Understanding the dose-response relationship between ingested pathogenic bacteria and infection probability is a key factor for appropriate risk assessment of foodborne pathogens. The objectives of this study were to develop and validate a novel mechanistic dose-response model for Campylobacter jejuni and simulate the underlying mechanism of foodborne illness during digestion. Bacterial behavior in the human gastrointestinal environment, including survival at low pH in the gastric environment after meals, transition to intestines, and invasion to intestinal tissues, was described using a Bayesian statistical model based on the reported experimental results of each process while considering physical food types (liquid or solid) and host age (young adult or elderly). Combining the models in each process, the relationship between pathogen intake and the infection probability of C. jejuni was estimated and compared with reported epidemiological dose-response relationships. Taking food types and host age into account, the prediction range of the infection probability of C. jejuni successfully covered the reported dose-response relationships from actual C. jejuni outbreaks. According to sensitivity analysis of predicted infection probabilities, the host age factor and the food type factor have relatively higher relevance than other factors. Thus, the developed Key Events Dose Response Framework can derive novel information for quantitative microbiological risk assessment in addition of dose-response relationship. The developed framework is potentially applicable to other pathogens to quantify the dose-response relationship from experimental data obtained from digestion. Importance Based on the mechanistic approach called Key Events Dose Response Framework alternative to previous non-mechanistic approach, the dose-response models for infection probability of C. jejuni were developed considering with age of people who take pathogen and food type. The developed predictive framework illustrated highly accurate prediction of dose (minimum difference 0.21 log CFU) for a certain infection probability compared with the previously reported dose-response relationship. In addition, the developed prediction procedure revealed that the dose-response relationship strongly depends on food type as well as host age. The implementation of Key Event Dose Response Framework will mechanistically and logically reveal the dose-response relationship and provide useful information with quantitative microbiological risk assessment of C. jejuni on foods.
Understanding the dose-response relationship between ingested pathogenic bacteria and infection probability is a key factor for appropriate risk assessment of foodborne pathogens. The objectives of this study were to develop and validate a novel mechanistic dose-response model for Campylobacter jejuni and simulate the underlying mechanism of foodborne illness during digestion. Bacterial behavior in the human gastrointestinal environment, including gastric reductions, transition to intestines, and invasion to intestinal tissues, was described using a Bayesian statistical model based on the reported experimental results of each process while considering physical food types (liquid or solid) and host age (young or elderly). Combining the models in each process, the relationship between pathogen intake and the cell invasion probability of C. jejuni was estimated and compared with reported epidemiological dose-response relationships. Taking food types into account, estimations of the cell invasion probability of C. jejuni successfully described the reported dose-response relationships from substantial accidents. The developed calculation framework is thus potentially applicable to other pathogens to quantify the dose-response relationship from experimental data obtained from digestion.
This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.