This page presents detailed model outputs associated with the following article:
Estimating the impact of school closures on the COVID-19 dynamics in 74 countries: a modelling analysis.
Romain Ragonnet, Angus E Hughes, David S Shipman, Michael T Meehan, Alec S Henderson, Guillaume Briffoteaux, Nouredine Melab, Daniel Tuyttens, Emma S McBryde, James M Trauer.
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Selected country: Germany
Selected analysis: Base case analysis
- The first panel presents a scenario comparison based on the maximum a-posteriori parameter set.
- The second and third panels present the uncertainty around the estimated epidemic trajectories, as median (black lines), interquartile range (dark shade) and 95% credible interval (light shade).
Relative outcomes
- Positive values indicate a positive effect of school closures on the relevant indicator.
- Negative values indicate that school closures exacerbated the relevant COVID-19 indicator..
|
N infections averted |
% infections averted |
% hospital peak reduction |
N deaths averted |
% deaths averted |
| percentile |
|
|
|
|
|
| 2.5% |
-5866014 |
-9.3 |
-7.7 |
-30146 |
-17.9 |
| 25.0% |
-154467 |
-0.3 |
21.7 |
-1761 |
-1.0 |
| 50.0% |
2014945 |
4.6 |
35.7 |
17857 |
8.6 |
| 75.0% |
4556541 |
9.4 |
46.4 |
35458 |
16.2 |
| 97.5% |
11828721 |
19.0 |
63.5 |
67261 |
27.1 |