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: Kenya
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% |
-3740292 |
-13.2 |
-38.5 |
-4432 |
-44.9 |
| 25.0% |
3439090 |
12.1 |
45.9 |
-482 |
-4.2 |
| 50.0% |
8637561 |
30.3 |
65.8 |
2586 |
19.5 |
| 75.0% |
13834883 |
44.1 |
79.3 |
5704 |
36.2 |
| 97.5% |
23182265 |
63.5 |
90.2 |
13019 |
60.5 |