PDF(Pubmed)
Abstract：
Salmonella is one of the main causes of human foodborne illness. It is endemic worldwide, with different animals and animal-based food products as reservoirs and vehicles of infection. Identifying animal reservoirs and potential transmission pathways of Salmonella is essential for prevention and control. There are many approaches for source attribution, each using different statistical models and data streams. Some aim to identify the animal reservoir, while others aim to determine the point at which exposure occurred. With the advance of whole-genome sequencing (WGS) technologies, new source attribution models will greatly benefit from the discriminating power gained with WGS. This review discusses some key source attribution methods and their mathematical and statistical tools. We also highlight recent studies utilizing WGS for source attribution and discuss open questions and challenges in developing new WGS methods. We aim to provide a better understanding of the current state of these methodologies with application to Salmonella and other foodborne pathogens that are common sources of illness in the poultry and human sectors.
摘要：
沙门氏菌是人类食源性疾病的主要病因之一。它是全世界特有的，将不同的动物和动物食品作为感染的宿主和媒介。确定沙门氏菌的动物宿主和潜在的传播途径对于预防和控制至关重要。源归因有很多方法，每个都使用不同的统计模型和数据流。一些旨在识别动物水库，而其他人则旨在确定暴露发生的点。随着全基因组测序（WGS）技术的进步，新的来源归因模型将极大地受益于WGS获得的鉴别力。这篇综述讨论了一些关键的来源归因方法及其数学和统计工具。我们还重点介绍了利用WGS进行来源归因的最新研究，并讨论了开发新WGS方法的开放问题和挑战。我们的目标是更好地了解这些方法的现状，并应用于沙门氏菌和其他食源性病原体，这些病原体是家禽和人类部门的常见疾病来源。
