DHS/NIST Workshop: Standards to 

Support an Enduring Capability in 

Wastewater Surveillance for Public 

Health

Poster Abstracts

June 14-18th 2021

Virtual Poster Session

https://swwsworkshop.virtualpostersession.org/
CEDAR-MC: Clinical and Environmental Dynamics of Antibiotic Resistance within 

Microbial Communities

George Hanna1,2, Bashir Hamidi1, Scott Curry1, Cheryl Carmack2, Alexander V. Alekseyenko1

1

Medical University of South Carolina; 2Charleston Waterkeeper

Introduction: Escape into the environment and the persistence of antibiotic resistance is an imminent threat to 

the healthcare advances attained in the 20th century. Microbial communities that co-exist with resistant bacteria 

may help uncover novel strategies for global antimicrobial control and curb emergence and maintenance of 

resistance. However, availability of clinically relevant specimens with complementary samples from the built and 

natural environment is a major obstacle to effective studies of the dynamics of resistance in the affected human 

populations and in their surroundings. 

Methods: We bring together environmental and clinical measurements of the microbial communities with 

evidence for emerging resistance by linking existing local clinical and environmental surveillance programs. The 

clinical specimens are sourced from the Medical University of South Carolina (MUSC) infection surveillance culture 

program that routinely samples the MUSC patient population for clinically relevant pathogens. The environmental 

specimens are the result of partnership with a local non-profit, Charleston Waterkeeper, that performs water 

quality monitoring at popular recreational spots in the area.

Results: The surplus infection surveillance specimens are made available for research via a Living μBiome Bank 

system that enables nuanced electronic phenotyping of patient populations for just-in-time capture of clinical 

microbiology specimens. We show the feasibility of sequencing these clinical specimens for microbiota 

composition, which in combination with resistance status is invaluable in characterizing the broader structure of 

resistant microbial communities. The environmental specimens collected from May 2018 through October 2020

have been banked to be assessed for evidence of antibiotic resistance of their constituent microbiota.

Discussion: We continue to expand the resources and the biobanks associated with the clinical and environmental 

surveillance programs with an overarching goal to control infections by understanding the dynamics of emergence 

and maintenance of resistance. This project demonstrates the value of collaboration between academic 

healthcare and community-funded environmental monitoring programs.

Key words: antibiotic resistance, living biobank, water quality

Standards and control materials used: Yes

Email for corresponding author: alekseye@musc.edu
A Step-By-Step Approach to Evaluating SARS-CoV-2 Methods: Adaptability for Future Use with Other Microorganisms

Brienna L. Anderson-Coughlin1 and Kalmia E. Kniel1

1

Center for Environmental and Wastewater-based Epidemiological Research/Department of Animal and Food Sciences, University of 

Delaware, Newark, Delaware

There is a breadth of research regarding enteric viruses in agricultural waters and using viruses such as pepper mild mottle virus 

(PMMoV) as fecal contamination indicators. Traditionally used in food safety research, PMMoV is now being employed for 

wastewater surveillance efforts during the COVID-19 pandemic. The purpose of this study was to determine how existing 

wastewater surveillance methods for SARS-CoV-2 could be adapted for other microorganisms, using PMMoV as a model.

Wastewater was collected across New Castle County, Delaware, incubated, filtered, and concentrated. Viral concentrates were 

extracted, and detection performed via RT-qPCR for PMMoV and the N1 and N2 SARS-CoV-2 targets. Variability in recovery along 

with impacts of incubation (none or 60°C for 60 min) and refrigerated storage (0-hour or 24-hour) were evaluated. Delta cycle 

threshold (dCT), the number of cycles before completion (CT=40) at which the target amplified across the threshold (e.g., 

CT38=dCT2).

PMMoV was detected in all (n=48) replicates for incubated and non-incubated samples with 0- and 24-hour holds. SARS-CoV-2 N1 

and N2 were detected in 95.8% (n=46) of incubated samples in each treatment of 0 and 24 hour holds, in 79.2% (n=19) of nonincubated with 0-hour hold, and 50% (n=12) of non-incubated with 24-hour hold. PMMoV detection in samples (n=6) was 

significantly (p<0.05) greater than N1 and N2. PMMoV increased by 3.16 ± 1.18 dCT in processed (9.25 ± 1.15 dCT) samples

compared to unprocessed (6.09 ± 0.98 dCT). N1 and N2 increased by 0.77 ± 1.38 and 0.63 ± 1.32 dCT in processed (0.95 ± 1.37 and 

1.04 ± 1.29 dCT) compared to unprocessed (0.18 ± 0.61 and 0.41 ± 0.90 dCT), respectively.

The detection and recovery efficacy of the method explored here confirmed the potential for its adaptation for use with additional 

organisms. These data provide evidence that with appropriate modifications, the methods and infrastructure created during the 

COVID-19 pandemic and currently used for SARS-CoV-2 surveillance, can be successfully utilized for viral, bacterial, and parasitic 

organisms of interest.

Key words: Wastewater surveillance, Method Adaptation, Viruses

Standards and control materials used: Positive and negative controls for this study consisted of plasmid gene sequences (IDTDNA: 

10006625) and nuclease-free water (Qiagen: 129114), respectively.

Email for corresponding author: BriennaA@udel.edu

Figure 1. The detection of PMMoV and SARS-CoV-2 (N1 and N2 genes) from wastewater samples. A. The number of replicates (n=12) for each target in which 

positive detection occurred, treatments evaluated included the incubation (60C for 60 minutes) or no incubation and storage (4C for 24 hours) or no storage prior to 

completing wastewater filtration, concentration, nucleic acid extraction and detection. B. The detection level, represented by ddCT values (the difference in CT between 

unprocessed and processed samples), of targets for each of the six samples processed in triplicate. Large variation in recovery was observed across wastewaters and 

between PMMoV and SARS-CoV-2.

A B
The impact of data on source control

Anne-li Steutel-Maron

Kando

This abstract will elaborate on how we should rethink wastewater for water reuse, and data's role in securing 

consistently high-quality wastewater. Raw wastewater is a valuable raw material. Having a consistent, stable, and 

high quality raw material is essential for maximizing its value. For wastewater, controlling the quality of inputs to 

the collection network is vital to realizing its value as a resource. Optimized ‘source control’ cannot rely on random 

sampling, as water-reuse requires high quality water that needs to rely on precise, reliable, and continuous flow 

of data, giving reuse plants and service providers a total understanding of their water quality.

Key words: waterreuse Key word 1; source control Key word 2; data

Standards and control materials used: ISO 5667-10:2020

Email for corresponding author: anne-li@kando.eco

Figure 1. Pollution found with grab sampling
Figure 2. Pollution found with smart monitoring & sampling
Optimizing Sampling Strategies for Large Rural Regions

Anuj Tiwari, Aaron Packman, Charles Williams, Wilnise Jasmin, Rachel Poretsky, Wayne Duffus, Sarah 

Patrick, Leslie Wise, Charlie Catlett1

Corresponding author: Charlie Catlett, ccatlett@uillinois.edu

Abstract 

Wastewater Based Epidemiology (WBE) typically focuses on wastewater treatment plants 

(WWTPs) and the corresponding community. However, many public health questions require 

insight across many communities such as at the county or state level. What is the optimal 

sampling strategy in regions such as rural counties with dozens of treatment plants and private 

septic systems, or in entire states with many such counties?

The State of Illinois is a primarily rural region comprising 58k square miles with a population of 

roughly 16M, over half of whom live within 50 miles of Chicago. Outside of the Chicago area, 

Illinois has roughly 140 cities with populations greater than 10k and nearly 1,000 with populations 

under 10k. To understand and track infectious disease such as COVID-19 across these 

communities, a comprehensive WBE sampling plan would involve over 1,000 WWTPs and 

countless private septic systems.

In Sep 2020, we introduced a machine learning based COVID-19 Vulnerability Index (C19VI) 

using CDC’s six themes: (a) socioeconomic status, (b) household composition & disability, (c) 

minority status & language, (d) housing type & transportation, (e) epidemiological factors, and (e) 

healthcare system factors2. This model uses an ensemble learning approach with recursive 

partitioning to optimally compute non-linear relationships between input themes. We refined the 

model in early 2021 with additional demographic and sequencing information to evaluate WBE 

sampling strategies across Illinois counties to support an expansion of WBE from currently several 

dozen to over 150 WWTPs. The vulnerability index supported the evaluation of various sampling 

strategies, such as selecting the largest population centers within each of the eleven COVID-19 

“Restore Illinois” regions3, and eventually the current strategy of sampling from the largest 

population center in each of Illinois’ 102 counties. In this poster we outline the models and 

methods used, including various sampling strategies explored, the current strategy, and 

experiments planned to evaluate the sampling strategy as we expand to 150 WWTPs in 2021.

Keywords: COVID-19; Wastewater Based Epidemiology (WBE); Wastewater Sampling Strategy; COVID-19 Vulnerability Modeling; 

Machine Learning (ML)

 1 Tiwari and Catlett are from the University of Illinois Discovery Partners Institute; Packman is from 

Northwestern University; Poretsky is from the University of Illinois-Chicago; Jasmin is from the Chicago 

Department of Public Health; and Williams, Duffus, Patrick, and Wise are from the Illinois Department of 

Public Health.

2 Tiwari, Anuj, Arya V. Dadhania, Vijay Avin Balaji Ragunathrao, and Edson RA Oliveira. "Using machine 

learning to develop a novel COVID-19 Vulnerability Index (C19VI)." Science of The Total Environment 773 

(2021): 145650.

3 Restore Illinois. Available at https://www.dph.illinois.gov/restore
Parameters influencing the methods of detection for SARS-CoV-2 RNA wastewater 

surveillance using RT-PCR quantification

Golam Islama*, Ashley Gedgea, Linda Lara-Jacoboa, Denina Simmonsa, Jean-Paul Desaulniersa, 

Andrea Kirkwooda

a

The University of Ontario Institute of Technology

Abstract

The COVID-19 pandemic presented many challenges to public health units attempting to track 

infected individuals by performing individual clinical testing of large populations. Due to the 

lack of trained personnel and shortage of testing materials, many undiagnosed but infected 

individuals caused substantial viral spread within communities1. Thus, it is crucial that 

alternative surveillance methods are explored, which can provide public health organizations 

with information on the number of infected individuals. Such methods allow for real-time

allocation of resources, staff, and restrictive measures to reduce further spread. Wastewater 

surveillance of viral RNA has emerged as a surprising approach to track and monitor the 

presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in communities. 

Considering the novelty of the methods used, the aim of this study was to determine which 

parameters are suitable in order to store, pasteurize, and concentrate the viral particles found in 

raw wastewater influent. Six wastewater treatment plants (WWTPs) provided 500mL samples 

three times a week from different municipalities in the Durham Region, Ontario, Canada.

Storage conditions were investigated by storing 30mL raw influent at 4◦C, -20◦C, -80◦C for 7, 

and 14 days and analyzed using a Three-Way ANOVA (p<0.005). Pre-treatment of the samples 

included pasteurization for 60 mins at 60◦C analyzed using t-tests (p<0.005), and concentrated 
using polyethylene glycol (PEG) for either 0 or 12 hours and analyzed using a t-test (p<0.005).

Combined, this study presents recommendations for developing reliable, accurate, sensitive and 

reproducible estimation of the evolution of the SARS-CoV-2 virus in wastewater. 

Keywords: Covid-19, SARS-CoV-2, Wastewater, RT-qPCR, Pasteurization, Viral 

Concentration

Standards and control materials used: Sars-CoV-2 Standard (EDX), pMMoV gBlock (IDT)

Email for Corresponding author: a*Islam.Golam@ontariotechu.ca

References

1. Wang,W., et al., Detection of Sars-CoV-2 in Different Types of Clinical Specimens. 

JAMA, 2020 323(18): p.1843-1844.
Metagenomics for Monitoring Antibiotic Resistance in Water and Wastewater: Key Considerations 

and a Path Towards Standard Protocols

Benjamin C. Davis1

, Jeannette Calarco2, Krista Liguori1, Erin Milligan1, Valerie J. Harwood2, Amy Pruden,1 Ishi 

Keenum1*

1 Via Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia

2 Department of Integrative Biology, University of South Florida, Tampa, Florida

*Corresponding Author

Environmental dimensions of antibiotic resistance are increasingly being recognized and are essential to

a One-Health framework for combatting antibiotic resistance [1]. Strategies are emerging for comprehensive 

surveillance of resistomes (i.e., all antibiotic resistance determinants carried across a microbial community) in 

surface water, wastewater, and recycled water matrices to both establish a baseline and to monitor for changes 

in resistance patterns that occur over time [2]. Metagenomics, i.e., the study of an entire microbial community’s 

genomic information via shotgun next-generation sequencing (NGS), is emerging as a powerful tool for 

characterizing these aquatic resistomes. Metagenomics is an attractive approach to monitoring because it 

theoretically allows for the simultaneous detection of all antibiotic resistance genes (ARGs), mobile genetic 

elements (MGEs), as well as the microbial composition in an environmental matrix without a priori knowledge of 

targets, circumventing the narrow target scopes of both quantitative polymerase chain reaction and culturing. 

With short- and long-read sequencing technologies, the contextualization of ARGs (e.g., their positions on MGEs

and taxonomic affiliation) are also further being realized [3]. However, NGS approaches to water quality 

monitoring have only been applied in the last decade and guidance is still needed with respect to sampling, DNA 

extraction, library preparation, sequencing platforms, sequencing depths required for unique matrices and 

targets, and metrics that are ultimately mined and derived from the raw sequencing data. 

Here we conducted a comprehensive, systematic literature review of articles that use NGS to investigate 

the resistomes of surface water, wastewater, and recycled water. We identified 98 peer-reviewed papers 

meeting our search criteria and systematically compiled and compared sample processing workflows, 

sequencing approaches, and bioinformatic analyses to find commonalities in data generation and data 

reporting. We also performed a robust meta-analysis of raw sequencing data retrieved from each study’s 

accompanied Sequence Read Archive (SRA) Bioproject to extract summary statistics as well as determine the 

intrinsic sequence diversities using Nonpareil [4]. The findings help inform a framework for standardized 

metagenomic monitoring of antibiotic resistance in aquatic environments.

Key words: metagenomics, water quality monitoring, antibiotic resistance, standardization

Standards and control materials used: Mock Community [5]

Email for corresponding author: ikeenum@vt.edu
Figure 1. Results of Nonpareil (Rodriguez et al. 2018), an estimator of sequence diversity and depth needed to achieve 100% coverage of metagenomes. 

Metagenomes (n=946) of diverse water and wastewater matrices were downloaded from the Sequence Read Archive (SRA) from all papers identified in a 

comprehensive literature review (98 articles). Trends show that an order of magnitude deeper sequencing (measured in giga base pairs (Gbp)) is needed to 

achieve 100% coverage of the complex microbial communities in many aquatic matrices. Negative Controls = miliq water; Influent = raw sewage entering a 

wastewater treatment plant; Effluent = treated wastewater. 

References:

1. European Commission: A European One Health Action Plan against Antimicrobial Resistance (AMR). 2017.

2. JPIAMR: Strategic Research and Innovation Agenda on Antimicrobial Resistance. 2019.

3. Che Y, Xia Y, Liu L, Li AD, Yang Y, Zhang T: Mobile antibiotic resistome in wastewater treatment plants revealed by 

Nanopore metagenomic sequencing. Microbiome 2019, 7:1–13.

4. Rodriguez-R LM, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT: Nonpareil 3: Fast Estimation of Metagenomic 

Coverage and Sequence Diversity. mSystems 2018, 3:1–9.

5. Peabody MA, Van Rossum T, Lo R, Brinkman FSL: Evaluation of shotgun metagenomics sequence classification 

methods using in silico and in vitro simulated communities. BMC Bioinformatics 2015, 16. 
Importance of Validation for Wastewater Surveillance

Brian M. Swalla

IDEXX Laboratories, One IDEXX Drive, Westbrook, Maine 04092

Wastewater surveillance has delivered actionable public health data over the course of the COVID-19 pandemic. 

Because of the urgent nature of the pandemic, the extent of validation for currently used methods varies widely. 

Many methods were deployed before significant data was gathered on performance, and may not have been 

widely tested with a diversity of wastewater samples. As wastewater surveillance moves into the mainstream, it 

is critical that methods be thoroughly validated using real-world wastewater samples, that the validation captures 

as much natural variation as possible (such as ensuring the validation is performed with samples from many 

different geographies), and that validation data be made available to laboratories interested in using the method. 

Such data are critical to evaluate method performance capabilities and limitations, facilitate successful adoption 

in new laboratories, and ensure consistent and reliable results can be achieved over time.

Key words: method validation, process controls, matrix controls, reference materials, quantification, wastewater, RT-qPCR

Standards and control materials used: PCR positive and negative controls(IDEXX), Extraction and PCR Internal Control (IDEXX), 

SARS-CoV-2 reference RNA (ATCC), BRSV matrix recovery control, PMMoV and crAssphage human fecal controls 

Email for corresponding author: brian-swalla@idexx.com

Example validation data demonstrating high Repeatability for detection of SARS-CoV-2 N1 and N2 from a geographically diverse collection of raw 

wastewaters. Samples were processed using PEG-based concentration, RNA purification with the IDEXX Water DNA/RNA Magnetic Bead Kit, and viral 

quantification with the IDEXX Water SARS-CoV-2 RT-PCR Test kit following validated protocols for each step.

Ct

28

30

32

34

36

1 2 2 2 1 1 2 2 1 2 2

6-Aug 5-Aug 6-Aug 5-Aug 5-Aug 6-Aug 6-Aug 5-Aug 13-Aug 13-Aug 18-Aug

3-Aug 29-Jul 3-Aug 29-Jul 3-Aug 4-Aug 29-Jul 30-Jul 12-Aug 11-Aug 17-Aug

179 168 173 167 174 183 166 172 190 193 210C

A E F G H I J K

analyst

test date

collection date

sample

Source
Early Warnings of COVID-19 Second Wave in Detroit MI

Miyani Brijen1

, Zhao Liang2, Spooner Maddie3, Gentry Zachary4, Mehrotra Anna5, Norton John6, Xagoraraki 

Irene7*

1,2,PhD candidate, Michigan State University; 3,4Michigan State University; 5

Environmental Engineering, CDM Smith, Inc; 6

Director of Energy, Research and Innovation, Great Lakes Water Authority; 7Professor of Environmental Engineering, 

Michigan State University; *

corresponding author

Abstract:

This study focuses on using wastewater-based-epidemiology to provide early warnings of the second COVID-19 wave in 

Detroit metropolitan area in MI, USA. SARS-CoV-2 RNA from untreated wastewater samples was compared to reported public 

health records. Untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) Water Resource 

Recovery Facility (WRRF), located in southeast Michigan, between Sept 6, 2020 and Dec 14, 2020. The WRRF receives 

wastewater from its service area via three main interceptors: Detroit River Interceptor (DRI), North Interceptor-East Arm 

(NIEA), and Oakwood-Northwest-Wayne County Interceptor (ONWI). A total of 144 untreated wastewater samples were 

collected (45, 48, and 51 for ONWI, NIEA and DRI respectively) at the point of intake into the WRRF. Virus-selective sampling 

was conducted, and viruses were isolated from wastewater using electropositive NanoCeram column filters. For each sample, 

an average of 33 L of wastewater was passed through NanoCeram electropositive cartridge filters at an average rate of 11 

L/m. Viruses were eluted and concentrated and SARS-CoV-2 RNA concentrations were quantified with RT-qPCR. SARS-CoV-2 

RNA was detected in 98% of samples and measured concentrations were in the range of 4.45E+04 to 5.30E+06 genomic 

copies/L. Early warnings of COVID-19 peaks were observed approximately four weeks prior to reported publicly available 

clinical data. This was confirmed by statistical analysis as well.

Key words: SARS-CoV-2, coronavirus, COVID-19, wastewater, wastewater-based-epidemiology (WBE), Detroit

Standards and control materials used: SARS-CoV-2 synthetic control as positive control in RT-qPCR.

Email for corresponding author: xagorara@egr.msu.edu

Figure: Biweekly confirmed COVID-19 cases and SARS-CoV-2 RNA concentrations
Wastewater SARS Public Health Environmental Response (W-SPHERE) Global 

Data Center 

Krystin Kadonsky1

, Colleen C. Naughton1, Gertjan Medema2, Panagis Katsivelis3, Vajra Allan4, Joan B. Rose5 

1,2University of California Merced; 2

KWR Water Research Institute, 3Venthic Technologies, 4PATH, 5Michigan State University 

Over a year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic there have been 

over 173 million cases and 3.7 million deaths. Using methods to track community spread of other viruses such as 

poliovirus, environmental virologists and those in the wastewater based epidemiology (WBE) field quickly 

adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality 

data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. We first 

created COVIDPoops19, a global dashboard for wastewater monitoring of SARS-CoV-2, that has grown into a 

global data center. 

Methods for the COVIDPoops19 ArcGIS online dashboard included google form submission of direct sampling of 

wastewater for SARS-CoV-2 in several countries and stakeholder engagement, literature review, social media and 

news key-word searches, and attendance at online wastewater surveillance webinars worldwide. After a year of 

data tracking, wastewater surveillance for SARS-CoV-2 is conducted in over 55 countries, 2,276 sites, and 263 

universities/institutions. A small subset (86) of those monitoring for SARS-CoV-2 in wastewater provide their data 

publicly and less than 20 provide downloadable data. Of the 55 that are conducting wastewater monitoring: 36 

(65%) are in high-income countries, 11 (20%) are upper middle income, 8 (15%) are lower middle income, and 0% 

are low income countries. 

COVIDPoops19 is informing a global data center W-SPHERE global data center (Wastewater SARS Public Health 

Environmental REsponse) using open data from individual country/city wastewater dashboards and soliciting 

data submissions and agreements from the research community. The mission of W-SPHERE is to advance 

environmental surveillance of sewage to inform local and global efforts for monitoring and supporting public 

health measures to combat COVID-19. 

Wastewater surveillance has been a powerful tool to build resilience to the COVID-19 pandemic. However, there 

is a lack of data standards, limited use in low-income countries, limited data sharing publicly and challenges in 

analysis of the data to communicate to public health officials for decision making. We will provide a global data 

center and standards to build resilience beyond COVID-19 in the face of climate change and increased pathogens 

in the environment. 

Key words: Dashboard, COVID-19, Geographic Information System (GIS), Wastewater Based Epidemiology (WBE) 

Standards and control materials used: Various standards and control methods used since data from many sources are 

aggregated for the data center. 

Email for corresponding author: kkadonsky@ucmerced.edu 

 
Figure 1. COVIDPoops19 Global Dashboard of Wastewater Monitoring for SARS-CoV-2 
Rapid Sample Concentration for Streamlined Workflow in the Wastewater Laboratory

Alburty, David1, David Goad, PhD1, and James Brayer2

1

InnovaPrep LLC; 2 Oxford Nanopore

Wastewater-based epidemiology (WBE) is a valuable tool for assessing population dynamics, infection rates, and 

most recently population-based assessment of vaccine efficacy and detection of variant strains. Collected samples 

are commonly concentrated for identification of viruses in liquid WW samples via PEG precipitation, ultrafiltration, 

or electronegative filters. RNA from concentrated samples is extracted and purified by COTS rapid methods such 

as RT-qPCR or ddRT-PCR and via genetic sequencing. To speed up sample processing through automation while 

eliminating the potential for sample carryover, an automated bioconcentrator can be used. In the concentrator, 

samples are aspirated into a single-use, high surface-area hollow fiber filter tip. Particles larger than the filter pore 

size are retained while the permeate fluid passes through. When the sample has been filtered the device stops 

and alerts the user to elute the sample. With a button press, a viscous, expanded wet foam is pushed through the 

retentate tangential to the filter surface recovering the particles in a user-selected volume of clean buffer (wet 

foam elution) which collapses immediately into a final volume of approximately 200 microliters, providing key 

benefits of decreased processing time, repeatability, and scalable concentration factor based on the input volume, 

output volume, and high efficiency to improve the limit of detection. Data are presented from a 3rd party 

investigation that showed better results for SARS-CoV-2 concentration vs PEG method when analyzed using 

ddPCR. Published data showed faster processing times and better performance than electronegative filtration1

and equivalent concentration using centrifugal ultrafiltration.

2, 3 In these studies, bovine coronavirus or MS-2 

were used as process controls. Details are presented including summarized materials and methods and 

comparative data for the complete processes from sample to analysis.

1 Juel, A.I. et.al. 2021; 2 Rusinol, M. et. al 2021 3 Forés et. al. 2021.

Key words: wastewater based epidemiology, SARS-CoV-2, sample preparation, viruses

Standards and control materials used: Bovine Coronavirus as a process control and internal standard for quantification of 

SARS-CoV-2.

Email for corresponding author: dalburty@innovaprep.com
Figure 1. Concentrating Pipette Select for Faster Wastewater Processing.
The Development of a Sensitive and Reliable qRT-PCR-Based SARS-CoV-2 

Wastewater Analysis Protocol

Agustin Pierri1 and Douglas Sieglaff2

1

Weck Laboratories, 2Agilent Technologies

Wastewater testing can offer valuable insight on community-level occurrence of infectious 

disease- causing microorganisms, including enveloped ssRNA+ viruses such as SARS-CoV-2. 

Quantitative reverse transcriptase PCR (qRT-PCR) is well suited for wastewater microbial 

surveillance due to its sensitivity, specificity, scalability, rapid implementation and costeffectiveness. Weck Laboratories developed a qRT-PCR-based SARS- CoV-2 wastewater testing 

procedure that includes sample concentration by ultrafiltration, and nucleic-acid extraction and 

analysis using Agilent Technologies reagents with the AriaDx Real-Time PCR System. The CDC 

EUA N1 and N2 primer probes were used to analyze wastewater samples. Each qRT-PCR run 

batch included wastewater samples analyzed in duplicate, a 5-log dilution standard line, a 

matrix spike-in process control, a negative template control, no template control, and PCRinhibition assessment of each wastewater sample tested. The validated procedure reliably 

interpreted SARS-CoV-2 viral RNA levels within a variety of raw wastewater samples, along with 

delivering high sensitivity (as low as 8,000 viral genome copies per liter of wastewater). The 

procedure developed and employed by Weck laboratories is an easily implemented, robust 

methodology for community-level SARS-CoV-2 surveillance.

Figure

Overview of Weck Laboratories’ workflow for extracting and detecting SARS-CoV-2 RNA in 

wastewater
Review of culture methods for monitoring antibiotic resistant Acinetobacter, 

Aeromonas, and Pseudomonas in wastewater, recycled and receiving water 

Erin Milligan1,2,Jeanette Calarco3

, Ben Davis1, Ishi Keenum1, Krista Liguori1, Amy Pruden1,2, Valerie J.

Harwood3* 

1

Via Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia 

2 Center for Emerging, Zoonotic, and Arthropod-Borne Pathogens, Virginia Polytechnic Institute and State 

University, Blacksburg, VA 24061, USA.

3

Department of Integrative Biology, University of South Florida, Tampa, Florida 

The continued and growing health threat posed by antibiotic-resistant bacterial pathogens has led to 

increased interest in antibiotic resistance outside of hospital settings, e.g., in wastewater and 

wastewater-influenced aquatic environments. Environmental dimensions to the antibiotic resistance 

problem are increasingly being recognized and there has correspondingly been an increase in calls for 

comparable means to assess antibiotic resistance in environmental samples (Larsson et al., 2018; Smalla 

et al., 2018; JPIAMR, 2019). Recently, substantial progress has been made in the standardization of 

methodologies for monitoring antibiotic resistant fecal indicator bacteria in the environment, e.g., 

extended-spectrum beta lactamase (ESBL)-producing Escherichia coli (World Health Organization, 2021) 

and ESBL-producing Enterobacteriaceae (Marano et al., 2020). However, non-fecal bacteria with 

environmental niches, especially those that are adept at persisting and growing in aquatic environments, 

may be a more meaningful target for assessing potential for evolution and dissemination of antibiotic 

resistance in environmental matrices. For example, the presence of such bacteria in wastewater

treatment plants and their versatile ability to survive and grow in receiving environments presents an 

opportunity to interact with bacteria in multiple niches, where they could potentially acquire and 

transfer antibiotic resistance genes along the way. Further, such organisms have greater potential than 

fecal bacteria to regrow in recycled water distribution systems. Human opportunistic pathogens that 

proliferate in aquatic environments are particularly key targets to consider for monitoring purposes, 

especially those that have developed a reputation for multi-drug resistance in clinical infections. 

Studying these organisms in culture provides the advantage of being able to confirm their viability while 

also being able to further characterize multi-drug resistance, both phenotypically and genotypically. We 

conducted a systematic literature review and extracted data from studies that quantified antibioticresistant Acinetobacter, Aeromonas, and Pseudomonas by culture methods. The search criteria yielded 

50 peer-reviewed articles across 25 countries over the past 20 years. Based on a systematic comparison 

of the isolation, confirmation, and antibiotic resistance assaying methods reported in these articles, we 

suggest a path forward for standardizing methodologies for monitoring antibiotic resistant strains of 

these bacteria in the water environment. 

Keywords: antibiotic resistance, wastewater, recycled water, surface water, culture, opportunistic pathogens 
Standards and control materials used: not applicable 

Email for corresponding author: vharwood@usf.edu 

Figure 1. Potential for acquisition of antibiotic resistance genes (ARGs) by environmentally-associated bacteria 

during wastewater treatment and in affected surface waters. 

References: 

JPIAMR. (2019). Strategic Research and Innovation Agenda on Antimicrobial Resistance. In Strategic Research and 

Innovation Agenda on Antimicrobial Resistance (pp. 1–54). 

Larsson, D. G. J., Andremont, A., Bengtsson-Palme, J., Brandt, K. K., de Roda Husman, A. M., Fagerstedt, P., Fick, J., 

Flach, C. F., Gaze, W. H., Kuroda, M., Kvint, K., Laxminarayan, R., Manaia, C. M., Nielsen, K. M., Plant, L., 

Ploy, M. C., Segovia, C., Simonet, P., Smalla, K., ... Wernersson, A. S. (2018). Critical knowledge gaps and 

research needs related to the 196 environmental dimensions of antibiotic resistance. Environment 

International, 117(January), 132–138. https://doi.org/10.1016/j.envint.2018.04.041 

Marano, R. B. M., Fernandes, T., Manaia, C. M., Nunes, O., Morrison, D., Berendonk, T. U., Kreuzinger, N., Telson, T., 

Corno, G., Fatta-Kassinos, D., Merlin, C., Topp, E., Jurkevitch, E., Henn, L., Scott, A., Heß, S., Slipko, K., Laht, 

M., Kisand, V., ... Cytryn, E. (2020). A global multinational survey of cefotaxime-resistant coliforms in urban 

wastewater treatment plants. Environment International, 144(August), 106035. 

https://doi.org/10.1016/j.envint.2020.106035 

Smalla, K., Cook, K., Djordjevic, S. P., Klümper, U., & Gillings, M. (2018). Environmental dimensions of antibiotic 

resistance: assessment of basic science gaps. FEMS Microbiology Ecology, 94(12), 1–6. 

https://doi.org/10.1093/femsec/fiy195 

World Health Organization. (2021). Global Tricycle Surveillance. 
Minimizing uncertainties of COVID-19 prevalence by establishing standards for 

wastewater surveillance

Guangming Jiang 1,2 *, Xuan Li 1, Shuxin Zhang 1, Jiahua Shi 1, Stephen P. Luby b

1

School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia; 2Illawarra Health and Medical 

Research Institute (IHMRI), University of Wollongong, Wollongong, Australia;

 3Woods Institute for the Environment, 

Stanford University, United States; *

Corresponding author. 

Wastewater-based epidemiology (WBE) is a promising approach for monitoring population-wide COVID-19 

prevalence through detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in 

wastewater. However, various methodological challenges associated with WBE affect the accuracy of prevalence 

estimation. Our previous study investigated the overall uncertainty of WBE and the impact of each step on the 

prevalence estimation. The uncertainties associated with the different steps in the WBE approach (i.e., virus 

shedding; in-sewer transportation; sampling and storage; analysis of SARS-CoV-2 RNA concentration in 

wastewater; back calculation) were quantified through systematic review. The uncertainties of virus shedding and 

in-sewer transportation are largely uncontrollable, but fortunately not a major contributor to the overall 

uncertainty in estimated COVID-19 prevalence. The uncertainty for the shedding of SARS-CoV-2 RNA becomes 

limited when there are more than 10 infected persons in the catchment area. Also, the relative stability of SARSCoV-2 in wastewater and moderate hydraulic residence time in the sewer system (normally within 12 hr) indicates 

a mild uncertainty due to in-sewer transportation. 

Based on the analysis of different uncertainties, the overall WBE uncertainty is mainly due to sampling and 

storage; analysis of SARS-CoV-2 RNA concentration in wastewater; back calculation. It is critical to minimize 

uncertainties of estimated COVID-19 prevalence through establishing and adopting standards for wastewater 

surveillance. The uncertainty can be reduced mostly by using a high-frequency flow-proportional or timeproportional sampling and estimating the prevalence through actual water usage data. And under such a scenario, 

the overall uncertainty can be further reduced by improving SARS-CoV-2 RNA detection in wastewater. It is critical 

to determine the virus recovery efficiency for the various concentration methods being used in different labs. A 

best-practice RT-qPCR protocol, including choice of primer-probe sets, should be encouraged.

Key words: COVID-19; SARS-CoV-2; Wastewater-based epidemiology; Uncertainty; Prevalence estimation; Standards

Standards and control materials used: No

Email for corresponding author: gjiang@uow.edu.au
Figure 1. Uncertainty analysis for monitoring COVID-19 community prevalence through wastewater surveillance. 
Using a high-resolution sampling in Davis, CA to 

understand how to best analyze and act on WBE data

H. Safford1, R. Zuniga-Montanez1, M. Kim2, L. Rueda2, R. Pechacek1, R. Guerrero1, 

M. Clauzel1

, X. Liu3, L. Wei3, M. Daza,3 M. Nuno,3 J. Sharpnack3, K. Shapiro2, H. Bischel1

1

UC Davis Department of Civil and Environmental Engineering; 2UC Davis Department of Veterinary Medicine; 3UC Davis 

Department of Statistics

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for pandemic 

response. The public-health benefits of WBE depend on the scale at which WBE is carried out. Samples 

from building or neighborhood outflows can support direct and targeted interventions. Samples

isolating different sub-regions of a community sewershed can help officials decide how to allocate 

resources (e.g., testing and public messaging) within the community. Samples from wastewater 

treatment plant (WWTP) influent provide information that can reinforce confidence in clinical trends 

or suggest when clinical testing may be missing key population segments. WBE data can also be 

incorporated into education and outreach campaigns. 

The Healthy Davis Together (HDT) program in Davis, CA applies WBE at all three of the above scales.

Since Fall 2020, HDT has been collecting and analyzing levels of SARS-CoV-2 in wastewater collected 

from the following sites:

x Building/neighborhood outflow [collected 1–3x/week]:

o 22 UC Davis residential buildings or complexes 

o 6 Davis neighborhoods 

o 1 apartment complex 

o 1 elementary school 

x Sewershed sub-regions [3x/week]: 

o 15 sub-regions of the Davis sewershed

x WWTP influent [7x/week]:

o City of Davis WWTP

o UC Davis WWTP

We are leveraging the high temporal and spatial resolution of HDT wastewater analysis to understand 

how to best analyze and act on WBE data. We are pleased to present and discuss early insights related to 

the following key topics and questions: 

x Treatment of non-detects. Relatively low concentrations of SARS-CoV-2 in environmental 

matrices like wastewater mean that qPCR technical replicates of the same sample frequently 

yield a mix of positive (“detect”) and negative (“non-detect”) results. Researchers commonly 

substitute a single constant value (e.g., zero or half the detection limit) for non-detects during 

data analysis. We are (i) illustrating how this crude approach biases results, and (ii) exploring 

multiple-imputation methods for more sophisticated handling of non-detects.

x Sub-regional comparison of wastewater and clinical data. Many groups have demonstrated 

strong correlation between trends in wastewater SARS-CoV-2 concentrations and clinically 
confirmed COVID-19 cases at the city or college level. We are exploring whether similar 

relationships exist at the sub-regional level. 

Key words: Wastewater-based epidemiology, public health, SARS-CoV-2, COVID-19, data imputation, data correlation

Standards and control materials used: Phi6 bacteriophage (process control), PMMoV (fecal strength indicator), N1/N2 gene 

regions (target for SARS-CoV-2 quantification), Oregon RNA and N1/N2 plasmids (positive control)

Email for corresponding author: hrsafford@ucdavis.edu

Figure 1. The rich dataset provided by the granular wastewater-sampling campaign and large-scale asymptomatic testing 

conducted through Healthy Davis Together enables novel insights into key questions such as “How do we handle non-detects in qPCR 

data collected on wastewater samples?” and “How well do WBE data correlate with clinical test results at the sub-city level?
DHS/NIST Workshop Type: Abstract

EzCOVID19: A Cloud-based Bioinformatics Platform for Rapid Detection,

Characterization and Epidemiological Sub-typing of SARS-CoV-2

Nur A. Hasan1, Mauricio Chalita2, Yeong Ouk Kim2, Michael Bailey2, Gihyun Lee2, Jongsik Chun2,3

1

EzBiome Inc., Gaithersburg, MD 20878, USA; 2ChunLab Inc., Seoul, Korea; 3School of Biological 

Sciences & Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Korea

Background: The COVID-19 pandemic has caused enormous social and economic disruption 

worldwide. Tracing the evolutionary development and spread of SARS-CoV-2 across the globe 

requires continuous and exhaustive genomic sequencing. With the development of next 

generation sequencing (NGS) technology, genomic information is accessible to many researchers. 

However, the data generated by scientists, globally, comes in varying formats and from different 

sources. Additionally, despite the need for consensus genome assemblies, there is no single 

consensus protocol for sequencing SARS-CoV-2. Such information requires standardizing and 

compiling before it can be accurately analyzed. EzCOVID19, is a cloud-based bioinformatics 

platform that enables researchers the ability to rapidly detect, standardize, and characterize SARSCoV-2 genomes from any NGS data suspected of containing SARS-CoV-2. 

Method: EzCOVID19 generates consensus genome assembles, locates genetic variations from the 

SARS-CoV-2 Wuhan-Hu-1 reference (NC_045512.2), utilizes a novel SNV-based classification 

system for accurate identification, and produces parsimony trees based on public GISAID 

genomes. 

Results: This user-friendly tool provides a platform for scientists to submit samples for rapid 

detection of SARS-CoV-2, download assembled genomes and profile tables, identify genetic 

variations, and compare with related genomes in public databases. EzCOVID19 also provides indepth analyses and visualizations of the data with parsimony and maximum likelihood trees based 

on novel SNV sites. Its cloud-based system and online support provide immediate results from 

regularly updated public databases, including monitoring of variants of concern. To analyze your 

samples, access EzCOVID19 here https://www.ezbiocloud.net/tools/sc2.

Conclusion: Many scientists and public health workers from various research backgrounds have 

been required to adapt viral genomics into their research as a means of understanding SARS-CoV-2 

without prior knowledge of virology or genomics. EzCOVID19 is a cloud-based, user-friendly, 

robust platform to assist scientists from different disciplines to research SARS-CoV-2. Regardless of 

method or sequencing instrument used, EzCOVID19 is able to integrate raw metagenomic or 

isolate sequence data for standardised bioinformatic analyses. Processed data are presented with 

detailed visuals and relevant information related to concurrently circulated publicly available 

SARS-CoV-2 genomes. 

Key words: COVID19 Surveillance, Bioinformatics, rapid detection, epidemiological sub-typing, 

mutational analysis.

Standards and control materials used: N/A

Email for corresponding author: hasan@ezbiome.com
Targeted communications using wastewater monitoring at the sub-sewershed scale in 

Davis, CA 

Heather N. Bischel1, Hannah R. Safford1, C. Winston Bess1, Michelle Dunigan1, Minji Kim1,2, Randi Pechacek1, 

Lezlie Rueda2

, Karen Shapiro2, Rogelio Zuniga-Montanez1, Tod Stoltz3

1

Department of Civil & Environmental Engineering, University of California, Davis; 2School of Veterinary Medicine, 

University of California, Davis; 3

UC Davis Health

Healthy Davis Together (HDT), a joint project between UC Davis and the City of Davis, collects wastewater 

samples from nodes within the city’s sewer system and monitors the City of Davis and the UC Davis 

Wastewater Treatment Plants. Samples are collected three times per week at 24 sewer nodes in the city 

and seven days per week from wastewater influent at the City of Davis and UC Davis WWTPs. Sample 

processing takes about 24 hours, and SARS-CoV-2 concentrations are normalized to pepper mild mottle 

virus (PMMoV) for presentation and analysis. 

HDT formed a Wastewater Action Committee (WAC) to coordinate communications of all wastewater 

results between HDT scientists and City leadership on a weekly basis and to develop and implement 

responses to wastewater results. A press release invited community members to opt into the preexisting Yolo Alert messaging system to receive notifications when elevations are detected. 

Virus levels in wastewater that exceed pre-defined action thresholds are reviewed by the WAC with 

three primary response strategies, together intended to encourage participation in HDT’s widely 

available, free asymptomatic COVID-19 testing program. First, HDT posts results on its website, broken 

down by sampling region to keep the public informed each week. The slope of a two-week moving 

average is evaluated to denote on the HDT website if levels in each sampling region are increasing, 

staying about the same, or decreasing. Second, the highest absolute normalized values of detection are 

used by HDT and the WAC to identify priority regions within the city and to cross-check participation in 

asymptomatic individual testing programs within different regions. Third and finally, geo-targeted text, 

email, and social media messages can be sent to a sub-sewershed region following a sustained elevation 

of normalized virus concentrations above the limit of detection. Sub-sewershed samples represent 

smaller populations (hundreds to low thousands of people) and are expected to frequently yield 

nondetects; an increase in levels above the detection limit represents a significant and easily identifiable 

change. The city used its opt-in text message alert system as well as Nextdoor to notify residents within 

the associated sub-sewershed region based on sewer system data collected in March 2021.

Key words: Sub-sewershed wastewater; actionable response strategies; COVID-19

Standards and control materials used: (short answer)
Email for corresponding author: Heather N. Bischel, hbischel@ucdavis.edu 

Figure 1. Sub-sewershed regions monitored in the City of Davis and 

Sub-sewershed

region

Healthy Davis 

Together (HDT)

sub-sewershed

surveillance regions

UC Davis
Assessment of qPCR- targets and protocols for quantifying anthropogenic impacts of antibiotic 

resistance to the water environment 

 

Ishi Keenum1, Jeanette Calarco2, Benjamin C. Davis1, Krista Liguori1, Erin Milligan1, Valerie J.

Harwood2, Amy Pruden1*

1

Via Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia, 2 Department of Integrative 

Biology, University of South Florida, Tampa, Florida 

 

There is growing recognition of the need for standardizing monitoring of antibiotic resistance in the aquatic 

environment. Quantitative polymerase chain reaction (qPCR) is attractive as a quantitative and sensitive means of 

enumerating antibiotic resistance genes (ARGs) that has been applied broadly over the past two decades to various 

water matrices. qPCR circumvents challenges and biases associated with culture-based methods, providing a 

reproducible, quantitative, and highly sensitive measure of specific ARGs carried across a bacterial community. 

qPCR-based measurements can serve to address key goals for monitoring antibiotic resistance in water 

environments (Berendonk et al., 2015; Huijbers et al., 2019). Measuring the incidence of specific ARGs can help to 

predict the potential for the accelerated evolution of antibiotic resistance in pathogens through pollution with 

selective agents (e.g., antibiotics, heavy metals, personal care products) and bacteria of human or animal origin 

(Karkman et al., 2018; Kohanski et al., 2010). Additionally, qPCR can be used to estimate the risk of ARB infection 

in humans by directly measuring the carriage of specific ARGs with clinical implications in a given microbial 

community. 

 

However, there are thousands of known ARGs that could be targeted, each varying in their relevance to human 

health and their overall contribution to dissemination of antibiotic resistance. Further, there are various 

methodological aspects, such as sample concentration, extraction, and PCR inhibition that need to be evaluated 

to ensure that measurements are representative and comparable across studies. Here we conducted a critical 

review to identify ARGs and assays that are most commonly measured by qPCR in wastewater, recycled water, 

and surface water, specifically: sul1, intI1, vanA, blaCTX-M, and tetA. We identified 117 peer-reviewed studies 

meeting the search criteria and systematically assessed the corresponding workflows reported, including sample 

collection and concentration, DNA extraction, amplification conditions, amplicon length, and level of validation. 

Resulting concentrations reported for various water matrices were compared across the studies. Based on this 

evaluation, recommend assays, a standardized workflow, and reporting guidelines for the five genes of interest. 

Implications for emerging qPCR approaches, such as droplet digital qPCR and high-throughput qPCR, are also 

discussed and a path forward for standardization is proposed. 

Key words: antibiotic resistance, quantitative polymerase chain reaction, standardization, wastewater, surface water, 

environment 

Standards and control materials used: not applicable. 

Email for corresponding author: apruden@vt.edu 

 
 

Figure 1(A) Number of articles that met the search criteria for each gene by water matrix (recycled/reuse, surface, and wastewater). Articles that 

examined more than one water matrix are double counted. (B) Target gene concentrations measured in each water matrix . Dots are colored by the study 

the reported data was obtained from. Box plots indicate the median, first, and third quartiles and whiskers extend no more than 1.5 times the 

interquartile range.

Berendonk, T.U., Manaia, C.M., Merlin, C., Fatta-Kassinos, D., Cytryn, E., Walsh, F., Bürgmann, H., Sørum, H., Norström, M., Pons, M.-N., 2015. Tackling 

antibiotic resistance: the environmental framework. Nat. Rev. Microbiol. 13, 310–317. 

Huijbers, P.M.C., Flach, C.-F., Larsson, D.G.J., 2019. A conceptual framework for the environmental surveillance of antibiotics and antibiotic resistance. 

Environ. Int. 130, 104880. https://doi.org/10.1016/j.envint.2019.05.074 

Karkman, A., Do, T.T., Walsh, F., Virta, M.P.J., 2018. Antibiotic-Resistance Genes in Waste Water. Trends Microbiol. 26, 220–228. 

https://doi.org/10.1016/j.tim.2017.09.005 

Kohanski, M.A., DePristo, M.A., Collins, J.J., 2010. Sublethal Antibiotic Treatment Leads to Multidrug Resistance via Radical-Induced Mutagenesis. Mol. Cell 

37, 311–320. https://doi.org/10.1016/j.molcel.2010.01.003 

 
A DNA-based reference material for pathogen detection via metagenomic nextgeneration sequencing (mNGS)

Jason G Kralj,

1 Monique Hunter,1 Blaza Toman,2 Scott Jackson1

1 Material Measurement Laboratory, NIST; 2 Information Technology Laboratory, NIST

NIST has developed a 20-component bacterial DNA-based reference material (RM 8376) to assess the 

analytical performance of mNGS analyses. Because mNGS includes many steps, each of which 

contributes bias to the results, it is critical that those biases are identified for optimizing performance. 

This RM was designed to assess sequencing and informatics. The components include many wastewaterbased pathogens (see Table), providing relevant controls for evaluating analytical performance. Further, 

because these materials are DNA, they may be employed in other diagnostics such as qPCR. 

The RM includes a wide range of known pathogens, including Gram positive/negative, high/low G+C 

content, genome size, and near neighbors. Each chromosome was assembled into a circular contig and is 

available for use. To quantify the chromosomal copy number concentration, droplet digital PCR assays 

were developed for each component. The homogeneity and stability of each component assessed over 

several months, with each genome at approximately 50 ng/PL, or 107 copy/PL. 

Keywords: bacterial DNA standards, metagenomics, pathogen detection

Email: jason.kralj@nist.gov

Table – NIST RM 8376 components, including source material, identity, assembled chromosome sizes, and copy 

number concentration with uncertainty.

ATCC ID Part Organism

Chr 

Size(s) Plasmids

Chromosomal copy 

number concentration 

×106 (copy/PL)(a)

43895 A Escherichia coli O157:H7 5564632 2 8.84 r 0.38

BAA 2309 B Escherichia coli O104:H4 5302905 1 8.89 r 0.28

700720 C Salmonella enterica enterica 4857492 1 9.72 r 0.38

12324 D Salmonella enterica arizonae 4482096 0 10.84 r 0.52

BAA 44 E Staphylococcus aureus 2964115 1 16.49 r 0.76

12600 F Staphylococcus aureus 2755072 1 17.38 r 0.68

12228 G Staphylococcus epidermidis 2504458 3 15.99 r 0.60

BAA 47 H Pseudomonas aeruginosa 6263669 0 8.27 r 0.34

19606 I Acinetobacter baumannii 3980879 0 12.01 r 0.56

13077 J Neisseria meningitidis 2181327 0 21.67 r 0.94

12344 K Streptococcus pyogenes 1914863 0 22.55 r 0.86

19433 L Enterococcus faecalis 2866948 0 14.75 r 0.50

27061 M Achromobacter xylosoxidans 6813185 0 7.28 r 0.36

35654 N Aeromonas hydrophila 4733720 0 9.97 r 0.34

13883 O Klebsiella pneumoniae 5303036 4 7.68 r 0.36

25931 P Shigella sonnei 4917056 0 9.67 r 0.36

35016 Q Vibrio furnissii(b)

3275680, 

1641536 1 9.70 r 0.36

19115 R Listeria monocytogenes 2950983 0 17.39 r 0.64

33152 S Legionella pneumophila 3409194 0 13.63 r 0.46

GM24385(c) T Homo sapiens 0.0323 r 0.0015

(a) The values are expressed as x r 2u(x), where x is the value and u(x) is the standard uncertainty of x. The 

standard uncertainty combines reaction volume, unit, and repetition. While the best estimate value lies within the 

interval x r 2u(x), this interval may not include the true value. 

(b) Component Q has 2 chromosomes

(c) Sourced from Coriell

An organism-centric approach to performance metrics for metagenomic NGSbased diagnostics

Jason G. Kralj, Stephanie L. Servetas, Samuel P. Forry, Scott A. Jackson

Complex Microbial Systems Group, NIST

Metagenomic Next-Generation Sequencing (mNGS) analyses applied to wastewater has potential for 

population-level characterization and tracking. Sequencing is generally agnostic to the DNA/RNA source, 

allowing the same data to be analyzed for >10k organisms (virus, bacteria, etc.) using different 

computational tools. The benefits are clear—outbreaks like SARS-CoV-2 could be retrospectively 

tracked, and health officials could respond quickly to rising levels of potential pathogens such as Listeria. 

However, mNGS-based diagnostics are also prone to false positives and negatives, and those can degrade 

confidence in the technology and public health administration in general. 

We have proposed evaluating mNGS performance on a per organism basis. This organism-centric

approach has particularly strong potential for wastewater because it allows end users to know the 

technical limitations and indicate how to address them, especially when distinguishing species or strains; 

the organism load is low; and the results of an analysis can be actionable. Further, the technology can 

provide indications of novel pathogens in need of a closer look, and this organism-centric approach can 

be scaled out to incorporate new taxa as needs evolve. 

Keywords: metagenomics, sequencing, pathogen detection

Email: Jason.kralj@nist.gov

Table 1 Performance metrics by taxon can reveal fine-grain information, especially since performance varies by organism. Here, 

10 hypothetical samples were compared by taxon, revealing poor performance for some taxa. Summarizing performance across 

all possible taxa (sample-centric) hides those potential deficiencies and overstates performance. When only a subset of the taxa 

are of interest,
Targeted NGS for Sensitive Detection of SARS-CoV-2 Genomes

Jordan RoseFigura1, Evan Hughes1, Karl Spork1, and Laurie Kurihara1

1

Integrated DNA Technologies, Ann Arbor, MI

Discovery and detection of pathogenic genomes is of increasing importance. Next 

Generation Sequencing (NGS) is a sensitive and thorough way to surveil a wide variety 

of samples. Sequencing also provides insight into the strains that are circulating in a 

population, including novel strains. Targeted sequencing enriches for sequences of 

interest from the sample background, increasing sensitivity and saving on sequencing 

costs.1 Swift Biosciences (now part of IDT) has developed the Swift NormalaseTM 

Amplicon Panels (SNAP) workflow to enable fast and efficient preparation of targeted 

libraries for NGS sequencing. The SNAP workflow takes approximately 2.5 hours from 

cDNA to library and consists of two PCR steps. This one tube workflow is compatible 

with a wide variety of sample types and capable of sequencing large target regions using 

overlapping amplicons to achieve continuous coverage. The SNAP SARS-CoV-2 

Additional Genome panel covers 99.7% of the SARS-CoV-2 genome using 345 amplicons. 

The SNAP technology performs well with low levels of target DNA/cDNA and with 

damaged samples. This panel has been used to determine the lineage of SARS-CoV-2 in 

wastewater samples.

2 Herein, we demonstrate the efficiency of the SARS-CoV-2 assay at 

low viral titers and show that this kit is capable of discovery of novel mutations while

maintaining high genomic coverage. This technology is not limited to SARS-CoV-2, but 

also able to target any sequence of interest.

1 Spurbeck et al. Science of the Total Environment. 789 (2021) 147829 

2 Fontenele el al. https://doi.org/10.1101/2021.01.22.21250320 

NGS: Targeted Sequencing; SARS-CoV-2; wastewater; amplicon

Standards and control materials used: SARS-CoV-2 standards from Twist Biosciences and BEI were used for input titration

experiments.

Email for corresponding author: jrosefigura@idtdna.com 
Figure 1. The SNAP Workflow diagram showing the one tube, two step process for library creation. The optional Normalase steps are also show. The 

SARS-CoV-2 genome coverage attained from the assay is visualized in IGV and show in purple. The performance metrics (% Reads aligned and % Bases 

>10X coverage) are shown for inputs of 10-106 viral copies. 

For research use only. Not for use in diagnostic procedures. Unless otherwise agreed to in writing, IDT does not intend

these products to be used in clinical applications and does not warrant their fitness or suitability for any clinical diagnostic

use. Purchaser is solely responsible for all decisions regarding the use of these products and any associated regulatory or 

legal obligations.
Sources Of Variability In Methods For Processing, Storing, And Concentrating SARSCoV-2 In Influent From Urban Wastewater Treatment Plants

J. A. Steele, A. G. Zimmer-Faust, J. F. Griffith, S. B. Weisberg 

Southern California Coastal Water Res. Project, Costa Mesa, CA

During the COVID-19 pandemic, wastewater surveillance of SARS-CoV-2 RNA has emerged as a way 

to track the virus in a broad population without the drawbacks of testing individuals. Understandably the 

emphasis has been on rapidly increasing the rate and extent of measuring SARS-CoV-2 RNA in 

wastewater to gain insight into outbreaks in communities globally. This has resulted in many different 

methods being used for sample collection, storage, virus capture, and quantification with few studies 

investigating the variability caused by these methodological differences and the impact of this variability 

on comparisons of wastewater surveillance data. In this study, controlled experiments were performed to 

test methods used to store wastewater samples, to inactivate virus in wastewater, to capture and 

concentrate virus in wastewater, and to extract and measure the viral RNA. We found the highest 

variability was caused by heat inactivation of the viruses (a 1-3 log decrease) and freezing of influent 

prior to concentration (1-4 log decrease), with impacts dependent on sample processing method. 

Sampling frequency, sampling strategy, concentration vs direct extraction, and PCR platform were also 

minor sources of variability. In contrast, the nucleocapsid gene target had nearly no effects. We found 

viral capture by membrane adsorption to be robust to changes in SARS-CoV-2 concentration and freezethaw variability. Pepper mild-mottle virus was much less sensitive to these methodological differences 

than was SARS-CoV-2, which challenges its use as a population-level control among studies using 

different methods. We applied the membrane adsorption method to monitor wastewater from a large 

wastewater treatment plant in Los Angeles County, California from April 2020-April 2021 and found a 

high correlation (r=0.78) to SARS-CoV-2 case counts. Wastewater based surveillance holds promise to 

efficiently measure the prevalence of SARS-CoV-2 in a larger, pooled population sample and has 

potential to serve as an early warning of future outbreaks. However, the diversity of methods, high 

variability reported among methods, and a lack of standardization make it difficult for municipalities 

and public health agencies to be able to interpret the SARS-CoV-2 concentrations from wastewater. 

Better characterizing the variability associated with methodological choices, in particular the limits of 

sensitivity of the methods, will aid decision makers in following the effects of vaccination campaigns, 

early detection of future outbreaks, and, potentially, monitoring the appearance of SARS-CoV-2 variants 

in the population.

Key words: droplet digital PCR, HA electronegative virus capture, magnetic bead extraction

Standards and control materials used: Bovine Coronavirus vaccine, Asuragen armored HepG RNA

Email for corresponding author: joshuas@sccwrp.org
Figure 1. Concentrations measured with and without pasteurization. Circles represent average concentration for 

the three WTPs and faint crosses represent results from the individual plants. Black circles indicate samples not 

pasteurized; red circles indicate pasteurized samples; (A) SARS-CoV-2 N1 (top row), SARS-CoV-2 N2 (middle 

row), and PMMV (bottom row) levels for samples processed by membrane concentration (HA) B) BoCoV levels 

by direct extraction methods (DE:BM & DE:Z).
Challenges with Standardizing the Measurement of SARS-CoV-2 Recovery Efficiency in 

Wastewater

Kara L. Nelson, Rose S. Kantor, Hannah D. Greenwald, Lauren C. Kennedy 

Civil and Environmental Engineering, University of California, Berkeley, CA, 94720 

A wide range of methods are currently used to quantify SARS-CoV-2 in wastewater and sludge, involving different 

concentration and extraction methods and variations on PCR. Quantifying the recovery efficiency of SARS-CoV-2 

by different methods would be useful for comparing results, and would ideally offer the ability to correct for 

different recovery efficiencies. The most common approach to quantify recovery efficiency is to use a proxy virus 

that is spiked into the sample prior to processing, and is intended to model the behavior of SARS-CoV-2. Proxy 

viruses that have been used to date include bovine coronavirus, bovine respiratory syncytial virus, murine 

hepatitis virus, and human coronavirus OC43. However, there are a number of factors that affect the recovery 

efficiency and may manifest differently depending on sample characteristics, concentration method, and the 

method used to quantify the initial stock solution. These factors can lead to comparison of “apples and oranges”. 

For example, if the proxy virus and SARS-CoV-2 have different association with solids, the proxy virus will not 

adequately quantify the differences between methods that capture signal from wastewater solids and those that 

do. Similarly, if the proxy virus is added as intact virus, and SARS-CoV-2 RNA is present in intact viruses and as free 

RNA (Wurtzer et al. 2021), the proxy virus will not adequately quantify differences between methods that capture 

signal from intact viruses and free RNA, and the biases will vary from sample to sample. An early study compared 

36 methods used in different laboratories and reported recovery efficiencies varying over seven orders of 

magnitude (Pecson et al. 2020). A strength of this study is that samples were prepared by a single laboratory and 

spiked with a proxy virus (betacoronavirus OC43), such that the recovery efficiency could be calculated relative to 

the same initial concentration and spike-in method. However, in current practice, every laboratory is preparing 

their own proxy virus and quantifying it differently so that recovery efficiencies cannot be directly compared 

across methods and labs. 

Key words: recovery efficiency, virus proxy 

Standards and control materials used: Virus proxy (spike-in) to measure SARS-CoV-2 recovery efficiency

Email for corresponding author: karanelson@berkeley.edu, rkantor@berkeley.edu 

 
Figure 1. Factors affecting quantification of SARS-CoV-2 from wastewater. SARS-CoV-2 likely exists in wastewater along a continuum of 

intact (red) and nonintact (blue) viruses, and the ratio of these forms, and their association with solids, changes during transport of the 

sewage, sampling, and sample processing. For a sludge sample, there may also be loss of signal during primary settling. Spike-in proxy 

virus controls (pink) can be added 1) at the point of sampling prior to storage or 2) after storage at the beginning of sample processing. 

Proxy virus controls can account for degradation during storage and loss of signal due to incomplete recovery during concentration (pink 

line). A second control would be required to independently quantify the loss of signal during RNA extraction (brown line) because the 

spike control is affected by loss during RNA extraction. (Figure from Kantor et al. 2021). 

References 

Kantor, R.S., K.L. Nelson, H.D. Greenwald, and L.C. Kennedy. (2021) “Challenges in Measuring the Recovery of SARS-CoV-2 from 

Wastewater.” Environmental Science & Technology. 55(6): 3514-3519. https://doi.org/10.1021/acs.est.0c08210. 

Pecson, B.M. et al. (2021) “Reproducibility and Sensitivity of 36 Methods to Quantify the SARS-CoV-2 Genetic Signal in Raw Wastewater: 

Findings from an Interlaboratory Methods Evaluation in the U.S.” Environmental Science: Water Research & Technology. 

https://doi.org/10.1039/D0EW00946F. 

Wurtzer, S., P. Waldman, A. Ferrier-Rembert, G. Frenois-Veyrat, J. M. Mouchel, M. Boni, Y. Maday, V. Marechal, and L. Moulin. “Several 

Forms of SARS-CoV-2 RNA Can Be Detected in Wastewaters: Implication for Wastewater-Based Epidemiology and Risk Assessment.” 

Water Research 198 (June 15, 2021): 117183. https://doi.org/10.1016/j.watres.2021.117183. 
SARS-CoV-2 Wastewater Surveillance in a remote municipality in the Aleutians Islands of 

Alaska

Karie Holtermann, Laboratory Manager, City of Unalaska Water and Wastewater Laboratory

The City of Unalaska is a municipality located in the Aleutian Island chain approximately 800 

miles southwest of Anchorage, Alaska. The City owns and operates a chemically enhanced 

primary treatment sewage facility which screens and disinfects an average of 0.483 million 

gallons of domestic wastewater per day. 

Dutch Harbor is the largest commercial fishing port in the Pacific and is number one in the US 

for volume of fish. There are approximately 4,768 full time residents on the island and during 

peak seasons of the year, an additional 5-6,000 people are added to this population. The 

community's health care services are provided by a local clinic operated by Iliuliuk Family & 

Health Services, Inc. (IFHS). The clinic obtained two types of "rapid" COVID-19 testing devices 

at the beginning of the Covid 19 Pandemic, the Abbott IDNow system and the Cepheid 

GeneXpert IV-2 Molecular system and to date have performed 8,890 local clinical tests. 

Wastewater-based epidemiology (WBE) began being explored as a new tool to track the spread 

of COVID-19 from the onset of the pandemic (Medema et al. 2020). Many studies report viral 

detection in sewage across the world. Detection of SARS-CoV-2 RNA in wastewater has been 

shown to be a valuable tool in early detection and informing public health decisions (Wu et al. 

2020). 

Weekly samples were collected at the Unalaska WWTP Influent and two lift stations from July 

2000 until the present. Two methods were used to quantify SARS-CoV-2 in raw sewage. We 

developed a sensitive, consistent and reliable method to allow for pooled surveillance of 

wastewater which now serves as an early warning system. 

Key words: SARS-CoV-2 Wastewater Surveillance, Method Development, Congregate living 

settings, Remote and rural environments 

Standards and control materials used: The primers (N1 and N2) and DNA standards of SARSCoV-2 nucleocapsid gene were used to quantify the titers of SARS-CoV-2 (Integrated DNA 

Technologies (IDT) 2019-nCoV CDC EUA qPCR Probe Assay primer/probe mix and 2019-

nCoV_N Positive Control plasmid). Two replicates were performed. Positive and negative 

controls were included in each run as well as internal standardization control Pepper Mild Mottle 

Virus (PPMoV) and the Seracare AccuPlex SARS-CoV-2 Verification Panel (0505-0168) was 

used as an extraction control.

kholtermann@ci.unalaska.ak.us
Figure 1. Isolated cases on vessels kept quarantined and not connected to the city collection 

system were not included in this graph. The City remained insulated from the pandemic until 

December of 2020 at which time it experienced two outbreaks, the first at Unisea in Jan. 2021 

and the second and more significant at Alyeska in Feb. 2021. Community spread remained low 

during the year and cases dropped off after vaccinations became widely available. Viral 

detection began at as low as ten reported active clinical cases. Viral load proceeded clinical 

cases by several days and followed clinical cases throughout the pandemic. 

References

Medema G, Heijnen L, Elsinga G, Italiaander R, Brouwer A. Presence of SARS-Coronavirus-2 

RNA in Sewage and Correlation with Reported COVID-19 Prevalence in the Early Stage of the 

Epidemic in The Netherlands. Environ Sci Technol Lett. 2020;acs.estlett.0c00357. Published 

2020 May 20. doi:10.1021/acs.estlett.0c00357 

Fuqing Wu, Amy Xiao, Jianbo Zhang, Katya Moniz, Noriko Endo, Federica Armas, Richard 

Bonneau, Megan A Brown, Mary Bushman, Peter R Chai, Claire Duvallet, Timothy B Erickson, 

Katelyn Foppe, Newsha Ghaeli, Xiaoqiong Gu, William P Hanage, Katherine H Huang, Wei Lin 

Lee, Mariana Matus, Kyle A McElroy, Jonathan Nagler, Steven F Rhode, Mauricio Santillana, 

Joshua A Tucker, Stefan Wuertz, Shijie Zhao, Janelle Thompson, and Eric J Alm. 2020. “SARSCoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 

cases.” medRxiv.
Direct RT-qPCR assay for SARS-CoV-2 variants of concern (B.1.1.7 and B.1.351) 

detection and quantification in wastewater

Karin Yaniv1

, Eden Ozer2, Marilou Shagan1, Satish Lakkakula1, Noam Plotkin1, Nikhil Suresh Bhandarkar1 and Ariel 

Kushmaro1,3

1 Avram and Stella Goldstein-Goren, Department of Biotechnology Engineering, Ben- 

 Gurion University of the Negev, Beer-Sheva, Israel.

2 Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

3 The Ilse Katz Center for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer 

Sheva 8410501, Israel.

Less than a year following the SARS-CoV-2 outbreak, variants of concern have emerged in the form of variant 

B.1.1.7 the British variant and B.1.351 the South Africa variant. Due to their high infectivity and morbidity, it has 

become clear that it is crucial to quickly and effectively detect these and other variants. Here, we report improved 

primers-probe sets for RT-qPCR for SARS-CoV-2 detection including a rapid, cost-effective, and direct RT-qPCR 

method for detection of the two variants of concern (B.1.1.7 and B.1.351). All the developed primers-probe sets 

were fully characterized, demonstrating sensitive and specific detection. These primer-probe sets were also 

successfully employed on wastewater samples aimed at detecting and even quantifying new variants in a 

geographical area, even prior to the reports by the medical testing. The novel primers-probe sets developed and 

presented here have important implications; it will promote proper responses and pandemic containment, and 

may provide a basis for developing tools for the detection of additional variants of concern.

Key words: Real-Time Polymerase Chain Reaction; Wastewater-Based Epidemiological Monitoring; SARS-CoV-2; Molecular 

Probes; Variants of concern

Standards and control materials used: This study use synthetic genes for SARS-CoV-2 RT-qPCR detection calibration and 

wastewater for field proof of concept experiments. 

Email for corresponding author: kariny@post.bgu.ac.il

Figure 1. B.1.1.7 variant detection in Beer- Sheva wastewater (WWTP) over time. Samples collected between November 2020 and March 2021 were tested 

for N gene, S1 (Original lineage) DQG6 ̈ (British B.1.1.7 lineage) detection.
Assessing the representativeness of Covid-19 testing in different communities 

through wastewater surveillance

Chenghua Long1, Dominic diSalvo2, Paul Storella3, Melanie Bernitz1, Wafaa El-Sadr1, and Kartik Chandran1

1

Columbia University; 2Bergen County Utilities Authority; 3AECOM

We highlight the results of wastewater surveillance employed in the following communities to track the prevalence 

of Covid-19 infections therein. 

In a sewershed that covers roughly 1 million residents in the greater New York City region, surveillance of 

SARS-CoV-2 concentrations is being conducted at different locations including the influent to different wastewater 

treatment plants. Based on the time-series-trends, concentrations of SARS-CoV-2 in the sewage streams have led 

the reported clinical case data by up to eleven days and in general have tracked the different waves of Covid-19 in 

the community.

In smaller residential populations (building-scale) in New York City, where clinical testing has been more 

frequent, wastewater testing has largely corresponded well with clinical data and has also been used to detect noncompliance with testing as well as the impact of any external interactions with the target community.

Data analysis and interpretation. The equivalence between the SARS-CoV-2 concentrations measured in 

wastewater and the corresponding fraction of the population infected is site-specific, as expected. Nevertheless, 

such equivalence calculations can be used to determine the severity of community infections as well as the impact 

of interventions such as vaccine administration. 

Importantly, from a social-perspective, based on sewage surveillance, the progressive non-representativeness of 

clinical testing within some communities is also revealed. 

Key words: wastewater; sewage; surveillance; population equivalence

Standards and control materials used: (short answer): Standards for quantifying target virus biomarkers copy numbers in 

samples; wastewater flow and load information to attempt virus concentration-population equivalence determination.

Email for corresponding author: kc2288@columbia.edu

Figure 1. Shifting trends in the representativeness of clinical testing as inferred through wastewater surveillance. Values 

higher than 1.0 reflect increasing degree of non-representativeness.
2021 Standards for Wastewater Surveillance 

Wastewater Surveillance’s Role as Part of a Whole-of-University Response in 

Campus Protection 

Jeffrey W. Bethel1

, Benjamin Dalziel2,3, Roy Haggerty4, Kathryn A. Higley5, Katherine R. McLaughlin6, F. 

Javier Nieto7

, Justin L. Sanders8, Brett M. Tyler9,10, and Tyler S. Radniecki11. 

1School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR; 2Department 

of Integrative Biology, Oregon State University, Corvallis, OR; 3Department of Mathematics, Oregon State 

University, Corvallis, OR; 4College of Science, Oregon State University, Corvallis, OR; 5School of Nuclear 

Science and Engineering, Oregon State University, Corvallis, OR; 6Department of Statistics, Oregon State 

University, Corvallis, OR; 7College of Public Health and Human Sciences, Oregon State University, 

Corvallis, OR; 8Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR; 9Center for 

Genome Research and Biocomputing, Oregon State University, Corvallis, OR; 10Department of Botany and 

Plant Pathology, Oregon State University, Corvallis, OR; 11School of Chemical, Biological, and 

Environmental Engineering, Oregon State University, Corvallis, OR. 

During the last year, campuses of higher education have struggled with how to protect their 

communities in the face of the SARS CoV-2 pandemic. Initial strategies included massive routine testing 

of students, faculty, and staff to no testing at all1

. At Oregon State University, selective COVID-19 testing 

of students, faculty and staff coupled with wastewater sampling and analysis, including RNA sequencing, 

across multiple campuses was used to inform the university’s COVID-19 Continuity Management Team2

. 

Health authorities in the relevant counties were also kept advised of the progression of the disease 

within the campus community, and the presence of variants of concern. While the testing strategy, of 

necessity, evolved over the course of the pandemic, wastewater remained a consistent, and initially 

under-appreciated tool for providing insight on locations and pockets of the disease within the college 

community. Results from routine wastewater sampling across multiple campuses were used by 

university decision makers in directing increased testing, and subsequently quarantining of on campus 

residents. The data were also used in crafting website and email messaging for off campus students. 

The net result was that information from wastewater surveillance informed health staff, underpinned 

rapid response testing of students, faculty, and staff, and help mitigate the spread of COVID-19 to the 

larger community.

 

1 https://www.forbes.com/sites/jemimamcevoy/2020/09/11/19-of-the-25-worst-us-coronavirus-outbreaks-are-incollegetowns/?sh=13d0f4491df7 2 https://trace.oregonstate.edu/ 

Key words: Surveillance; COVID-19; wastewater sequencing; TRACE. 
Email for corresponding author: tyler.radniecki@oregonstate.edu

Figure 1. Process followed to collect, analyze, assess results, and direct additional sampling on the OSU campuses.

 
Towards Standardizing Antimicrobial Resistance Surveillance of Water Systems: An 

Expert Survey and Workshop 

Krista Liguori1, Ishi Keenum1, Jeanette Calarco2, Benjamin C. Davis1, Erin Milligan1, Valerie J. Harwood2, Amy 

Pruden1*

1

Via Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia; 

2 Department of Integrative Biology, University of South Florida, Tampa, Florida

Monitoring sewage for antibiotic resistant bacteria and antibiotic resistance genes has the potential to inform the 

status of antimicrobial resistance (AMR) in human populations, while evaluation of treated effluent and recycled 

water can provide insight into the efficacy of treatment processes for reducing risk of spread in receiving 

environments (Hendrikson et al., 2019) and monitoring of surface water can reveal concerns for exposure via 

ingestion or recreation (Nappier et al., 2020). However, standardized methods for monitoring AMR in wastewater, 

recycled water, and surface water are needed in order to ensure that the data collected are meaningful and 

comparable across studies and surveillance efforts. While there have been numerous calls for standardization of 

methods for environmental AMR monitoring (Berendonk et al., 2015; Pruden et al., 2018; Hujibers et al., 2019), a 

key step towards achieving this goal will be agreement upon the purpose of such monitoring and prioritization of 

specific monitoring targets for achieving this purpose. To this end, we conducted a survey of 105 expertsspanning 

the fields of academia and research, state and federal government, consulting, and water/wastewater utilities to 

obtain their recommendations regarding potential AMR targets. Following the online survey, we conducted a 4-

day workshop attended by experts to discuss the state of the science, assess existing levels of standardization and 

feasibility, and obtain a final ranking of priorities for AMR monitoring in the U.S. water industry and regulatory 

community. Specifically, culture-based, quantitative polymerase chain reaction (qPCR)-based, and metagenomicbased methods were evaluated. Of special consideration was the prioritization of variables that consider overall 

potential to achieve monitoring objectives and address key research questions, for a wide-variety of stakeholders. 

A decision-tree framework was developed to assess which methods and targets are most appropriate based on 

specific monitoring objectives. Without such an effort, AMR research and surveillance will continue in silos and 

there will be a loss of opportunity to compare spatial and temporal trends, which will be critical to assessing the 

local and global rates of evolution and spread of AMR, assuring comparability of data and assessing the efficacy 

of mitigation measures. This perspectives study takes an important step towards identifying suitable targets for 

AMR monitoring standardization within water and wastewater systems in the U.S. and beyond. 

Key words: Antibiotic Resistance; Wastewater Surveillance; Standardized Methods. 

Standards and control materials used: not applicable. 

Email for corresponding author: apruden@vt.edu
Figure 1. Workshop Experts rank their first, second, and third choices for a feasible and informative qPCR target for AMR monitoring in water for the US 

water industry. 

References:

Berendonk, Thomas U., Célia M. Manaia, Christophe Merlin, Despo Fatta-Kassinos, Eddie Cytryn, Fiona Walsh, Helmut 

Bürgmann, Henning Sørum, Madelaine Norström, Marie Noëlle Pons, Norbert Kreuzinger, Pentti Huovinen, Stefania Stefani, 

Thomas Schwartz, Veljo Kisand, Fernando Baquero, and José Luis Martinez. 2015. “Tackling Antibiotic Resistance: The

Environmental Framework.” Nature Reviews Microbiology 13(5):310–17.

Hendriksen, R.S., Munk, P., Njage, P. et al. Global monitoring of antimicrobial resistance based on metagenomics analyses of 

urban sewage. Nat Commun 10, 1124 (2019). https://doi.org/10.1038/s41467-019-08853-3

Huijbers PMC, Flach CF, Larsson DGJ. 2019. A conceptual framework for the environmental surveillance of antibiotics and 

antibiotic resistance. Environ Int 130:104880.

Nappier SP, Liguori K, Ichida AM, Stewart JR, Jones KR. Antibiotic Resistance in Recreational Waters: State of the Science. 

International Journal of Environmental Research and Public Health. 2020; 17(21):8034. 

https://doi.org/10.3390/ijerph17218034

Pruden, A., Alcalde, R. E., Alvarez, P. J., Ashbolt, N., Bischel, H., Capiro, N. L., ... & Zhou, Z. (2018). An environmental science 

and engineering framework for combating antimicrobial resistance. Environmental Engineering Science, 35(10), 1005-1011.
First detection of SARS-CoV-2 proteins in wastewater samples by mass spectrometry 

Lara-Jacobo Linda R1, Islam Golam1, Gedge Ashley1, Desaulniers Jean-Paul1, Kirkwood Andrea E1 and Simmons Denina BD1

1The University of Ontario Institute of Technology 

On March 12, 2020, the World Health Organization (WHO) declared COVID-19 as a global pandemic. COVID-19 is 

SURGXFHGE\DQRYHOȕ-coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) 

[1]. Several studies have detected SARS-CoV-2 RNA in urine, feces, and other biofluids from both symptomatic 

and asymptomatic people with COVID-19 [2], suggesting that SARS-CoV-2 RNA could be detected in human 

wastewater [3]. Thus, wastewater-based epidemiology (WBE) is now used as an approach to monitor COVID-19 

prevalence in many different places around the world [4-10]. Reverse transcription quantitative polymerase chain 

reaction (RT-qPCR) is the most common SARS-CoV-2 detection method in WBE, but there are other methods for 

viral biomolecule detection that could work as well. The aim of this study was to evaluate the presence of SARSCoV2 proteins in untreated wastewater (WW) influents collected from two wastewater treatment plants (WWTPs), from 

Durham Region, Ontario, Canada, using a LC-MS/MS-based proteomics approach. Twenty-four-hour composite 

influent samples from each of the two wastewater treatment plants (WWTP) were obtained over the course of 15 

weeks – for a total of 171 samples across all sampling times and locations. A cross correlation was performed first 

with all the 160 pairs of data (x: Protein pp1ab 7-day midpoint mean viral signal, y: 7-day midpoint mean in reported 

new cases of COVID-19 by onset date) and with lags between -15 to 15 as the maximum (cross correlation in time 

series). The lag with the highest value of r was selected and was used to perform a Pearson correlation analysis 

(one-tailed with a confident interval of 95%). We identified many SARS-CoV-2 proteins in these wastewater 

samples, with peptides from pp1ab being the most consistently detected and with consistent abundance (protein 

related to the COVID-19 infection). 

 

Key words: SARS-CoV-2, COVID-19, liquid-chromatography mass spectrometry, wastewater, proteomics 

 

Standards and control materials used: N/A

 

Email for corresponding author: Denina.Simmons@ontariotechu.ca

 

Figure 1. Workflow for protein identification by LC-MS and the correlation of COVID-19 cases vs protein pp1ab. 
References 

1. Li, Q., et al., Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

N Engl J Med, 2020. 382(13): p. 1199-1207. 

2. Wang, W., et al., Detection of SARS-CoV-2 in Different Types of Clinical Specimens. JAMA, 2020. 

323(18): p. 1843-1844. 

3. Kitajima, M., et al., SARS-CoV-2 in wastewater: State of the knowledge and research needs. Sci Total 

Environ, 2020. 739: p. 139076. 

4. Ahmed, W., et al., First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof 

of concept for the wastewater surveillance of COVID-19 in the community. Sci Total Environ, 2020. 728: 

p. 138764. 

5. D’Aoust, P.M., et al., Catching a resurgence: Increase in SARS-CoV-2 viral RNA identified in wastewater 

48 hours before COVID-19 clinical tests and 96 hours before hospitalizations. 2020. 

6. D’Aoust, P.M., et al., Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities 

with low COVID-19 incidence and prevalence. 2020. 

7. Sherchan, S.P., et al., First detection of SARS-CoV-2 RNA in wastewater in North America: A study in 

Louisiana, USA. Sci Total Environ, 2020. 743: p. 140621. 

8. Westhaus, S., et al., Detection of SARS-CoV-2 in raw and treated wastewater in Germany - Suitability for 

COVID-19 surveillance and potential transmission risks. Sci Total Environ, 2021. 751: p. 141750. 

9. Randazzo, W., et al., SARS-CoV-2 RNA in wastewater anticipated COVID-19 occurrence in a low 

prevalence area. Water Res, 2020. 181: p. 115942. 

10. Lodder, W. and A.M. de Roda Husman, SARS-CoV-2 in wastewater: potential health risk, but also data 

source. The Lancet Gastroenterology & Hepatology, 2020. 5(6): p. 533-534. 
WBE Data Sharing, Ethics, and Community Outreach

Lauren Anderson1,2, Alexis Ecarma1,2, and Ted Smith1,2

1

Center for Healthy Air Water and Soil; 2 Christina Lee Brown Envirome Institute, University of Louisville

Key words: wastewater based epidemiology, COVID-19, SARS-Cov-2, environmental monitoring, research ethics, 

community engagement 

Standards and control materials used: n/a

Email for corresponding author: lauren.anderson@louisville.edu

Abstract: Issues of privacy or stigmatization pose potential concerns for research, data collection, and analysis of 

wastewater. However, through the assurance of anonymous results, the protection of identifiable information, 

and diversity of selected sampling sites, the Co-Immunity Project has incorporated ethical approaches to their 

work which safeguard the safety and well-being of individual privacy in effective ways. By developing strategies 

for transparency around scientific findings and research outcomes, as well as plans for crafting community 

agreements that incorporate the input of our community members, ethical research methods have become a 

major component of the Co-Immunity wastewater study. As further knowledge and insights regarding the ethics 

of wastewater testing continue to emerge and evolve, we are committed to adjusting our own principles and 

adopting new guidelines into our studies with the intent of promoting equity and inclusivity in the realms of 

medicine and public health.

Four strategies have emerged that create opportunities to increase transparency and establish bi-directional 

communication with the public around our wastewater monitoring research: 

1. Online dashboard: This dashboard is updated weekly and allows anyone to see current and past levels of 

SARS-CoV-2 in Louisville’s wastewater samples. 

2. WBE ethics-centric website: This website hosts facts and frequently asked questions about wastewater 

work, a history of water monitoring for public health, a link to the online dashboard, and a gallery detailing 

how wastewater samples are collected. 

3. Office Hours: Beginning on Thursday, June 10, 2021 the research team will host an open office hour via 

Zoom and Facebook Live to make wastewater researchers available to the public, to learn what people 

think about wastewater monitoring, and hear about possible concerns. 

4. Community Survey: The next round of Co-Immunity’s Community Testing will run from June 17 through 

June 23. This round will include a survey about our wastewater monitoring work. This survey will collect 

the public’s level of knowledge about wastewater monitoring, how supportive people are of this type of 

work, and about possible concerns. 
Figure 1. UofL Envirome Institute Wastewater Dashboard Map, May 17, 2021. Access via 

https://louisville.edu/envirome/thecoimmunityproject/dashboard

Figure 2. Co-Immunity Project’s Wastewater Research Office Hour Flyer for June 10, 2021
Systematic review and meta-analysis of correlations for time-lagged COVID-19 

cases and viral load in wastewater 

Michael Austin 

San Diego State University 

 

 Early detection of cases by the diagnostic testing of symptomatic persons and regular screening, 

isolation of presumed and confirmed cases and contact tracing are the key to controlling an infectious 

disease outbreak. However, the standard public health approach to an outbreak requires augmented 

ancillary surveillance mechanisms to successfully control COVID-19. Amid the pandemic, numerous 

studies have reported a positive correlation between COVID-19 epidemic indicators and the normalized 

viral load of SARS-CoV-2 in wastewater. Additionally, studies report that the viral load in wastewater is a 

leading indicator of confirmed cases within a population by days to weeks. Yet, significant 

methodological questions remain to robustly trend community cases with the viral signal in wastewater 

utilizing the technique known as wastewater-based epidemiology (WBE). The aim of this study is to 

systematically review the literature on WBE for studies trending normalized viral load of SARS-CoV-2 

with disease indicators and to compare the effects observed at baseline with those that include a 

timelag. We also aim to pool results for studies reporting common effect sizes and outcomes to 

delineate study-level heterogeneity. 

Key words: N/A 

Standards and control materials used: N/A

Email for corresponding author: maustin9138@sdsu.edu 

Nucleic Acid Extraction with Microbubbles from Wastewater Produces Simple and 

High-Yield Workflows

M. Maloney1

, C. Livi1, J. Roussey1, C. Wegner1, 1

Akadeum Life Sciences, Inc., Ann Arbor, MI 

The COVID-19 pandemic has highlighted the need for simple but sensitive technologies and simple workflows 

to enable environmental monitoring for communicable disease agents. Nearly everything about human 

behavior leaves a signal in urine, stool, or blood – this makes sewage an efficient pooled-sample source to 

monitor circulating infectious agents in a community. Novel approaches to surveillance will enable sensitive, 

specific and timely response to infections. 

 

Akadeum’s microbubbles are overcoming barriers to rare target capture from complex matrices such as 

wastewater utilizing an innovative approach: field-deployable, buoyant, functionalized microbubbles. In this 

presentation we demonstrate the utility and benefits of floatation-based capture reagents and associated 

workflows. Here proprietary microbubbles are specifically functionalized to capture nucleic acids. Unlike the 

inherent limitations of magnetic bead-based separation, microbubbles do not have the same volume and 

equipment restrictions. Using microbubbles for nucleic acid extraction employs a positive selection protocol in 

which the microbubbles bind to the desired target – in this case, total RNA including SARS-CoV-2 if present – 

isolating and enriching the analyte for downstream genomic analysis. 

 

First demonstrated in saliva samples, the microbubbles were able to interrogate large fluidic volumes, which 

enables a pooled sample approach desirable in community surveillance of viral infection. In fact, microbubble 

extraction delivered 25x higher sensitivity in detecting SARS-CoV-2 RNA based on qPCR detection compared to 

a magnetic isolation kit. Translating this workflow to wastewater samples, the microbubble nucleic acid 

extraction can directly interrogate large fluidic volumes of unfiltered sewage samples to increase RNA capture 

for downstream processing. A sensitivity of at least 100 copies per mL was observed with a protocol that avoids 

preprocessing steps such as the removal of nucleic acid-rich solids. 

 

Akadeum offers a simplified and cost-effective performance platform for the isolation of cells, proteins and 

nucleic acids that can be seamlessly integrated into existing workflows. Akadeum is seeking partnerships for 

applications of the nucleic acid microbubble in diagnostics and community surveillance including cell, protein 

and nucleic acid-based analyte enrichment for testing.

Email for corresponding author: michael@akadeum.com 
Figure 1. Akadeum microbubble-based RNA extraction technology enables a simplified workflow that avoids preprocessing cleaning steps such as the 

removal of solids. This increases sensitivity by retaining the RNA that would otherwise be lost by preprocessing. Here we demonstrate detection of covid 

RNA in a wastewater sample (n = 3) spiked with 100 cp/mL of Sars-CoV-2 RNA. 

. 
Single Particle ICP-MS: A Powerful Tool for Characterization of Nanomaterials in 

Wastewater Surveillance 

Monique E. Johnson1

, Karen E. Murphy,1 Antonio R. Montoro Bustos1, and Michael Winchester1

1

National Institute of Standards and Technology, Inorganic Chemical Metrology Group (646.01) 

Nanomaterials, defined as having at least one dimension falling in the range from 1 nm to 100 nm, have 

been identified as contaminants of emerging concern by the Environmental Protection Agency [1]. Similar 

to traditional chemical contaminants, some synthetic nanomaterials have been shown to be toxic to 

microbes, plants, and animals. The ever-increasing incorporation of nanomaterials into consumer products 

results in many routes of environmental exposure, including wastewater.

Analytical methods, critical for the detection and characterization of nanomaterials in wastewater, can 

address current gaps in knowledge. In particular, single particle inductively coupled plasma mass 

spectrometry (spICP-MS) is an emerging technique that enables measurements of size distributions and 

number concentrations of nanoparticles suspended in liquids. Special characteristics of spICP-MS that 

make it attractive for wastewater surveillance include extremely good nanoparticle detection capability

down to truly environmentally relevant levels and extremely rapid analysis. The use of spICP-MS for 

wastewater surveillance has been outlined in recent reviews [2,3] and demonstrated in publications 

describing the detection and sizing of TiO2 nanoparticles in municipal sewage treatment plants [4] and the 

size characterization of silver nanoparticles in wastewater [5,6]. However, the technique presents 

challenges and limitations that researchers have highlighted and are striving to overcome, particularly 

with respect to the lack of reference materials and standardization of spICP-MS methodologies. Provision 

of suitable reference materials and standard methods would enable widespread effective and efficient 

application of spICP-MS for wastewater surveillance to ensure that human health is not affected 

detrimentally by nanomaterials. 

The goal of our presentation is to highlight a few examples of the work that has been done within the 

NIST Inorganic Chemical Metrology Group (646.01) toward the advancement of spICP-MS as a mature 

technique. This work has provided a foundation for developing the standards and reference materials that 

are necessary to enable routine wastewater surveillance for nanoparticles. In the past five years, our group 

has engaged in several activities to build a robust nanomaterial spICP-MS measurement infrastructure, 

including: 

x validation of spICP-MS for routine characterization of gold nanoparticles of different sizes, 

coatings, and surface charge at environmentally relevant concentrations in water;

x analysis of silver and titanium dioxide nanoparticles in water; 

x characterization of silicon dioxide food additive materials in aqueous media; 

x the characterization of the uptake of gold nanoparticles in Caenorhabditis elegans; and

x the potential application of spICP-MS for the characterization of nanoplastics suspended in water. 

Key words: Nanomaterials, single particle ICP-MS, environmentally relevant concentration, reference materials, standards.

Standards and control materials used: NIST RM 8012 and 8013 gold nanoparticles; NIST RM 8017 silver nanoparticles; NIST 

SRM 1898 TiO2; gold, silver, silicon, and titanium ionic standard solution calibrants
Email for corresponding author: monique.johnson@nist.gov

Figure 1. Schematic representation of spICP-MS operation principle and simultaneous information provided.

References

[1] https://www.epa.gov/sites/production/files/2014-03/documents/ffrrofactsheet_emergingcontaminant_nanomaterials_jan2014_final.pdf

[2] Nano/microplastics in water and wastewater treatment processes – Origin, impact, and potential solutions. 

https://doi.org/10.1016/j.watres.2019.06.049 

[3]https://pubs.rsc.org/en/content/articlehtml/2020/ja/c9ja00206e. A critical review of single particle inductively coupled plasma mass 

spectrometry – A step towards an ideal method for nanomaterial characterization. 

[4] https://link.springer.com/article/10.1007/s00128-017-2031-8. Detection of TiO2 Nanoparticles in Municipal Sewage Treatment Plant 

and Their Characterization Using Single Particle ICP-MS. 

[5] https://www.azonano.com/article.aspx?ArticleID=4232. Particle Size Measurements on Silver Nanoparticles in Waste Water with 

Single Particle ICP-MS. 

[6] https://doi.org/10/1016/j.watres.2019.03.031 Incidence and persistence of silver nanoparticles throughout the wastewater treatment 

process. 
A Direct Nucleic Acid Capture Method for Purification and Detection of SARS-CoV-2 Genetic Material 

from Wastewater

Nathan Feirer1 and Subhanjan Mondal1 

1

Promega Corporation, 5430 E Cheryl Pkwy, Madison, WI 53711

Early in the COVID-19 pandemic, scientific studies demonstrated that the genetic material of SARS-CoV-2, an enveloped 

RNA virus, could be detected in wastewater. This finding mobilized investigation of whether wastewater-based 

epidemiology (WBE) monitoring the genetic signal of SARS-CoV-2 could be used to track the appearance and spread of 

COVID-19 in communities. The SARS-CoV-2 genetic signal is present at low concentrations in wastewater, making sample 

concentration a prerequisite for sensitive detection and utility in WBE. We hypothesized that a direct capture method that 

renders total nucleic acid conducive to binding to affinity resin may be able to overcome cumbersome, non-standardized, 

and variable viral concentration steps. This led to development of a simple, rapid, and modular alternative to existing 

purification methods from wastewater. In this approach, chaotropic agents are added to raw sewage allowing nucleic acid 

binding to a silica matrix. The captured nucleic acid is then washed to remove co-purifying PCR inhibitors, and then eluted 

with water. The eluted nucleic acid can then be further processed in a second step with either a spin column or using an 

automated nucleic acid purification system, like the Maxwell RSC®

. 

In parallel, we formulated RT-qPCR enzyme mixes that demonstrate resistance to PCR inhibitors commonly found in 

wastewater. RT-qPCR assays were developed to detect N1, N2 (nucleocapsid) and E (envelope) gene fragments of SARSCoV-2 as part of multiplexed assays. Pepper Mild Mottle Virus (PMMoV), a fecal indicator RNA virus present in wastewater, 

and an exogenous inhibition control were included in all PCR reactions for quality control. The workflow has a limit of 

detection of 1.6 GC/ ml with 40 ml of raw wastewater sample. Using this workflow, we monitored wastewater samples 

from three WWTP in Dane County, Wisconsin, serving a combined population of over 300,000 people, for four months 

covering the peak of community prevalence. Our analysis was compared to the COVID-19 cases declared by the 

municipalities, demonstrating strong correlation between the SARS-CoV-2 viral load present in wastewater and clinical 

cases.

Key words: SARS-CoV-2, Wastewater, RT-qPCR, COVID-19, Direct Capture

Standards and control materials used: Processing/Testing Methods

Email for corresponding author: nathan.feirer@promega.com
Figure 1. Workflow of the direct nucleic acid capture method for purification and detection of SARS-CoV-2 genetic material from 

wastewater. Image on the left details the direct capture and purification procedure. Table on right demonstrates components of 

multiplex RT-qPCR reaction.
Using municipal data to develop geographically-precise sampling frame standards

1

Christina Lee Brown Envirome Institute, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY 40202, United 

States, 2

Department of Environmental and Occupational Health Sciences, School of Public Health and Information Sciences, 

University of Louisville, 485 E. Gray St., Louisville, KY 40202, United States, 3

James Graham Brown Cancer Center, School of 

Medicine, University of Louisville, 505 S. Hancock St., Louisville, KY 40202, United States, 4

Department of Oncology, St. Jude 

Children’s Research Hospital, 262 Danny Thomas Pl, Memphis, TN 38105, United States, 7

Louisville/Jefferson County 

Metropolitan Sewer District, Morris Forman Water Quality Treatment Center, 4522 Algonquin Parkway, Louisville KY 40211, 

United States.

Wastewater monitoring for SARS-CoV-2 within communities can be utilized as a powerful to surveil and respond to the 

current COVID-19 pandemic, variants of concern, and future outbreaks with pandemic potential. However, there are currently 

no evidence-based and widely-accepted standards for urban sampling site identification and assessment. To inform 

development of such standards, we describe a protocol for developing a geographically-resolved wastewater sampling 

methodology in Jefferson County, Kentucky, and describe our preliminary results. We utilized this site selection protocol to 

identify 17 sample locations, based on municipal sewer data, representing distinct wastewater catchment areas. We collected 

samples (n = 285) at these locations from September 8 to October 30, 2020 from one to four times per week. We then 

compared SARS-CoV-2 testing results with contemporaneous and geographically-matched clinical testing-based COVID-19 

rates. We found that SARS-CoV-2 RNA was consistently present in each catchment area with significant spatial and temporal 

variation. We also observed substantial differences between trends in wastewater-based detection and clinical-testing. These 

findings verify that our site selection protocol is an efficacious approach, which may be used to inform development of a 

standardized best-practice approach of geographically-resolved SARS-CoV-2 wastewater sample site selection in urban areas.

Key words: Wastewater, Geographic, GIS, sewershed, catchment

Standards and control materials used: Municipal data and preliminary monitoring results

Email for corresponding author: Rayeag01@louisville.edu

Figure 1. Visualization of geographically-resolved site selection process. 

R. Yeager1,2, R. H. Holm1, K. Saurabh3,4, D. Talley7, A. Bhatnagar1 and T. Smith1
Rapid Capture of SARS-CoV-2 Using Nanotrap® Magnetic Virus Particles

Alex Barclay1, Smruthi Karthikeyan2,Ben Lepene1, Patrick Andersen1, Daniel Goldfarb1, Kevin Kolb1, 

Joshna Seelam1, Tara Jones-Roe1, Rob Knight2, Robbie Barbero1

1

Ceres Nanosciences, Inc. 

2

University of California San Diego

SARS-CoV-2 is the causative agent of COVID-19, a disease that has caused a worldwide pandemic and 

claimed over 3 million lives. SARS-CoV-2 is shed in feces, enabling wastewater-based surveillance of 

the disease, which can allow for monitoring of infection rates in communities as well as to help identify 

SARS-CoV-2 variants of concern that may occur in an area. Methods currently employed to isolate 

SARS-CoV-2 from wastewater are long, arduous, and are not suitable for high throughput testing. Here, 

we offer an alternative method for viral isolation, use of Ceres Nanosciences’ Nanotrap® Magnetic 

Virus Particles, which capture and concentrate whole virus from wastewater. This new method gives 

comparable results to PEG/ultracentrifugation and HA filtration across a range of viral titers despite 

using 80% less initial volume than either while also reducing processing time by several hours. Here we 

demonstrate that this method is compatible with multiple viral RNA extraction kits and that it can 

readily be automated, allowing for high-throughput testing. Overall, the Nanotrap® Magnetic Virus 

Particles offer a shorter, more user-friendly workflow than competing virus isolation methods while 

maintaining comparable sensitivity.

Key words: viral enrichment, viral concentration, wastewater processing

Standards and control materials used: Heat-inactivated SARS-CoV-2 (ATCC)

Email for corresponding author: rbarbero@ceresnano.com

Figure 1. Wastewater spiked with heat-inactivated SARS-CoV-2 at 1000 copies/mL. Virus concentration performed using Nanotrap® Magnetic Virus 

Particles and compatibility with three standard RNA extraction kits demonstrated using the CDC nCoV-2019 N1 RT-PCR assay.
Equity in standardized collection of pooled community stool for pathogen detection: 

Moving from pit latrines to sewered systems globally

Rochelle H. Holm1

, and Ted Smith2

1

Centre of Excellence in Water and Sanitation, Mzuzu University, Mzuzu, Malawi; 2Christina Lee Brown Envirome Institute, 

University of Louisville, Louisville, Kentucky, United States of America

Sustainable Development Goal (SDG) 3 covers health and 6 covers sanitation, and the COVID-19 pandemic has 

brought the research community interest in health monitoring using pooled community stool to the forefront. 

While 41% of the world’s population uses a sewered connection, an equal 41% uses a non-sewered sanitation 

system such as septic tanks, pit latrines and other improved on-site systems (UNICEF and WHO, 2019). Both 

sewered and non-sewered systems can track pathogens (Capone et al., 2021; Yeager et al., 2021). Yet, sample 

collection standards for both sewered and non-sewered systems use similar equipment and human capacity; 

though existing pit latrine sampling utilizing fecal sludge management approaches for pathogen detection are 

more similar than wastewater sampling approaches for environmental compliance. The pandemic has brought 

more equitable sharing of sample collection methods globally through avenues such as the National Science 

Foundation Research Coordination Network webinar series, a wastewater focused Slack channel, and journals 

waiving publication fees for COVID-19 research. The pandemic has also brought attention to value new 

professionals entering the sanitation field, where researchers from the global south with experience looking at 

pathogen detection in pit latrines have unique experience to share with researchers pivoting other research 

interests (including graduate students, post-docs and early career professionals) in the global north. Postpandemic, instead of a ‘brain drain’ of sanitation professionals leaving the global south there could be greater 

incentive to continue their health monitoring using pooled community stool. The equity in pooled community 

stools for pathogen detection has uniquely brought about collaboration and cooperation during the pandemic for 

standardized sample collection that can only help global sanitation capacity building with practical skills across 

the global south and north to meet the SDGs and support a better post-pandemic world. 

Key words: sample collection; capacity building; pit latrines; sewered sanitation systems

Standards and control materials used: Sample collection standards for both sewered and non-sewered systems use similar 

equipment and human capacity.

Email for corresponding author: rochelle.holm@louisville.edu

Figure 1. Sample collection methods for pathogens from pit latrines (left) and sewered systems (right).
First detection of SARS-CoV-2 RNA in wastewater in North America: A study in Louisiana, USA

Samendra P. Sherchana 

Department of Environmental Health Sciences, Tulane University, 1440 Canal Street, Suite 2100, New 

Orleans, LA 70112, USA

We investigated the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in 

wastewater samples in southern Louisiana, USA. Untreated and treated wastewater samples were collected on 

five occasions over a four-month period from January to April 2020. The wastewater samples were concentrated 

via ultrafiltration (Method A), and an adsorption–elution method using electronegative membranes (Method B). 

SARS-CoV-2 RNA was detected in 2 out of 15 wastewater samples using two reverse transcription-quantitative 

polymerase chain reaction (RT-qPCR) assays (CDC N1 and N2). None of the secondary treated and final effluent 

samples tested positive for SARS-CoV-2 RNA. To our knowledge, this is the first study reporting the detection of 

SARS-CoV-2 RNA in wastewater in North America, including the USA. However, concentration methods and RTqPCR assays need to be refined and validated to increase the sensitivity of SARS-CoV-2 RNA detection in 

wastewater.

Keywords

Wastewater-based epidemiology

SARS-CoV-2 

Surveillance

COVID-19

RT-qPCR

Wastewater 

Standards and control materials used: phi6

Email for corresponding author: sshercha@tulane.edu
Fig. 1. SARS-CoV-2 RNA detection in wastewater and confirmed COVID-19 cases in southern Louisiana, USA. 

Circles, squares, and triangles represent sample types, i.e.,influent, secondary-treated, and final effluent, 

respectively. Red and blue symbols represent samples collected from WWTPs A and B, respectively. Closed and 

open symbols denote positive and negative SARS-CoV-2 RNA detections, respectively.
Whole Cell Reference Materials to Assess Microbial Detection in Wastewater

Sandra Da Silva1, Joy P. Dunkers1, Kirsten H. Parratt1, Guilherme Pinheiro1,2, Samuel T. Hailemichael1,3, and 

Nancy J. Lin1

1Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, 

Gaithersburg, MD; 2 Metrology Institute (INMETRO), Rio de Janeiro, Brazil; 

3Montgomery College, Germantown, MD

Wastewater surveillance (WWS) holds great promise for monitoring public health concerns such as 

emerging pathogens (e.g., SARS-CoV-2), microbes (e.g., enteric bacterial pathogens), or antimicrobial 

resistance (AMR) genes. For example, a global effort is underway to monitor wastewater for AMR genes 

to assess the extent of AMR in communities.1 When detecting microbes or their genes in wastewater, it 

is challenging to compare protocols and assess overall process efficiency due to high variability in samples

and workflows across the country. Highly characterized whole cell reference materials (RMs) can 

normalize analytical workflows, enable method comparison, and challenge the entire process from 

sample collection to data analysis, ultimately increasing confidence in results. NIST is developing two 

viable whole cell RMs as surrogates for microbial (bacterial or fungal) targets of interest to assess 

workflow parameters, such as sampling efficiency, DNA extraction efficiency, limit of detection, and 

bioinformatics pipelines. The first consists of Escherichia coli NIST0056 cells characterized for total and 

viable cell number and genome copies/cell using flow cytometry and optical microscopy. The second, NIST 

RM 8230–Saccharomyces cerevisiae NE095 (target date Jan 2022), is characterized for total cell number 

and colony forming units and engineered to contain a noncoding chromosomal DNA target. This target 

eliminates false positives from near neighbors and can serve as a surrogate for AMR genes in molecular 

detection methods. These existing RMs could be applied directly to WWS or our capabilities could be 

translated to develop RMs using other relevant microorganisms. One could envision a whole cell RM based 

on non-replicating bacteria or fungi to safely spike into any point of the WWS workflow at a known 

concentration. RMs such as this could serve as internal references to assess the overall process, including 

operators, technologies, and protocols, or as tools for training, method comparison, or risk management 

exercises. These current and potential future whole cell microbial RMs could support WWS capabilities 

and ultimately improve assurance in the results provided to public health decision makers.

Keywords: antimicrobial resistance, Escherichia coli, flow cytometry, genome copy number, microbial detection, 

reference material, Saccharomyces cerevisiae, viable

Corresponding author: sandra.dasilva@nist.gov

1 Hendriksen, R.S., Munk, P., Njage, P. et al. Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. 

Nat Commun 10, 1124 (2019). https://doi.org/10.1038/s41467-019-08853-3

This E. coli RM under development will be characterized for total number of 

cells and genome copies/cell, two parameters that challenge our ability to 

confidently quantify microbial systems. Viability will also be reported. The 

characterization is done using flow cytometry (shown, where n is genome copy 

number) and optical microscopy. The final RM will be lyophilized pellets.
NIST SRM 2917: A Plasmid DNA Standard for Molecular Recreational 

Water Quality Testing 

Scott A. Jackson1, Jason G. Kralj1, Blaza Toman2, Stephanie L. Servetas1, Monique E. Hunter1, Jessica 

R. Willis3, Orin C. Shanks3 

1

Biosystems and Biomaterials Division, Material Measurement Laboratory, National Institute of Standards and Technology, 

Gaithersburg, MD, USA; 2

Statistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, 

Gaithersburg, MD, USA; 3

U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA

Contamination of waterways with fecal material can lead to the spread of pathogens that can have 

serious impacts on human and environmental health. The U.S. Environmental Protection Agency (EPA) 

is responsible for protecting human and environmental health through the safeguard of recreational

waters. Traditional monitoring practices involve time consuming cultivation procedures which can delay 

decision making. To accelerate this process molecular techniques, specifically quantitative polymerase 

chain reaction (qPCR) methods, for identifying host-associated genetic markers of fecal pollution and 

quantifying fecal indicator bacteria have been developed at EPA and by other researchers. National 

implementation of these methods requires rigorous proficiency testing by state and local public health 

agencies, as well as commercial entities that hope to adopt these methods. In a collaborative effort to 

support the adoption of these molecular methods, the EPA and NIST developed a plasmid DNA 

Standard Reference Material (NIST SRM 2917) for the purpose of implementing select qPCR assays for 

recreational water quality monitoring applications (figure 1). The material consists of 6 Levels of a 

linearized plasmid DNA containing 13 single-copy PCR targets selected by the EPA. The vector 

consists of a standard pUC plasmid with an ampicillin resistance gene, an origin of replication, and M13 

universal priming sites flanking the target genetic marker construct. Dilution levels span approximately 

5 to 500,000 plasmid copies per PL. Each tube of material contains approximately 200 PL of plasmid 

DNA in TE buffer (pH 8.0) with 10 ng/PL of RNA stabilizer (yeast tRNA) in a 1.5 mL low retention 

microcentrifuge vial. The material is stored at 4 °C and should not be frozen. Approximately 1,000 

units were generated. The material was characterized by NIST using droplet digital PCR to establish 

homogeneity and stability of the material as well as assign an absolute copy number to each dilution 

level. 

Key words: Reference material, qPCR, ddPCR, molecular detection methods, fecal indicator bacteria

Disclaimers: Information has been subjected to U.S. EPA peer and administrative review and has been approved for 

external publication. Any opinions expressed in this paper are those of the authors and do not necessarily reflect the official 

positions and policies of the U.S. EPA. Any mention of trade names or commercial products does not constitute endorsement 

or recommendation for use. Certain commercial equipment, instruments, or materials are identified in this paper to specify 

adequately the experimental procedures. Such identification does not imply recommendation or endorsement by the National 

Institute of Standards and Technology; nor does it imply that the materials or equipment identified are necessarily the best for 

the purpose.
Figure 1. The 1.7 kb construct containing the 13 targets was synthesized de novo using the IDT gBlock technology. The 13 targets include genetic markers 

for human (HF183/BacR287, HumM2, CPQ_056, CPQ_064), ruminant (Rum2Bac), pig (Pig2Bac), cattle (CowM2, CowM3), dog (DG3, DG37), avian 

(GFD), Enterococcus (Entero1a), and E. coli (EC23S857) pollution sources for fecal indicator bacteria. The gBlock was then inserted into a pUCIDT vector 

(2752 bp) carrying an AMP selection marker (AMPR) and an origin or replication (ORI) to produce the 4421 bp plasmid (shown circular, but final SRM is 

linearized). 
Development of RNA Standards for Quantification of SARS-CoV-2 and PMMoV by RT-qPCR for 

Wastewater Surveillance 

 

Subhanjan Mondal, Nathan Feirer, and Dongping Ma 

Promega Corporation, 5430 E Cheryl Parkway, Fitchburg, WI. United States 

 

 

Over the course of the COVID-19 pandemic, wastewater surveillance has emerged as a promising tool to monitor 

spread of the virus in a community. Wastewater is a complex matrix, so analytical methods like RT-qPCR needs to 

be designed with appropriate controls to quantitate and normalize viral levels for trend analysis. In this work we 

describe methods for designing and manufacture of quantification standards for SARS-CoV-2 and Pepper Mild 

Mottle Virus (PMMoV) RNA. PMMoV is a plant virus with a ssRNA genome and is a well-documented human 

fecal indicator. PMMoV RNA also serves as a useful process control and normalization tool for wastewater 

surveillance. 

To generate quantitative standards, we first cloned the Envelope and Nucleocapsid (E/N) genes of SARS-CoV2 in 

pGEM3z vector. Likewise, a 362bp fragment of the PMMoV genome consisting the RT-qPCR target is also cloned 

in a pGEM3z vector. The two plasmids are then linearized by XbaI and in-vitro transcribed to generate RNA 

transcripts. Any remaining DNA in the reaction is eliminated by DNase treatment. RNA was then quantified with a 

fluorescent RNA dye (QuantiFluor RNA System) and by droplet digital PCR (ddPCR). The relationship of quantity 

of RNA (in pg) corresponding to copy number as determined by ddPCR is established. The RNA was then diluted 

at 4 million copies/ul corresponding to 20pg/ul and 7.5pg/ul for the SARS-CoV-2 (E/N) and PMMoV RNA 

respectively. Both the RNA was then tested with the primes/probe set prescribed by the US Centers for Disease 

Control (CDC) that target the nucleocapsid (N1 and N2) gene, or the envelope (E) gene of the SARSCoV2 RNA and primers/probes for PMMoV for the PMMoV RNA. The quantitation standards were stored 

at -20°C and subjected to ten freeze-thaw cycles. No decrease in Ct values was observed implying that the 

quantification standards were stable. The standards were used to quantify SARS-CoV-2 and PMMoV RNA from 

three wastewater treatment plants in Dane county, WI. Normalization of SARS-CoV-2 RNA with PMMoV RNA 

resulted in better correlation with 7-moving average of new clinical cases a municipality served by a treatment plant. 

Key words: RT-qPCR, quantitation standards, in-vitro transcribed RNA 

Standards and control materials used: In-vitro transcribed RNA 

Email for corresponding author: subhanjan.mondal@promega.com 

 

 

 
Figure 1. Development of RNA standards for quantification of SARS-CoV-2 and PMMoV by RT-qPCR for 

Wastewater Surveillance
Assessing Community Acceptance: Wastewater Monitoring Community Survey (WMCS)

Ted Smith1, Kandi L. Walker2, Joy L. Hart2, Rochelle H. Holm1, Rachel Keith1, Lauren Anderson1, Lauren Heberle3, 

Dan Riggs1

, and Aruni Bhatnagar1 

1

University of Louisville, School of Medicine; 2University of Louisville, Department of Communication; 3University of 

Louisville, Department of Sociology

Community wastewater monitoring can be a powerful early warning tool to protect public health. 

However, given the wide range of possible implementations, and the situational interpretation of the 

medical ethics issues present when conducted in a non-regulatory fashion, standards development 

should include a public perspective. The University of Louisville has developed a straightforward 

instrument to quickly assess both awareness and acceptance of wastewater monitoring, specifically 

focused on COVID-19 wastewater surveillance. We propose that standards development and 

implementation adopt a common feedback approach nationally which could inform regional 

sensitivities to public health surveillance acceptance as well as strategies for standard approaches to 

implementation. This seven-item questionnaire includes three items that assess awareness of this type 

of public health surveillance and three items that focus on key aspects known to affect acceptance of 

specific implementations. For example, the instrument measures the importance of data sharing with 

the public and the size of catchment areas that a community member is comfortable having sampled. 

The instrument is being evaluated as a component of a larger public health community trial which will 

allow comparison with other data sources and present opportunities to increase its predictive validity.

Key words: Wastewater Surveillance; Ethics; Community Feedback. 

Standards and control materials used: NONE

Email for corresponding author: ted.smith@louisville.edu
Figure 1. Wastewater Monitoring Community Survey (WMCS)
Comparison of Sampling Frequency and Concentration Methodology for the Detection 

and Quantification of SARS-CoV-2 in Wastewater

Andrea D. George1,2, Devrim Kaya2

, Blythe A. Layton1, Kestrel Bailey1, Christine Kelly2,3, Kenneth J. Williamson1, 

Tyler S. Radniecki2,3,*

1

Department of Research & Innovation, Clean Water Services, Hillsboro, OR, 97123; 2School of Chemical, 

Biological, and Environmental Engineering, Oregon State University, Corvallis, OR, 97331; 3

TRACE (Team-based 

Rapid Assessment of Community-level coronavirus Epidemics), Oregon State University, Corvallis, OR, 97331; 

*Corresponding Author

Wastewater-based epidemiology (WBE) has been implemented across the world to track the COVID-19 disease 

burden of a community through the quantification of SARS-CoV-2 (the virus responsible for COVID-19) in 

wastewater samples. Due to the rapid implementation of WBE programs in combination with supply chain 

issues and varying budget constraints, many different protocols for sampling and analysis have been developed. 

However, the effects of these various techniques on the interpretation of the reported detection and 

quantification of SARS-CoV-2 is limited. To that end, studies were conducted to evaluate a variety of sampling 

and viral concentration techniques. Two of the most common sampling techniques utilized for WBE, grab and 

composite sampling, were evaluated by comparing the SARS-CoV-2 concentrations in 24 hourly grab samples 

with their associated 24-h composite sample at four sewershed scales (city, neighborhood, city block and 

individual building). Additionally, the effects of sampling frequency on reported SARS-CoV-2 composite 

concentrations were evaluated at a low-flow building site with sampling frequency varying from 5 min to 1 h. 

The results indicated that composite sampling should be utilized at every sewershed scale. However, at the city 

scale (e.g. wastewater treatment plant influent), grab samples may be acceptable if only attempting to 

determine the presence or absence of SARS-CoV-2. At the scale of city block and individual buildings, highfrequency composite sampling (e.g. 15 min sampling) is required to capture the temporal variation in viral 

signal. Another critical step to optimize is the concentration of SARS-CoV-2 from wastewater. Six common WBE 

concentration methods were compared by quantifying the SARS-CoV-2 concentration from the same 

wastewater treatment plant influent sample. The best relative recovery was found in the methods that utilized 

electronegative membrane filtration. To supplement this knowledge, the different solid and liquid fractions of 

an influent were separated into the individual components (i.e., liquid, settleable solids and non-settleable 

solids) to evaluate where SARS-CoV-2 RNA was partitioned in the wastewater. Of the SARS-CoV-2 captured by 

the electronegative membrane, roughly 90% was found in the non-settleable solid fraction. Thus, future

optimization of concentration methods should focus on retaining the SARS-CoV-2 RNA from the non-settleable 

solids fraction of wastewater. 

Key words: SARS-CoV-2; Wastewater-based Epidemiology; Composite Sample; Grab Sample; Concentration; Frequency; 

Filtration; Non-settleable Solids

Standards and control materials used: Positive SARS-CoV-2 controls containing the E, N, ORF1ab, RdRP, and S genes and 

human RNAse P RNA (EDX SARS-CoV-2 Standard, Exact Diagnostics, Fort Worth, TX) and negative controls containing certified 

SARS-CoV-2-free human RNAse P RNA (EDX SARS-CoV-2 Negative, Exact Diagnostics, Fort Worth, TX) were included in each 

extraction plate. Extraction blanks of phosphate buffered saline (PBS) were included with every run as an extraction 
contamination control. Bovine coronavirus (Bovine Rotavirus-Coronavirus Vaccine from Zoetis, NJ, USA), was selected as a 

process recovery control due to its morphological and structural similarity to SARS-CoV-2.

Email for corresponding author: tyler.radniecki@oregonstate.edu

Figure 1. Overview of SARS-CoV-2 sampling frequency and SARS-CoV-2 concentration analyses
PiGx SARS͡CoV͡2 wastewater͆ A pipeline for reproducible wastewater

sequencing analysis providing comprehensible geo͡tagged time series

reports

Authors: Altuna Akalin1, Vic-Fabienne Schumann1, Ricardo Wurmus1, Miriam Faxel

1

,

Jan Dohmen1, Rafael Cuadrat

1

1 Max-Delbrück Centrum, Berlin Institute for MЈedical Systems Biology

Setting up monitoring systems for the development of SARS-CoV-2 through

wastewater sampling has become a crucial mission for many nations all over the

world [1],[2] . Developing protocols for comparable sampling and sequencing on

the one side but also developing robust and scalable analysis tools on the other

side remains an ongoing challenge so far.

We present the PiGx SARS͡CoV͡2 wastewater sequencing pipeline [3] , a Bit by

Bit reproducible pipeline using GuixHpC [4] which provides reports that are

intuitive to use and easy to interpret. They combine visualisation, access to quality

control reports and downloadable data tables for sharing and further processing.

They grant geo-tagged visual time series overviews over the dynamics of single

mutations and abundances of given variants of concern (VOC) which were

derived by deconvolution. Under development right now are features in order to

identify untracked mutations that show significant increase over time and also to

track the relative abundance of SARS-CoV-2 in wastewater samples.

We aim to collaborate with many groups working with different strategies in

order to make this pipeline as easily accessible as possible and applicable for data

from various sequencing protocols. With PiGx SARS͡CoV͡2 wastewater we aim

to develop a tool to support combined and global research efforts and make

wastewater sequencing data comparable, reportable and reproducible.

[1] www.cdc.gov, “Developing a wastewater surveillance sampling strategy”

(accessed: 21/06/06)

[2] www.dw.com, “Eu states must monitor sewage systems for covid”

(accessed: 21/06/06)

[3] https://github.com/BIMSBbioinfo/pigx_sarscov2_ww

(accessed: 21/06/06)

[4] https://hpc.guix.info/, (accessed: 21/06/06)