SARS-CoV-2 in schools: genome analysis shows that concurrent cases in the second and third wave were often unconnected

  1. Madlen Stange
  2. Eva Wuerfel
  3. Jelissa Katharina Peter
  4. Helena Seth-Smith
  5. Tim Roloff
  6. Severin Gsponer
  7. Alfredo Mari
  8. Blanca Cabrera Gil
  9. Aitana Lebrand
  10. Fanny Wegner
  11. Ulrich Heininger
  12. Julia Bielicki
  13. Sarah Tschudin Sutter
  14. Tanja Stadler
  15. Karoline Leuzinger
  16. Hans H. Hirsch
  17. Markus Ledergerber
  18. Simon Fuchs
  19. Adrian Egli

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Abstract

Background

The risk of SARS-CoV-2 (SCoV2) infection in schools and student households is typically assessed using classical epidemiology whereby transmission is based on time of symptom onset and contact tracing data. Using such methodologies may be imprecise regarding transmission events of different, simultaneous SCoV2 variants spreading with different rates and directions in a given population. We analysed with high resolution the transmission among different communities, social networks, and educational institutions and the extent of outbreaks using whole genome sequencing (WGS).

Methods and Findings

We combined WGS and contact tracing spanning two pandemic waves from October 2020 to May 2021 in the Canton of Basel-City, Switzerland and performed an in-depth analysis of 235 cases relating to 22 educational institutions. We describe the caseload in educational institutions and the public health measures taken and delineate the WGS-supported outbreak surveillance.

During the study period, 1,573 of 24,557 (6.4%) children and 410 of 3,726 (11%) staff members from educational institutions were reported SCoV2 positive. Thereof, WGS data from 83 children, 35 adult staff in 22 educational institutions and their 117 contacts (social network, families) was available and analysed. 353 contextual sequences from residents of the Canton of Basel-City sequenced through surveillance were identified to be related to cases in the educational institutions. In total, we identified 55 clusters and found that coinciding SCoV2-cases in individual educational institutions were mostly introduced from different sources such as social networks or the larger community. More transmission chains started in the community and were brought into the educational institutions than vice versa (31 vs. 13). Adolescents (12-19 years old) had the highest case prevalence over both waves compared to younger children or adults, especially for the emerging Alpha variant.

Conclusions

Introduction of SCoV2 into schools accounts for most events and reflects transmission closely related to social activity, whereby teenagers and young adults contribute to significant parallel activity. Combining WGS with contact tracing is pivotal to properly inform authorities about SCoV2 infection clusters and transmission directions in educational settings and the effectiveness of enacted public health measures. The gathered data showing more clusters to seed in the community than vice versa as well as few subsequent in-school transmissions indicate that the agilely employed health measures for educational institutions helped to prevent outbreaks among staff and children.

The clinical trial accession number is NCT04351503 ( clinicaltrials.gov ).

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  1. ScreenIT

    SciScore for 10.1101/2022.01.26.22269824: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Here, case clusters with suspected in-school transmission and contacts were identified for WGS and subjected to a molecular epidemiological outbreak
    WGS
    suggested: None
    Tools used for data wrangling, statistical analysis, and visualisation of results: Data processing was done either in R version 4.0.3 [21] or Python v3.8.9 [22].
    Python
    suggested: (IPython, RRID:SCR_001658)
    The following packages were used for data wrangling and visualisation: tidyr v1.1.3 [24], ggplot2 v3.3.3 [25], pivottabler v1.5.2 [26], tibble v3.1.0 [27], hrbrthemes v0.8.0 [28], ggpubr v0.4.0 [29], pandas v1.2.4 [30], and plotly v4.14.3 [31].
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study bears important limitations caused by missing data due to unsequenced cases. We found 22 single cases which had - derived from contact tracing - been related to clusters in schools or childcare facilities, for which we failed to detect other school or community cases despite our extensive SCoV2 database for the Canton of Basel-City. Some of these might indeed be “single cases” within the Canton of Basel-City and might have been imported from other cantons or countries. However, particularly after the establishment of VOCs, WGS more often failed because of pre-analytical quality or low viral load in the collected sample. This was probably due to changes in contact tracing policies, now advising also asymptomatic contact persons, as well as people with mild symptoms to undergo testing. Another important aspect is the sampling bias due to changing recommendations. We tried to sequence as many cases as possible to generate a comprehensive picture. The SCoV2 pandemic is highly dynamic and therefore scientific results are in many ways short-lived. After completion of this study, the Delta variant (B.1.617.2) became the dominant virus variant as of July 2021 in the Canton of Basel-City. It caused the fourth epidemic wave for about three months, whereafter the first Omicron variant (B.1.1.529) cases were reported in our region in December 2021. During the fourth wave, we registered an increasing number of apparent infection clusters in schools and childcare facilities. It ...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04351503RecruitingA Systems Approach to Predict the Outcome of SARS-CoV-2 in t…

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2022.01.26.22269824v1 on medRxiv