Changing epidemiology of invasive non-typhoid Salmonella infection: a nationwide population-based registry study

Abstract

Objectives: Non-typhoid Salmonella (NTS) may invade beyond the intestine, causing bacteraemia, sepsis, and infection of normally sterile sites. The epidemiology of invasive NTS (iNTS) infection is under-researched. We determined trends, risk factors, serotype distribution, antimicrobial resistance (AMR), and attributable sources of iNTS infection in a high-income setting.

Methods: 22,837 records of culture-confirmed human salmonellosis cases and 10,008 serotyped Salmonella isolates from five putative animal reservoirs (pigs, cattle, broilers, layers, reptiles) in the Netherlands during 2005-2018 were retrieved from national surveillance registries. Risk factors for iNTS infection were identified using logistic regression analysis. Source attribution modelling was based on serotyping, prevalence, and exposure data.

Results: The average annual percentage of iNTS infections was 4.6% (range 3.5-5.7%). An increase in iNTS infections was observed since 2012 (odds ratio (OR) 1.09, 95% confidence interval (95% CI) 1.04-1.14). Increased iNTS infection risk was associated with wintertime (OR 1.37, 95% CI 1.12-1.66), male sex (OR 1.73, 95% CI 1.51-1.99), older age (ORs: 3.27 to 16.33, depending on age groups), and living in rural areas (OR 1.54, 95% CI 1.23-1.93). While 52% of iNTS infections (n = 950) were caused by serotypes Enteritidis and Typhimurium, those displaying the highest invasiveness relative to their occurrence were Dublin (32.9%, n = 163), Panama (21.6%, n = 106), and Poona (14.1%, n = 71). Cattle were a larger source of iNTS than non-iNTS infections (12.2% vs. 7.6%). Lower AMR and multi-resistance rates were observed among iNTS (37.9%) than non-iNTS isolates (48.6%).

Discussion: The increase in iNTS infections, which is reported also in other countries, is of public health and clinical concern. The underlying reasons seem to be multi-factorial in nature. iNTS infection risk depends more on the infecting serotypes and patient demographics, and less on the attributable reservoirs and AMR profiles.

Keywords: Antibiotic resistance; Bloodstream infection; Risk factors; Salmonellosis; Source attribution; Trends; Zoonoses.