What can deliberately infecting healthy people tell us about infectious diseases? How is this useful for developing treatments, and how do we manage the risks?
- On 20th March, the Scientific Advisory Group for Emergencies (SAGE) released the evidence behind the government response to Coronavirus disease (COVID-19). This series of short articles summarises these 32 documents. You can view all our reporting on this topic under COVID-19.
- This article covers the effectiveness of measures such as school closures and mass gathering.
- It goes over different scenarios and what models predict for the UK.
SPI-M-O: Consensus view on the impact of mass school closures (19 February 2020)
On 19th February, SPI-M-O was asked to comment on the possible impact of school closures on the epidemic. Previous modelling around school closures had been done for pandemic influenza. During the 2009 pandemic, the summer school holiday did interrupt transmission. This resulted in two waves, one before summer and the other in autumn when children returned.
At the time of this guidance, the role of children in transmitting COVID-19 was unclear. The smaller the role of children in transmission, the lower the impact of school closures. The group therefore based how transmissible the infection is by children on their experience of influenza. However, they expected the impact of school closures to be less than it was in 2009. That’s because, when compared with influenza:
- The serial interval (the time between infection starting in one person to infection starting in their contact) is longer for COVID-19. Schools would need to be closed for longer to have the same impact on COVID-19.
- R0 (average number of people infected by each case) is higher in Wuhan for COVID-19.
- Some adults have pre-existing immunity to influenza, leaving children as the main transmitters. For COVID-19, both adults and children can be expected to be equally susceptible and therefore both act as transmitters.
Developing models of school closures
Three models were developed. These models considered different scenarios, including proactive compared with reactive school closures. When developing models, assumptions need to be made as exact data are not known. Sometimes models can be “sensitive” to these assumptions. This means that changing the value of the assumptions affects the results from modelling. In this case, the models were sensitive to:
- The precise age-structures of mixing (mixing between school year groups).
- How the infectiousness of an individual changes during their illness.
- How school closures lead to different types of mixing. For example, instead of meeting up in school children meeting up at their homes or in parks.
- How susceptible children are to COVID-19. And if infected, how easily they transmit it to others.
Similarities and differences in results from the models
All three models suggested that, regardless of approach, school closures will only delay the epidemic peak for 3 weeks maximum. In many cases the models suggested it may be much less than this. The models also suggested that the impact on total numbers of cases will be very limited.
School closures may extend how long the UK epidemic lasts, which would reduce its peak (flattening the curve). In general, longer school closures are more likely to be effective than shorter ones. Closures may reduce the peak number of cases, but their effect on the final epidemic size will be limited. The ability of school closures to do this is very dependent on the R0 (average number of people infected by each case). The higher R0 is, the less effective school closures will be.
There was a difference between the models when considering the impact on the peak size of the epidemic. Where models were based on each individual students, a school closure of 6 to 12 weeks will lead to a 20 to 60% reduction in the peak. However, where models were based on a population, this effect reduced to only a 7.5 to 30% reduction.
The effect of school closures for a range of R0 values is shown in Figure 1. This model assumed:
- Children and adults are equally susceptible to the infection
- Children and adults can equally transmit the infection
- Closing schools leads to increased household contact of 25%
From this figure it can be seen that, with an R0 of 1.7, a 2-week closure would reduce peak cases by just over 10%. A 16-week closure would reduce it by 65%. However, this effect decreases substantially if the R0 increases. At an R0 of 2.9, a 16-week closure doesn’t have much more impact than a 2-week closure.
When should school closures start?
The SPI-M-O view was that for school closures of 6 weeks or longer, starting them as early as possible will have the most impact. The timing of short school closures will not change the course of the epidemic as much.
Closing schools for 2 to 4 weeks may lead to two peaks of cases, as seen in the 2009 influenza pandemic. They may work best when used just before the peak, but this would be very difficult to time.
So the impact of school closures is highly dependent on their timing. But predicting the timing of the epidemic peak is very difficult. This means that it will be very hard to predict when best to start school closures.
Other things that were considered
A key unknown in the models is what the effect of closing a school will be on contact or social mixing patterns. For example, how will contact between individuals in a household change? How will contact with grandparents or other family members change? Will social mixing continue in parks and playgrounds? And what will all of these changes do to the transmission of the virus?
School closures will have significant economic and educational costs. There is a risk of increasing absence among the health and social care workforce. In addition, there is a risk that parents will rely on grandparents for their children’s care. This would lead to more severe cases. And, as in 2009, when schools reopen there may again be an increase in cases.
SPI-M-O: Consensus view on public gatherings (11 February 2020)
On 11th February, SPI-M-O provided a viewpoint on stopping mass/public gatherings. They considered the direct impact on the spread of the coronavirus through the population. Their conclusion was that impact would be low. This is because such gatherings would only make up a small proportion of the attendee’s contacts with other people.
There may also be indirect impacts of stopping public gatherings. There is a risk of replacement of banned activities with others. For example, rather than going to a football match, fans might watch it in the pub. This might accelerate spread. But the spread may also be slowed because the public change other behaviours, such as stopping handshakes, due to the message these cancellations would give.
Rather than simply stopping large gatherings, more impactful would be to stop all non-essential activities. There are lots of small gatherings in any one week compared with large gatherings. The cumulative effect of stopping all this contact would therefore be greater.
The size of the event isn’t what determines transmission. What impacts transmission is the number of people you have close contact with and how long this contact is for. So, the risk of attending a large event can be similar to a small one.
Some gatherings may pose more of a risk than others. For example, in a cinema there may be minimal contact with other people. Other gatherings may attract more older people, and therefore would be higher risk.
SPI-B: Insights on public gatherings (12 March 2020)
SPI-B was also asked to provide insights into the behavioural aspects of banning public gatherings. However, they had very little evidence to depend upon to inform their thinking. Therefore, most of their comments were based on expert opinion.
Public expectations of a ban
When considering social and behavioural interventions, SPI-B noted that communication is key. In the context of other countries banning or restricting gatherings, a clear expectation of why this is not happening in the UK is needed.
The Department of Health and Social Care started weekly polling of 2000 people from early on in the outbreak. Since 10th February they have been asking the public if they agree or disagree that keeping away from crowded places is a good way to prevent COVID-19. At a poll between the 9th and the 11th March, 73% of respondents agreed with this statement.
A YouGov survey of 1618 people reported that 36% of respondents thought the UK should cancel large sporting events and concerts. In a survey of 2031 people, 22% felt the Government should cancel Euro 2020. Without careful communication, by not banning events the public may feel the Government isn’t doing enough.
Perceptions and consequences of a ban
If a decision is made to ban gatherings, a clear explanation of the legitimacy of this decision will be needed. Disruptive interventions not seen as legitimate may increase public dissatisfaction. The figures given above suggest that a majority of people feel that events should not be cancelled.
SPI-B could not agree on the impact of not applying widespread social distancing when isolating at-risk groups. Suggesting that only one section of society should isolate may lead to discontent.
SPI-B was also concerned that cancellation of events will displace activity elsewhere. For example, cancelling football matches will lead to people watching it in the pub. Applying multiple interventions at the same time may have complex and unforeseen effects.
In order for the intervention to be seen as fair, any measure will have to be equally applied to large and small gatherings. Any ambiguity or loopholes could also lead to tension. Following the modelling presented on 12th March, SPI-B noted that reducing social contacts would reduce risk of infection. The efficacy of day-to-day adjustments to reduce contacts and increase social distancing should be communicated.
You can find more content from POST on COVID-19 here.
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