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: Italy
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% |
-3625956 |
-7.2 |
-27.8 |
-30832 |
-16.2 |
| 25.0% |
-1214106 |
-2.4 |
7.5 |
-17827 |
-9.3 |
| 50.0% |
-92932 |
-0.2 |
14.7 |
-10943 |
-5.7 |
| 75.0% |
1101649 |
3.2 |
25.0 |
718 |
0.4 |
| 97.5% |
4203952 |
12.4 |
50.7 |
28567 |
14.4 |