Analysing wastewater can be used to track infectious disease agents that are shed via stool and urine. Sewage surveillance of SARS-CoV-2 has been suggested as tool to determine the extent of COVID-19 in cities and serve as early warning for (re-)emergence of SARS-CoV-2 circulation in communities. The focus of this review is on the strength of evidence, opportunities and challenges for the application of sewage surveillance to inform public health decision making. Considerations for undertaking sampling programs are reviewed including sampling sites, strategies, sample transport, storage and quantification methods; together with the approach and evidence base for quantifying prevalence of infection from measured wastewater concentration. Published SARS-CoV-2 sewage surveillance studies (11 peer reviewed, and 10 pre-prints) were reviewed to demonstrate the current status of implementation to support public health decisions. Whilst being very promising, a number of areas were identified requiring additional research to further strengthen this approach and take full advantage of its potential. In particular, design of adequate sampling strategies, spatial and temporal resolution of sampling, sample storage, replicate sampling and analysis, controls for the molecular methods used for quantification of SARS-CoV-2 RNA in wastewater. The use of appropriate prevalence data and methods to correlate or even translate SARS-CoV-2 concentrations in wastewater to prevalence of virus shedders in the population is discussed.
Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering additional community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater can provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2, culminating in recommended strategies that can be implemented to identify and mitigate these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.
The potential health risk from viruses, associated with the consumption of lettuce crops spray irrigated with secondary‐treated municipal effluent, has been evaluated in the first level investigation of a tiered microbial risk assessment. The study assessed the impact of two factors on the estimated risk of infection: a suitable probability density function for the occurrence of human enteroviruses in irrigation water and appropriate die‐off rates for viruses on lettuce crops. A Monte Carlo simulation using a log‐normal and a nonparametric, kernel estimated probability density function indicated that slight changes in the upper tail of the probability density function had a relatively low effect on the estimated infection rates. Predicted infection rates were much more sensitive to the decay rate of viruses than occasional high virus numbers. The median and 99th percentile risks of infection from the overall model were 0.10 and 0.51/10 000 lettuce consumers, respectively, indicating possible human health concern, and the justification of a more detailed microbial risk assessment.
Quantitative microbial risk assessment (QMRA), the assessment of microbial risks when model inputs and estimated health impacts are explicitly quantified, is a valuable tool to support water safety plans (WSP). In this paper, research studies undertaken on the application of QMRA in drinking water systems were reviewed, highlighting their relevance for WSP. The important elements for practical implementation include: the data requirements to achieve sufficient certainty to support decision-making; level of expertise necessary to undertake the required analysis; and the accessibility of tools to support wider implementation, hence these aspects were the focus of the review. Recommendations to support the continued and growing application of QMRA to support risk management in the water sector are provided.
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