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: Greece
Selected analysis: SA2: Without Google mobility data
- 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% |
-1856314 |
-22.8 |
-40.1 |
-7714 |
-25.2 |
| 25.0% |
-688664 |
-6.4 |
6.0 |
-1746 |
-5.1 |
| 50.0% |
-184156 |
-1.4 |
22.6 |
880 |
2.5 |
| 75.0% |
100306 |
0.6 |
39.9 |
2949 |
7.0 |
| 97.5% |
597494 |
4.4 |
63.0 |
7193 |
15.2 |