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: Kazakhstan
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% |
-386974 |
-2.9 |
-36.0 |
257 |
1.2 |
| 25.0% |
3033196 |
14.6 |
48.3 |
10380 |
37.2 |
| 50.0% |
4552426 |
20.2 |
72.3 |
15295 |
45.9 |
| 75.0% |
5843666 |
24.7 |
80.4 |
19938 |
51.9 |
| 97.5% |
7964975 |
30.7 |
88.1 |
30162 |
58.8 |