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: Finland
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% |
-326209 |
-6.6 |
-39.5 |
-1271 |
-15.2 |
| 25.0% |
-22101 |
-0.5 |
-9.1 |
71 |
0.7 |
| 50.0% |
54486 |
1.1 |
-0.9 |
439 |
4.6 |
| 75.0% |
133486 |
3.0 |
7.9 |
836 |
9.1 |
| 97.5% |
526217 |
12.5 |
54.3 |
3455 |
30.3 |