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.
| Original language | English |
|---|---|
| Pages (from-to) | 67-78 |
| Number of pages | 12 |
| Journal | Risk Analysis |
| Volume | 41 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2021 |
Bibliographical note
Funding Information:This study was funded by the UK Home Office. The research was also partially funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response at King's College London and in Modelling Methodology at Imperial, both in partnership with Public Health England (PHE). IH is Principal Investigator of the NIHR Policy Research Programme in Operational Research for Emergency Response Analysis (OPERA, PR-R17-0916-21001). IH and SL are also Members of NIHR Health Protection Research Units in Emerging and Zoonotic Infections and IH is a Member of the NIHR HPRU in Gastrointestinal Infections, both at Liverpool. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health, Home Office, or Public Health England. The authors declare that they have no competing?interests.
Funding Information:
This study was funded by the UK Home Office. The research was also partially funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response at King's College London and in Modelling Methodology at Imperial, both in partnership with Public Health England (PHE). IH is Principal Investigator of the NIHR Policy Research Programme in Operational Research for Emergency Response Analysis (OPERA, PR‐R17‐0916‐21001). IH and SL are also Members of NIHR Health Protection Research Units in Emerging and Zoonotic Infections and IH is a Member of the NIHR HPRU in Gastrointestinal Infections, both at Liverpool. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health, Home Office, or Public Health England. The authors declare that they have no competing interests.
Publisher Copyright:
© 2020 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Keywords
- Competing-risks framework
- dose–response modeling
- quantitative microbial risk assessment