Is regular COVID-19 testing in schools more effective than bubble quarantines?

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As children are at relatively low risk of being infected with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and suffering from severe coronavirus disease 2019 (COVID-19), vaccinating children is not common. However, owing to the emergence of variants of concern and uncertainty about the future course of the pandemic, many countries, including the UK, are contemplating COVID-19 mass vaccination of secondary age children.

Study: Analysis of alternative Covid-19 mitigation measures in school classrooms: an agent-based model of SARS-CoV-2 transmission. Image Credit: Dmytro Zinkevych/ ShutterstockStudy: Analysis of alternative Covid-19 mitigation measures in school classrooms: an agent-based model of SARS-CoV-2 transmission. Image Credit: Dmytro Zinkevych/ Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

Scientists are concerned that even though children are not prone to COVID-19 infection, schools containing many unvaccinated individuals may trigger rapid transmission of SARS-CoV-2. Further, schools can act as a potential environment for the development of new variants. But, the measure to mitigate this problem that involves closure of schools and implementation of online schooling has brought about major disruption to learning. Many reports have also indicated that some jobs have been compromised owing to childcare responsibilities. Therefore, there is an urgent need to formulate effective strategies to reduce the transmission of the disease and minimize disruption in education.

A new study

A new study focused on developing a basic stochastic model for predicting the possibility of the transmission of SARS-CoV-2 occurring in primary schools. The study authors developed a discrete agent-based compartmental epidemiological model that can empirically represent the probability of SARS-CoV-2 transmission owing to proximity within class-sized interactive networks.

A previous study that included 36 primary schools in England statistically defined close contact as face-to-face contact within 1 meter for at least five minutes between children and adults within school settings. In this study, the researchers used teachers’ expert judgments undertaken in Spring/Summer 2020 and formulated mitigation measures such as reduced class sizes, formation of bubbles, and other social distancing rules.

In the current study, researchers assessed the viability of the newly developed model by comparing the data on school attendances and self-isolation imposed owing to the COVID-19 outbreak at home or school. Scientists also compared the predictions of the model with the actual prevalence of SARS-COV-2 infection in both schools and communities.

A preprint version of the study is available on the medRxiv* server, while the article undergoes peer review.

Assumptions of the new model

The researchers have developed the model by combining a discrete compartmental epidemiological framework with a random network for daily person-to-person contacts within a classroom. They assumed that a classroom consisted of a single teacher, few assistant teachers, and a set number of pupils. Researchers further assumed the modeled classroom population to be isolated from other classes. Therefore, this model does not include interactions with other people in the school.

These assumptions are best suited for primary school settings, where one classroom can be separated from the other as an initiative to reduce COVID-19 transmission in school settings. This approach was undertaken in the primary schools in England that remained open for vulnerable children and frontline workers in March 2020. This framework was also followed in schools that were reopened for selected age groups in June 2020.

Main findings

This model was applied to the autumn term (Term 1) in 2020 when UK schools first reopened for full classes and were used to forecast Term 1 2021. Researchers observed that testing-based (regular rapid lateral flow testing regime) surveillance was more effective than bubble-quarantine, as the latter could lead to many absentees. The augmented PCR tests had little benefit since a positive lateral flow result was, in most cases, confirmed by a PCR test.

Further, maintaining a reduced contact rate had a major beneficial impact on managing the spread of infection in school settings. The model suggested that implementing practices that reduce contact could lower in-school transmission by up to 30%.

The results supported the idea that outbreaks could be defined as infections exceeding five individuals in a class-sized mixing group. The forecasts indicated larger and more frequent infections in Term 1 of 2021. This is largely driven by the presence of the highly transmissible Delta SARS-CoV-2 variant. The worst-case scenario could be that all school classes will have at least one infection in Term 1 of 2021.

Conclusion

The model makes several assumptions and has some limitations. The study only focused on close contacts, which is a simplification of actual patterns of human interactions. The model also assumes each classroom to be isolated, but there may well be pupil-pupil interactions. The model could also consider other measures to mitigate transmission, for example, masks, cleaning, and ventilation. An important development point for the model could be forecast reliability. Conditional on that, the model could be combined with near real-time data on observed incidence to generate reasonably dependable short-term forecasts, out to a few weeks ahead.

 

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • Apr 12 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Dr. Priyom Bose

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Dr. Priyom Bose

Priyom holds a Ph.D. in Plant Biology and Biotechnology from the University of Madras, India. She is an active researcher and an experienced science writer. Priyom has also co-authored several original research articles that have been published in reputed peer-reviewed journals. She is also an avid reader and an amateur photographer.

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