Bettridge, Judy ORCID: 0000-0002-3917-4660, Snow, L. C., Tang, Y., Petrovska, L. ORCID: 0000-0003-2638-5052, Lawes, J. and Smith, R. P. ORCID: 0000-0001-6871-4673 (2023) Using SNP addresses for Salmonella Typhimurium DT104 in routine veterinary outbreak detection. Epidemiology and Infection, 151:e187. pp. 1-14. ISSN 0950-2688 (Print), 1469-4409 (Online) (doi:https://doi.org/10.1017/S0950268823001723)

Preview

PDF (Publisher VoR) 44884_BETTRIDGE_ Using_SNP_addresses_for_Salmonella_Typhimurium_DT104_in_routine_veterinary_outbreak_detection.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (2MB) | Preview

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.

Item Type:	Article
Uncontrolled Keywords:	genomic typing; molecular epidemiology; Salmonella (Typhimurium); surveillance; veterinary epidemiology
Subjects:	Q Science > Q Science (General) Q Science > QR Microbiology > QR355 Virology S Agriculture > S Agriculture (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Natural Resources Institute Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Last Modified:	15 Nov 2023 09:41
URI:	http://gala.gre.ac.uk/id/eprint/44884

Actions (login required)

View Item

Downloads