Estimation of the rate of egg contamination from Salmonella-infected chickens

Abstract

Salmonella enterica serovar Enteritidis (S. Enteritidis) is one of the most prevalent causes for human gastroenteritis and is by far the predominant Salmonella serovar among human cases, followed by Salmonella Typhimurium. Contaminated eggs produced by infected laying hens are thought to be the main source of human infection with S. Enteritidis throughout the world. Although previous studies have looked at the proportion of infected eggs from infected flocks, there is still uncertainty over the rate at which infected birds produce contaminated eggs. The aim of this study was to estimate the rate at which infected birds produce contaminated egg shells and egg contents. Data were collected from two studies, consisting of 15 and 20 flocks, respectively. Faecal and environmental sampling and testing of ovaries/caeca from laying hens were carried out in parallel with (i) for the first study, testing 300 individual eggs, contents and shells together and (ii) for the second study, testing 4000 eggs in pools of six, with shells and contents tested separately. Bayesian methods were used to estimate the within-flock prevalence of infection from the faecal and hen post-mortem data, and this was related to the proportion of positive eggs. Results indicated a linear relationship between the rate of contamination of egg contents and the prevalence of infected chickens, but a nonlinear (quadratic) relationship between infection prevalence and the rate of egg shell contamination, with egg shell contamination occurring at a much higher rate than that of egg contents. There was also a significant difference in the rate of egg contamination between serovars, with S. Enteritidis causing a higher rate of contamination of egg contents and a lower rate of contamination of egg shells compared to non-S. Enteritidis serovars. These results will be useful for risk assessments of human exposure to Salmonella-contaminated eggs.

Keywords: Salmonella spp; foodborne pathogens; mathematical modeling; risk assessment.