key: cord-0923557-o5oidt3h
authors: Reeves, K.; Liebig, J. N.; Feula, A. D.; Saldi, T.; Lasda, E.; Johnson, W. J.; Lilienfeld, J.; Maggi, J. R.; Pulley, K.; Wilkerson, P. J.; Real, B.; Zak, G.; Davis, J. C.; Fink, M. R.; Gonzalez, P.; Hager, C. R.; Ozeroff, C.; Tat, K. L.; Alkire, M. L.; Butler, C. E.; Coe, E.; Darby, J.; Freeman, N.; Heuer, H.; Jones, J. R.; Karr, M.; Key, S.; Maxwell, K.; Nelson, L.; Saldana, E. M.; Salveson, L.; Shea, R.; Tomlinson, K.; Vargas-Barriga, J.; Vigil, B.; Brisson, G.; Parker, R.; Leinwand, L. A.; Bjorkman, K. K.; Mansfeldt, C. B.
title: High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention
date: 2021-05-26
journal: nan
DOI: 10.1101/2021.05.24.21257632
sha: cc29e6756770d0575feeccf282cc37b4782efe20
doc_id: 923557
cord_uid: o5oidt3h

To assist in the COVID-19 public health guidance on a college campus, daily composite wastewater samples were withdrawn at 20 manhole locations across the University of Colorado Boulder campus. Low-cost autosamplers were fabricated in-house to enable an economical approach to this distributed study. These sample stations operated from August 25th until November 23rd during the fall 2020 semester, with 1,512 samples collected. The concentration of SARS-CoV-2 in each sample was quantified through two comparative reverse transcription quantitative polymerase chain reactions (RT-qPCRs). These methods were distinct in the utilization of technical replicates and normalization to an endogenous control. (1) Higher temporal resolution compensates for supply chain or other constraints that prevent technical or biological replicates. (2) The endogenous control normalized data agreed with the raw concentration data, minimizing the utility of normalization. The raw wastewater concentration values reflected SARS-CoV-2 prevalence on campus as detected by clinical services. Overall, combining the low-cost composite sampler with a method that quantifies the SARS-CoV-2 signal within six hours enabled actionable and time-responsive data delivered to key stakeholders. With daily reporting of the findings, wastewater surveillance assisted in decision making during critical phases of the pandemic on campus, from detecting individual cases within populations ranging from 109 to 2,048 individuals to monitoring the success of on-campus interventions.

and asymptomatic persons (7)-(11). Further, symptoms may take up to two weeks to develop post-infection 48 (12)-(14), and even when symptomatic, individuals may not self-report. As a result, clinical testing alone 49 fails to identify many infected individuals before they transmit the disease to others and under-represents 50 caseload numbers utilized by officials to inform public health directives. The need to address these 51 shortcomings with a supplementary epidemiological tool was recognized early in the pandemic with a 52 global collaborative of researchers advocating for wastewater-based epidemiology (WBE) (15). 53 WBE efficiently and non-invasively monitors community metrics by sampling generated wastewater and 54 screening for chemical and biological entities, with previous success demonstrated in tracking community 55 drug use (16),(17) and poliovirus circulation (18)-(20). Wastewater networks can be sampled at points at 56 which discharges from community members have combined, aggregating a semi-anonymous signal 57 representative of the upstream community. Analyzing aggregated wastewater for SARS-CoV-2 RNA 58 therefore provides an opportunity to test entire communities within a single sample. Moreover, as SARS-59

CoV-2 RNA is present in the feces of both symptomatic (21)-(28) and asymptomatic (29)-(31) COVID-19-60 infected individuals, wastewater analysis offers insight into infection prevalence unhindered by factors such 61 as symptom onset and the healthcare-seeking behavior of individuals. Further, whereas aggregated testing 62 cannot pinpoint infected individuals, this approach can allow for more effective use of clinical testing 63 resources. For example, WBE can quickly identify the regions and communities with the most infections 64 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint Table 3 ). Collection occurred daily between 7 AM and 12 PM, with power banks replaced every 48 hours 124 and ice packs replaced daily when ambient average temperatures exceeded 4°C. Samplers were only turned 125 off for the following three events: a September blizzard, a supply chain disruption in October, and a cold 126 event in October. 127 Sample Collection. Two 50-mL subsamples and one 40-mL subsample were collected from each sampler 128 daily. One 50-mL subsample was collected for RNA extraction and viral detection, and the second 50-mL 129 subsample was collected for determination of basic water quality parameters. The 40-mL subsample was 130 collected as a backup sample. Subsamples were poured from the 5-gal jerrycan after swirling the contents. 131

All samples were collected in pre-weighed sterile polypropylene tubes loaded with 500 μL of 10% Tween TM 132 20 detergent (Thermo Fisher), which served to inactivate infectious agents for worker safety. Samples were 133 stored on ice immediately after collection and during transport back to the laboratory. After sample 134 collection at each sampler, ½-in. O.D. PVC tubing was connected to the jerrycan, fed through the D-pick 135 of the manhole cover, and used to drain excess withdrawn wastewater. Emptied jerrycans were then briefly 136 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Fluorometer (Q33238, Thermo Fisher) using the High Sensitivity RNA Kit to quantify the total RNA 156 extracted and roughly assess the success of the extraction process (Supplemental Table 6 ). 157 RT-qPCR. Two separate RT-qPCR pipelines were then used to detect and quantify SARS-CoV-2 RNA. 158

The first RT-qPCR pipeline, entitled SURV1, was executed simultaneously with the sampling campaign. 159

Immediately after the RNA extraction step, a 5-μL aliquot of extracted RNA from each sample was 160 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (52). From August 28th to September 29th, the N1 primer and probe set was used to detect the nucleocapsid 168 region. After September 30th, the N2 primer and probe set was used instead because of supply availability. 169

Multiple technical replicates were not run. The wastewater samples were analyzed by SURV1 the same day 170 as sample collection. 171

The second RT-qPCR pipeline, entitled SENB+, was executed in December 2020 after the fall sampling 172 campaign had ended. In this second pipeline, the extracted RNA samples (frozen at -80℃) were reevaluated 173 for SARS-CoV-2 RNA using a wastewater-specific RT-qPCR multiplex assay detecting the following 174 targets: SARS-CoV-2 N (N2), SARS-CoV-2 E, the spiked internal control bovine coronavirus, and 175 genogroup II F+ RNA bacteriophage (Supplemental Table 7 ). Genogroup II F+ RNA bacteriophage was 176 targeted to serve as a human fecal indicator (53). (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint minutes, reverse transcription at 53°C for 10 minutes, polymerase activation at 95°C for 2 minutes, and 186 amplification in 40 cycles of 95°C for 3 seconds (denaturing step) and 60°C for 30 seconds (annealing and 187 elongation step). Reactions were performed in triplicate. Each run included between one and three triplicate 188 negative control reactions (with 5 μL of RNase-free water instead of template RNA) and a ten-fold serial 189

Coralville, IA, USA) and RNA (SARS-CoV-2 (SARS-CoV-2 Jul-28-20 #2; Twist Biosciences, San 193

Francisco, CA, USA) and bovine coronavirus (direct extraction of the Bovilis® Coronavirus quantified 194 using a Qubit 4)) standards for standard curve quantification. The ten-fold dilutions ranged from 10 5 , 10 6 , 195 and 10 6 copies to 1, 10, and 10 copies of SARS-CoV-2, bovine coronavirus, and F+ bacteriophage standard 196 per reaction, respectively (Supplemental Figure 7) . The lower standard amount established the limit of 197 quantification (LOQ). The limit of detection (LOD) was set at amplification occurring before the 40th cycle their amplifications were greatly displaced from their expected position. More specifically, ten-fold 209 standard dilutions amplified with 100% efficiency should be spaced 3.32 cycle numbers apart. Let n 210 represent the intervals between dilutions such that 10 6 and 10 5 dilutions are n = 1 interval apart and 10 6 and 211 10 4 dilutions are n = 2 intervals apart. A standard dilution was excluded from standard curve creation if the 212 average Ct of its amplifications was either less than 2n or greater than 5n cycle numbers apart from the 213 average Ct of the amplifications of the closest higher dilution accepted and positioned n before it. 214 Data Normalization. SARS-CoV-2 data from SURV1 was normalized by subtracting the RNaseP Ct value 215 from the SARS-CoV-2 E Ct value because these values are logarithmic in nature. The N gene was utilized 216 to confirm trends. Data from SENB+ was processed by calculating copies per liter of wastewater using the 217 recorded masses of sample concentrated and eluted (Supplemental Table 10 ) and the following equation: 218

The bovine coronavirus and F+ bacteriophage signals were used to track sample variability but not to 220 Diego, CA, USA) to confirm suspected cases within the community. These data are considered as "positive 228 detections" within the residential structures, and the date of each positive is used to denote the case (though 229 that date is not the date of actual infection) (Supplemental Table 11 ). Isolation space utilization tracks the 230 number of beds in designated isolation spaces occupied on a given day (Supplemental Table 12 ). 231

Performance of the Composite Samplers. In general, the composite samplers performed well, reliably 233 withdrawing sample mass. The design achieved the objectives and provided an economical sampling unit. 234

Additionally, if a source of electricity is near the sample point, then the cost decreases with removing the 235 necessity of the power bank. Throughout the campaign, concerns were noted over (1) ranges to surrounding dates, highlighting the need and utility of multiplexed controls. This peak occurred 257 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint on a Sunday 24 hours after the identification and isolation of numerous cases at the end of the September 258 surge (Figure 2 f, h) and is notable when isolation building inputs are excluded from the wastewater 259 concentration data. 260

Well after the expiration of those public health orders, another increase in wastewater concentrations was 261 Both the SURV1 data and the SENB+ data reflected the medical services data throughout the campaign 271 (Figure 2 b, d; Supplemental Tables 8, 9) . Overall, the data from the SURV1 and SENB+ pipelines are of wastewater) was also similar for both targets. The E target, however, reported fewer non-detects and thus 282 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint 13 displayed a higher sensitivity than the N2 target. The E target was therefore utilized as the primary dataset 283 considered daily, with the N2 target serving a confirmatory function. 284

Relating the concentration of SARS-CoV-2 RNA in wastewater to the medical services data was 285 importantly influenced by the isolation strategy used on campus. The majority of positive individuals 286 received temporary housing in the primary isolation building up until September 18 th and after October 6 th 287 and were assigned to a secondary building between September 18 th and October 5 th (Figure 3) . However, 288 select students were allowed to isolate in place (structures A and B). Isolation in these alternate structures 289 complicated the signal in their associated wastewater flows as well as in the combined G(FEDCBA) flow 290 (the E2(CBA) flow is not noted given the sampler serving that structure primarily operated after October 291 5 th ). Additionally, such combined flows bias the median data (Figure 2 a) November at approximately 10 7 SARS-CoV-2 copies/L wastewater (Figure 3) . These peaks resulted from 305 the co-occurrence of disease progression and virus/viral RNA shedding in stool, explaining the two peaks' 306 nearly identical wastewater concentrations despite substantially different infected resident numbers. In this 307 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. produce between 100-1,000 mL of feces per day (5×10 3 -10 7.6 copies/mL feces) (57). The campus 318 additionally relied on a secondary isolation building during the peak of infections in September (Figure 3) . 319

Notably, this structure displayed a similar maximum SARS-CoV-2 wastewater concentration. 320

The concentration of fecal matter becomes more critical when considering wider communities with 321 industrial, infiltration, and other diluting contributions to wastewater. In initial attempts to normalize to the 322 varying concentrations of fecal matter within the wastewater samples, the genogroup II F+ bacteriophage 323 was selected as an internal reference marker for the fall campaign to align with other sampling efforts 324 ongoing within Colorado. At the micro-sewershed level, the F+ bacteriophage signal displayed inconsistent 325 geographical and temporal trends (Figure 4) . Select sites (e.g., R, Q, and O) displayed consistently low 326 signals, within the range of 10 4 to 10 6 copies/L, whereas other sites (e.g., G(FEDCBA), J, and L(Admin)) 327 displayed signals often approaching 10 9 copies/L. Even more concerning, sites such as C, F, H, M, and N 328 display inconsistent temporal trends, fluctuating over five orders of magnitude during the fall campaign. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Additionally, clinical testing data later in the semester identified cases with low viral loads without an active 350 infection, highlighting cases in which progression through the disease profile occurred off campus. Finally, 351 during scenario (6), wastewater data also effectively monitors individuals as they exit the infectious period 352 but may still be shedding viral RNA. On campus, students were permitted to leave the isolation structure 353 and return to their residences after ten days. These reentry events could be detected in the wastewater (e.g., 354 see site O, Figure 2) . Reentries thus must also be taken into consideration to prevent shifts in policy based 355 on a true detected signal that is not reflective of a case of concern. 356 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. valuable feedback into the design and operation of the campaign. Funding for this project was provided by 380 the CARES Act, administered by the Office of Equity, Compliance, and Integrity at the University of 381 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The supporting tables contain the sample location details, component list for the sampler design, daily mass 388 of wastewater collected, daily wastewater pH, daily wastewater total suspended solids (TSS), concentration 389 of total RNA extracted, primers and probes used in the SENB+ multiplex, SURV1 RT-qPCR Ct data, 390 SENB+ RT-qPCR concentration values, processing data required to back-calculate to copies per L of 391 wastewater, medical services determined positives per manhole, and residency within isolation structures. 392

The supporting figures contain the schematic of the sampler design, daily wastewater mass, daily 393 wastewater pH, daily wastewater TSS, processing controls, standard curves, extraction blanks, bovine 394 coronavirus recovery, and comparison between the nucleocapsid (N) and envelope (E) targets. A 395 supplemental compressed file contains the required script and files to generate the presented data analysis 396 and statistical graphics. 397 All rights reserved. No reuse allowed without permission.

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(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted May 26, 2021. ; https://doi.org/10.1101/2021.05.24.21257632 doi: medRxiv preprint