Effects of a 20 year rain event: a quantitative microbial risk assessment of a case of contaminated bathing water in Copenhagen, Denmark

Abstract

Quantitative microbial risk assessments (QMRAs) often lack data on water quality leading to great uncertainty in the QMRA because of the many assumptions. The quantity of waste water contamination was estimated and included in a QMRA on an extreme rain event leading to combined sewer overflow (CSO) to bathing water where an ironman competition later took place. Two dynamic models, (1) a drainage model and (2) a 3D hydrodynamic model, estimated the dilution of waste water from source to recipient. The drainage model estimated that 2.6% of waste water was left in the system before CSO and the hydrodynamic model estimated that 4.8% of the recipient bathing water came from the CSO, so on average there was 0.13% of waste water in the bathing water during the ironman competition. The total estimated incidence rate from a conservative estimate of the pathogenic load of five reference pathogens was 42%, comparable to 55% in an epidemiological study of the case. The combination of applying dynamic models and exposure data led to an improved QMRA that included an estimate of the dilution factor. This approach has not been described previously.

A review on microbial contaminants in stormwater runoff and outfalls: Potential health risks and mitigation strategies

“…Undertaking QMRA for various exposures to stormwater can nevertheless be challenging due to difficulties in discerning the sources and concentrations of pathogen contamination in stormwater, and assumptions regarding pathogen sources, fate, and transport are needed depending on the availability of site-specific information. Several (n = 16) QMRA studies have relied upon concentrations of pathogens observed in stormwater-impacted coastal, recreational waters, or drinking source waters for assessment of health risks (Donovan et al, 2008;Soller et al, 2010;ten Veldhuis et al, 2010;Fewtrell et al, 2011;Tseng and Jiang, 2012;Andersen et al, 2013;McBride et al, 2013;de Man et al, 2014;Sales-Ortells and Medema, 2014;Schoen et al, 2014;Soller et al, 2014;Adell et al, 2016;Krkosek et al, 2016;Lim et al, 2017;Soller et al, 2015;Soller et al, 2017), and two have used other modelling approaches for microbial health risks such as Bayesian network modelling (Goulding et al, 2012) or disease transmission models (Soller et al, 2006). These recreational water QMRAs are reviewed in detail by Federigi et al (2019).…”

“…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). Limited information is available for pathogen removal by stormwater treatment barriers and would be informative for conducting risk analyses.…”

A new methodology for modelling of health risk from urban flooding exemplified by cholera – case Dhaka, Bangladesh

“…The simulation of the pathogens and their transport in the urban drainage system and on the surface were carried out using a 1D advection-dispersion model (MOUSE TRAP) (Garsdal et al, 1995) of the urban drainage system, which was coupled with a 2D advection-dispersion model (MIKE 21) (Hartnack et al, 2009). The 1D advection-dispersion models have previously been applied to cases for simulation of the transport and dilution of wastewater (Mark et al, 1996(Mark et al, , 1998Andersen et al, 2013).…”

Evaluating health hazard of bathing waters affected by combined sewer overflows

“…In the former study, hazard was assessed by statistical analysis of observed bacterial concentrations during 6 days in a year that was considered as representative whereas in the latter one it was estimated by simple assumptions. Andersen et al (2013) presented a coupled urban drainage and sea water quality model to quantify microbial risk during a swimming competition where lots of gastrointestinal illnesses occurred due to the presence of CSO in sea water. O'Flaherty et al 2019evaluated human exposure to antibiotic resistant-Escherichia coli through recreational water.…”

“…Sokolova et al (2013) and Thupaki et al (2010) presented hydrodynamic 3D models of lakes to simulate E. Coli based on contaminant discharges estimated from observations at the affluent rivers and/or sewers. Also, coupled urban drainage and water quality models of receiving water bodies were developed to simulate spatial and temporal variations of bacterial concentrations for bathing water quality affected CSOs (Andersen et al, 2013;Marchis et al, 2013).…”