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: Lebanon
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% |
-2159215 |
-20.7 |
-95.1 |
-2229 |
-20.5 |
| 25.0% |
-427306 |
-4.6 |
-3.3 |
-555 |
-4.8 |
| 50.0% |
-16461 |
-0.2 |
13.3 |
476 |
3.9 |
| 75.0% |
607378 |
5.5 |
48.0 |
2189 |
15.6 |
| 97.5% |
2037796 |
19.8 |
79.4 |
8486 |
36.4 |