title: A weighted composite dose-response model for human salmonellosis.
abstract: This article describes the development of a weighted composite dose-response model for human salmonellosis. Data from previously reported human challenge studies were categorized into two different groups representing low and moderately virulent/pathogenic Salmonella strains based on a disease end point. Because epidemiological data indicate that some Salmonella strains are particularly pathogenic, and in the absence of human feeding study data for such strains, Shigella dysenteriae was used as a proxy for highly virulent strains. Three single-hit dose-response models were applied to the human feeding study data and evaluated for best fit using maximum likelihood estimation: (1) the exponential (E-1pop), (2) the two-subpopulation exponential (E-2pop), and (3) the Beta-Poisson (BP). Based on the goodness-of-fit test, the E-1pop and BP were the best-fit models for low and moderately virulent/pathogenic Salmonella strains, and the E-2pop and BP models were better for highly virulent/pathogenic strains. Epistemic analysis was conducted by determining the degree of confidence associated with the selected models, which was found to be 50%/50% (E-1pop/BP) for low and moderately pathogenic Salmonella strains, and 9.8%/90.2% (E-2pop/BP) for highly virulent strains. The degree of confidence for each component model and variations in the proportion of strains within each virulence/pathogenicity category were incorporated into the overall composite model. This study describes the influence of variation in strain virulence and host susceptibility on the shape of the population dose-response relationship.
authors: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, USA.
authors: H K
authors: HK
authors: Latimer
authors: L A
authors: LA
authors: Jaykus
authors: R A
authors: RA
authors: Morales
authors: P
authors: P
authors: Cowen
authors: D
authors: D
authors: Crawford-Brown
mesh_terms: D015169:Colony Count, Microbial; D005516:Food Microbiology; D006801:Humans; D016013:Likelihood Functions; D008954:Models, Biological; D012306:Risk; D012475:Salmonella / Q000472:pathogenicity; D012478:Salmonella Food Poisoning / Q000209:etiology*; D012477:Salmonella enteritidis / Q000472:pathogenicity; D014774:Virulence