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.