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: Base case analysis
- 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% |
-2885999 |
-5.8 |
-25.0 |
-23257 |
-11.8 |
| 25.0% |
-585886 |
-1.2 |
19.3 |
-7698 |
-3.8 |
| 50.0% |
807375 |
2.2 |
29.5 |
2217 |
1.1 |
| 75.0% |
2413678 |
6.3 |
35.9 |
19628 |
9.1 |
| 97.5% |
6837093 |
16.2 |
62.2 |
57163 |
23.0 |