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.
Back to analysis selection index page
Selected country: Slovenia
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% |
-907297 |
-40.5 |
-67.9 |
-3598 |
-48.3 |
| 25.0% |
-313175 |
-11.7 |
1.4 |
-1533 |
-17.5 |
| 50.0% |
-127522 |
-5.1 |
21.3 |
-629 |
-7.1 |
| 75.0% |
-20815 |
-0.9 |
36.3 |
70 |
0.9 |
| 97.5% |
220350 |
9.0 |
53.5 |
1415 |
16.7 |