Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Abstract

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Keywords: College campus; Maintenance hole; Neighborhood-level monitoring; Random surveillance testing; Saliva testing; Sewer; Wastewater collection system; Wastewater-based epidemiology; Wi-fi data.

Graphical abstract

Fig. 1

SARS-CoV-2 genome copies day⁻¹ in wastewater on individual days across a large U.S. university campus (A), and population normalized viral load (SARS-CoV-2 genome copies L⁻¹ per 1000 people) (B). Note viral loads are the summation of both the major and minor sewer catchment contributions on a given day; Wi-Fi population estimates were not available until mid-September 2020, so population normalized data for this time period are not shown.

Fig. 2

Campus population estimates obtained by using de-identified unique Wi-Fi connections and total on-campus student resident data. Note that only 30% (outlined in brown) of the total residential population was used in the analysis because Wi-Fi captured a portion of those buildings. Each cluster of three bars represents the Monday, Wednesday, and Friday of the sampling week (representative day).

Fig. 3

Relationship between average weekly population normalized viral loads (SARS-CoV-2 genome copies per day per 1000 people) and the percent positive random COVID-19 clinical tests during each week of the Fall 2020 semester at a large U.S. university campus. Relationships are illustrated through (A) chronological trends and (B) linear correlations. Each presented wastewater value is six samples (major and minor catchments collected over three days). Note on the week of 23 November 2020, only one sample was collected due to the holiday and was below the detection limit (nd). The Pearson Correlation Coefficient was r = 0.71 throughout the entire duration of the study (n = 15 comparison, n = 76 wastewater samples).