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: India
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% |
109336626 |
13.0 |
21.3 |
-102785 |
-16.3 |
| 25.0% |
163181494 |
19.4 |
52.5 |
30001 |
4.5 |
| 50.0% |
202428775 |
24.5 |
64.3 |
107479 |
15.0 |
| 75.0% |
251818815 |
30.7 |
73.4 |
202579 |
24.8 |
| 97.5% |
394150241 |
50.5 |
85.8 |
500759 |
46.0 |