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: Philippines
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% |
-21271242 |
-15.1 |
-21.7 |
2116 |
2.5 |
| 25.0% |
1542461 |
1.2 |
25.7 |
9137 |
10.2 |
| 50.0% |
10850908 |
7.9 |
42.9 |
13045 |
14.3 |
| 75.0% |
19244314 |
16.1 |
56.5 |
18250 |
19.4 |
| 97.5% |
32586312 |
33.6 |
79.6 |
30570 |
28.8 |