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: Viet Nam
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% |
9448545 |
16.1 |
25.3 |
13722 |
19.9 |
| 25.0% |
13677487 |
28.9 |
37.6 |
21625 |
31.6 |
| 50.0% |
16082452 |
39.0 |
50.7 |
29019 |
39.1 |
| 75.0% |
18418774 |
48.4 |
63.3 |
38049 |
45.8 |
| 97.5% |
24703564 |
60.9 |
76.3 |
52617 |
56.7 |