Pupils returning to primary schools in England during 2020: rapid estimations of punctual COVID-19 infection rates
Metadatos
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Royal Society
Materia
England primary school COVID-19 risks Schools opening Stochastic uncertainty analysis Bayesian belief network Scenario sensitivity tests
Date
2021-09-15Referencia bibliográfica
Aspinall WP... [et al.] 2021 Pupils returning to primary schools in England during 2020: rapid estimations of punctual COVID-19 infection rates. R. Soc. Open Sci. 8: 202218. [https://doi.org/10.1098/rsos.202218]
Patrocinador
Royal Society education policy unit; Royal Society RAMP initiative for COVID-19; UK Research & Innovation (UKRI) Medical Research Council UK (MRC) European Commission MR/V0285545/1; UK MRC Integrative Epidemiology Unit at the University of Bristol MC_UU_00011/5Résumé
Drawing on risk methods from volcano crises, we developed
a rapid COVID-19 infection model for the partial 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. Assuming average national adult
prevalence, for the first scenario (as at 1 June 2020) we found
that between 178 and 924 [90% CI] schools would have at
least one infected individual, out of 16 769 primary schools in
total. For the second return (July), our estimate ranged
between 336 (2%) and 1873 (11%) infected schools. For a full
return in September 2020, our projected range was 661 (4%)
to 3310 (20%) infected schools, assuming the same prevalence
as for 5 June. If national prevalence fell to one-quarter of
that, the projected September range would decrease to
between 381 (2%) and 900 (5%) schools but would increase
to between 2131 (13%) and 9743 (58%) schools if prevalence
increased to 4× June level. When regional variations in prevalence and school size distribution were included in the model, a slight decrease in the projected
number of infected schools was indicated, but uncertainty on estimates increased markedly. The latter
model variant indicated that 82% of infected schools would be in areas where prevalence exceeded the
national average and the probability of multiple infected persons in a school would be higher in such
areas. Post hoc, our model projections for 1 September 2020 were seen to have been realistic and
reasonable (in terms of related uncertainties) when data on schools' infections were released by
official agencies following the start of the 2020/2021 academic year.