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expert reaction to two papers looking at schools, test and trace, and the likelihood of a second wave

Two studies, one modelling study from the UK, one real-world study from Australia, both published in the Lancet Child & Adolescent Health, looked at schools, test and trace, and the likelihood of a second wave of COVID-19 occurring.

This Roundup accompanied an SMC Briefing

 

Prof Martin Hibberd, Professor of Emerging Infectious Disease, London School of Hygiene & Tropical Medicine, said:

“This new research, looking at the role of schools in spreading SARS-CoV-2 transmission, is highly informative and timely.  It gives reasonable scenarios where school openings could occur, while COVID-19 cases are not increasing.  However, a clear message is that contact tracing needs to be effective in order to control the number of infections as contact rates increase with school openings, even if children are less effective at transmitting the virus than adults.  The evidence from the UK system of track and trace is not yet clear on whether it will be effective enough to play this role.  In the study, from Australia, their contact tracing identified an average of about 50 contacts per SARS-CoV-2 positive case, from a diversity of cases.  The numbers of contacts in Singapore and South Korea are larger, partially aided by the contact tracing phone Apps.  While in the UK, the “NHS” test and trace are identifying an average of 2 contacts, who typically live in the same household as the case.  This new modelling research identifies thresholds for preventing an increase in cases, that involves increasing the case detection rates from the current much lower levels to at least 65%, while contact tracing needs to identify at least 40% of all the true contacts (that may be more than the few currently being reported).  Between now and when schools open we should be aiming to achieve these goals to give the best chance of preventing further lockdown measures.”

 

Commenting on the modelling study:

Dr Thomas House, Reader in Mathematical Statistics, University of Manchester, said:

“This modelling study highlights the importance of robust testing and tracing as society considers the urgent question of how to restart education.  As the authors state, very many uncertainties still remain in key epidemiological quantities around these questions.

“From the experience in the UK and other countries, there is still potential for significant transmission of coronavirus, however in some areas this has been slower than expected for reasons that are not currently fully understood.

“The study does not attempt to quantify all uncertainties through, for example, a full statistical fit of the model to data, and as such the exact numbers reported should be viewed as plausible but potentially pessimistic scenarios rather than precise predictions.”

 

Commenting on the modelling study:

Prof Matt Keeling, Professor of Populations and Disease, University of Warwick, said:

“The paper addresses an important and timely question: given R is already close to one across the UK, and given that many areas are experiencing ‘spikes’ of infection, how do we allow schools to reopen in September?  There have already been some excellent comments from Prof Graham Medley reported in the media over the weekend, suggesting that there is likely to be a tradeoff between reopening the country and reopening schools – we cannot have both if we want to avoid a second wave.

“In essence the problem is simple, reopening schools is going to increase the reproductive number (R) so if we are to keep R below 1 and prevent a second wave, some other forms of control are necessary.  This basic question has already been addressed by previous publications (e.g. publications 1 and 2 listed below).  However, as with any policy-relevant document, the details are extremely important.

“My biggest concern is that the paper’s title does not completely reflect the model assumptions – the large increase in R that occurs in September is not simply due to schools reopening but also “increases in workplace and community transmission probabilities”.  The authors “assumed that if schools were to reopen full time …. the transmission probability in community settings would be 90% of its pre-lockdown value”.  Therefore the paper actually models the impact of the UK removing almost all of its lock-down measures including the re-opening of schools.  Under such considerations it is unsurprising that a large second wave is predicted.

“The reopening of schools should clearly be a key priority for the UK, many children will have gone over 5 months without setting foot in a classroom.  The key questions are how much impact will school reopening have on the epidemic and what can be done to mitigate this.  The partial reopening that occurred in June has not seen a steep rise in cases nor many local outbreaks associated with schools.  In fact, most school outbreaks are centred around teaching staff rather than students, reflecting the fact that younger children are generally less susceptible and may transmit less when asymptomatic.  (The staff room may be far more dangerous than the classroom.)  The precise dynamics within secondary schools is less clear, given relatively little data, but in countries that have reopened schools this alone has not been seen as a major amplifier of infection.  The paper by Panovska-Griffiths et al takes the view that any increase in R should be balanced by an increase in test-trace-isolate, however it is not suggested in the paper how such improvements to the UK’s existing test and trace scheme could be realised.  Other mitigation methods, such as closing some non-essential leisure activities such as pubs, are more straightforward although have a larger impact on the economy.

“This paper therefore is an important addition to the debate around how the country can safely reopen.  Its focus is mainly on test-trace-isolate to control the relaxation of most lockdown measures, rather than determining an “optimal strategy for reopening schools”, but the general message about the advantages of a strong and swift tracing system are universal.”

1. Brooks-Pollock et al 2020 Using social contact data to predict and compare the impact of social distancing policies with implications for school re-opening.  https://doi.org/10.1101/2020.07.25.20156471

2. Keeling et al 2020 The impact of school reopening on the spread of COVID-19 in England. https://doi.org/10.1101/2020.06.04.20121434

 

Commenting on the modelling study:

Dr Adam Kucharski, Associate Professor in Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, said:

“The paper highlights the importance of testing a high proportion of symptomatic COVID-19 cases and tracing a large proportion of their contacts, but as the authors note, the analysis looks at a very optimistic scenario about the speed and performance of testing – it assumes the test is 100% accurate, results are received within a day, and everyone isolates for two weeks.  In reality, there will be a trade off with speed and effectiveness – even if a high proportion of people ill with COVID-19 are tested, it won’t stop transmission if test results end up taking too long or infected contacts aren’t traced before they become infectious.  To have maximum impact, test & trace will need to identify and isolate a large proportion of infected cases and their contacts, but also do so quickly enough to get ahead of the outbreak.”

 

 

Modelling study: ‘Determining the optimal strategy for reopening schools, the impact of test and trace interventions, and the risk of occurrence of a second COVID-19 epidemic wave in the UK: a modelling study’ by Jasmina Panovska-Griffiths et al. was published in the Lancet Child & Adolescent Health at 23:30 UK time on Monday 3 August 2020.

DOI: 10.1016/S2352-4642(20)30250-9

 

Real-world study: ‘Transmission of SARS-CoV-2 in Australian educational settings: a prospective cohort study’ by Kristine Macartney et al. was published in the Lancet Child & Adolescent Health at 23:30 UK time on Monday 3 August 2020.

DOI: /10.1016/S2352-4642(20)30251-0

 

Declared interests

None received.

 

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