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With recent spikes in Covid-19 cases and hospitalizations across the country — including in children — the Delta variant has dramatically changed the country’s back-to-school risk calculus.

Fearing outbreaks, many schools are scrambling to adjust their reopening plans. Discussions about school safety have largely focused on mitigation measures like improving ventilation and requiring students and staff to wear masks and get vaccinated. Some have also noted the value of routine school-wide testing of students and staff for SARS-CoV-2, the virus that causes Covid-19, to detect infections early and prevent transmission.


We believe that discussions of different strategies often overlook another important benefit of testing: providing information to help schools know when they need to add these new mitigation measures and when, after the Delta surge retreats, it’s safe to ease up. Testing for SARS-CoV-2 is an underappreciated tool to inform planning and decision-making by providing real-time, context-specific situational awareness.

Because the Delta variant is about twice as transmissible as the original SARS-CoV-2 virus, schools now have less “headroom” for dodging outbreaks when mitigation is weak or inconsistent. Data suggest that safe reopening is possible: with significant mitigation, Covid-19 transmission in the United Kingdom, Australia, and U.S. summer schools remained low even in the presence of the Delta variant. Nevertheless, transmission has been reported among masked children at camp and students with only brief contact, and some U.S. schools have already experienced large outbreaks, triggering closures. The question is: How can schools determine which measures are needed, now and throughout the year?

During the 2020-2021 school year, community-based indicators like test positivity and case rates dominated guidance for school decision-making around wearing masks, testing, and closures, based on the logic that the risk of introducing SARS-CoV-2 into schools would mirror trends in their surrounding communities. But the relationship between Covid-19 in a community and Covid-19 in its schools varies. With high-quality mitigation, transmission may remain low even if infected people are in school.


Passive school-based indicators, like reported cases of Covid-19, are also problematic. Testing for children with symptoms is not widely available in all communities. And because children and adolescents often have mild or non-specific symptoms, relying on positive tests to signal trouble may miss outbreaks until they are difficult to control or have spread to families.

Testing data can address the shortcomings of both community and passive indicators, providing reliable school-specific data to guide planning. We see strategic in-school testing as having two components: regular asymptomatic testing (either everyone in a school or a random sample of 10% to 20% of its population each week), and testing contacts of known cases.

Asymptomatic testing allows educators to accurately estimate how many students or staff infected with SARS-CoV-2 arrive at school. And by testing contacts of infected individuals, schools can measure how much viral spread follows these introductions. Having information about both can make the difference between acting quickly enough to arrest outbreaks and being forced to close unexpectedly.

First, testing can estimate the prevalence of Covid-19 in a school, a key indicator of transmission risk. A positive test rate of 0.3%, for example, suggests that, in a school of 700 kids, about two are infected. Tracking prevalence allows a school to react swiftly to changes in the number of infected people who enter it. When these numbers rise, enhanced measures like strict cohorting of students within small-class groups or using higher-quality masks may be needed to reduce exposures and prevent outbreaks.

But it’s important not to directly compare the positivity rate in a school with that in the surrounding community because almost all those being tested in a school are asymptomatic while many who seek testing in the community do so because they have symptoms or have been exposed to someone with Covid-19.

Second, contact tracing can provide a better understanding of in-school transmission. When a case of Covid-19 is identified, a school should provide rapid antigen or PCR testing to the individual’s contacts. This can reduce the disruption associated with quarantines. In a “test to stay” strategy, for example, as implemented in Utah and the United Kingdom and planned in Massachusetts, exposed contacts can stay in school provided they use regular rapid tests and isolate only if positive.

Contact testing also signals when infections are spreading in classrooms rather than entering from the community, allowing schools to adjust mitigation measures like classroom distancing or lunchtime precautions to arrest in-school transmission. If testing can substitute for quarantine, schools can even cast a wider net in defining “close contacts” of identified cases — expanding to full classrooms and casual contacts, for example — to get a clearer view on spread in the school and act accordingly.

While sample-based surveillance and contact testing are informative, they are unlikely to directly prevent most transmission of SARS-CoV-2. By contrast, implementing regular school-wide testing of all students and staff, rather than just a small percentage, both provides data and significantly reduces transmission by detecting and isolating most infections before they are transmitted to others. This is the most comprehensive and powerful approach to testing and may be useful for keeping schools open through fall and winter surges.

Although critics have argued that school-wide screening is too resource intensive and only reasonable when SARS-CoV-2 is widespread, many parts of the country have case rates well above suggested thresholds for adopting it.

While concerns about costs and feasibility have previously limited enthusiasm for testing, the Biden administration has allocated $10 billion in funding for school testing programs and recently emphasized their importance. Meanwhile, testing in schools has already been implemented in many countries and some states.

For schools weighing benefits against logistical and financial costs, a mixed approach may provide an attractive compromise — for example, tracking data from sample-based testing or contact testing and defining conditions that would trigger a switch to school-wide screening.

The choices that schools make are now more consequential than ever, as leaders aim for a full return to uninterrupted in-person schooling. And despite some arguments to the contrary, avoiding large-scale outbreaks in schools is important for several reasons. First, even though Covid-19 is mild in most children, some children and families are at high risk for complications, and with the Delta variant, schools may amplify community transmission, especially in minority and vulnerable communities. Second, scientists are still studying whether Delta might lead to more severe outcomes in children than previous variants. Third, in the coming weeks and months, vaccination for children under 12, and further uptake among adolescents, will likely help defang the virus in these groups, making it meaningful to avoid outbreaks now.

In the meantime, however, school interruptions harm children through their effects on learning, as well as loss of peer interactions and breaks in delivery of social services. Surveillance testing, then, gives school leaders the ability to strike a comfortable risk balance, adapt plans as needed, and provide reliable information to parents and educators making decisions for children and families.

No one knows what will happen during the fall and beyond. But if we agree that schools are essential institutions, they should be given what they need to make smart, data-informed decisions during the uncertain year ahead.

Alyssa Bilinski is an assistant professor of health policy and biostatistics at Brown University School of Public Health. Joshua A. Salomon is a professor of health policy at Stanford University School of Medicine and director of the school’s Prevention Policy Modeling Lab.

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