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Review 1: "Evaluating the Sensitivity of SARS-CoV-2 Infection Rates on College Campuses to Wastewater Surveillance"

Published onMar 10, 2022
Review 1: "Evaluating the Sensitivity of SARS-CoV-2 Infection Rates on College Campuses to Wastewater Surveillance"
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Evaluating the Sensitivity of SARS-CoV-2 Infection Rates on College Campuses to Wastewater Surveillance
Description

AbstractAs college campuses reopen, we are in the midst of a large-scale experiment on the efficacy of various strategies to contain the SARS-CoV-2 virus. Traditional individual surveillance testing via nasal swabs and/or saliva is among the measures that colleges are pursuing to reduce the spread of the virus on campus. Additionally, some colleges are testing wastewater on their campuses for signs of infection, which can provide an early warning signal for campuses to locate COVID-positive individuals. However, a representation of wastewater surveillance has not yet been incorporated into epidemiological models for college campuses, nor has the efficacy of wastewater screening been evaluated relative to traditional individual surveillance testing, within the structure of these models. Here, we implement a new model component for wastewater surveillance within an established epidemiological model for college campuses. We use a hypothetical residential university to evaluate the efficacy of wastewater surveillance to maintain low infection rates. We find that wastewater sampling with a 1-day lag to initiate individual screening tests, plus completing the subsequent tests within a 4-day period can keep overall infections within 5% of the infection rates seen with traditional individual surveillance testing. Our results also indicate that wastewater surveillance can be an effective way to dramatically reduce the number of false positive cases by identifying subpopulations for surveillance testing where infectious individuals are more likely to be found. Through a Monte Carlo risk analysis, we find that surveillance testing that relies solely on wastewater sampling can be fragile against scenarios with high viral reproductive numbers and high rates of infection of campus community members by outside sources. These results point to the practical importance of additional surveillance measures to limit the spread of the virus on campus and the necessity of a proactive response to the initial signs of outbreak.Author SummaryCollege campuses have employed a variety of measures to keep their communities safe amid the SARS-CoV-2 pandemic. Many colleges are implementing surveillance testing programs wherein students are randomly selected to be tested for SARS-CoV-2. These strategies aim to manage the number of infections among the student population by isolating infected individuals. Some colleges are monitoring wastewater on their campuses for signs of the virus, which has been found to be capable of detecting viral RNA. If a wastewater sample shows signs of viral RNA, then screening tests are administered to the individuals who live or work in the buildings that contribute to the sewer in question. We present a model for such wastewater surveillance within a larger model for the spread of SARS-CoV-2 on a college campus. We show that wastewater surveillance can reduce the number of false positive cases and the associated disruptions to student life, while maintaining similar overall numbers of infections. However, we find that surveillance testing strategies that rely solely on wastewater sampling may be less effective if the local transmission rate of the virus is high, or if the rate of infection of members of the campus community by outside sources is high.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.

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Review:

The authors have relied on recent reports of identification of SARS-CoV-2 RNA from wastewater water samples to enhance the well-known Susceptible/Exposed/Infected/Recovered model (a modification of the Kermack and McKendrick SIR model). They proposed a further modification which would consider sample results from municipal wastewater collection system (i.e. laterals or the sewer pipes under the streets). A well written, detailed description of the model design and sensitivity analysis has been presented. The general idea is interesting, and the authors have demonstrated a clear understanding of the epidemiology of COVID-19 and transmission of SARS-CoV-2, for example by choosing a 14 day window in the model. However, conspicuous in its absence is a clear description of the dynamics of the wastewater collection system and the influences of that on the model parameters. The authors use their home institution, the Rochester Institute of Technology as the case study, but we see no mention of individuals from the Monroe County Public Works Department, in the Acknowledgements, which accounts for the lack of discussion of important infrastructure considerations such as the flows in a combined storm and sanitary sewer in wet and dry seasons. There is no spatial component to the model at all. This is important because assumptions were made regarding the location of sample sites relative to where infected individuals reside. Given the omission of the details of the wastewater collection system and how they would impact uncertainty in the modelled results, it has not been demonstrated that inclusion of wastewater data as described in the manuscript would provide any benefit beyond traditional testing.


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