September 21, 2020

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McKinley Olsen Coauthored a Paper on Quantitative Microbial Risk Assessment in Journal Science of the Total Environment

McKinley (Mac) Olsen (California) coauthored a paper entitled “Informing water distribution line rehabilitation through quantitative microbial risk assessment” that was published in Science of the Total Environment on June 6, 2020.

Mac’s coauthors were Rubayat Jamal, Sierra Sahulka, Ramesh Goel, Jennifer Weidhass, Shaista Murarak, Junaid Kori, Ayesha Tajammul, Jamil Ahmed, and Rasool Mahar.

Mac Olsen is a Senior Staff Engineer based in California with more than six years of experience focused on environmental engineering, particularly involving water resources, groundwater and soil remediation, and water and sediment sampling.

Science of the Total Environment, published by Elsevier, is an international, multi-disciplinary journal for publication of novel, hypothesis-driven, and high-impact research on the total environment, which interfaces the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.

Elsevier is a leader in information and analytics for customers across the global research and health ecosystems. By facilitating insights and critical decision-making for customers across the global research and health ecosystems, Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society.


Poor urban water quality has been linked to diminished source water quality, poorly functioning water treatment systems and infiltration into distribution lines after treatment resulting in microbiological contamination. With limited funding to rehabilitate distribution lines, developing nations need tools to identify the areas of greatest concern to human health so as to target cost effective remediation approaches. Herein, a case study of Hyderabad, Pakistan was used to demonstrate the efficacy of combining quantitative microbial risk assessment (QMRA) for multiple pathogens with spatial distribution system modeling to identify areas for pipe rehabilitation. Abundance of Escherichia coli, Enterococcus (enterococci), Salmonella spp., Shigella spp., Giardia intestinalis, Vibrio cholera, norovirus GI and adenovirus 40/41, were determined in 85 locations including the source water, treatment plant effluent and the city distribution lines. Bayesian statistics and Monte Carlo simulations were used in the QMRA to account for left-censored microbial abundance distributions. Bacterial and viral abundances in the distribution system samples decreased as follows: 9400 ± 19,800 norovirus gene copies/100mL (average ± standard deviation, 100% of samples positive); 340 ± 2200 enterococci CFU/100mL (94%), 71 ± 97 Shigella sp. CFU/100 mL (97%), 60 ± 360 E. coli CFU/100 mL (89%), 35 ± 79 adenovirus gene copies/100 mL (100%), and 21 ± 46 Salmonella sp. CFU/100 mL (76%). The QMRA revealed unacceptable probabilities of illness (>1 in 10,000 illness level) from the four exposure routes considered (drinking water, or only showering, tooth brushing, and rinsing vegetables consumed raw). Disease severity indices based on the QMRA combined with mapping the distribution system revealed areas for targeted rehabilitation. The combined intensive sampling, risk assessment and mapping can be used in low- and middle-income countries to target distribution system rehabilitation efforts and improve health outcomes.

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