scholarly journals The impact of school reopening on the spread of COVID-19 in England

2021 ◽  
Vol 376 (1829) ◽  
pp. 20200261
Author(s):  
Matt J. Keeling ◽  
Michael J. Tildesley ◽  
Benjamin D. Atkins ◽  
Bridget Penman ◽  
Emma Southall ◽  
...  

By mid-May 2020, cases of COVID-19 in the UK had been declining for over a month; a multi-phase emergence from lockdown was planned, including a scheduled partial reopening of schools on 1 June 2020. Although evidence suggests that children generally display mild symptoms, the size of the school-age population means the total impact of reopening schools is unclear. Here, we present work from mid-May 2020 that focused on the imminent opening of schools and consider what these results imply for future policy. We compared eight strategies for reopening primary and secondary schools in England. Modifying a transmission model fitted to UK SARS-CoV-2 data, we assessed how reopening schools affects contact patterns, anticipated secondary infections and the relative change in the reproduction number, R . We determined the associated public health impact and its sensitivity to changes in social distancing within the wider community. We predicted that reopening schools with half-sized classes or focused on younger children was unlikely to push R above one. Older children generally have more social contacts, so reopening secondary schools results in more cases than reopening primary schools, while reopening both could have pushed R above one in some regions. Reductions in community social distancing were found to outweigh and exacerbate any impacts of reopening. In particular, opening schools when the reproduction number R is already above one generates the largest increase in cases. Our work indicates that while any school reopening will result in increased mixing and infection amongst children and the wider population, reopening schools alone in June 2020 was unlikely to push R above one. Ultimately, reopening decisions are a difficult trade-off between epidemiological consequences and the emotional, educational and developmental needs of children. Into the future, there are difficult questions about what controls can be instigated such that schools can remain open if cases increase. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

Author(s):  
Matt J. Keeling ◽  
Michael J. Tildesley ◽  
Benjamin D. Atkins ◽  
Bridget Penman ◽  
Emma Southall ◽  
...  

AbstractBackgroundIn the UK, cases of COVID-19 have been declining since mid-April and there is good evidence to suggest that the effective reproduction number has dropped below 1, leading to a multiphase relaxation plan for the country to emerge from lockdown. As part of this staggered process, primary schools are scheduled to partially reopen on 1st June. Evidence from a range of sources suggests that children are, in general, only mildly affected by the disease and have low mortality rates, though there is less certainty regarding children’s role in transmission. Therefore, there is wide discussion on the impact of reopening schools.MethodsWe compare eight strategies for reopening primary and secondary schools in England from 1st June, focusing on the return of particular year groups and the associated epidemic consequences. This is assessed through model simulation, modifying a previously developed dynamic transmission model for SARS-CoV-2. We quantify how the process of reopening schools affected contact patterns and anticipated secondary infections, the relative change in R according to the extent of school reopening, and determine the public health impact via estimated change in clinical cases and its sensitivity to decreases in adherence post strict lockdown.FindingsWhilst reopening schools, in any form, results in more mixing between children, an increase in R and hence transmission of the disease, the magnitude of that increase can be low dependent upon the age-groups that return to school and the behaviour of the remaining population. We predict that reopening schools in a way that allows half class sizes or that is focused on younger children is unlikely to push R above one, although there is noticeable variation between the regions of the country. Given that older children have a greater number of social contacts and hence a greater potential for transmission, our findings suggest reopening secondary schools results in larger increases in case burden than only reopening primary schools; reopening both generates the largest increase and could push R above one in some regions. The impact of less social-distancing in the rest of the population, generally has far larger effects than reopening schools and exacerbates the impacts of reopening.DiscussionOur work indicates that any reopening of schools will result in increased mixing and infection amongst children and the wider population, although the opening of schools alone is unlikely to push the value of R above one. However, impacts of other recent relaxations of lockdown measures are yet to be quantified, suggesting some regions may be closer to the critical threshold that would lead to a growth in cases. Given the uncertainties, in part due to limited data on COVID-19 in children, school reopening should be carefully monitored. Ultimately, the decision about reopening classrooms is a difficult trade-off between increased epidemiological consequences and the emotional, educational and developmental needs of children.


2021 ◽  
Author(s):  
Jasmina Panovska-Griffiths ◽  
Robyn Stuart ◽  
Cliff Kerr ◽  
Katherine Rosenfeld ◽  
Dina Mistry ◽  
...  

Abstract Background Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the new variant of the SARS-CoV-2 virus, B.1.1.7, a third national lockdown was imposed from January 5, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, it is important to assess the conditions under which reopening schools from early March is likely to lead to resurgence of the epidemic. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. Methods We used our previously published model, Covasim, to model the emergence of B.1.1.7 over September 1, 2020 to January 31, 2021. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, assuming 200,000 daily doses of the vaccine in people 75 years or older with vaccination that offers 95% reduction in disease acquisition and 10% reduction of transmission blocking. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (Y11 and Y13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-Rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2020. Results Our calibration across different scenarios is consistent with the new variant B.1.1.7 being around 60% more transmissible. Strict social distancing measures, i.e. national lockdowns, are required to contain the spread of the virus and control the hospitalisations and deaths during January and February 2021. The national lockdown will reduce the number of cases by early March levels similar to those seen in October with R also falling and remaining below 1 during the lockdown. Infections start to increase when schools open but if other parts of society remain closed this resurgence is not sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas will lead to lower increases in cases and R than if all schools open. Under the current vaccination assumptions and across the set of scenarios considered, R would increase above 1 if society reopens simultaneously, simulated here from April 19, 2021.Findings Our findings suggest that stringent measures are necessary to mitigate the increase in cases and bring R below 1 over January and February 2021. It is plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 may keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, with the vaccination strategy we model, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.


2021 ◽  
Author(s):  
J. Panovska-Griffiths ◽  
R.M. Stuart ◽  
C.C. Kerr ◽  
K. Rosenfield ◽  
D. Mistry ◽  
...  

BackgroundFollowing the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the new variant of the SARS-CoV-2 virus, B.1.1.7, a third national lockdown was imposed from January 5, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, it is important to assess the conditions under which reopening schools from early March is likely to lead to resurgence of the epidemic. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021.MethodsWe used our previously published model, Covasim, to model the emergence of B.1.1.7 over September 1, 2020 to January 31, 2021. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, assuming 200,000 daily doses of the vaccine in people 75 years or older with vaccination that offers 95% reduction in disease acquisition and 10% reduction of transmission blocking. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (Y11 and Y13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-Rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2020.ResultsOur calibration across different scenarios is consistent with the new variant B.1.1.7 being around 60% more transmissible. Strict social distancing measures, i.e. national lockdowns, are required to contain the spread of the virus and control the hospitalisations and deaths during January and February 2021. The national lockdown will reduce the number of cases by early March levels similar to those seen in October with R also falling and remaining below 1 during the lockdown. Infections start to increase when schools open but if other parts of society remain closed this resurgence is not sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas will lead to lower increases in cases and R than if all schools open. Under the current vaccination assumptions and across the set of scenarios considered, R would increase above 1 if society reopens simultaneously, simulated here from April 19, 2021.FindingsOur findings suggest that stringent measures are necessary to mitigate the increase in cases and bring R below 1 over January and February 2021. It is plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 may keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, with the vaccination strategy we model, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.


Author(s):  
Ellen Brooks-Pollock ◽  
Jonathan M Read ◽  
Angela R McLean ◽  
Matt J Keeling ◽  
Leon Danon

Background Social distancing measures, including school closures, are being used to control SARS-CoV-2 transmission in many countries. Once "lockdown" has driven incidence to low levels, selected activities are being permitted. Re-opening schools is a priority because of the welfare and educational impact of closures on children. However, the impact of school re-opening needs to be considered within the context of other measures. Methods We use social contact data from the UK to predict the impact of social distancing policies on the reproduction number. We calibrate our tool to the COVID-19 epidemic in the UK using publicly available death data and Google Community Mobility Reports. We focus on the impact of re-opening schools against a back-drop of wider social distancing easing. Results We demonstrate that pre-collected social contact data, combined with incidence data and Google Community Mobility Reports, is able to provide a time-varying estimate of the reproduction number (R). From an pre-control setting when R=2.7 (95%CI 2.5, 2.9), we estimate that the minimum reproduction number that can be achieved in the UK without limiting household contacts is 0.45 (95%CI:0.41-0.50); in the absence of other changes, preventing leisure contacts has a smaller impact (R=2.0,95%CI:1.8-2.4) than preventing work contacts (R=1.5,95%CI:1.4-1.7). We find that following lockdown (when R=0.7 (95% CI 0.6, 0.8)), opening primary schools in isolation has a modest impact on transmission R=0.83 (95%CI:0.77-0.90) but that high adherence to other measures is needed. Opening secondary schools as well as primary school is predicted to have a larger overall impact (R=0.95,95%CI:0.85-1.07), however transmission could still be controlled with effective contact tracing. Conclusions Our findings suggest that primary school children can return to school without compromising transmission, however other measures, such as social distancing and contract tracing, are required to control transmission if all age groups are to return to school. Our tool provides a mapping from policies to the reproduction number and can be used by policymakers to compare the impact of social-easing measures, dissect mitigation strategies and support careful localized control strategies.


2021 ◽  
Vol 17 (1) ◽  
pp. e1008619
Author(s):  
Matt J. Keeling ◽  
Edward M. Hill ◽  
Erin E. Gorsich ◽  
Bridget Penman ◽  
Glen Guyver-Fletcher ◽  
...  

Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a “stay at home” order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020 on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. We find that significant relaxation of social distancing measures from 7th May onwards can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Our work confirms the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provides strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units.


Author(s):  
Nicholas G. Davies ◽  
Adam J. Kucharski ◽  
Rosalind M. Eggo ◽  
Amy Gimma ◽  
W. John Edmunds ◽  
...  

AbstractBackgroundNon-pharmaceutical interventions have been implemented to reduce transmission of SARS-CoV-2 in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been critical to support evidence-based policymaking during the early stages of the epidemic.MethodsWe used a stochastic age-structured transmission model to explore a range of intervention scenarios, including the introduction of school closures, social distancing, shielding of elderly groups, self-isolation of symptomatic cases, and extreme “lockdown”-type restrictions. We simulated different durations of interventions and triggers for introduction, as well as combinations of interventions. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (intensive care unit, ICU) treatment, and deaths.FindingsWe found that mitigation measures aimed at reducing transmission would likely have decreased the reproduction number, but not sufficiently to prevent ICU demand from exceeding NHS availability. To keep ICU bed demand below capacity in the model, more extreme restrictions were necessary. In a scenario where “lockdown”-type interventions were put in place to reduce transmission, these interventions would need to be in place for a large proportion of the coming year in order to prevent healthcare demand exceeding availability.InterpretationThe characteristics of SARS-CoV-2 mean that extreme measures are likely required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs.Research in ContextEvidence before this studyAs countries have moved from early containment efforts to planning for the introduction of large-scale non-pharmaceutical interventions to control COVID-19 outbreaks, epidemic modelling studies have explored the potential for extensive social distancing measures to curb transmission. However, it remains unclear how different combinations of interventions, timings, and triggers for the introduction and lifting of control measures may affect the impact of the epidemic on health services, and what the range of uncertainty associated with these estimates would be.Added value of this studyUsing a stochastic, age-structured epidemic model, we explored how eight different intervention scenarios could influence the number of new cases and deaths, as well as intensive care beds required over the projected course of the epidemic. We also assessed the potential impact of local versus national targeting of interventions, reduction in leisure events, impact of increased childcare by grandparents, and timing of triggers for different control measures. We simulated multiple realisations for each scenario to reflect uncertainty in possible epidemic trajectories.Implications of all the available evidenceOur results support early modelling findings, and subsequent empirical observations, that in the absence of control measures, a COVID-19 epidemic could quickly overwhelm a healthcare system. We found that even a combination of moderate interventions – such as school closures, shielding of older groups and self-isolation – would be unlikely to prevent an epidemic that would far exceed available ICU capacity in the UK. Intermittent periods of more intensive lockdown-type measures are predicted to be effective for preventing the healthcare system from being overwhelmed.


2021 ◽  
Vol 17 (8) ◽  
pp. e1009264
Author(s):  
Simon Mauras ◽  
Vincent Cohen-Addad ◽  
Guillaume Duboc ◽  
Max Dupré la Tour ◽  
Paolo Frasca ◽  
...  

The COVID-19 epidemic has forced most countries to impose contact-limiting restrictions at workplaces, universities, schools, and more broadly in our societies. Yet, the effectiveness of these unprecedented interventions in containing the virus spread remain largely unquantified. Here, we develop a simulation study to analyze COVID-19 outbreaks on three real-life contact networks stemming from a workplace, a primary school and a high school in France. Our study provides a fine-grained analysis of the impact of contact-limiting strategies at workplaces, schools and high schools, including: (1) Rotating strategies, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off strategies, where the whole group alternates periods of normal work interactions with complete telecommuting. We model epidemics spread in these different setups using a stochastic discrete-time agent-based transmission model that includes the coronavirus most salient features: super-spreaders, infectious asymptomatic individuals, and pre-symptomatic infectious periods. Our study yields clear results: the ranking of the strategies, based on their ability to mitigate epidemic propagation in the network from a first index case, is the same for all network topologies (workplace, primary school and high school). Namely, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day. Moreover, our results show that below a certain threshold for the original local reproduction number R 0 l o c a l within the network (< 1.52 for primary schools, < 1.30 for the workplace, < 1.38 for the high school, and < 1.55 for the random graph), all four strategies efficiently control outbreak by decreasing effective local reproduction number to R 0 l o c a l < 1. These results can provide guidance for public health decisions related to telecommuting.


Author(s):  
Stephen RJ Sparks ◽  
William P Aspinall ◽  
Ellen Brooks-Pollock ◽  
Leon Danon ◽  
Roger Cooke ◽  
...  

Background Contact patterns are the drivers of close-contacts infections, such as COVID-19. In an effort to control COVID-19 transmission in the UK, schools were closed on 23 March 2020. With social distancing in place, Primary Schools were partially re-opened on 1 June 2020, with plans to fully re-open in September 2020. The impact of social distancing and risk mitigation measures on childrens contact patterns is not known. Methods We conducted a structured expert elicitation of a sample of Primary Headteachers to quantify contact patterns within schools in pre-COVID-19 times and how these patterns were expected to change upon re-opening. Point estimates with uncertainty were determined by a formal performance-based algorithm. Additionally, we surveyed school Headteachers about risk mitigation strategies and their anticipated effectiveness. Results Expert elicitation provides estimates of contact patterns that are consistent with contact surveys. We report mean number of contacts per day for four cohorts within schools along with a range at 90% confidence for the variations of contacts among individuals. Prior to lockdown, we estimate that, mean numbers per day, younger children (Reception and Year 1) made 15 contacts [range 8..35] within school, older children (Year 6) 18 contacts [range 5..55], teaching staff 25 contacts [range 4..55) and non-classroom staff 11 contacts [range 2..27]. Compared to pre-COVID times, after schools re-opened the mean number of contacts were reduced by about 53% for young children, about 62% for older children, about 60% for classroom staff and about 64% for other staff. Contacts between teaching and non-teaching staff reduced by 80%, which is consistent with other independent estimates. The distributions of contacts per person are asymmetric indicating a heavy tail of individuals with high contact numbers. Conclusions We interpret the reduction in childrens contacts as a consequence of efforts to reduce mixing with interventions such as forming groups of children (bubbles) who are organized to learn together to limit contacts. Distributions of contacts for children and adults can be used to inform COVID-19 transmission modelling. Our findings suggest that while official DfE guidelines form the basis for risk mitigation in schools, individual schools have adopted their own bespoke strategies, often going beyond the guidelines.


Author(s):  
Mirjam E. Kretzschmar ◽  
Ganna Rozhnova ◽  
Michiel van Boven

AbstractBackgroundNovel coronavirus (SARS-CoV-2) has extended its range of transmission in all parts of the world, with substantial variation in rates of transmission and severity of associated disease. Many countries have implemented social distancing as a measure to control further spread.MethodsWe evaluate whether and under which conditions containment or slowing down COVID-19 epidemics are possible by isolation and contact tracing in settings with various levels of social distancing. We use a stochastic transmission model in which every person generates novel infections according to a probability distribution that is affected by the incubation period distribution (time from infection to symptoms), distribution of the latent period (time from infection to onset of infectiousness), and overall transmissibility. The model distinguishes between close contacts (e.g., within a household) and other contacts in the population. Social distancing affects the number of contacts outside but not within the household.FindingsThe proportion of asymptomatic or unascertained cases has a strong impact on the controllability of the disease. If the proportion of asymptomatic infections is larger than 30%, contact tracing and isolation cannot achieve containment for an R0 of 2.5. Achieving containment by social distancing requires a reduction of numbers of non-household contacts by around 90%. Depending on the realized level of contact reduction, tracing and isolation of only household contacts, or of household and non-household contacts are necessary to reduce the effective reproduction number to below 1. A combination of social distancing with isolation and contact tracing leads to synergistic effects that increase the prospect of containment.InterpretationIsolation and contact tracing can be an effective means to slow down epidemics, but only if the majority of cases are ascertained. In a situation with social distancing, contact tracing can act synergistically and tip the scale towards containment, and can therefore be a tool for controlling COVID-19 epidemics as part of an exit strategy from current lockdown measures.FundingThis research was partly funded by ZonMw project number 91216062.Research in contextEvidence before this studyAs of 8 April 2020, the novel coronavirus (SARS-CoV-2) has spread to more than 170 countries and has caused near 90,000 deaths of COVID-19 worldwide. In the absence of effective medicines and vaccines, the preventive measures are limited to social distancing, isolation of confirmed and suspected cases, and identification and quarantining of their contacts. Evidence suggests that a substantial portion of transmission may occur before the onset of symptoms and before cases can be isolated, and that many cases remain unascertained. This has potentially important implications for the prospect of containment by combinations of these measures.Added value of this studyUsing a stochastic transmission model armed with current best estimates of epidemiological parameters, we evaluated under which conditions containment could be achieved with combinations of social distancing, isolation and contact tracing. We investigated the level of social distancing needed for containment, and how an additional implementation of isolation and contact tracing may likely help to in reducing the effective reproduction number to below 1, the critical threshold. We analyzed what proportion of household and non-household contacts need to be isolated effectively to achieve containment depending on the level of social distancing in the population. We estimated the impact of combinations of these measures on epidemic growth rate and doubling time for the number of infections. We find that under realistic assumptions on the level of social distancing, additional isolation and contact tracing are needed for stopping the epidemic. Whether quarantining only household contacts is sufficient, depends on levels of social distancing and timeliness of tracing and isolation.Implications of all the available evidenceOur analyses based on best understanding of the epidemiology of COVID-19, highlight that if social distancing is not complete, isolation and contact tracing at least of household contacts can help to delay and lower the epidemic peak. High levels of timely contact tracing of household and non-household contacts may be sufficient to control the epidemic.


2020 ◽  
Author(s):  
Jasmina Panovska-Griffiths ◽  
Cliff Kerr ◽  
Robyn Margaret Stuart ◽  
Dina Mistry ◽  
Daniel Klein ◽  
...  

Background In order to slow down the spread of SARS-CoV-2, the virus causing the COVID-19 pandemic, the UK government has imposed strict physical distancing (lockdown) measures including school 'dismissals' since 23 March 2020. As evidence is emerging that these measures may have slowed the spread of the pandemic, it is important to assess the impact of any changes in strategy, including scenarios for school reopening and broader relaxation of social distancing. This work uses an individual-based model to predict the impact of a suite of possible strategies to reopen schools in the UK, including that currently proposed by the UK government. Methods We use Covasim, a stochastic agent-based model for transmission of COVID-19, calibrated to the UK epidemic. The model describes individuals' contact networks stratified as household, school, work and community layers, and uses demographic and epidemiological data from the UK. We simulate a range of different school reopening strategies with a society-wide relaxation of lockdown measures and in the presence of different non-pharmaceutical interventions, to estimate the number of new infections, cumulative cases and deaths, as well as the effective reproduction number with different strategies. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages. Findings We found that with increased levels of testing of people (between 25% and 72% of symptomatic people tested at some point during an active COVID-19 infection depending on scenarios) and effective contact-tracing and isolation for infected individuals, an epidemic rebound may be prevented across all reopening scenarios, with the effective reproduction number (R) remaining below one and the cumulative number of new infections and deaths significantly lower than they would be if testing did not increase. If UK schools reopen in phases from June 2020, prevention of a second wave would require testing 51% of symptomatic infections, tracing of 40% of their contacts, and isolation of symptomatic and diagnosed cases. However, without such measures, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a secondary pandemic wave, as are other scenarios for reopening. When infectiousness of <20 year olds was varied from 100% to 50% of that of older ages, our findings remained unchanged. Interpretation To prevent a secondary COVID-19 wave, relaxation of social distancing including reopening schools in the UK must be implemented alongside an active large-scale population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of symptomatic and diagnosed individuals. Such combined measures have a greater likelihood of controlling the transmission of SARS-CoV-2 and preventing a large number of COVID-19 deaths than reopening schools and society with the current level of implementation of testing and isolation of infected individuals.


Sign in / Sign up

Export Citation Format

Share Document