Abstract
Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping to meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet, economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, especially viral pathogen exposure, limit the widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate the viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling viral health risks in the context of water reuse. First, we describe current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We outline promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies will be ready to identify and implement viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in a more robust assessment of water reuse risk.
