All Stories

  1. Particulate contaminants and treatment decision-making: maximizing the value of raw water pathogen monitoring for drinking water safety

    Article • Journal of Water and Health, May 2025, IWA Publishing

    Philip Schmidt

  2. Drinking water QMRA and decision-making: Sensitivity of risk to common independence assumptions about model inputs

    Article • Water Research, August 2024, Elsevier

    Philip Schmidt

  3. Filter operation effects on plant‐scale microbial risk: Opportunities for enhanced treatment performance

    Article • AWWA Water Science, September 2023, Wiley

    Philip Schmidt

  4. Ensuring That Fundamentals of Quantitative Microbiology Are Reflected in Microbial Diversity Analyses Based on Next-Generation Sequencing

    Article • Frontiers in Microbiology, March 2022, Frontiers

    Philip Schmidt

  5. Enhancing diversity analysis by repeatedly rarefying next generation sequencing data describing microbial communities

    Article • Scientific Reports, November 2021, Springer Science + Business Media

    Philip Schmidt

  6. Ensuring that fundamentals of quantitative microbiology are reflected in microbial diversity analyses based on next-generation sequencing

    Article • June 2021, Cold Spring Harbor Laboratory Press

    Philip Schmidt

  7. Reply to Comment on “Describing water treatment process performance: Why average log-reduction can be a misleading statistic” by Schmidt, P.J., Anderson, W.B., and Emelko, M.B. [Water Research 176 (2020), 115702]

    Article • Water Research, October 2020, Elsevier

    Philip Schmidt

  8. To rarefy or not to rarefy: Enhancing microbial community analysis through next-generation sequencing

    Article • September 2020, Cold Spring Harbor Laboratory Press

    Philip Schmidt

  9. Evaluation of the 50% Infectious Dose of Human Norovirus Cin-2 in Gnotobiotic Pigs: A Comparison of Classical and Contemporary Methods for Endpoint Estimation

    Article • Viruses, August 2020, MDPI AG

    Philip Schmidt, Dr Lijuan Yuan

  10. Describing water treatment process performance: Why average log-reduction can be a misleading statistic

    Article • Water Research, June 2020, Elsevier

    Philip Schmidt

  11. Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit

    Article • Risk Analysis, August 2019, Wiley

    Philip Schmidt

  12. Confirming the need for virus disinfection in municipal subsurface drinking water supplies

    Article • Water Research, June 2019, Elsevier

    Philip Schmidt

  13. Learning Something From Nothing: The Critical Importance of Rethinking Microbial Non-detects

    Article • Frontiers in Microbiology, October 2018, Frontiers

    Philip Schmidt

  14. Comment on “Guidelines for Use of the Approximate Beta-Poisson Dose-Response Model”: Previously Published Guidelines Continue to be Ignored

    Article • Risk Analysis, February 2017, Wiley

    Philip Schmidt

  15. Comment on “CryptosporidiumInfection Risk: Results of New Dose-Response Modeling” - Discussion of Underlying Assumptions and Their Implications

    Article • Risk Analysis, December 2016, Wiley

    Philip Schmidt

  16. Towards a more accurate quantitative assessment of seasonal Cryptosporidium infection risks in surface waters using species and genotype information

    Article • Water Research, November 2016, Elsevier

    Philip Schmidt

  17. Estimating the burden of acute gastrointestinal illness due toGiardia, Cryptosporidium, Campylobacter, E. coliO157 and norovirus associated with private wells and small water systems in Canada

    Article • Epidemiology and Infection, November 2015, Cambridge University Press

    Philip Schmidt

  18. Norovirus Dose-Response: Are Currently Available Data Informative Enough to Determine How Susceptible Humans Are to Infection from a Single Virus?

    Article • Risk Analysis, December 2014, Wiley

    Philip Schmidt

  19. Variance decomposition: A tool enabling strategic improvement of the precision of analytical recovery and concentration estimates associated with microorganism enumeration methods

    Article • Water Research, May 2014, Elsevier

    Philip Schmidt

  20. Bacteria, viruses, and parasites in an intermittent stream protected from and exposed to pasturing cattle: Prevalence, densities, and quantitative microbial risk assessment

    Article • Water Research, October 2013, Elsevier

    Philip Schmidt

  21. Using Campylobacter spp. and Escherichia coli data and Bayesian microbial risk assessment to examine public health risks in agricultural watersheds under tile drainage management

    Article • Water Research, June 2013, Elsevier

    Philip Schmidt

  22. Analytical recovery of protozoan enumeration methods: Have drinking water QMRA models corrected or created bias?

    Article • Water Research, May 2013, Elsevier

    Philip Schmidt

  23. Harnessing the Theoretical Foundations of the Exponential and Beta-Poisson Dose-Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo

    Article • Risk Analysis, January 2013, Wiley

    Philip Schmidt

  24. QMRA and decision-making: Are we handling measurement errors associated with pathogen concentration data correctly?

    Article • Water Research, January 2011, Elsevier

    Philip Schmidt

  25. Particle and Microorganism Enumeration Data: Enabling Quantitative Rigor and Judicious Interpretation

    Article • Environmental Science & Technology, March 2010, American Chemical Society (ACS)

    Philip Schmidt

  26. Quantification of Analytical Recovery in Particle and Microorganism Enumeration Methods

    Article • Environmental Science & Technology, March 2010, American Chemical Society (ACS)

    Philip Schmidt

  27. Quantification of uncertainty in microbial data-reporting and regulatory implications

    Article • American Water Works Association, March 2008, Wiley

    Philip Schmidt