Johansson Michael A, Vasconcelos Pedro F C, Staples J Erin
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.
Trans R Soc Trop Med Hyg. 2014 Aug;108(8):482-7. doi: 10.1093/trstmh/tru092. Epub 2014 Jun 30.
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.
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.
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).
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.
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。
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。
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)。
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。