@article {1949, title = {Development of a dose{\textendash}response model for Naegleria fowleri}, journal = {Journal of Water and Health}, volume = {17}, year = {2018}, month = {10}, pages = {63-71}, abstract = {

{This study develops novel dose{\textendash}response models for Naegleria fowleri from selected peer-reviewed experiments on the virulence based on the intranasal exposure pathway. One data set measured the response of mice intranasally inoculated with the amebae and the other study addressed the response of mice swimming in N. fowleri infected water. The measured response for both studies was death. All experimental data were best fit by the beta-Poisson dose{\textendash}response model. The three swimming experiments could be pooled, and this is the final recommended model with an LD50 of 13,257 amebae. The results of this study provide a better estimate of the probability of the risk to N. fowleri exposure than the previous models developed based on an intravenous exposure. An accurate dose{\textendash}response model is the first step in quantifying the risk of free-living amebae like N. fowleri, which pose risks in recreational environments and have been detected in drinking water and premise plumbing systems. A better understanding of this risk will allow for risk management that limits the ability for pathogen growth, proliferation, and exposure.}

}, issn = {1477-8920}, doi = {10.2166/wh.2018.181}, url = {https://doi.org/10.2166/wh.2018.181}, author = {Dean, Kara and Weir, Mark H. and Mitchell, Jade} } @article {weir2017development, title = {Development of a microbial dose response visualization and modelling application for QMRA modelers and educators}, journal = {Environmental Modelling \& Software}, volume = {88}, year = {2017}, pages = {74{\textendash}83}, publisher = {Elsevier}, author = {Weir, Mark H and Mitchell, Jade and Flynn, William and Pope, Joanna M} } @article {1821, title = {A dose response model for the inhalation route of exposure to {P}. aeruginosa}, journal = {Microbial Risk Analysis}, volume = {15}, year = {2020}, pages = {100115}, abstract = {

This study develops a dose response model for Pseudomonas aeruginosa for the inhalation route of exposure using pre-existing data. P. aeruginosa is an opportunistic pathogen capable of causing community and hospital-acquired lung infections. As such, a dose response model for this route of exposure is needed to assess risks posed by the inhalation of aerosols from showers, humidifiers, or hot tubs contaminated with P. aeruginosa. Single-hit theory models traditionally used for dose response modeling did not provide significant fits to the limited available data. The multi-hit dose response model operates under the cooperativity theory and did provide a significant fit, suggesting that a single P. aeruginosa bacterium is not sufficient to initiate a pulmonary infection in an immunocompetent host. A hierarchical Bayesian analysis was used to benchmark this model against additional dose response experiments and results further suggested that the multi-hit model may better represent the dose response behavior for this exposure route. The best fitting model has an LD50 of 2,588,047 Colony Forming Units. This model can be used to quantify risk in inhalation exposure scenarios, however, due to the limited amount of primary data, it is especially important for any future risk assessment to analyze the impact that using different dose response models may have on the final risk estimates and recommended control measures.

}, issn = {23523522}, doi = {10.1016/j.mran.2020.100115}, url = {https://linkinghub.elsevier.com/retrieve/pii/S2352352220300219}, author = {Dean, Kara and Mitchell, Jade} } @article {1853, title = {A dose response model for the inhalation route of exposure to P. aeruginosa}, journal = {Microbial Risk Analysis}, volume = {15}, year = {2020}, month = {2020/08//}, pages = {100115}, abstract = {

This study develops a dose response model for Pseudomonas aeruginosa for the inhalation route of exposure using pre-existing data. P. aeruginosa is an opportunistic pathogen capable of causing community and hospital-acquired lung infections. As such, a dose response model for this route of exposure is needed to assess risks posed by the inhalation of aerosols from showers, humidifiers, or hot tubs contaminated with P. aeruginosa. Single-hit theory models traditionally used for dose response modeling did not provide significant fits to the limited available data. The multi-hit dose response model operates under the cooperativity theory and did provide a significant fit, suggesting that a single P. aeruginosa bacterium is not sufficient to initiate a pulmonary infection in an immunocompetent host. A hierarchical Bayesian analysis was used to benchmark this model against additional dose response experiments and results further suggested that the multi-hit model may better represent the dose response behavior for this exposure route. The best fitting model has an LD50 of 2,588,047 Colony Forming Units. This model can be used to quantify risk in inhalation exposure scenarios, however, due to the limited amount of primary data, it is especially important for any future risk assessment to analyze the impact that using different dose response models may have on the final risk estimates and recommended control measures.

}, isbn = {23523522}, url = {https://linkinghub.elsevier.com/retrieve/pii/S2352352220300219}, author = {Dean, Kara and Mitchell, Jade} } @article {1800, title = {Modeling the Dose Response Relationship of Waterborne Acanthamoeba}, journal = {Risk Analysis}, volume = {41}, year = {2021}, doi = {10.1111/risa.13603}, url = {https://onlinelibrary.wiley.com/doi/10.1111/risa.13603}, author = {Dean, Kara and Tamrakar, Sushil and Huang, Yin and Rose, Joan and Mitchell, Jade} } @article {1819, title = {Modeling the {Dose} {Response} {Relationship} of {Waterborne} {{Acanthamoeba}}, journal = {Risk Analysis}, volume = {41}, year = {2021}, pages = {79{\textendash}91}, issn = {0272-4332, 1539-6924}, doi = {10.1111/risa.13603}, url = {https://onlinelibrary.wiley.com/doi/10.1111/risa.13603}, author = {Dean, Kara and Tamrakar, Sushil and Huang, Yin and Rose, Joan B. and Mitchell, Jade} }