Effectiveness of Wastewater-Based Epidemiology as an Early Warning Tool to Detect SARS-CoV-2 (COVID-19)

Medical diagnostic tests to detect Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for individuals in the United States were initially limited to people who were traveling or symptomatic to track disease incidence due to the cost of providing testing for all people in a community on a routine basis. As an alternative to randomly sampling large groups of people to track disease incidence at significant cost, wastewater-based epidemiology (WBE) is a well-established and cost-effective technique to passively measure the prevalence of disease in communities without requiring invasive testing. WBE can also be used as a forecasting tool since the virus is shed in individuals prior to developing symptoms that might otherwise prompt testing. This study applied the WBE approach to understand its effectiveness as a possible forecasting tool by monitoring the SARS-CoV-2 levels in raw wastewater sampled from sewer lift stations at a large public university campus setting including dormitories, academic buildings, and athletic facilities. The WBE analysis was conducted by sampling from building-specific lift stations and enumerating target viral copies using RT-qPCR analysis. The WBE results were compared with the 7-day rolling averages of confirmed infected individuals for the following week after the wastewater sample analysis. In most cases, changes in the WBE outcomes were followed by similar trends in the clinical data. The positive predictive value of the applied WBE approach was 86% for the following week of the sample collection. In contrast, positive correlations between the two data with Spearmen correlation (rs) ranged from 0.16 to 0.36. A stronger correlation (rs = 0.18 to 0.51) was observed when WBE results were compared with COVID-19 cases identified on the next day of the sampling events. The P value of 0.007 for Dorm A suggests high significance, while moderate significance was observed for the other dormitories (B, C, and D). The outcomes of this investigation demonstrate that WBE can be a valuable tool to track the progression of diseases like COVID-19 seven days before diagnostic cases are confirmed, allowing authorities to take necessary measures in advance and also enable authorities to decide to reopen a facility after a quarantine.

Application of wastewater-based epidemiological monitoring of COVID-19 for disease surveillance in the city

Wastewater-based surveillance serves as a supplementary approach to clinical surveillance of COVID-19 during the epidemic.This study aimed to track the prevalence of the disease and the viral genetic variability through wastewater-based surveillance in the post-epidemic era.Between January to December 2023,samples were collected from the influent lines of two wastewater treatment plants(WWTPs),concentrated using PEG8000,and subjected to detection of the target genes ORF 1ab and N of SARS-CoV-2 via reverse transcriptional quantitative PCR(RT-qPCR).For next-generation sequencing(NGS),high-quality samples from both wastewater and clinical patients were selected.Weekly analysis were performed using R software to evaluate the correlation between the SARSCoV-2 RNA concentrations in wastewater and positive rate of reported cases,indicating a positive correlation.Genetic diversity patterns of SARS-CoV-2 in wastewater resembled those in the patient source based on Principal Coordinates Analysis(PCoA)with three clusters for different stages.The rise of RNA concentration in wastewater indicates the growth of cases and the emergence of new variants,serving as an early warning of potential viral mutations,disease outbreaks even possible epidemics.Furthermore,the genomic surveillance of wastewater could help identify new variants that may not be captured through population monitoring,especially when sample sizes are insufficient.Consequently,surveillance of SARS-CoV-2 in municipal wastewater has emerged as a reliable,earlywarning monitoring system for COVID-19 in the post-epidemic era.

Monitoring of regional drug abuse through wastewater-based epidemiology—A critical review

Wastewater-based epidemiology is a new approach to monitor drug abuse. It involves collecting wastewater, analysis of residues of drugs or its metabolites in wastewater, and back-calculation of drug consumption by taking into account wastewater flow, stability of drug target residues in wastewater, and excretion rates of drugs/metabolites. Wastewater-based epidemiology has the advantages of being inexpensive and yielding more consistent and near real-time results. It has the great potential to supplement the existing drug monitoring methods. It can be used to build large-scale(regional, national, or even continental) monitoring networks that would yield spatial patterns and temporal trends in drug abuse. This paper described in detail the principle and procedures of this wastewater-based approach. Application of this approach across the globe was also reviewed. The uncertainties involved in the approach and knowledge gaps were identified. Finally, necessity, benefits, and feasibility to set up nation or province-wide monitoring networks based on wastewater analysis in China were discussed.

Estimating the effective reproduction number of COVID-19 from population-wide wastewater data:An application in Kagawa,Japan

Although epidemiological surveillance of COVID-19 has been gradually downgraded globally,the transmission of COVID-19 continues.It is critical to quantify the transmission dynamics of COVID-19 using multiple datasets including wastewater virus concentration data.Herein,we propose a comprehensive method for estimating the effective reproduction number using wastewater data.The wastewater virus concentration data,which were collected twice a week,were analyzed using daily COVID-19 incidence data obtained from Takamatsu,Japan between January 2022 and September 2022.We estimated the shedding load distribution(SLD)as a function of time since the date of infection,using a model employing the delay distribution,which is assumed to follow a gamma distribution,multiplied by a scaling factor.We also examined models that accounted for the temporal smoothness of viral load measurement data.The model that smoothed temporal patterns of viral load was the best fit model(WAIC=2795.8),which yielded a mean estimated distribution of SLD of 3.46 days(95%CrI:3.01–3.95 days).Using this SLD,we reconstructed the daily incidence,which enabled computation of the effective reproduction number.Using the best fit posterior draws of parameters directly,or as a prior distribution for subsequent analyses,we first used a model that assumed temporal smoothness of viral load concentrations in wastewater,as well as infection counts by date of infection.In the subsequent approach,we examined models that also incorporated weekly reported case counts as a proxy for weekly incidence reporting.Both approaches enabled estimations of the epidemic curve as well as the effective reproduction number from twice-weekly wastewater viral load data.Adding weekly case count data reduced the uncertainty of the effective reproduction number.We conclude that wastewater data are still a valuable source of information for inferring the transmission dynamics of COVID-19,and that inferential performance is enhanced when those data are combined with weekly incidence data.

Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity:A prediction study

Background:The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems.The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19.We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data.Methods:Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties,we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29,2020 to June 30,2022.We included covariates such as COVID-19 vaccine coverage in the county,comorbidities,demographic variables,and holiday gatherings.Findings:Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission.Models that included wastewater had higher predictive power than models that included clinical cases only,increasing the accuracy of the model by 15%.Predicted hospital admissions correlated highly with observed admissions(r¼0.77)with an average difference of 0.013 hospitalizations per 100,000(95%CI¼[0.002,0.025])Interpretation:Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone.The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.

The use of wastewater analysis in forensic intelligence:drug consumption comparison between Sydney and different European cities

Wastewater analysis offers objective and complementary information to illicit drug agencies by monitoring patterns of illicit drug consumption.In this study,wastewater samples from three different wastewater treatment plants in Sydney,Australia were collected in March 2016.Ten targeted drugs were analysed and temporal and geographical analyses were performed to obtain a better understanding of the type and amount of illicit drugs consumed in Sydney in comparison with similar studies conducted around Australia and in Europe.Among the targeted drugs,methamphetamine was consumed the most,followed by cocaine and 3,4-methylenedioxymethamphetamine(MDMA).Weekly patterns were observed where a peak during the weekend was present.The geographical analysis showed differences between the regions targeted.This observation may be related to socio-demographic aspects.The comparison of our study to other data sources from Australia showed a high consumption of methamphetamine in Sydney and Western Australia.The comparison between Sydney and different European cities revealed a difference in consumption,which is in line with traditional market indicators.The information obtained through wastewater analysis provides complementary information regarding illicit drug consumption,the size,and the evolution of the illicit drug market.This,ultimately,will assist authorities in making informed decisions.

Environmental surveillance of SARS-CoV-2 RNA in wastewater systems and related environments in Wuhan:April to May of 2020

Wastewater-based epidemiology(WBE)has emerged as an effective environmental surveillance tool in monitoring fecal-oral pathogen infections within a community.Congruently,SARS-Co V-2,the etiologic agent of COVID-19,has been demonstrated to infect the gastrointestinal tissues,and be shed in feces.In the present study,SARS-Co V-2 RNA was concentrated from wastewater,sludge,surface water,ground water,sediment,and soil samples of municipal and hospital wastewater systems and related environments in Wuhan during the COVID-19 middle and low risk periods,and the viral RNA copies quantified using reverse transcription quantitative polymerase chain reaction(RT-q PCR).From the findings of this study,during the middle risk period,one influent sample and three secondary effluents collected from waste water treatment plant 2,as well as two samples from Jinyintan Hospital wastewater system influent were SARS-Co V-2 RNA positive.One sludge sample collected from Guanggu Branch of Tongji Hospital,which was obtained during the low risk period,was also positive for SARS-Co V-2 RNA.These study findings demonstrate the significance of WBE in continuous surveillance of SARS-Co V-2 at the community level,even when the COVID-19 prevalence is low.Overall,this study can be used as an important reference for contingency management of wastewater treatment plants and COVID-19 prevention and control departments of Wuhan.