National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
National Institute of Health Dr. Ricardo Jorge, Lisbon, Portugal.
Euro Surveill. 2018 Sep;23(37). doi: 10.2807/1560-7917.ES.2018.23.37.1700802.
BackgroundHAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbreak detection. A descriptive analysis was performed on the timeliness, completeness, epidemiological data and geographic coverage of the dataset. Length and genomic region of the sequences were reviewed as well as the numerical and geographical distribution of the genotypes. The geographical signal in the sequences was assessed based on a short common nt stretch using a 100% identity analysis. The 9,211 reports were heterogeneous for completeness and timeliness, and for length and genomic region of the sequences. Some parts of the world were not represented by the sequences. Geographical differences in prevalence of HAV genotypes described previously could be confirmed with this dataset and for a third (1,075/3,124) of the included sequences, 100% identity of the short common sequence coincided with an identical country of origin. Analysis of a subset of short, shared sequences indicates that a geographical annotation on the level of individual countries is possible with the HAVNet data. If the current incompleteness and heterogeneity of the data can be improved on, HAVNet could become very useful as a worldwide reference set for geographical annotation and for backtracing and outbreak detection.
HAVNet 是一个国际实验室网络,在在线数据库中共享甲型肝炎病毒的序列和相应的元数据。我们概述了该数据集的流行病学和遗传数据,并评估了其用于地理注释、溯源和暴发检测的可用性。对数据集的及时性、完整性、流行病学数据和地理覆盖范围进行了描述性分析。审查了序列的长度和基因组区域以及基因型的数值和地理分布。根据 100%同一性分析,基于短的共同 nt 片段评估了序列中的地理信号。9211 份报告在完整性和及时性、序列的长度和基因组区域方面存在差异。世界上的一些地区没有序列代表。本数据集可证实先前描述的甲型肝炎病毒基因型的流行在地理上的差异,并且对于包含的序列中的三分之一(1,075/3,124),短的共同序列的 100%同一性与相同的起源国相吻合。对短共享序列的子集进行分析表明,HAVNet 数据可用于对个别国家进行地理注释。如果能够改进当前数据的不完整性和异质性,HAVNet 可能会成为一个非常有用的全球参考数据集,用于地理注释以及溯源和暴发检测。