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: Brazil
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% |
9893318 |
3.0 |
63.4 |
-63832 |
-10.0 |
| 25.0% |
56218933 |
16.6 |
82.6 |
211802 |
24.4 |
| 50.0% |
70092254 |
19.7 |
89.2 |
293203 |
30.6 |
| 75.0% |
80805240 |
22.0 |
91.3 |
353970 |
34.3 |
| 97.5% |
95188983 |
24.7 |
93.2 |
450603 |
38.7 |