Light switches and clusters: social distancing strategies for COVID-19

  • Modelling suggests that, to prevent current intensive care capacity from being exceeded, some degree of social distancing will continue to be required. This will be until either effective therapies and vaccines are widely available, or a sufficient level of herd immunity is generated.
  • Intermittent ‘light switch’ approaches reduce contact by turning social distancing ‘on’ and ‘off’ like a light switch.
  • Strategic ‘cluster’ approaches reduce high-impact contact – contacts that have a high risk of spreading the disease – rather than reducing the number of interactions.  
  • Whichever approach governments take, clear and specific guidance explaining exactly which activities can be resumed by whom, why, when, and in what way will be needed to support adherence. 
  • This is part of our rapid response content on COVID-19. You can view all our reporting on this topic under COVID-19 This article will be updated as the research progresses.  

The Scottish Government is considering a ‘bubble’ approach to social distancing. The media has reported that UK ministers are considering a similar ‘cluster’ approach to easing current ‘stay at home’ guidance, alongside other ‘light switch’ approaches.   

This article looks at why some degree of prolonged social distancing may be needed and what research tells us about different approaches to social distancing that may form part of exit strategies across the UK.  

What is social distancing? 

Many countries have adopted ‘social distancing’ or ‘physical distancing’ measures in response to the COVID-19 outbreak. They are used to reduce the number of infections and slow transmission by reducing contact and increasing the physical space between people.  

Social distancing can reduce the intensity (peak) of the epidemic (‘flatten the curve’). If fewer people get sick at once, it is less likely that the healthcare system will be overwhelmed. It can also delay the peak (‘move the curve to the right’). This buys time to increase health resources, such as staff, ventilators, hospital beds and therapies, to treat everyone who gets sick.

Different countries define social distancing in different ways. It can refer to a range of non-pharmaceutical interventions (NPIs), such as isolation of individuals with symptoms, quarantine of household members, closing schools and workplaces, and limiting the sizes of gatherings. In the UK, the current interventions mean social distancing for the entire population, with everyone staying at home and only leaving for the limited reasons defined by the Government and staying at least 2 metres away from non-household members.  

Modelling the impact of social distancing  

Observational data on the effects of social distancing during the current COVID-19 pandemic are limited. Statistical models can simulate how infectious diseases spread in a population and provide a way to test how different public health measures might affect transmission in different scenarios.  

Models vary in their complexity and have different advantages and disadvantages. Some require less computing power and are faster to run, while others simulate more realistic contact patterns. Which approach is appropriate depends on the question being asked and whether the assumptions being made make a difference to the results. For example, whether contact networks are expected to differ across cultures, between urban and rural communities, or over time.

Models are being used extensively by national governments and the World Health Organization to support decision-making on the best strategies to pursue in mitigating the effects of COVID-19. 

Why might some degree of social distancing be needed for the next year or longer? 

Previously, we have summarised the models from the Imperial College London group on social distancing. The authors simulated the impact of relaxing social distancing for the entire population after 5 months (from September). They reported that in the absence of a vaccine, this may result in a second wave in winter 2020–21 that would overwhelm Intensive Care Unit (ICU) capacity (estimated at 5,000 in GB). This is because suppression will lead to fewer people being exposed to the virus, and therefore less herd immunity is generated. A second peak in winter could be harder to flatten than in the summer and would also coincide with the annual seasonal increase in peak influenza and other respiratory illnesses, further straining the healthcare system.

Modelling by the London School of Hygiene and Tropical Medicine (LSHTM), as well as Harvard and Stanford Universities, similarly suggests that a substantial resurgence of infections would be expected if lockdown restrictions are lifted at almost any point before a vaccine is available.

This suggests that to prevent current ICU capacity from being exceeded, some degree of social distancing will be required until either effective therapies and vaccines are widely available, or a sufficient level of herd immunity is generated.

However, stringent social distancing measures also result in social, psychological and economic harms. Although comprehensive assessment of the social and economic impact of lockdown measures has not yet been conducted, the World Health Organization and the European Commission have stated that it is likely to be considerable. Early research also suggests that social distancing is having significant impacts on people’s mental health and well-being.

Modelling studies have been used to explore two key strategies for prolonging social distancing to reduce transmission rates, whilst reducing the social, psychological and economic impact of lockdown: intermittent ‘light switch’ approaches and strategic ‘cluster’ approaches.

Intermittent ‘light switch’ approaches to reduce contact 

This is where social distancing is switched on and off like a light switch. Switches could last a set amount of time, such as 3 weeks on followed by 3 weeks off. Or they could be tied to a threshold and triggered by data, such as the number of COVID-19 patients in hospital ICUs.  

The Imperial group modelled the impact of intermittent social distancing in GB. In a non-peer-reviewed report on the impact of NPIs, social distancing was estimated to reduce contact outside the household by 75% overall. Of the scenarios they looked at, they suggested that to remain within ICU capacity (5,000 beds in GB), intermittent social distancing would need to be in force for at least two-thirds of the time until a vaccine was available. They also reported that using a threshold-based trigger would provide more certainty of keeping within ICU capacity than switches that lasted a fixed duration. 

Figure 4. Illustration of adaptive triggering of suppression strategies, for an R0 of 2.2, a policy of all four interventions considered, an “on” trigger of 100 ICU cases per week and an “off” trigger of 50 cases. The policy is in force approximate two thirds of the time. Only social distancing and school and university closure are triggered; other policies remain in force throughout. Weekly ICU incidence is shown in orange, policy triggering in blue.
Illustration of adaptive triggering of suppression strategies, for an R0 of 2.2, a policy of all four interventions considered, an “on” trigger of 100 ICU cases per week and an “off” trigger of 50 cases. The policy is in force approximate two thirds of the time. Only social distancing and school and university closure are triggered; other policies remain in force throughout. Weekly ICU incidence is shown in orange, policy triggering in blue.

Similar findings were reported from modelling by the LSHTM group. In a non-peer reviewed article on the effect of non-pharmaceutical interventions in the UK they noted that using a higher threshold ICU bed occupancy to trigger switches would result in more frequent, shorter lockdown periods, with less time spent in lockdown overall, but higher peak demands on ICU bed capacity.

In the US, intermittent social distancing has been modelled by groups at Stanford and Harvard Universities. These similarly suggest that intermittent social distancing by the entire population until herd immunity is generated could prevent ICU capacity in the US being overwhelmed, without measures being in place indefinitely.

However, it is not clear precisely what the timing, duration, intensity or reach (local versus national) of intermittent social distancing would need to be to reduce the impact of COVID-19.

This depends in part on factors that, in principle, could be determined and used to hone the models. These include the extent of undocumented asymptomatic infections that lead to immunity and seasonal changes in transmission rate, as seen in our latest summary. Effective treatments or vaccines would reduce the duration and intensity of social distancing required. Increasing ICU capacity could also reduce the overall duration of social distancing, while ensuring that critically ill patients receive appropriate care. 

It’s also unclear how feasible a light switch approach would be. To be successful it would require widespread surveillance to monitor when the prevalence thresholds that trigger the beginning or end of distancing have been crossed, as well as zero delay between sensing (ICU occupancy) and reacting (social distancing).  

SAGE (the Scientific Advisory Group for Emergencies), which is advising the UK Government, has noted that there are also practical barriers to stopping and restarting some activities. For example, hiring and furloughing staff and arranging childcare. This could disproportionately affect those on low incomes, potentially leading to community tension. 

Feasibility also depends on levels of adherence. Local triggers may reduce the total number of cases and deaths and reduce peak demands on the healthcare system. But varying timings in difference parts of the country may lead to differences in the implementation of or adherence to social distancing measures.

Strategic ‘cluster’ approaches to reduce high-impact contact 

This is where social distancing is targeted at reducing high-impact contact – contacts that have a high risk of spreading the disease – rather than reducing the number of interactions. This requires clustering contacts, to keep interactions in small groups or ‘bubbles’ and reduce contact between groups to interrupt the transmission of the virus and keep the curve flat. For example, repeated social meetings of individuals of similar ages that live alone are comparatively low risk. However, if each person in a household of five meets their own sets of friends, there is a much higher risk of spreading the disease.   

Groups investigating cluster approaches tend to use models that simulate complex social interactions. These models may help to explain differences between countries in rates of disease transmission and suggest how different control measures will perform in different countries.  

In a non-peer-reviewed study, an Oxford group modelled three strategic cluster approaches designed to ‘keep the curve flat’ by increasing the average network distance between individuals:

  • reducing contact with dissimilar people (homophily), by restricting contact to those who share key attributes, such as age, geography or organisation
  • reducing contact with people who are not connected to one’s usual social contacts (triadic) by decreasing ties that bridge social clusters
  • repeatedly interacting with the same social contacts (repetition), by creating micro-communities.
Animation by the Oxford group of social networks with shorter and longer path lengths by Oxford group. Two example networks, A and C, have the same number of individuals (nodes) and social interactions (ties) but different structures that result in different infection curves, B and D. Bold ties highlight the shortest infection path from the infection source to the last infected individual in the respective networks. Network node colour indicates at which step a node is infected and maps onto colours of histogram bars.

They found that limiting interaction to a few repeated contacts was the most effective strategy.

Maintaining similarity across contacts and decreasing ties that bridge social clusters were also found to be highly effective when compared to reducing contact at random. Based on the findings, the authors suggest that reducing high impact contact, rather than reducing or removing it overall, can mitigate adverse social, behavioural and economic impacts of lockdown approaches while keeping risks low.  

They also suggest that recommendations to reduce contact strategically may be more palatable to people than complete isolation, and therefore lead to higher adherence. To date however, there has not been much discussion of how feasible this approach would be.

The LSHTM group is currently using social and behavioural data from over 40,000 individuals in the UK to model strategic cluster approaches for households with children. Findings will be available in the next few weeks.

 Illustration by the Oxford group of average infection curves comparing four contact reduction strategies to doing nothing. The x-axis represents time as measured in network distance (steps) and the y-axis represents the number of individuals infected out of a population of 1,000. The first scenario in blue shows an interaction model in which there is no social distancing and people interact at random. The next four strategies all employ a 50% contact reduction compared to doing nothing to compare the different contact reduction strategies.
Illustration by the Oxford group of average infection curves comparing four contact reduction strategies to doing nothing. The x-axis represents time as measured in network distance (steps) and the y-axis represents the number of individuals infected out of a population of 2,000. The first scenario in blue shows an interaction model in which there is no social distancing and people interact at random. The next four strategies all employ a 50% contact reduction compared to doing nothing to compare the different contact reduction strategies.

Communicating strategies to the public 

Intermittent light switch approaches and strategic cluster approaches could, in principle, be applied to the entire population or to specific groups only. The modelling studies reviewed above tend to focus on scenarios where the approach is applied to everyone.

The Scottish Government has stated that it if pursues a cluster approach, it would not apply to people currently in the ‘shielded’ group, who would be asked to continue to stay at home. However, it states no decision has been made as to how it could be applied to people who are not shielding but are at heightened risk (over 70s, pregnant, certain pre-existing conditions). 

The report by the Oxford group does not specifically assess the potential impact of using a cluster approach for specific groups only. However, the authors argue that cluster approaches provide a basis for concrete behavioural guidelines for different contexts. For example, guidelines on the need for consistent networks of medical or community-based carers for people at heightened risk from COVID-19 (older people or those with pre-existing conditions). This would reduce the risk of the virus entering the cluster and, if it does, to limit the transmission of the virus.

The behavioural science subgroup of SAGE (SPI-B) has noted that there are different opinions on how the public would respond if social distancing measures were applied to some groups and not others. Some experts thought it would cause discontent, while others thought the public would find it acceptable if it was explained that the reason was to generate some herd immunity.  

Whichever approach governments take to prolong social distancing, effectively communicating recommendations to the public will be essential. SPI-B has stated that to increase adherence to social distancing measures, clear and specific guidance will be needed, explaining exactly which activities can be resumed by whom, why, when, and in what way. SPI-B has also stated that, while simple rules are easiest to follow, gradually resuming activity cannot be covered by a simple rule such as ‘stay at home’ and that guidance and its implementation need to be flexible and comprehensive and allow for differences in risks to and from people.

In regard to intermittent approaches, the modelling subgroup of SAGE has noted that the duration of switches would be less important than the extent to which contacts are reduced. However, it is unclear what individuals would need to do in their daily lives to reduce their contacts to set levels, say 40% or 75%, as switches were turned off and on.

The Oxford group have argued that cluster approaches could be used to empower the public with more knowledge. This would allow them to design their own personal distancing strategies to generate safe social networks in the medium to long term. As of 7 May, SAGE has not published any comment on cluster approaches.


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