Document Type

Article

Publication Date

8-1-2018

Publication Title

Royal Society Open Science

Abstract

Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. The utility of characterizing the effects of strain variation and individual/subgroup susceptibility on dose-response outcomes has motivated the search for new approaches beyond the popular use of the exponential dose-response model for listeriosis. While descriptive models can account for such variation, they have limited power to extrapolate beyond the details of particular outbreaks. By contrast, this study exhibits dose-response relationships from a mechanistic basis, quantifying key biological factors involved in pathogen-host dynamics. An efficient computational algorithm and geometric interpretation of the infection pathway are developed to connect dose-response relationships with the underlying bistable dynamics of the model. Relying on in vitro experiments as well as outbreak data, we estimate plausible parameters for the human context. Despite the presence of uncertainty in such parameters, sensitivity analysis reveals that the host response is most influenced by the pathogen-immune system interaction. In particular, we show how variation in this interaction across a subgroup of the population dictates the shape of dose-response curves. Finally, in terms of future experimentation, our model results provide guidelines and highlight vital aspects of the interplay between immune cells and particular strains of Listeria monocytogenes that should be examined.

Comments

This study is supported by Public Health Agency of Canada. D.M. acknowledges support from ClevelandState University start-up funding (STARTUP42). A.R.’s postdoctoral fellowship is supported by a research contractfrom the Public Health Agency of Canada and by the NSERC CREATE project Advanced Disaster, Emergency andRapid Response Simulations. J.W.’s research has been funded by the Natural Sciences and Engineering ResearchCouncil of Canada and by the Canada Research Chairs program.

DOI

10.1098/rsos.180343

Version

Publisher's PDF

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Volume

5

Issue

8

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