Abstract
Drawing on risk methods from volcano crises, we developed a rapid COVID-19 infection model for the return of pupils to Primary Schools in England in June and July 2020, and a full return in September 2020. The model handles uncertainties in key parameters, using a stochastic re-sampling technique, allowing us to evaluate infection levels as a function of COVID-19 prevalence and projected pupil and staff headcounts. For the first scenario (at 1st June 2020), between 178 and 924 [90% CI] schools would have at least one infected individual, out of 16,769 schools in total. For a full return in September 2020, the range was 661 (4%) to 3,310 (20%) infected schools. When regional variations in prevalence and school size distribution were included in the model, a slight decrease in projected number of infected schools was indicated, but uncertainty on estimates increased markedly. Post hoc, our model projections for September 2020, were seen to be realistic for decision support when official data on schools’ infections were released following the start of the 2020/21 academic year.
Original language | English |
---|---|
Article number | 202218 |
Number of pages | 21 |
Journal | Royal Society Open Science |
Volume | 8 |
Issue number | 9 |
Early online date | 15 Sept 2021 |
DOIs | |
Publication status | E-pub ahead of print - 15 Sept 2021 |
Keywords
- England Primary School COVID-19 risks
- schools opening
- stochastic uncertainty analysis
- Bayesian Belief Network
- scenario sensitivity tests