Quantifying threat from COVID-19 infection hazard in Primary Schools in England
Sparks, S. R.; Aspinall, W. P.; Cooke, R.; Scarrow, J. H.
Show abstract
We have constructed a COVID-19 infection hazard model for the return of pupils to the 16,769 state Primary Schools in England that takes into account uncertainties in model input parameters. The basic probabilistic model estimates likely number of primary schools with one or more infected persons under three different return-to-school circumstances. Inputs to the infection hazard model are: the inventory of children, teachers and support staff; the prevalence of COVID-19 in the general community including its spatial variation, and the ratio of adult susceptibility to that of children. Three scenarios of inventory are: the counts on 1st June when schools re-opened to Nursery, Reception, Year 1 and Year 6 children, when approximately one-third of eligible children attended; a scenario assuming a full return of eligible children in those cohorts; and a return of all primary age children, scheduled for September. With a national average prevalence, we find that for the first scenario between 178 and 924 schools out of 16,769 in total (i.e. about 1% and 5.5% respectively) may have infected individuals present, expressed as a 90% credible interval. For the second scenario, the range is between 336 (2%) and 1873 (11%) schools with one (or more) infected persons, while for the third scenario the range is 661 (4%) to 3310 (20%) schools, assuming that the prevalence is the same as it was on 5th June. The range decreases to between 381 (2%) and 900 (5%) schools with an infected person if prevalence is one-quarter that of 5th June, and increases to between 2131 (13%) and 9743 (58%) schools for the situation where prevalence increases to 4 times the 5th June level. Net prevalence of COVID-19 in schools is reduced relative to the general community because of the lower susceptibility of primary age children to infection. When regional variations in prevalence and school size distribution are taken into account there is a slight decrease in number of infected schools, but the uncertainty on these projected numbers increases markedly. The probability of having an infected school in a community is proportional to the local prevalence and school size. Analysis of a scenario equivalent to a full return to school with an average national prevalence of 1 in 1700 and spatial prevalence variations, estimated from data for late June, indicates 82% of infected schools would be located in areas where prevalence exceeds the national average. The probability of having multiple infected persons in a school increases markedly in high prevalence areas. Assuming national prevalence characteristic of early June, individual, operational and societal risk will increase if schools reopen fully in September due to both increases in numbers of children and the increased challenges of sustaining mitigation measures. Comparison between incidents in primary schools with positive tests in June and July and our estimates of number of infected schools indicates at least an order of magnitude difference. The much lower number of incidents reflects several factors, including effective reduction in transmission resulting from risk mitigation measure instigated by schools.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Modelling Suggests Limited Change in the Reproduction Number from Reopening Norwegian Kindergartens and Schools During the COVID-19 Pandemic 94%
- In the long shadow of our best intentions: model-based assessment of the consequences of school reopening during the COVID-19 pandemic 94%
- Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction 93%
Similar papers in this journal
- Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis 92%
- Network analysis of England’s single parent household COVID-19 control policy impact: a proof-of-concept study 91%
- Extending upon: What effect might border screening have on preventing importation of COVID-19 compared with other infections? – Considering the additional effect of post-arrival isolation 91%
Similar papers in this journal
- Timely Epidemic Monitoring in the Presence of Reporting Delays: Anticipating the COVID-19 Surge in New York City, September 2020 92%
- Inclusive Health: Modeling COVID-19 In Correctional Facilities And Communities 92%
- Human behaviour, NPI and mobility reduction effects on COVID-19 transmission in different countries of the world 91%
Similar papers in this journal
- Border quarantine, vaccination and public health measures to mitigate the impact of COVID-19 importations: a modelling study 93%
- The effect of school closures and reopening strategies on COVID-19 infection dynamics in the San Francisco Bay Area: a cross-sectional survey and modeling analysis 92%
- Modelling the impact of household size distribution on the transmission dynamics of COVID-19 92%
Similar papers in this journal
- Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK 93%
- SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study 92%
- Non-pharmaceutical interventions and vaccinating school children required to contain SARS-CoV-2 Delta variant outbreaks in Australia: a modelling analysis 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.