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: South Africa
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% |
-1841587 |
-2.9 |
-7.6 |
-18969 |
-20.7 |
| 25.0% |
2828188 |
3.6 |
31.9 |
-3635 |
-3.4 |
| 50.0% |
5312147 |
5.8 |
48.9 |
7199 |
6.0 |
| 75.0% |
8326312 |
8.9 |
62.0 |
27466 |
18.9 |
| 97.5% |
15212063 |
14.8 |
80.1 |
66058 |
36.6 |