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: Denmark
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% |
-831553 |
-17.6 |
-56.3 |
-3168 |
-35.2 |
25.0% |
-83669 |
-1.4 |
-10.2 |
-178 |
-2.0 |
50.0% |
159985 |
3.3 |
2.5 |
1048 |
10.8 |
75.0% |
521980 |
10.0 |
34.6 |
2677 |
24.5 |
97.5% |
1899342 |
33.9 |
73.4 |
7019 |
47.1 |