COVID-19 wastewater surveillance in rural communities: Comparison of lagoon and pumping station samples

8 Wastewater-based epidemiology/wastewater surveillance has been a topic of significant interest over the last 9 year due to its application in SARS-CoV-2 surveillance to track prevalence of COVID-19 in communities. Although 10 SARS-CoV-2 surveillance has been applied in more than 50 countries to date, the application of this surveillance has 11 been largely focused on relatively affluent urban and peri -urban communities. As such, there is a knowledge gap 12 regarding the implementation of reliable wastewater surveillance in small and rural communities for the purpose of 13 tracking rates of incidence of COVID-19 and other pathogens or biomark ers. This study examines the relationships 14 existing between SARS-CoV-2 viral signal from wastewater samples harvested from an upstream pumping station and 15 from an access port at a downstream wastewater treatment lagoon with the community’s COVID-19 rate of incidence 16 (measured as percent test positivity) in a small , rural community in Canada. Real -time quantitative polymerase chain 17 reaction (RT-qPCR) targeting the N1 and N2 genes of SARS -CoV-2 demonstrate that all 24-hr composite samples 18 harvested from the pumping station over a period of 5.5 weeks had strong viral signal, while all samples 24-hr composite 19 samples harvested from the lagoon over the same period were below the limit of quantification. RNA concentrations 20 and integrity of samples harvested from the lagoon were both lower and more variable than from samples from the 21 upstream pumping station collected on the same date, indicating a higher overall stability of SARS -CoV-2 RNA 22 upstream of the lagoon. Additionally, measurements of PMMoV signal in wastewater allowed to normalize SARS-CoV-23 2 viral signal for fecal matter content, permitting the detection of actual changes in community prevalence with a high 24 level of granularity. As a result, in sewered small and rural communities or low-income regions operating wastewater 25 lagoons, samples for wastewater surveillance should be harvested from pumping stations or the sewershed as opposed 26 to lagoons. 27 28

wastewater treatment lagoon; SARS -CoV-2; wastewater-based epidemiology; wastewater surveillance; 29 COVID-19; pepper mild mottle virus 30 31 32 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 3 1. Introduction 33 In late 2019, cases of COVID-19 began to spread rapidly internationally (Li et al., 2020) . It became clear to 34 public health officials across the world that this new disease, caused by the severe acute respiratory synd rome 35 coronavirus 2 (SARS -COV-2) (Eurosurveillance Editorial Team, 2020) , was rapidly becoming a pandemic-potential 36 pathogen due to its relatively low virulence but high degree of infectiousness (He et al., 2020). More than a year after 37 the first cases of COVID-19, the world is still grappling with the disease and newer and more infectious variants of the 38 virus are spreading (Duong, 2021; Galloway et al., 2021; Volz et al., 2020; Walensky et al., 2021), causing widespread 39 disease and death (WHO COVID-19 Dashboard https://covid19.who.int/). At the time of writing (May 20th, 2021), more 40 than 2.4% of the global population (191.1 M) has been infected by SARS-CoV-2, and 2.1% of those infected have died 41 (4.1 M) (WHO COVID-19 Dashboard). 42 Now widely applied in over 1,000 sites in more than 50 countries worldwide (Ahmed et al., 2020; Arora et al., 43 2020; Bivins et al., 2020b; D’Aoust et al., 2021a; Gonzalez et al., 2020; Mao et al., 2020; Medema et al., 2020; Naughton 44 et al., 2021; Polo et al., 2020; Randazzo et al., 2020; Sims an d Kasprzyk-Hordern, 2020; Thompson et al., 2020) , 45 Wastewater surveillance (WWS) efforts conducted with RT-qPCR are underway around the world, focused primarily in 46 larger metropolitan areas of higher income countries (Bivins et al., 2020b) . By and large rural communities and low-47 income countries have not had the same services afforded to them as urban and peri -urban communities (WEF 48 Network of Wastewater-Based Epidemiology, 2021) and higher income countries, which is based on numerous factors 49 that include but are not limited to: i) discrepancies in financial and material resources, ii) distance to research, academic 50 and governmental facilities capable of carrying out the analyses and iii) capacity of the local public health unit to take 51 in the results and act upon them. Furthermore, smaller, rural communities and low-income countries without larger 52 mechanical water resource recovery facilities may not have the staff, equipment or expertise to carry out sampling for 53 SARS-CoV-2 viral detec tion in wastewater (Haider et al., 2016; Naughton et al., 2021; Switzer et al., 2016) . Larger 54 facilities are often equipped with automatic composite samplers throughout the plant, making the implementation of a 55 WWS monitoring program in comparison relatively easy for routine purposes. Furthermore, there is a growing 56 consensus that higher concentrations of SARS-CoV-2 viral particles are found in wastewater solids (Chik et al., 2021; 57 D’Aoust et al., 2021b; Graham et al., 2020; Peccia et al., 2020; Pecson et al., 2021) and as such several WWS efforts 58 are now focusing on measuring signal from solid fractions of samples (Chik et al., 2021; Wolfe et al., 2021) . In small 59 and rural communities, harvesting solids may be p roblematic as d edicated solid separation units present in l arger 60 facilities located in urban and peri -urban communities may not exist in smaller facilities, requiring different sampling 61 approaches. Unfortunately, the limited resources available in small an d rural communities or lower income countries 62 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 4 often compromise the WWS efforts. The communities may in turn be at the mercy of funding or mandate s due to the 63 lack physical, material and/or financial resources. As an example of the precariousness of WWS in smaller 64 communities, Finnish authorities recently announced in June 2021 that they would -be discontinuing SARS -CoV-2 65 WWS efforts in cities with populations smaller than 150,000 (Finnish institute for health and welfare, 2021). In contrast, 66 remote communities in the Northwest Territories of Canada have implemented wastewater surveillance to monitor the 67 communities for COVID-19 viral signal (Government of Northwest Territories, 2021), despite the low population of the 68 geographic area (<45,000). Having clear guidelines, appropriate analytical methods and lo w-cost strategies for 69 surveillance which are also applicable for smaller communities will therefore be critical to ensure that WWS efforts 70 service the most residents in each region. 71 Most WWS efforts attempt to predict trends of epidemiological metrics of COVID-19 in the general population 72 by quantifying increases and decreases in the rates of clinical cases of COVID-19 (Bivins et al., 2020a; D’Aoust et al., 73 2021a; Hill et al., 2020; Kumar et al., 2021; Polo et al., 2020). These environmental studies will often focus on collecting 74 samples within the raw influent or primary sludge due to the relatively high concentration of solids in these wastewater 75 streams (Hill et al., 2020). However, several municipalities operating smaller types of treatment systems such as waste 76 stabilization ponds, also known as wastewater treatment lagoons, do not have direct access to raw influent or primary 77 sludge. Smaller communities may however have direct access to the waste stabilization ponds and pumping/lift stations 78 (MOE Ontario, 2008). Wastewater treatment lagoons are commonly used in the world, with over 1,200 in operation in 79 Canada (Statistics Canada, 2016) , over 5,500 in Europe (Mara, 2009), and over 8,000 in the United States alone 80 (USEPA, 2011). Solids separation occurs in lagoons due to the slowing of flow velocities, leading to particle settling, 81 particularly in the same area of the lagoon that oxidizes carbonaceous deleterious substances or in lagoon areas or 82 isolated lagoon units designed specifically for solids sedimentation (Asano et al., 2007; D’Aoust et al., 2021c; Leblond 83 et al., 2020). As such, harvesting of wastewater solids in lagoon treatment systems with the goal of performing WWS 84 is very difficult due to potentially long retention times in lagoons, the degradation of RNA targets due to environmental 85 temperature fluctuations and the difficulty of collecting “fresh” solids from a lagoon representing current incidence of 86 COVID-19 in the community. Furthermore, as lagoon syst ems are located outdoors and exposed to ambient 87 temperatures, in locales where air temperatures can dip below freezing these systems may become difficult to sample 88 due to the presence of ice-cover. High temperatures during summer months and UV radiation fr om sunlight may also 89 further degrade viral RNA (Verbyla et al., 2017) . As a result, smaller communities may not have evident sampling 90 locations to collect wastewater samples containing SARS-CoV-2 viral particles which can accurately represent changes 91 in prevalence of the disease in the communi ty. Another factor easing the implementation of WWS programs in small 92 and rural communities is to see if the community is sewered or not. In communities that are not sewered and where 93 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 5 centralized sampling points are not available, sewage brought to lagoons can be sampled from sewage and sludge 94 trucks while they are being emptied at the facility (Telliard, 1989). 95 In preparation for applying SARS-CoV-2 wastewater surveillance initiatives in a small sewered community in 96 Eastern Ontario (Canada), wastewater samples were collected from an access/sampling point situated between the 97 first and second cells of a lagoon treatment system , and from the last pumping station on the sewer network located 98 upstream of the lagoon treatment system. The specific objectives of this study were to: i) compare SARS-CoV-2 signal 99 at both sampling locations for strength of the RNA viral signal and RNA integrity and ii ) compare the higher integrity 100 longitudinal SARS-CoV-2 signal to existing community epidemiological data to ascertain the ability of WWS to track 101 and predict and correlate with trends in rates of incidence of COVID-19 in small and rural communities. 102 2. Experimental methods 103 Rural community sampling locations 104 The wastewater of a rural community of less than 5,000 inhabitants in Eastern Ontario (Canada) were sampled 105 in this study between October 2020 and May 2021 (Figure 1). The rural community is sewered , with the wastewater 106 flowing into the main pumping station located 1.3 km upstream of a wastewater treatment lagoon. The lagoon system 107 consists of 3 cells/ponds (total surface area of approximately 182,000 m 2) operated in-series that flow from cell #1 to 108 #2 to #3. The lagoon receives continuous inflow with an average daily flow rate of 2,110 m 3/d. The lagoon system 109 discharges to a nearby river twice annually, in Spring (Mar. 7th to May 15th) and Fall (Oct. 1st to Dec. 19th). The lagoon 110 system does not include a wetland component. Cell #3 has bottom -mounted aerators that are engaged prior to and 111 during discharge to strip hydrogen sulfide before the release of treated wastewater to the natural environment. To 112 control phosphorus concentrations in the final effluent of the lagoon treatment facility, a polyaluminum sulphate solution 113 is injected directly into the pressurized wastewater pipe following the pumping station (force main) immediately before 114 being released to the first cell of the lagoon system. The yearly average treatment efficiency of cBOD5, total suspended 115 solids, total phosphorus, total ammonia nitrogen, total Kjeldahl nitrogen and alkalinity is of 96.0%, 94.9%, 98.0%, 116 96.9%, 94.1% and 64.6% removal efficiency, respectively. 117 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 6 Two locations were sampled for wastewater in the rural community : i) the upstream pumping station, which 118 receives the same annual volumetric flow of wastewater as the wastewater treatment lagoon system itself, and ii) an 119 access/sampling point situated between cells 1 and 2 of the lagoon treatment system (Figure 1). The wastewater travel 120 time between the pumping station and the inlet of the lagoon is approximately 15 minutes, while the residence time of 121 the wastewater at the sampling location between the two cells of the lagoon ranges significantly due to the annual 122 discharge design of the system (approximated residence times rang ing between 80 hours and 10 days during the 123 period of the study). The typical wastewater characteristics at the pumping station and at the lagoon effluent are shown 124 in Table 1. 125 126 127 Lagoon sampling point Figure 1: Sampling locations and configurations: a ) geographic locations of pumping station and lagoon, b ) lagoon treatment system consisting of three cells, identification of sampling point, c ) automatic sampler at pumping station, sampler dispenses samples into refrigerator, and d ) automatic sampler under the solar panel at lagoon sampling point and sampling point. Lagoon Pumping station a) b) d) c) Automatic sampler location Sampling point . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 7 Table 1. Yearly average wastewater characteristics at the pumping station and lagoon effluent. 128 Yearly average pumping station wastewater characteristics (avg. ± standard dev.) Yearly average pumping lagoon wastewater characteristics (avg. ± standard dev.) cBOD5 (mg/L) 88.4 ± 80.3 3.5 ± 0.9 Total suspended solids (mg/L) 224.3 ± 154.1 11.4 ± 6.1 Total phosphorus (mg P/L) 8.0 ± 5.6 0.2 ± 0.1 Total ammonia nitrogen (mg N/L) 34.2 ± 10.5 1.1 ± 1.1 Total Kjeldahl nitrogen (mg N/L) 49.0 ± 20.9 2.9 ± 2.2 Alkalinity (mg/L as CaCO3) 356.2 ± 60.4 126.2 ± 34.0 129 Sample collection 130 At the pumping station, 24-hr composite samples of wastewater were collected every 3 to 7 days from October 131 16th, 2020, to May 2nd, 2021, using an ISCO 6700 series automatic sampler (Teledyne ISCO, Lincoln, NE, USA). The 132 autosampler located at the pumping station pumped the wastewater into a storage container located inside an adjacent 133 refrigerator to maintain the samples at 4°C until collection (within 24 hours). At the lagoon sampling point , 24 -hr 134 composite samples of wastewater were also collected every 3 to 7 days from Dec ember 3rd, 2020, to January 11 th, 135 2021. The autosampler located at the lagoon pumped the wastewater into a sealed bottle in an insulated foam container 136 located adjacent to the autosampler. Outdoor temperatures at the lagoon during the study period (Dec. 3r d, 2020, to 137 Jan. 11th, 2021) oscillated between -5.5°C and 1.3°C, hence allowing safe preservation of the samples between 138 sampling and collection without additional refrigeration being required. composite samples were comprised of twenty-139 four 50 mL aliquot s. During the pairwise comparison of both locations from Dec. 3rd, 2020, to Jan. 11th, 2021), t he 140 automatic samplers were programmed to collect samples at the same time at both locations. After every sampling cycle 141 ended, the composite samples were collected and were transported on ice to the laboratory for analysis. Once in the 142 laboratory, samples were concentrated immediately, and the result ing pellets were frozen at -30°C and processed 143 within 14 days. After January 11th, site access became difficult due to low outdoor temperatures, freezing of the lagoon, 144 and snowing conditions, making access to the automatic sampler highly difficult, which led to the cessation of sampling 145 at the lagoon. 146 Sample concentration, extraction, and PCR quantification 147 The composite samples were concentrated by allowing the samples to settle at 4°C for an hour, followed by 148 the decantation of the supernatant to isolate the settled solids fraction. 40 mL of remaining solid fraction was then 149 transferred to a 40 mL centrifuge tube and samples were then centrifuged for 45 mins at 10,000 x g at 4°C to isolate 150 the centrifuged pellet. Sample pellets which could not be immediately processed were frozen at -30°C for a period of 151 up to 14 days before being extra cted. RNA was extracted and purified from the resulting pellet using the RNeasy 152 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 8 PowerMicrobiome kit (Qiagen, Germantown, MD, USA) using a QIAcube Connect automated extraction platform, with 153 the protocol modifications specified in an earlier study (D’Aoust et al., 2021b). The SARS-CoV-2 signal in the samples 154 was assayed using a singleplex one -step RT-qPCR targeting the N1 and N2 gene regions of SARS-CoV-2 genome. 155 The signal of pepper mild mottle virus (PMMoV) was also measured in each of the samples (samples were diluted 1/10 156 for measurements of PMMoV). In each PCR reaction, the reaction mix consisted of 1.5 µl of RNA template, 500 nM of 157 each of forward and reverse primer (IDT, Kanata, Canada) in 4x TaqMan® Fast Virus 1-step Mastermix (Thermo-Fisher, 158 USA) with 125 nM probe (IDT, Kanata, Canada) in final volume of 10 µl. The samples were run in triplicates with non -159 template controls and were quantified using a five-point gradient of the EDX SARS-CoV-2 COV-19 RNA standard 160 (Exact Diagnostics, USA). Reverse transcription (RT) was performed at 50°C for 5 minutes followed by RT inactivation 161 and initial denaturation at 95°C for 20 seconds. This was followed by 45 cycles of denaturation at 95°C for 3 seconds 162 and annealing/extension at 60°C for 30 seconds with a CFX Connect qPCR thermocycler (Bio-Rad, USA). The assay 163 limit of detection (ALOD, ≥95% detection) was assessed (D’Aoust et al., 2021b) and determined to be approximately 2 164 copies/reaction for both N1 and N2 SARS-CoV-2 gene targets. The assay limit of quantification (ALOQ, CV=35%) was 165 determined to be approximately 3.2 copies /reaction for N1 and 8.1 copies/reaction for N2 SARS-CoV-2 gene targets. 166 SARS-CoV-2 N1 and N2 gene region viral signals were normalized by dividing the N1 and N2 gene copies per reaction 167 by the PMMoV gene copies per reaction, as a means of normalizing the N1 and N2 signal by the quantity of fecal matter 168 in the sample (D’Aoust et al., 2021b, 2021a; Graham et al., 2020; Kitajima et al., 2018). Vesicular stomatitis virus (VSV) 169 was used as an internal control to monitor the efficiency of the viral concentration and extraction processes and was 170 spiked into the sample prior to extraction. The extraction efficiency quantified with the VSV spike -in was between 3 -171 4.5%. All samples were checked for inhibition by diluting the samples by a factor of 4 and 10 and measuring the 172 corresponding drop in signal of PMMoV. 173 Assessment of RNA Integrity 174 Samples were analysed for RNA integrity using an Agilent 2100 Bioanalyzer. RNA (2 µL) of each sample was 175 loaded on an RNA 6000 Pico Chip (#5067 -1513). Data analysis and RNA concentration calculations were performed 176 using Agilent’s proprietary 2100 Expert software (version B.02.10.SI764). 177 Collection of epidemiological data and correlation to wastewater viral signal 178 Weekly e pidemiological data was obtained from the ICES COVID -19 dashboard 179 (https://www.ices.on.ca/DAS/AHRQ/COVID-19-Dashboard) and the Eastern Ontario Health Unit (EOHU) dashboard 180 (https://eohu.ca/en/covid/covid-19-status-update-for-eohu-region). Correlation analyses were then performed between 181 the PMMoV-normalized SARS-CoV-2 viral signal in wastewater and the available epidemiological data. 182 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 9 . 183 3. Results & discussion 184 During the pairwise comparison of samples collected from both locations at the same time-point, all samples 185 (5/5) from the pumping station showed detectable signal for the N1 and N2 gene regions of SARS -CoV-2 (Figure 2), 186 as well as for PMMoV. Measurements of viral signal for the N1 gene region of the samples collected from the pumping 187 station ranged from 5.5 x 10 3 - 4.6 x 10 4 genomic copies/L while measurements for the N2 gene region ranged from 188 4.3 x 10 3 – 3.2 x 10 4 genomic copies/L. Meanwhile, all composite samples collected at the lagoon sampling point 189 between cells #1 and #2 of the lagoon were below the ALOQ and the ALOD for the N1 and N2 gene , and 4 out of 5 190 samples had no detectable SARS-CoV-2 viral signal altogether. During the same short span of side-by-side test period, 191 PMMoV was only observed in three of the five lagoon samples. 192 In samples collected from the pumping station, measurements of PMMoV ranged from 1.4 x 10 5 – 4.8 x 106 193 genomic copies/L, and in lagoon samples with PMMoV measurements, the PMMoV concentration ranged from 6.9 x 194 102 – 9.9 x 105 genomic copies/L. The lack of PMMoV signal in some of the l agoon samples could potentially signify 195 that near complete RNA degradation of PMMoV RNA occurred in the lagoon. When comparing viral signal 196 measurements from the RT-qPCR analyses for the N1 and N2 SARS -CoV-2 gene regions and PMMoV between the 197 pumping station and lagoon samples, pairwise comparisons clearly outline a stronger detection of both SARS-CoV-2 198 N gene regions and PMMoV viral signal in the samples collected from the pumping station (Figure 2). Furthermore, 199 due to the ubiquity of PMMoV in wastewater, observing PMMoV measurements may allow to distinguish SARS-CoV-2 200 N1 and N2 gene region true non-detects from false-negatives caused by sample degradation or severe inhibition of the 201 sample (Hong et al., 2021). 202 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 10 RNA of the SARS-CoV-2 and PMMoV targets in samples collected from the sampling location in the lagoon 203 may have experienced more degradation due to extended residence times within the lagoon . Although temperature 204 and storage time have been shown to affe ct SARS-CoV-2 viral signal degradation in wastewater (Hart and Halden, 205 2020), the similar storage temperature of the pumping station and lagoon samples during the pairwise study along with 206 the short storage time until analysis enable this study to isolate the difference in signals to the conditions of the two 207 sampling locations. Furthermore, due to the low temperature of the wastewater in the pumping station and within the 208 lagoon during the study, viral degradation due to elevated temperatures is not a likely pathway of degradation. It is also 209 possible that the RNA of the samples in the lagoon may have been subject to UV degradation once within the lagoon 210 itself (Fongaro et al., 2012; Verbyla et al., 2017) . Furthermore, as SARS-CoV-2 viral particles are believed to likely 211 partition preferentially to wastewater solids in typical wastewater conditions (Arora et al., 2020; Chakraborty et al., 2021; 212 0 20000 40000 60000 80000 N1 genomic copies/L Dec. 3, 2020 Dec. 6, 2020 Dec. 10, 2020 Dec. 13, 2020 Jan. 11, 2021 LagoonPumping station N.D. N.D. N.D. N.D. * 0 2×106 4×106 6×106 PMMoV genomic copies/L Dec. 3, 2020 Dec. 6, 2020 Dec. 10, 2020 Dec. 13, 2020 Jan. 11, 2021 N.D. N.D.N.D. N.D. 0 20000 40000 60000 80000 N2 genomic copies/L Dec. 3, 2020 Dec. 6, 2020 Dec. 10, 2020 Dec. 13, 2020 Jan. 11, 2021 N.D. N.D. N.D. N.D. * Figure 1: Comparison of genomic copies/L of pumping station samples and waste stabilization pond samples over time for the N1 and N2 SARS -CoV-2 gene regions, and PMMoV. Bars with a star (*) indicate that the sample signal was below the ALOQ. . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 11 D’Aoust et al., 2021a; Graham et al., 2020; McLellan et al., 2021), a significant portion of the viral RNA may have settled 213 throughout the first lagoon cell as the flow velocity of the wastewater immediately decreases upon entering the lagoon 214 system’s first cell. Additionally, this facility doses polyaluminum sulphate for phosphorus abatement , which likely 215 contributes to a more rapid and pronounced settling of solids . It is believed that the polyaluminum may also help 216 flocculate SARS -CoV-2 genetic material , as evidenced by several studies employing aluminum -driven flocculation 217 concentration methods (Barril et al., 2021; Randazzo et al., 2020) . It is noted that all mechanisms contributing to 218 potential degradation of viral signal in the lagoon are symptomatic of treatment of wastewater in the lagoon. Further 219 investigations with a control location wh ich does not use polyaluminum sulphate could be conducted to verify this 220 hypothesis. 221 Total RNA concentrations were measured in a series of samples collected from the pumping station and the 222 lagoon sampling point. Results of the analyses are shown in Figure 3. RNA concentrations are distinctly lower in lagoon 223 samples as compared to pumping station samples. This is likely due to the presence of less fecally-associated biological 224

or greater degradation in the material collected in the samples collected in the lagoon. 225 The epidemiological data pertaining to this study were not available at the granulation of the studied 226 community itself (pop.: ~4,000; ~5 km2), but rather for a larger geographical region (pop.: ~200,000; ~5,300 km2) that 227 includes the community. The lack of available epidemiological data for the small community itself is indicative of the 228 need for additional resources for small, rural communities and the potential for the application of WWS in these 229 communities as an effective indicator of incidence of infections at the granulation of the community. Further, the clinical 230 metric that was available at the geographic region level was percent positivity as opposed to daily clinical new cases. 231 As such, this study compares the SARS-CoV-2 viral signal in wastewater to the percent positivity data acquired at the 232 20 40 60 0 400 800 1200 1600 Time (s) Fluorescence units (FU) Dec 3, '20 Dec 6, '20 Dec 13, '20 Avg. RNA conc.: 1.4 ± 1.2 x 103 pg/µL 20 40 60 0 400 800 1200 1600 Time (s) Fluorescence units (FU) Dec 3, '20 Dec 6, '20 Dec 13, '20 Avg. RNA conc.: 9.6 ± 2.7 x 103 pg/µL Figure 2: Electropherograms of samples from the a) pumping station and the b) lagoon, showing drastic differences in the RNA profiles. a) b) . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 12 geographic region. The studied rural community ( 2,500-5,000 people) represents approximately 2% of the whole 233 population within the health unit’s geographical boundaries for which epidemiological data are available. Although travel 234 between communities in this geographic area is common, it is noted that presentation of the community SARS-CoV-2 235 viral signal against the epidemiological data at the geographic region level assumes that this town and its citizens 236 behave similar to the residents of the larger region, which may not necessarily be a correct assumption. However, due 237 to the limitations of available epidemiological information no other data were available to perform a comparison. As 238 outlined by these results, it appears that samples harvested from the pumping station of the community could provide 239 similar viral signal trends to the clinical data sets, making the pumping station a suitable sampling location for rural 240 communities that are serviced by wastewater treatment lagoons. It is hypothesized that samples collected from the last 241 pumping station of a smaller rural community will have similar usability for wastewater surveillance to samples collected 242 from influent of a larger mechanical wastewater treatment plant. 243 When comparing the pumping station sample s expressed as PMMoV-normalized viral genomic copies, viral 244 genomic copies per gram of wastewater solids and viral genomic copies per L to available epidemiological data (clinical 245 test percent positivity for the whole popul ation) (Figure 4), a degree of visible agreement could be seen between the 246 SARS-CoV-2 viral signal in wastewater and the reported percent positivity in the geographic region. However, this 247 comparison may not be of significant relevance as the clinical data references a larger geographical zone than the 248 sampled sewershed. It has been outlined in several studies that mass or volumetric normalization of SARS-CoV-2 viral 249 signal alone may not truly capture sewershed dilution effects (Bivins et al., 2021; D’Aoust et al., 2021b; Wu et al., 2020). 250 Furthermore, it is believed that while not observed or demonstrated with solid mass (copies/g) or volume (copies/L) 251 normalized SARS-CoV-2 viral genomic copies, PMMoV -normalized viral genomic copies show a true change in 252 community prevalence as the normalization with PMMoV helps account for the intrinsic quantity of fecal material in the 253 wastewater (Graham et al., 2020; Kitamura et al., 2021; Wolfe et al., 2021; Wu et al., 2021) . PMMoV normalization in 254 WWS applications is believed to be particularly important in the context of surveillance of fecally shed pathogens as it 255 allows to call true localized changes in prevalence which could otherwise be missed without normalizing for the quantity 256 of fecal material in wastewater. 257 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 13 258 0.00 0.01 0.02 0.03 0.04 0.05 0 3 6 9 12 15 18 Date N1-N2 average copies/copies PMMoV Weekly clinical test percent positivity (%) Oct 30, '20 Nov 13, '20 Nov 27, '20 Dec 11, '20 Dec 25, 20' Jan 8, 21' Jan 22, '21 Feb 5, '21 Feb 19, '21 Mar 5, '21 Mar 19, '21 Apr 2, '21 Apr 16, '21 Apr 30, '21 Clinical test percent positivity (%) Daily viral signal (Copies/copies PMMoV) 0 4,000 8,000 12,000 16,000 20,000 0 3 6 9 12 15 18 Date N1-N2 average copies/g Weekly clinical test percent positivity (%) Oct 30, '20 Nov 13, '20 Nov 27, '20 Dec 11, '20 Dec 25, 20' Jan 8, 21' Jan 22, '21 Feb 5, '21 Feb 19, '21 Mar 5, '21 Mar 19, '21 Apr 2, '21 Apr 16, '21 Apr 30, '21 Daily viral signal (Copies/g) Clinical test percent positivity (%) 0 30,000 60,000 90,000 120,000 150,000 0 3 6 9 12 15 18 Date N1-N2 average copies/L Weekly clinical test percent positivity (%) Oct 30, '20 Nov 13, '20 Nov 27, '20 Dec 11, '20 Dec 25, 20' Jan 8, 21' Jan 22, '21 Feb 5, '21 Feb 19, '21 Mar 5, '21 Mar 19, '21 Apr 2, '21 Apr 16, '21 Apr 30, '21 Clinical test percent positivity (%) Daily viral signal (Copies/L) a) b) c) Figure 3: Average SARS-CoV-2 signal in the pumping station wastewater samples expressed as a) PMMoV normalized SARS-CoV-2 viral genomic copies, b) SARS -CoV-2 viral copies/g and c) SARS -CoV-2 viral genomic copies/L, along with the weekly COVID-19 test percent positivity. . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 14 4. Conclusions and recommendations 259 As many locations throughout the world have experienced new resurgence in COVID-19 cases due to the 260 rapid spread of infectious variants of concern , i t has become increasingly important for communities to implement 261 effective C OVID-19 wastewater monitoring programs that can rapidly detect and predict upcoming resurgences in 262 COVID-19 cases. WWS programs may provide epidemiological information at a higher level of granularity to public 263 health units than what is currently available in small, rural communities and low-income countries. Unfortunately, such 264 programs are not frequently found in smaller, rural communities or low-income countries, and these communities often 265 rely on low-cost, more passive treatment systems, compounding the gap of knowledge between the application of WWS 266 to high-income, peri-urban and urban communities compared to low -income and rural communities . These smaller 267 communities are particularly vulnerable to changes in funding or mandates as they may not have the resources to take 268 over or start WWS initiatives on their own. 269 In this study, it was observed that i n municipalities with wastewater lagoons, s urveillance of changes in 270 incidence of COVID-19 in the general population is possible via sampling from an upstream pumping station within the 271 sewershed. Measurements of N1 and N2 SARS -CoV-2 gene regions and PMMoV in wastewater demonstrate 272 consistent strong detection in samples collected at the upstream pumping station, but not from samples collected in 273 wastewater treatment lagoons. Preliminary results show that samples collected from the wastewater treatment lagoon 274 dosing polyaluminum sulphate for phosphorus removal demonstrates significant weaker detect ion due to potential 275 preferential partitioning of SARS -CoV-2 viral particles to solids which rapidly settle upon entering the lagoon inlet 276 structure. Furthermore, degradation of SARS -CoV-2 and PMMoV genetic material in the lagoon may be associated 277 with the long retention time of the system. Finally, UV light exposure and degradation of the genetic material may also 278 be a potentially significant mechanism of genetic material degradation. Even though SARS -CoV-2 genetic material is 279 largely attached/associated to solids, the long retention time of the lagoon system may enable UV degradation of the 280 solids partitioned material across a significant period of time. Additionally , it is observed that PMMoV-normalized viral 281 signal may allow for detection of true increases in prevalence by normalizing measurements for the quantity of fecal 282

in wastewater. By observing PMMoV viral signal in wastewater, it may also be possible to distinguish SARS -283 CoV-2 N1 and N2 non-detects from false -negatives caused by sample degr adation or severe inhibition. Finally, it is 284 observed that wastewater -acquired SARS-CoV-2 viral signal from the upstream pumping station can be measured 285 without difficulty and as such, could be used effectively in tandem with local epidemiological data to help detect and 286 track new and existing COVID -19 outbreaks, even where localized increases in COVID -19 prevalence would not be 287 visible with low granularity publicly available weekly regional epidemiological information. 288 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 9, 2021. ; https://doi.org/10.1101/2021.05.01.21256458doi: medRxiv preprint 15 Declaration of competing interests 289 The authors declare that no known competing financial interests or personal relationships could appear to 290 influence the work reported in this manuscript. 291

292 The authors wish to acknowledge the help and assistance of the University of Ottawa, the Ottawa Hospital, 293 the Children’s Hospital of Eastern Ontario, the Children’s Hospital of Eastern Ontario’s Research Institute, Public Health 294 Ontario and all their employees involved in the project. Their time, facilities, resources, and feedback are greatly 295 appreciated. The authors also wish to specifically outline the assistance of Mr. Alain Castonguay. 296 Funding 297 This research was supported by the Province of Ontario’s Wastewater Surveillance Initiative (WSI) . This 298 research was also supported by a CHEO (Children’s Hospital of Eastern Ontario) CHAMO (Children’s Hospital 299 Academic Medical Organization) grant, awarded to Dr. Alex E. MacKenzie. 300 . CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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