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: Ukraine
Selected analysis: SA1: Increased household transmission during closures
- 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% |
-538918 |
-2.5 |
-76.3 |
-7977 |
-7.4 |
| 25.0% |
-59872 |
-0.3 |
-14.8 |
-2614 |
-2.5 |
| 50.0% |
51782 |
0.2 |
14.5 |
439 |
0.4 |
| 75.0% |
367131 |
1.4 |
39.9 |
4819 |
4.0 |
| 97.5% |
3422380 |
8.7 |
62.4 |
18160 |
13.0 |