2015
DOI: 10.1016/j.scitotenv.2015.03.077
|View full text |Cite
|
Sign up to set email alerts
|

Assessment of public health risk associated with viral contamination in harvested urban stormwater for domestic applications

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
61
0
1

Year Published

2015
2015
2023
2023

Publication Types

Select...
8
1
1

Relationship

3
7

Authors

Journals

citations
Cited by 100 publications
(62 citation statements)
references
References 96 publications
0
61
0
1
Order By: Relevance
“…This model is also a more conservative model yielding higher risk estimates, which may lead to a more cautious risk management approach. The same model selection decision was also made by many QMRA models involving NoV [29,30,41,42]. However, future research is urgently needed to fill the data gap and to improve the understanding of NoV dose-response for an improved risk assessment result.…”
Section: Uncertainties Of the Risk Outcomesmentioning
confidence: 98%
“…This model is also a more conservative model yielding higher risk estimates, which may lead to a more cautious risk management approach. The same model selection decision was also made by many QMRA models involving NoV [29,30,41,42]. However, future research is urgently needed to fill the data gap and to improve the understanding of NoV dose-response for an improved risk assessment result.…”
Section: Uncertainties Of the Risk Outcomesmentioning
confidence: 98%
“…Dilution factors are sometimes applied to estimate pathogen loads between stormwater and receiving recreational bodies; for example, McBride et al (2013) used a 30-fold dilution factor applied to the concentrations of pathogens observed in stormwater discharges. Other studies have applied an estimated microbial decay factor for particular pathogens or indicators as surrogates for pathogens in stormwater, sometimes also coupled with a dilution factor (Petterson et al, 2016;Lim et al, 2015). The use of hydrodynamic mixing and inactivation models such as those applied by Andersen et al (2013) could be used to obtain more accurate site-specific dilution information, or a distribution of dilution factors could be incorporated into a Monte Carlo approach in QMRA models as performed in Soller et al, 2017. Improved characterization of different removal values for bacteria, protozoans and viruses in stormwater treatment processes can also improve QMRA estimates, as previous estimates have been based on FIB rather than pathogens themselves due to limited data (Davies et al, 2008;Page et al, 2010aPage et al, , 2010bPage et al, , 2010cPage et al, , 2010dPetterson et al, 2016).…”
Section: Page Et Al 2010bmentioning
confidence: 99%
“…Therefore, adaptation of QMRA for antimicrobial resistant infections will require expanding conversion factors to account for longer disease duration and greater severity. Expanding conversion factors will require consideration of country-level differences, as conversion is based on disease surveillance data that are regionally-bounded, and therefore may not be representative of the population from different countries [80].…”
Section: Risk Characterization and Managementmentioning
confidence: 99%