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Dose response models for Eastern US, Western US and Venezuelan equine encephalitis viruses in mice – Part I: Standard dose response model and inference of host age
Journal article   Open access   Peer reviewed

Dose response models for Eastern US, Western US and Venezuelan equine encephalitis viruses in mice – Part I: Standard dose response model and inference of host age

Alexis L. Mraz, Sharon Nappier, Charles N. Haas and Mark H. Weir
Microbial risk analysis, v 14, 100087
Apr 2020
DOI: https://doi.org/10.1016/j.mran.2019.100087
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
http://hdl.handle.net/10072/389228View
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Abstract

Dose response Encephalitis Model QMRA Virus
•The dose response relationship in three equine encephalitis viruses was modeled.•Age nesting analyses were performed but not successfully.•Likely need to develop host age dependent dose response models for these pathogens. Data regarding mice exposed to Eastern, Venezuelan and Western equine encephalitis viruses (EEV, VEV and WEV respectively) were used to optimize two physiologically plausible dose response models. A rich data set was extracted from an intensive literature review, with 42 independent dose groups over three exposure routes: subcutaneous, intracranial and intraperitoneal. The data demonstrate the highly infectious nature of these encephalitis viruses to a general population. However, from an examination of the data, a dependency in the dose response relationship with respect to host age is likely. This host age dependency is manifesting as an increased resistance with increased host age, conversely, higher susceptibility at lower host ages. Considering the inability to pool host age groups under a nested model, this likely host age dependency is highlighted to a greater extent. Most of the host age groups (65%) could not be used for dose-response model optimization, leaving 13 host age groups of the original 37 that could be used for optimization. Those that could be used resulted in the exponential model being the better fitting model for 61% of those data, with the approximated form of the beta Poisson being the better fitting model for the remaining five data sets.

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Environmental Sciences
Food Science & Technology
Microbiology
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