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: South Africa
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% |
-1368046 |
-1.8 |
0.1 |
-9616 |
-10.4 |
| 25.0% |
3468762 |
3.9 |
45.7 |
12521 |
10.7 |
| 50.0% |
6266007 |
7.2 |
62.3 |
30430 |
22.2 |
| 75.0% |
9379567 |
10.0 |
73.7 |
48236 |
29.8 |
| 97.5% |
16289006 |
16.9 |
83.9 |
79872 |
41.2 |