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: Bolivia, Plurinational State 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% |
-2244828 |
-16.1 |
-5.4 |
-3840 |
-18.4 |
| 25.0% |
634461 |
3.7 |
26.5 |
-1494 |
-8.0 |
| 50.0% |
1873769 |
13.9 |
55.6 |
-200 |
-1.0 |
| 75.0% |
2936067 |
23.0 |
68.9 |
1112 |
5.6 |
| 97.5% |
6208807 |
42.0 |
79.5 |
4670 |
23.1 |