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: Korea, Republic of
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% |
-892324 |
-2.0 |
-60.8 |
4868 |
10.5 |
| 25.0% |
2259625 |
4.5 |
-27.1 |
11066 |
20.8 |
| 50.0% |
3695544 |
8.1 |
-12.1 |
16613 |
29.6 |
| 75.0% |
5781730 |
13.2 |
6.6 |
23883 |
38.5 |
| 97.5% |
13039870 |
27.6 |
64.1 |
55768 |
60.2 |