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: Russian Federation
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% |
-1886681 |
-1.1 |
-8.3 |
3164 |
0.9 |
| 25.0% |
5498928 |
4.1 |
14.3 |
19139 |
4.3 |
| 50.0% |
7883195 |
6.3 |
21.2 |
26557 |
6.0 |
| 75.0% |
10291861 |
8.8 |
27.9 |
34831 |
7.7 |
| 97.5% |
15003216 |
13.7 |
44.8 |
54916 |
11.9 |