PDF(Pubmed)
Abstract：
SNP addresses are a pathogen typing method based on whole-genome sequences (WGSs), assigning groups at seven different levels of genetic similarity. Public health surveillance uses it for several gastro-intestinal infections; this work trialled its use in veterinary surveillance for salmonella outbreak detection. Comparisons were made between temporal and spatio-temporal cluster detection models that either defined cases by their SNP address or by phage type, using historical data sets. Clusters of SNP incidents were effectively detected by both methods, but spatio-temporal models consistently detected these clusters earlier than the corresponding temporal models. Unlike phage type, SNP addresses appeared spatially and temporally limited, which facilitated the differentiation of novel, stable, or expanding clusters in spatio-temporal models. Furthermore, these models flagged spatio-temporal clusters containing only two to three cases at first detection, compared with a median of seven cases in phage-type models. The large number of SNP addresses will require automated methods to implement these detection models routinely. Further work is required to explore how temporal changes and different host species may impact the sensitivity and specificity of cluster detection. In conclusion, given validation with more sequencing data, SNP addresses are likely to be a valuable addition to early warning systems in veterinary surveillance.
摘要：
SNP地址是一种基于全基因组序列（WGS）的病原体分型方法，在七个不同的遗传相似性水平上分配群体。公共卫生监测将其用于多种胃肠道感染；这项工作尝试了其在兽医监测中用于沙门氏菌爆发检测的用途。在时间和时空簇检测模型之间进行了比较，这些模型通过SNP地址或噬菌体类型定义了病例，使用历史数据集。两种方法都有效地检测到了SNP事件的集群，但是时空模型始终比相应的时间模型更早地检测到这些集群。与噬菌体类型不同，SNP地址在空间和时间上似乎受到限制，这促进了小说的分化，稳定,或在时空模型中扩展聚类。此外，这些模型在首次检测时标记了仅包含两到三种情况的时空集群，与噬菌体型模型中7例的中位数相比。大量的SNP地址将需要自动化方法来常规地实现这些检测模型。需要进一步的工作来探索时间变化和不同的宿主物种如何影响簇检测的灵敏度和特异性。总之,给定更多测序数据的验证，SNP地址可能是兽医监测中预警系统的宝贵补充。
