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: Ireland
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% |
-646842 |
-13.2 |
-76.0 |
-2531 |
-23.6 |
| 25.0% |
-89968 |
-1.6 |
-3.9 |
-644 |
-6.7 |
| 50.0% |
34083 |
0.7 |
15.5 |
-127 |
-1.4 |
| 75.0% |
298775 |
4.9 |
37.6 |
566 |
5.9 |
| 97.5% |
1521535 |
20.7 |
60.6 |
3328 |
26.7 |