A new study posted to the medRxiv* preprint server explores environmental surveillance of elementary school settings for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through wastewater and surface samples monitoring. The researchers demonstrated that 93% of the COVID-19 cases in public elementary schools could be identified using this method.
Coronavirus disease 2019 (COVID-19) pandemic, caused by SARS-CoV-2, globally shut down institutions, places of work, and businesses, either in a phased manner or entirely, depending on the government’s policy and guidelines. Based on mitigation strategies and vaccine rollouts for adults, the safe reopening of places is determined by the spread of disease in the country and the number of cases of infection.
Reopening schools and keeping them operational during the COVID-19 pandemic is a public health challenge. Schools need to be reopened for in-person education, which is essential for the children’s social, physical, and emotional wellbeing. Schools also enable parental workforce participation by providing essential childcare. Loss of jobs resulting in poverty due to school closures can also be avoided.
Unvaccinated children, however, are at high risk of SARS-CoV-2 exposure in school settings as they spend extended periods with each other in close proximity, typically indoors. As a result, functioning schools become potentially high-risk environments for virus transmission.
Besides masking, improved ventilation, and symptom screening, strategies to rapidly identify COVID-19 cases in communities with low vaccination coverage and testing rates are also needed in order to achieve health equity, reduce morbidity and mortality, and prevent the emergence of new variants of concern.
Recently, wastewater surveillance through genome-sequencing has gained attention as a tool for passive surveillance of community-level SARS-CoV-2 infections. In a previous report, large-scale wastewater monitoring allowed a sizeable residential university to identify cases in specific campus buildings and residential halls. This information helped increase diagnostic testing uptake among the residents.
Similarly, this passive nature of wastewater sampling is promising for school COVID-19 surveillance in communities where students, parents, and staff work - who may face structural barriers to vaccinate and undertake diagnostic testing.
To monitor and detect COVID-19 cases in environments such as elementary schools and childcare settings, the present study utilizes wastewater and daily surface samples in a project Safer At School Early Alert (SASEA).
The SASEA consists of four primary components:
- Daily environmental sampling for SARS-CoV-2 using wastewater from the whole site and surface swabs (typically the center of a classroom floor) from individual classrooms;
- Notification of results - rapid results reporting to administrators via email (approximately 30 hours after sample collection);
- Responsive testing: On-site diagnostic testing of students and staff when SARS-CoV-2 was detected in wastewater or surface samples; and
- Risk mitigation via environmental modification (e.g., moving classes outdoors, increasing ventilation in classrooms with a potential case) and health communication (e.g., encouraging double masking, recommending wider testing among household members).
The researchers undertook surface sampling and recovered traces of viral RNA in rooms occupied by infected individuals in a hospital setting, suggesting that surface sampling can provide a complementary approach to wastewater viral monitoring.
About the Study
The project SASEA was piloted in nine public elementary schools in San Diego County during the 2020-2021 academic year. The researchers conducted daily wastewater monitoring at each site and collected surface sampling for testing from each classroom where children were present. Further, to validate the environmental monitoring system, they also provided weekly diagnostic testing for all consenting students and staff on campus and used the results to correlate with the data from wastewater or surface samples.
For the collection of the wastewater samples, the researchers employed autosamplers deployed above ground at sewer cleanouts and manholes. They were programmed to sample every 10-15 minutes over a seven-hour interval.
Over the 12-week study period, the researchers collected data in approximately 50 school days per site and detected SARS-CoV-2 in surface samples and wastewater samples. Correlating with the on-campus test results, the researchers reported that, of the 89 identified on-campus SARS-CoV-2 positive cases, 83 (93%) were associated with positive wastewater or same-room surface sample in the 7-day window preceding the individual’s last day on campus. The majority of these, 76%, were associated with a positive wastewater sample.
Similarly, in a single classroom, 40% of the cases corresponded with a positive surface sample in the associated room. While 67% of the cases were associated with a positive wastewater sample alone.
The researchers observed testing uptake within SASEA partner schools was higher than in nearby districts.
Importantly, in addition to tracking the viral prevalence in a given community, the viral genome sequencing of positive wastewater samples can elucidate strain geospatial distributions - thereby identifying outbreak clusters and tracking prevailing/newly emerging variants.
Wastewater and surface sampling and 95% confidence interval across full 12-week pilot period, and with consent at 70% or above (weeks 9-12)
The sequencing of the positive environmental samples yielded results that confirmed the presence of the Alpha variant (B.1.1.7) and the Epsilon variant, which were also confirmed in the diagnostic testing (nasal swabs).
One SARS-CoV-2 genome sequenced from a carpeted floor surface was associated with a genome from a SASEA clinical testing sample via clustering in a phylogenetic tree. The researchers suggested that surface sampling provides higher spatial resolution than wastewater sampling alone.
Limitations of passive wastewater surveillance in school settings
In a non-residential setting, two significant concerns about the potential effectiveness of wastewater sampling are that 1) not all individuals have daily bowel movements on site to shed the virus, and 2) the spatial resolution is limited to entire buildings or building clusters because of sewer access locations.
The findings from this study suggest that environmental surveillance via wastewater and surface sampling can be an effective passive screening tool to complement and potentially enhance individual testing approaches.
Ninety-three percent of on-campus COVID-19 cases in public elementary schools are associated with either a wastewater or surface sample.
In addition, the study showed that 67% were associated with a positive wastewater sample, and 40% were associated with a positive surface sample.
Notably, positive samples can be sequenced to monitor for variants of concerns with neighborhood-level resolution.
The researchers write that even in the absence of a diagnosed case, positive environmental samples serve as a behavioral cue to increase or re-implement risk mitigation measures in a classroom or entire school.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
- Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project, Rebecca Fielding-Miller, Smruthi Karthikeyan, Tommi Gaines, Richard S. Garfein, Rodolfo Salido, Victor Cantu, Laura Kohn, Natasha K Martin, Carrissa Wijaya, Marlene Flores, Vinton Omaleki, Araz Majnoonian, Patricia Gonzalez-Zuniga, Megan Nguyen, Anh V Vo, Tina Le, Dawn Duong, Ashkan Hassani, Austin Dahl, Samantha Tweeten, Kristen Jepsen, Benjamin Henson, Abbas Hakim, Amanda Birmingham, Adam M. Mark, Chanond A Nasamran, Sara Brin Rosenthal, Niema Moshiri, Kathleen M. Fisch, Greg Humphrey, Sawyer Farmer, Helena M. Tubb, Tommy Valles, Justin Morris, Jaeyoung Kang, Behnam Khaleghi, Colin Young, Ameen D Akel, Sean Eilert, Justin Eno, Ken Curewitz, Louise C Laurent, Tajana Rosing, SEARCH, Rob Knight, medRxiv 2021.10.19.21265226; doi: https://doi.org/10.1101/2021.10.19.21265226, https://www.medrxiv.org/content/10.1101/2021.10.19.21265226v1