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Developing an Integrated “Regression-QMRA method” to Predict Public Health Risks of Low Impact Developments (LIDs) for Improved Planning

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Abstract

Worldwide Low Impact Developments (LIDs) are used for sustainable stormwater management; however, both the stormwater and LIDs carry microbial pathogens. The widespread development of LIDs is likely to increase human exposure to pathogens and risk of infection, leading to unexpected disease outbreaks in urban communities. The risk of infection from exposure to LIDs has been assessed via Quantitative Microbial Risk Assessment (QMRA) during the operation of these infrastructures; no effort is made to evaluate these risks during the planning phase of LID treatment train in urban communities. We developed a new integrated “Regression-QMRA method” by examining the relationship between pathogens’ concentration and environmental variables. Applying of this methodology to a planned LID train shows that the predicted disease burden of diarrhea from Campylobacter is highest (i.e. 16.902 DALYs/1000 persons/yr) during landscape irrigation and playing on the LID train, followed by Giardia, Cryptosporidium, and Norovirus. These results illustrate that the risk of microbial infection can be predicted during the planning phase of LID treatment train. These predictions are of great value to municipalities and decision-makers to make informed decisions and ensure risk-based planning of stormwater systems before their development.

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Acknowledgements

We would like to thank Natural Sciences and Engineering Research Council of Canada for supporting this research. Special thanks are extended to Ms. Anber Rana for assistance with the charts. We would also like to thank the editors and anonymous reviewers for their helpful and constructive comments that greatly contributed to improving the quality of this content analysis.

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Correspondence to Rehan Sadiq.

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The authors declare no competing interests.

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Ishaq, S., Sadiq, R., Chhipi-Shrestha, G. et al. Developing an Integrated “Regression-QMRA method” to Predict Public Health Risks of Low Impact Developments (LIDs) for Improved Planning. Environmental Management 70, 633–649 (2022). https://doi.org/10.1007/s00267-022-01657-0

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  • DOI: https://doi.org/10.1007/s00267-022-01657-0

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