https://doi.org/10.1016/j.scitotenv.2022.158964

Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches

https://doi.org/10.1016/j.scitotenv.2023.164495

Monitoring influenza and respiratory syncytial virus in wastewater. Beyond COVID-19

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028212

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747234

COVID-19 health data analysis and personal data preserving: A homomorphic privacy enforcement approach

As wastewater-based epidemiology is utilized for the surveillance of COVID-19 at the community level in many countries, it is crucial to develop and validate reliable methods for virus detection in sewage. The most important step in viral detection is the efficient concentration of the virus particles and/or their genome for subsequent analysis. ABSTRACT Wastewater-based epidemiology (WBE) has been widely used to track levels of SARS-CoV-2 infection in the community during the COVID-19 pandemic. Due to the rapid expansion of WBE, many methods have been used and developed for virus concentration and detection in wastewater. However, very little information is available on the relative performance of these approaches. In this study, we compared the performance of five commonly used wastewater concentration methods for the detection and quantification of pathogenic viruses (SARS-CoV-2, norovirus, rotavirus, influenza, and measles viruses), fecal indicator viruses (crAssphage, adenovirus, pepper mild mottle virus), and process control viruses (murine norovirus and bacteriophage Phi6) in laboratory spiking experiments. The methods evaluated included those based on either ultrafiltration (Amicon centrifugation units and InnovaPrep device) or precipitation (using polyethylene glycol [PEG], beef extract-enhanced PEG, and ammonium sulfate). The two best methods were further tested on 115 unspiked wastewater samples. We found that the volume and composition of the wastewater and the characteristics of the target viruses greatly affected virus recovery, regardless of the method used for concentration. All tested methods are suitable for routine virus concentration; however, the Amicon ultrafiltration method and the beef extract-enhanced PEG precipitation methods yielded the best recoveries. We recommend the use of ultrafiltration-based concentration for low sample volumes with high virus titers and ammonium levels and the use of precipitation-based concentration for rare pathogen detection in high-volume samples. IMPORTANCE As wastewater-based epidemiology is utilized for the surveillance of COVID-19 at the community level in many countries, it is crucial to develop and validate reliable methods for virus detection in sewage. The most important step in viral detection is the efficient concentration of the virus particles and/or their genome for subsequent analysis. In this study, we compared five different methods for the detection and quantification of different viruses in wastewater. We found that dead-end ultrafiltration and beef extract-enhanced polyethylene glycol precipitation were the most reliable approaches. We also discovered that sample volume and physico-chemical properties have a great effect on virus recovery. Hence, wastewater process methods and start volumes should be carefully selected in ongoing and future wastewater-based national surveillance programs for COVID-19 and beyond.

https://doi.org/10.1128/spectrum.01102-22

Comparative Assessment of Filtration- and Precipitation-Based Methods for the Concentration of SARS-CoV-2 and Other Viruses from Wastewater

https://doi.org/10.1016/j.scitotenv.2022.152958

Longitudinal monitoring of SARS-CoV-2 in wastewater using viral genetic markers and the estimation of unconfirmed COVID-19 cases

Abstract. This study examined selected disease burdens in Bangladesh associated with particulate matter exposure using gridded population and PM2.5 data between 2001 and 2019. The Global Exposure Mortality Model (GEMM) was used to determine hazard ratio (HR) and disease specific mortality. Besides, trend of PM2.5 and selected diseases were evaluated. Results revealed that strong seasonality existed in PM2.5 with winter exhibited maximum concentration. The trend assessment showed PM2.5 was increasing over time. Among five diseases assessed, LRI was most sensitive to an increase of PM2.5, followed by IHD, LC, CEV and COPD. Excess mortality was found to be elevating because of PM2.5, particularly in major cities. This study could be useful in advancing research in the disease burden attributable to ambient air pollution in Bangladesh.


AN EXPLORATORY STUDY TO EXAMINE ABUNDANCE OF PM2.5 AND ASSOCIATED DISEASE BURDEN IN BANGLADESH

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Longitudinal monitoring of SARS-CoV-2 in wastewater using viral genetic markers and the estimation of unconfirmed COVID-19 cases

AN EXPLORATORY STUDY TO EXAMINE ABUNDANCE OF PM<sub>2.5</sub> AND ASSOCIATED DISEASE BURDEN IN BANGLADESH