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: Bangladesh
Selected analysis: SA1: Increased household transmission during closures
- 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% |
-52659 |
-0.1 |
-114.4 |
-209 |
-0.6 |
| 25.0% |
9192608 |
20.6 |
7.8 |
10108 |
23.7 |
| 50.0% |
14453319 |
35.7 |
41.4 |
19536 |
39.2 |
| 75.0% |
20317024 |
49.1 |
62.2 |
30617 |
50.8 |
| 97.5% |
33912000 |
68.0 |
83.4 |
55915 |
67.4 |