Salmonella enterica subspecies enterica serovar Mississippi (S. Mississippi) is a polyphyletic serovar endemic in Australia, New Zealand, the United Kingdom, and the United States. From 2018 to 2024, it was the 13th most frequently reported clinical Salmonella serovar in the United States. Its incidence in the United States is geographically focused within the Southeast, with 78% of US cases in that region. The objective of this study was to determine the phylogeographical patterns of clinical S. Mississippi in the southeastern United States using sequenced clinical isolate data and metadata from 10 state public health laboratories in the region. Phylogenetic analysis, based on core single-nucleotide polymorphism (SNP) differences, resulted in five major clades (Ai, Aii, Bi, Bii, and C), four of which were consistent with previous studies. Clade Ai, comprising 99% of study isolates, was systematically divided into seven subclades. County-level mapping of clade Ai revealed distinct geographical distributions at the clade and subclade levels. For example, subclade Ai1 was predominantly distributed along the East Coast, while subclade Ai3 was primarily in western Tennessee. Moran's I analysis revealed significant county-level spatial autocorrelation for clade Ai and its subclades, providing statistical evidence supporting the observed geographical clustering. Additionally, simple linear regression showed statistically significant (P S. Mississippi.IMPORTANCESalmonella Mississippi is a significant public health concern in the southeastern United States; understanding its transmission dynamics is critical for improving surveillance and control. This study leverages a unique data set obtained through regional state public health laboratories, enabling county-level geographical analysis that provides finer resolution than previous studies. A novel, multifaceted approach was applied to characterize the phylogeography of S. Mississippi, integrating phylogenetic, spatial, and regression analyses. Moran's I confirmed strong spatial autocorrelation, while regression analyses showed statistically significant positive associations between genomic and geographical distances. Collectively, these analyses revealed localized clustering, suggesting regional transmission pathways or enzootic reservoirs. Identifying sources or contributing factors could facilitate development and implementation of locally targeted control strategies. These findings provide insight into the spatial ecology of this serovar and establish a framework for future primary-base studies to develop models based on more predictors and conduct more detailed investigations of ecological and epidemiological predictors.
Yoshimoto et al. (Tue,) studied this question.