University of Mannheim: Protection against Covid-19 in schools
It’s holiday time – but the third school year affected by the pandemic needs to be well prepared to keep Covid-19 at bay. Outbreaks of infection in schools can be effectively avoided or at least mitigated by dividing classes when the incidence increases, thereby reducing possible contagion contacts. The division should, however, take into account the friendship networks of the students and thus also the contacts outside the schools. This is the result of a study in which the sociologists David Kretschmer and Dr. Lars Leszczensky from the Mannheim Center for European Social Research (MZES) are involved. Together with first author Anna Kaiser, Ph.D., from Columbia University (USA), they conducted the first independently peer-reviewed scientific study on the subject of group division Switching classes and Covid-19 published in European schools. The study was published in the journal “The Lancet Regional Health – Europe” and is freely available as an “Open Access” publication.
Contacts in 507 classes analyzed: four strategies, differently effective
Based on the actual social relationships between 14- to 15-year-old students in 507 classes at secondary schools in England, the Netherlands, Sweden and Germany, the research team modeled the spread of SARS-CoV-2 in the school context. The scientists simulated the infection process after the virus was entered in the class under the following conditions:
Random division of the classes into two groups
Division into two groups according to gender
Division into two groups based on complete network data
Self-organized division into two groups by students who indicate their contacts themselves
The result: All four strategies contain the infection process – but to a different extent.
“As expected, the random distribution, for example alphabetically according to the first letters of the name, has the weakest effect,” explains David Kretschmer. The division by gender is much more effective, since school-age children and young people tend to meet members of their own gender, according to the sociologist. Additional contacts and thus infections between the gender groups are therefore not so common. In the model, however, the division, taking into account the actual social contacts indicated by the students in scientific surveys, proved to be particularly effective. First author Anna Kaiser: “In the data we can see who is in close contact with whom, even outside of school. If you divide the classes accordingly,
Self-organized division as a replacement for complete network data
According to the study, effects that are almost as good as using complete data on the entire contact network of all pupils can be achieved if individuals mutually indicate their contacts: For example, if a pupil names all classmates in the class with whom she often also outside of school Has contact. One of the named persons then names all classmates with whom she is in contact outside of school until the network comprises half of the class. Both halves of the class then each form a lesson group. “This approach is very easy to implement in everyday school life, as the teachers do not have to first collect all the contacts in the class, as was done for the data in our study,” explains Lars Leszczensky.
Alternating instruction works
In addition, the research team was able to show that the changing lessons of divided school classes on a weekly basis can interrupt chains of infection in the model better than forms of teaching in which the class halves are present in the school on the same day and, for example, use different rooms at different times. Weekly change works like a kind of short quarantine, during which a burgeoning infection process can subside, according to the one result of the study.
Background: The long-term study CILS4EU at the MZES
Kaiser, Kretschmer and Leszczensky used data from the international long-term survey CILS4EU (Children of Immigrants Longitudinal Survey in Four European Countries) for their investigation. The survey mainly compares the development of children and young people with and without a migration background in Germany, England, the Netherlands and Sweden. In addition to many other data relevant to integration, such as school success, family environment and career entry, the social relationships of the participating students are also collected. Funded by the European funding network NORFACE and the German Research Foundation (DFG), the project has been coordinated by the MZES with the respective country teams for over ten years.