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: Spain
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% |
-685741 |
-2.3 |
1.6 |
-5912 |
-4.5 |
| 25.0% |
-80696 |
-0.3 |
22.9 |
-1542 |
-1.2 |
| 50.0% |
131023 |
0.4 |
25.3 |
248 |
0.2 |
| 75.0% |
548244 |
1.6 |
27.6 |
2556 |
1.9 |
| 97.5% |
2303390 |
5.4 |
30.3 |
9473 |
6.6 |