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: Chile
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% |
1055571 |
3.5 |
31.3 |
8098 |
14.7 |
| 25.0% |
3977617 |
11.4 |
67.7 |
25395 |
33.9 |
| 50.0% |
5313987 |
14.6 |
75.4 |
30694 |
38.7 |
| 75.0% |
6590402 |
17.0 |
81.4 |
36257 |
42.7 |
| 97.5% |
8294432 |
20.7 |
88.9 |
45343 |
49.3 |