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.
Back to analysis selection index page
Selected country: Slovakia
Selected analysis: SA2: Without Google mobility data
- 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% |
-2355491 |
-29.8 |
-77.6 |
-5704 |
-27.5 |
| 25.0% |
-653431 |
-8.4 |
-10.5 |
-2048 |
-10.2 |
| 50.0% |
-244870 |
-3.2 |
4.0 |
-875 |
-3.9 |
| 75.0% |
-18641 |
-0.2 |
22.7 |
2 |
0.0 |
| 97.5% |
364860 |
4.4 |
53.5 |
2184 |
8.3 |