ADONIS: Assessing Determinants of the Non-Decreasing Incidence of Salmonella
The Project #ADONIS
Salmonellosis remains the second most common zoonosis in humans in the EU despite a significantly long-term decreasing trend in human cases since 2008. In recent years this decreasing trend has levelled off. In laying hens, the prevalence of positive flocks for the target serovars, and especially for S. Enteritidis, has also increased after a long period of documented reduction.
Several hypotheses have been made, including more complete reporting and improvements in the surveillance of human salmonellosis, premature relaxation of Salmonella control measures at primary production, possible deficiencies in the enforcement of existing control measures and sensitivity of statutory sampling programmes, and changed/increased exposure patterns.
The ADONIS project will identify determinants underlying the stagnation/reversal of the decreasing trend in Salmonella Enteritidis incidence in humans and poultry in the EU. We will apply a cross-sectorial approach where we will investigate possible explanatory factors at the levels of primary production, epidemiology/exposure, and the pathogen itself.
At the primary production level, the project will evaluate possible changes in flock management and possible insufficiencies in control measures implemented to date in poultry farms related to the implementation of vaccination programmes as well as the application of strict farm hygiene controls and sensitivity of the statutory sampling implemented in commercial flocks.
At the public health level, this project will evaluate national surveillance systems for S. Enteritidis in humans, assess changes over time regarding epidemiological characteristics, and calculate the total reservoir output exposure loads.
At the pathogen level, we will assess whether the recent plateau in salmonellosis incidence in Europe could be related to the genetic variation of the Salmonella bacterium, primarily S. Enteritidis, such as the emergence or clonal expansion of specific bacterial strains with increased fitness in the form of e.g. increased bacterial division, increased virulence or antibiotic resistance. Finally, the data and information gathered will be ranked and prioritised by a Multi-Criteria Decision Analysis (MCDA) modelling
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