Mark H. Weir, PhD

Dr. Weir is an environmental engineer with a research specialization in mathematical and computational methods for health risk assessment. He is most interested in preventing cancer by understanding the mechanisms of its formation and progression. He brings his expertise in the following to characterize and intervene on risks of cancer in diverse populations: a) chemical and microbial dose-response modeling, b) risk assessment for human exposures to chemical and biological (microbial) carcinogenic hazards in the built environment, c) mathematical and computational methods development addressing risk model uncertainty and d) how to design and incorporate sustainability-focused infrastructure into the built environment without adversely impacting, but enhancing human health outcomes.

Dr. Weir’s current research program engages i) artificial intelligence-driven risk monitoring for cancer susceptibility from disinfection byproducts and other chemical co-exposures in hospital water systems, ii) modeling of human exposures to mixtures of contaminants with an emphasis on the interaction cascade of gastric carcinogenesis, Helicobacter pylori infection, and arsenic exposure in drinking water, and iii) investigating the preclinical in-vitro dose-response of gastric cells and organoids following exposure to mixtures of Helicobacter pylori and inorganic arsenic.

1. Building water systems and healthy indoor spaces
2. Sustainability and risk assessment
3. Risk analysis methodology
4. Cumulative risk assessment
5. Water treatment and wastewater reuse

• PhD, Environmental Engineering, Drexel University, 2009
• BS, Environmental Engineering, Wilkes University, 2004

• PUBHEHS 7375: Quantitative Microbial Risk Analysis Modeling
• PUBHEHS 6310: Principles of Environmental Health Science

Select Publications

 Ma, Daniel, Weir, M.H., and Natalie M. Hull. (2023) “Fluence-Based QMRA Model for Bacterial Photorepair and Regrowth in Drinking Water after Decentralized UV Disinfection.” Water Research 231 (March 1, 2023): 119612. https://doi.org/10.1016/j.watres.2023.119612.

Weir, M.H., Traven A. Wood, and Amy Zimmer-Faust. (2021) “Development of Methods to Estimate Microcystins Removal and Water Treatment Resiliency Using Mechanistic Risk Modelling.” Water Research 190 (February 15, 2021): 116763. https://doi.org/10.1016/j.watres.2020.116763.

Hamilton, K.A., Chen, A., Johnson, E.dG., Gitter, A., Kozak, A., Niquice, C., Zimmer-Faust, A.G., Weir,M.H., Mitchell, J., Gurian, P. (2018) Salmonella risks due to consumption of aquaculture-produced shrimp. Microbial Risk Analysis.

Weir,M.H., Mraz, A.L., Nappier, S., Haas, C.N. (2018) Dose Response Models for Eastern, Western and Venezuelan Encephalitis Viruses in Mice - Part II: Quantification of the Effects of Host Age on the Dose Response. Microbial Risk Assessment.

Brouwer AF, Weir MH, Eisenberg MC, Meza R, Eisenberg JNS. (2017) Dose-response relationships for environmentally mediated infectious disease transmission models. PLoS Comput Biol. Apr 7;13(4):e1005481. doi: 10.1371/journal.pcbi.1005481. eCollection 2017 Apr.

Weir, M.H. (2016) “Dose-Response Modeling and Use: Challenges and Uncertainties in Environmental Exposure.” In Manual of Environmental Microbiology, 4th ed., 3.5.3-1-3.5.3-17. ASM. http://www.asmscience.org/content/book/10.1128/9781555818821.

Hamilton KA, Weir MH, Haas CN. Dose response models and a quantitative microbial risk assessment framework for the Mycobacterium avium complex that account for recent developments in molecular biology, taxonomy, and epidemiology. Water Res. 2017 Feb 1;109:310-326. doi: 10.1016/j.watres.2016.11.053. Epub 2016 Nov 24. Review.

Weir,M.H., Mitchell, J., Flynn, W.K., Pope, J.M. (2017) Development of a Microbial Dose Response Visualization and Modeling Application for QMRA Modelers and Educators. Environmental Modeling and Software. 88: 74-83

Weir,M.H., Shibata, T., Masago, Y., Cologgi, D., Rose, J.B. (2016) Effect of Surface Sampling and Recovery of Viruses and Non-Spore-Forming Bacteria on a Quantitative Microbial Risk Assessment Model for Fomites Environmental Science and Technology. 50(11): 5945-5952