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Dose–Response Modeling: Extrapolating From Experimental Data to Real‐World Populations

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  • Adrian Pratt
  • Emma Bennett
  • Joseph Gillard
  • Steve Leach
  • Ian Hall

Abstract

Dose–response modeling of biological agents has traditionally focused on describing laboratory‐derived experimental data. Limited consideration has been given to understanding those factors that are controlled in a laboratory, but are likely to occur in real‐world scenarios. In this study, a probabilistic framework is developed that extends Brookmeyer's competing‐risks dose–response model to allow for variation in factors such as dose‐dispersion, dose‐deposition, and other within‐host parameters. With data sets drawn from dose–response experiments of inhalational anthrax, plague, and tularemia, we illustrate how for certain cases, there is the potential for overestimation of infection numbers arising from models that consider only the experimental data in isolation.

Suggested Citation

  • Adrian Pratt & Emma Bennett & Joseph Gillard & Steve Leach & Ian Hall, 2021. "Dose–Response Modeling: Extrapolating From Experimental Data to Real‐World Populations," Risk Analysis, John Wiley & Sons, vol. 41(1), pages 67-78, January.
    • Handle: RePEc:wly:riskan:v:41:y:2021:i:1:p:67-78
    DOI: 10.1111/risa.13597
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    References listed on IDEAS

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    1. Damon J A Toth & Adi V Gundlapalli & Wiley A Schell & Kenneth Bulmahn & Thomas E Walton & Christopher W Woods & Catherine Coghill & Frank Gallegos & Matthew H Samore & Frederick R Adler, 2013. "Quantitative Models of the Dose-Response and Time Course of Inhalational Anthrax in Humans," PLOS Pathogens, Public Library of Science, vol. 9(8), pages 1-18, August.
    2. P. F. M. Teunis & A. H. Havelaar, 2000. "The Beta Poisson Dose‐Response Model Is Not a Single‐Hit Model," Risk Analysis, John Wiley & Sons, vol. 20(4), pages 513-520, August.
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