Shut and re-open: the role of schools in the spread of COVID-19 in Europe
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Abstract
We investigate the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden and German states as case studies. By comparing the growth rates in daily hospitalizations or confirmed cases under different interventions, we provide evidence that school closures contribute to a reduction in the growth rate approximately 7 days after implementation. Limited school attendance, such as older students sitting exams or the partial return of younger year groups, does not appear to significantly affect community transmission. In countries where community transmission is generally low, such as Denmark or Norway, a large-scale reopening of schools while controlling or suppressing the epidemic appears feasible. However, school reopening can contribute to statistically significant increases in the growth rate in countries like Germany, where community transmission is relatively high. In all regions, a combination of low classroom occupancy and robust test-and-trace measures were in place. Our findings underscore the need for a cautious evaluation of reopening strategies.
This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
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SciScore for 10.1101/2020.06.24.20139634: (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 Sentences Resources The ABC fitting of the SEIR model was achieved through the PyGom package for Python [14]. PyGomsuggested: NoneThe Poisson Gaussian process regression method, carried using a Bayesian latent variable approach, uses the PyMC3 probabilistic programming package for Python [15]. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The …
SciScore for 10.1101/2020.06.24.20139634: (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 Sentences Resources The ABC fitting of the SEIR model was achieved through the PyGom package for Python [14]. PyGomsuggested: NoneThe Poisson Gaussian process regression method, carried using a Bayesian latent variable approach, uses the PyMC3 probabilistic programming package for Python [15]. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The Gaussian process regression method allows one to account for differences between the simulated epidemic trajectories and the observed cases, however this process is not without its limitations. The fact that closures occurred very early on in the epidemic means that the Gaussian process method often had to be trained on a limited number of data points (the short posterior predictive trajectories from the ODE before the intervention). Although a GP, itself being a probabilistic model, is tailored to handle small data with exact uncertainty quantification, the process of estimating its hyperparameters, using MCMC, becomes challenging due to less than optimal mixing of some of these parameters. Since the instantaneous growth rate relies on the derivative of splines, it is subject to increased error at the boundaries of the data. However, the observed signals are qualitatively robust to this limitation. Due to the presence of weekend effects and the noisiness of some data streams due to the relatively low incidence following mass quarantine, the values of the instantaneous growth rate should be taken as a quantification of the trend in incidence rather than the true value on any given day. With some exceptions, we have considered the effects of school closure and reopening on the national level without accounting for inevitable geographic variability, the age distribution of those studied, and their profession (i.e. likelihood of exposure to infected individuals). The analysi...
Results from TrialIdentifier: No clinical trial numbers were referenced.
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.
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SciScore for 10.1101/2020.06.24.20139634: (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 Sentences Resources The ABC fitting of the SEIR model was achieved through the PyGom package for Python [14]. PyGomsuggested: NoneThe Poisson Gaussian process regression method, carried using a Bayesian latent variable approach, uses the PyMC3 probabilistic programming package for Python [15]. Pythonsuggested: (IPython, SCR_001658)Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage …
SciScore for 10.1101/2020.06.24.20139634: (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 Sentences Resources The ABC fitting of the SEIR model was achieved through the PyGom package for Python [14]. PyGomsuggested: NoneThe Poisson Gaussian process regression method, carried using a Bayesian latent variable approach, uses the PyMC3 probabilistic programming package for Python [15]. Pythonsuggested: (IPython, SCR_001658)Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.
Results from OddPub: Thank you for sharing your data.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.
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