Using Cryptosporidium genomics for investigating outbreaks and disease transmission

使用隐孢子虫基因组学调查爆发和疾病传播

• 批准号: 2884013
• 金额: --
• 依托单位: Aberystwyth University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2884013
• 关键词: Using; Cryptosporidium; genomics; investigating; outbreaks

Cryptosporidiosis is a significant diarrhoeal disease globally, caused by several species of the apicomplexan Cryptosporidium. As a zoonosis, Cryptosporidium has a wide host range, including livestock. The project will involve close work with the National Cryptosporidium Reference Unit (CRU) for England and Wales. The aim is to improve the detection of outbreaks, for instance by identifying more linked cases, and to ensure that the CRU is using the most appropriate tools e.g. for investigating disease transmission, improving monitoring and managing zoonotic risk, and preparing for future outbreaks. To address this, we hypothesise that (a) whole genome sequencing (WGS) for the discrimination of Cryptosporidium subtypes is better than (b) multiple loci variable number of tandem repeats analysis (MLVA) for elucidating population structure; and hence also for case clustering and outbreak identification

隐孢子虫病是由隐孢子虫属的几种隐孢子虫引起的一种全球性的重要传染病。隐孢子虫是一种人畜共患病，宿主范围广泛，包括家畜。该项目将与英格兰和威尔士国家隐孢子虫参考单位（CRU）密切合作。其目的是通过识别更多的关联病例来改善疫情的检测，并确保CRU使用最适当的工具，例如调查疾病传播，改善监测和管理人畜共患病风险，并为未来的疫情做好准备。为了解决这个问题，我们假设（a）全基因组测序（WGS）用于隐孢子虫亚型的区分优于（B）多位点可变数目串联重复序列分析（MLVA）用于阐明种群结构，因此也用于病例聚类和爆发鉴定