Predicting the dynamics of COVID-19 in Schools, Universities and Workplaces has been a key focus on research in the Zeeman Institute. These close-contact settings are potential transmission hot-spot for infection, so it is important to quantify the risks. We have worked closely with Universities and the Department for Education to help translate our analysis and projections into helpful policy guidance.
Our publications and pre-prints on COVID-19 in specific settings are:
Trystan Leng, Edward M Hill, Robin N Thompson, Michael J Tildesley, Matt J Keeling, Louise Dyson. (2022) "Assessing the impact of lateral flow testing strategies on within-school SARS-CoV-2 transmission and absences: A modelling study" PLoS Comp. Biol. 18(5): e1010158. https://doi.org/10.1371/journal.pcbi.1010158
UK secondary schools have implemented a range of measures to control transmission within schools, including the isolation of close contacts of confirmed cases from September 2020 - July 2021, and twice weekly testing of staff and pupils since March 2021. We have developed an individual-based model to understand the impact of school control measures on pupil-to-pupil transmission, pupil absences and testing volume. Using an individual-based model of a secondary school implementing a bubbling strategy at the level of year-groups, and simulating infections over the course of a seven-week half-term, we evaluated a range of strategies with differing isolation and rapid test strategies. In particular, we found that a policy of daily contact testing resulted in a similar reduction in transmission to an isolation of year-groups policy, but markedly reduced absences.
|Trystan Leng, Edward M Hill, Alex Holmes, Emma Southall, Robin N Thompson, Michael J Tildesley, Matt J Keeling, Louise Dyson. (2021) "Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England" Nat Commun 13, 1106. https://doi.org/10.1038/s41467-022-28731-9|
Since, we have incorporated various data into the individual-based model of secondary schools in order to quantify SARS-CoV-2 transmission between secondary school pupils in England. We have used community swab testing data to inform community prevalence for schools according to their local area and to inform a school's level of participation in lateral flow testing; we have used secondary school absences data to inform the size of group a school isolates upon identification of a positive case; and we have fitted this model to community swab testing data in 11-16 year olds and secondary school absences data. With this fitted model, we simulated outbreaks from 31st Aug 2020 - 21st May 2021 to quantify SARS-CoV-2 transmission in secondary schools in England. Doing so, we evaluated the impact of twice weekly lateral flow testing (LFT) of pupils on transmission, finding that twice weekly mass testing likely played an important role in controlling pupil-to-pupil transmission in secondary schools in England. We also considered the counterfactual impact of alternative strategies, finding that strategies involving mass testing have the potential to control within-school transmission while substantially reducing absences.
|Emma Southall, Alex Holmes, Edward M. Hill, Benjamin D. Atkins, Trystan Leng, Robin N. Thompson, Louise Dyson, Matt J. Keeling, Michael J. Tildesley (2021) "An analysis of school absences in England during the Covid-19 pandemic " BMC Medicine, 19 (137). https://doi.org/10.1186/s12916-021-01990-x|
Our research has analysed data on pupil and staff absences due to confirmed COVID-19 infection during September-December 2020. During this early phase there is no significant evidence to suggest that schools are playing a substantial role in driving spread in the community. We conclude that careful monitoring was required as schools re-opened in 2021 to determine the effect associated with open schools upon community incidence.
|Keeling, M. J., Tildesley, M. J., Atkins, B. D., Penman, B., Southall, E., Guyver-Fletcher, G., Holmes, A., McKimm, H., Gorsich, E., Hill, E. M., and Dyson, L. (2021). "The impact of school reopening on the spread of COVID-19 in England" Phil. Trans. R. Soc. B. 376 (1829): 20200261. https://doi.org/10.1098/rstb.2020.0261|
We have used the Warwick COVID model for the UK to investigate potential scenarios for reopening schools in England. We consider different combinations of years returning to school, including the potential for teaching students in smaller classes which reduces infection risk. We find that, on its own, returning children to school is unlikely to lead to a second wave of infection, however there remains uncertainty if other measures are relaxed simultaneously.
Even if R remains below one, any return of children to school will inevitably lead to some increase in transmission and therefore to an increase in cases, ICU admissions and, regrettably, deaths. We find that secondary school students returning leads to higher increases than if only primary schools reopen, though in all scenarios the magnitude of changes depends upon the wider context when the reopening of schools occurs. This can be seen in the figure above: if transmission in the general community increases, this alone increases cases (faded colours) and exacerbates the increases seen in by school reopening (solid colours). However the size of the increase due to schools returning is much smaller than the increase due directly to the increase in community transmission.
|Hill, E.M., Atkins, B.D., Keeling, M.J., Tildesley, M., Dyson, L. (2021) "Modelling SARS-CoV-2 transmission in a UK university setting" Epidemics 36: 100476. https://doi.org/10.1016/j.epidem.2021.100476|
The higher education system in the United Kingdom comprises a large student population. Therefore, in the setting of the COVID-19 pandemic bringing together these student communities presents questions regarding the strength of interventions required to control transmission. We constructed a network-based model to capture the interactions of a student population in different settings within a university environment (housing, social and study) and ran an SEIR type epidemic process.
Our work shows high adherence to isolation guidance and effective contact tracing both curbed transmission and reduced the expected time an adhering student would spend in isolation. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared with students resident off-campus. Room isolation as an additional intervention generated minimal benefits. Finally, a one-off mass-testing instance would not drastically reduce the term-long case load or end-of-term prevalence, but regular weekly or fortnightly testing could reduce both measures by more than 50% (compared to having no mass testing).
|Jessica Enright, Edward M. Hill, Helena B. Stage, Kirsty J. Bolton, Emily J. Nixon, Emma L. Fairbanks, Maria L. Tang, Ellen Brooks-Pollock, Louise Dyson, Chris J. Budd, Rebecca B. Hoyle, Lars Schewe, Julia R. Gog & Michael J. Tildesley. (2021) "SARS-CoV-2 infection in UK university students: lessons from September–December 2020 and modelling insights for future student return", Roy. Soc. Open Sci. 8(8). https://doi.org/10.1098/rsos.210310|
In this paper, we present work on SARS-CoV-2 transmission in UK higher education settings using multiple approaches to assess the extent of university outbreaks, how much those outbreaks may have led to spillover in the community, and the expected effects of control measures.
Firstly, we found that the distribution of outbreaks in universities in late 2020 was consistent with the expected importation of infection from arriving students. Considering outbreaks at one university, larger halls of residence posed higher risks for transmission. The dynamics of transmission from university outbreaks to wider communities is complex, and while sometimes spillover does occur, occasionally even large outbreaks do not give any detectable signal of spillover to the local population.
Secondly, we explored proposed control measures for reopening and keeping open universities. We found the proposal of staggering the return of students to university residence is of limited value in terms of reducing transmission. We show that student adherence to testing and self-isolation is likely to be much more important for reducing transmission during term time. Finally, we explored strategies for testing students in the context of a more transmissible variant and found that frequent testing would be necessary to prevent a major outbreak.
Figure: Temporal profiles of cumulative case counts for a simulated population of 15 000 students under differing during-term asymptomatic screening scenarios. We present two scenarios for variant transmissibility: (a) lower-transmissibility variant; (b) higher-transmissibility variant (1.5 times more transmissible than the lower-transmissibility variant). Asymptomatic screening scenarios considered are: no asymptomatic testing (red), each person randomly tested with probability 1/14 (yellow), 1/10 (purple), 1/7 (blue), or 1/3 (green) per day, to simulate testing approximately every 14, 10, 7 or 3 days, respectively. Figure produced from: https://doi.org/10.1098/rsos.210310.
|Hill, E.M., Atkins, B.D., Keeling, M.J., Dyson, L., Tildesley, M. (2021) "A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2" PLoS Comp. Biol. 17(6): e1009058. https://doi.org/10.1371/journal.pcbi.1009058|
As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. We used an individual-based network model to analyse transmission of SARS-CoV-2 amongst a working population that was stratified into work sectors.
Our study found the progress of an outbreak to be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, asynchronous work patterns may help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. Finally, smaller work teams and a greater reduction in transmission risk led to a flatter temporal profile for both infections and the number of people isolating, and reduced the probability of large, long outbreaks.