Cargando…

Epidemiologic patterns of human Salmonella serotype diversity in the USA, 1996–2016

Although researchers have described numerous risk factors for salmonellosis and for infection with specific common serotypes, the drivers of Salmonella serotype diversity among human populations remain poorly understood. In this retrospective observational study, we partition records of serotyped no...

Descripción completa

Detalles Bibliográficos
Autores principales: Judd, M. C., Hoekstra, R. M., Mahon, B. E., Fields, P. I., Wong, K. K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518743/
https://www.ncbi.nlm.nih.gov/pubmed/31063111
http://dx.doi.org/10.1017/S0950268819000724
Descripción
Sumario:Although researchers have described numerous risk factors for salmonellosis and for infection with specific common serotypes, the drivers of Salmonella serotype diversity among human populations remain poorly understood. In this retrospective observational study, we partition records of serotyped non-typhoidal Salmonella isolates from human clinical specimens reported to CDC national surveillance by demographic, geographic and seasonal characteristics and adapt sample-based rarefaction methods from the field of community ecology to study how Salmonella serotype diversity varied within and among these populations in the USA during 1996–2016. We observed substantially higher serotype richness in children <2 years old than in older children and adults and steadily increasing richness with age among older adults. Whereas seasonal and regional variation in serotype diversity was highest among infants and young children, variation by specimen source was highest in adults. Our findings suggest that the risk for infection from uncommon serotypes is associated with host and environmental factors, particularly among infants, young children and older adults. These populations may have a higher proportion of illness acquired through environmental transmission pathways than published source attribution models estimate.