Modeling the health impact of wastewater contamination events in drinking water networks

Pathogen intrusion in drinking water systems can pose severe health risks. To better prepare in planning and responding to such events, computational models that capture the intrusion and health impact dynamics are needed. This study presents a novel benchmark testbed that integrates current knowledge on pathogen transport and fate in chlorinated systems and can assess infection risk from contamination events. The model considers organic matter degradation, chlorine decay mechanisms, pathogen inactivation kinetics, as well as stochastic water demands. We studied modeling of wastewater intrusion events that can occur anywhere within a chlorinated and non-chlorinated network. We applied the Quantitative Microbial Risk Assessment framework focusing on three pathogens: enterovirus, Campylobacter , and Cryptosporidium , and their respective dose-response models. Synthetic household-level water demand time series were used to model the individual water consumption timing and calculate the infection risk (exposure via ingestion). Model outcomes indicate that while chlorination aids mitigation, larger contaminations can still lead to infections due to chlorine resistance (for Cryptosporidium ) and chlorine depletion at the contamination point. In our example scenarios, chlorine-susceptible pathogens infected 0.78 – 26.6 % of the downstream population, while chlorine-resistant ones infected the entire downstream population. Enterovirus infection risk is higher, despite the concentrations in the contamination source being lower, due to the lower susceptibility to chlorine than Campylobacter. In non-chlorinated networks, the modeled wastewater contamination events led to 11 – 46 % infection risk in the total population, depending on the contamination location. Hydraulic uncertainty had a limited influence on infection risk. Furthermore, Campylobacter's infection risk is more sensitive to the initial concentration in the contamination source whereas enterovirus infection risk to the inactivation rate. The model further indicates that the time window for effective mitigation of the magnitude of a waterborne outbreak is short (within hours). • Chlorination reduces infections by susceptible pathogens around 50 times. • The response time for mitigation is usually 5–10 h post-contamination. • A wastewater contamination event causes infections, despite chlorination. • Pathogen concentration, inactivation rate, and duration influence infection risk. • In chlorinated systems enterovirus infection risk is higher than Campylobacter.

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Publication Details

Journal
Journal of Cleaner Production
Published
2024-10-18
DOI
https://doi.org/10.1016/j.jclepro.2024.143997
Citations
3
Primary Topic
Water Treatment and Disinfection
Type
article
Field-Weighted Citation Impact
0.94

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article

Modeling the health impact of wastewater contamination events in drinking water networks

Gertjan Medema, Δημήτριος Γ. Ηλιάδης, Stelios G. Vrachimis, Patrick Smeets et al.
3 citations
Journal of Cleaner Production
Water Treatment and Disinfection
0.94
article

Modeling the health impact of wastewater contamination events in drinking water networks

Gertjan Medema, Δημήτριος Γ. Ηλιάδης, Stelios G. Vrachimis, Patrick Smeets, Sotirios Paraskevopoulos, Marios M. Polycarpou, Marios Kyriakou
article en
3 citations

Abstract

Pathogen intrusion in drinking water systems can pose severe health risks. To better prepare in planning and responding to such events, computational models that capture the intrusion and health impact dynamics are needed. This study presents a novel benchmark testbed that integrates current knowledge on pathogen transport and fate in chlorinated systems and can assess infection risk from contamination events. The model considers organic matter degradation, chlorine decay mechanisms, pathogen inactivation kinetics, as well as stochastic water demands. We studied modeling of wastewater intrusion events that can occur anywhere within a chlorinated and non-chlorinated network. We applied the Quantitative Microbial Risk Assessment framework focusing on three pathogens: enterovirus, Campylobacter , and Cryptosporidium , and their respective dose-response models. Synthetic household-level water demand time series were used to model the individual water consumption timing and calculate the infection risk (exposure via ingestion). Model outcomes indicate that while chlorination aids mitigation, larger contaminations can still lead to infections due to chlorine resistance (for Cryptosporidium ) and chlorine depletion at the contamination point. In our example scenarios, chlorine-susceptible pathogens infected 0.78 – 26.6 % of the downstream population, while chlorine-resistant ones infected the entire downstream population. Enterovirus infection risk is higher, despite the concentrations in the contamination source being lower, due to the lower susceptibility to chlorine than Campylobacter. In non-chlorinated networks, the modeled wastewater contamination events led to 11 – 46 % infection risk in the total population, depending on the contamination location. Hydraulic uncertainty had a limited influence on infection risk. Furthermore, Campylobacter's infection risk is more sensitive to the initial concentration in the contamination source whereas enterovirus infection risk to the inactivation rate. The model further indicates that the time window for effective mitigation of the magnitude of a waterborne outbreak is short (within hours). • Chlorination reduces infections by susceptible pathogens around 50 times. • The response time for mitigation is usually 5–10 h post-contamination. • A wastewater contamination event causes infections, despite chlorination. • Pathogen concentration, inactivation rate, and duration influence infection risk. • In chlorinated systems enterovirus infection risk is higher than Campylobacter.

Journal of Cleaner ProductionVol. 479
University of Cyprus (CY), KWR Water Research Institute (NL), Delft University of Technology (NL)
Horizon 2020 Framework Programme, European Research Council
Clean water and sanitation
Openalex Percentile: Top 24%
Water Treatment and Disinfection
0.94
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