文献

3
Impact of yellow fever on the developing world.黄热病对发展中世界的影响。
Adv Virus Res. 1999;53:5-34. doi: 10.1016/s0065-3527(08)60341-3.
4
The global burden of yellow fever.全球黄热病负担。
Elife. 2021 Mar 16;10:e64670. doi: 10.7554/eLife.64670.
7
Yellow fever: the recurring plague.黄热病:反复出现的瘟疫。
Crit Rev Clin Lab Sci. 2004;41(4):391-427. doi: 10.1080/10408360490497474.
8
Yellow fever in Asia-a risk analysis.亚洲的黄热病——风险分析。
J Travel Med. 2021 Apr 14;28(3). doi: 10.1093/jtm/taab015.
10
Yellow fever.黄热病
J Clin Virol. 2015 Mar;64:160-73. doi: 10.1016/j.jcv.2014.08.030. Epub 2014 Oct 24.

引用本文的文献

4
Mouse models as a tool to study asymptomatic DENV infections.小鼠模型作为研究登革病毒无症状感染的工具。
Front Cell Infect Microbiol. 2025 Mar 26;15:1554090. doi: 10.3389/fcimb.2025.1554090. eCollection 2025.
5
Pathogenesis and clinical management of arboviral diseases.虫媒病毒病的发病机制与临床管理
World J Virol. 2025 Mar 25;14(1):100489. doi: 10.5501/wjv.v14.i1.100489.
9
Assessing yellow fever outbreak potential and implications for vaccine strategy.评估黄热病爆发潜力及其对疫苗策略的影响。
PLOS Glob Public Health. 2024 Nov 13;4(11):e0003781. doi: 10.1371/journal.pgph.0003781. eCollection 2024.

本文引用的文献

4
5
The enigma of yellow fever in East Africa.东非黄热病之谜。
Rev Med Virol. 2008 Sep-Oct;18(5):331-46. doi: 10.1002/rmv.584.
7
The global distribution of yellow fever and dengue.黄热病和登革热的全球分布情况。
Adv Parasitol. 2006;62:181-220. doi: 10.1016/S0065-308X(05)62006-4.
9
Yellow fever: an update.黄热病:最新情况
Lancet Infect Dis. 2001 Aug;1(1):11-20. doi: 10.1016/S1473-3099(01)00016-0.

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