| Summary: | Abstract This assessment relates the percentage of broiler‐associated human salmonellosis cases to different Salmonella prevalences in broiler flocks in the European Union. It considers the contribution and relevance of different Salmonella serovars found in broilers to human salmonellosis. The model developed to provide quantitative estimates, which is based on the microbial‐subtyping approach, considers 22 Member States, four animal‐food sources of Salmonella (broilers, laying hens, pigs and turkeys) and 23 Salmonella serovars. The model (called the ‘Broiler Target Salmonella Attribution Model’ or BT‐SAM model) employes data from the EU Baseline Surveys and EU statutory monitoring on Salmonella in animal‐food sources, data on incidence of human salmonellosis and food availability data. It is estimated that around 2.4%, 65%, 28% and 4.5% of the human salmonellosis cases are attributable to broilers, laying hens (eggs), pigs and turkeys respectively. Of the broiler‐associated human salmonellosis cases, around 42% and 23% are estimated to be due to the serovars Salmonella Enteritidis and Salmonella Infantis respectively, while other serovars individually contributed less than 5%. Different scenarios are presented showing changes in the percentage of broiler‐associated human salmonellosis cases under different prevalences of Salmonella in broiler flocks. Compared to 2006, the 2009 Salmonella in broiler flocks prevalence has achieved a reduction of 69% in the number of broiler‐associated human salmonellosis cases. When comparing the results of the adjusted prevalences for Salmonella Enteritidis and Salmonella Typhimurium as reported in 2009 with a theoretical combined prevalence of 1% for these two serovars, the difference between the percentages of broiler‐associated cases is small. However, when adjusting the combined prevalence of all serovars to 1%, a large reduction in the percentage of broiler‐associated cases compared to the one achieved with the two previous serovars only is expected. Uncertainty and data limitations are discussed, including recommendations on how these could be overcome.
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