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: Venezuela, Bolivarian Republic of
Selected analysis: SA2: Without Google mobility data
- 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% |
-1519828 |
-16.3 |
-37.9 |
2179 |
15.4 |
| 25.0% |
2491385 |
28.2 |
49.0 |
5404 |
42.8 |
| 50.0% |
4028778 |
49.0 |
72.3 |
9271 |
58.9 |
| 75.0% |
6217421 |
66.2 |
83.8 |
14532 |
73.9 |
| 97.5% |
12557570 |
86.5 |
94.5 |
32047 |
89.5 |