Social bubbles, physical distancing, masks: Which method is most effective in controlling COVID-19 spread at events
A new study published in the Proceedings of the National Academy of Sciences (PNAS) has conducted precisely this type of evaluation of various social settings which can lead to COVID-19 outbreaks to understand which preventive methods are best suited for which type of situation
When the COVID-19 pandemic first started, various steps were taken to control the transmission of this disease globally. From imposing lockdowns and shutting down schools to limiting the number of people allowed to gather at an event, many measures were introduced to control the rate of infection, which would help healthcare systems handle the COVID-19 caseload better.
However, as economies are opening up and travel bans are being lifted, people are now able to move more freely without restrictions and can reduce their risks of COVID-19 as long as they stick to handwashing, wearing masks, social distancing and limiting interactions in crowded spaces.
Even so, the world is now seeing another surge in the number of new infections, indicating that a better evaluation of methods to control the spread of COVID-19 is needed urgently.
A new study published in the Proceedings of the National Academy of Sciences (PNAS) has conducted precisely this type of evaluation of various social settings which can lead to COVID-19 outbreaks to understand which preventive methods are best suited for which type of situation.
Introducing Event R
To be better able to guide both policymakers and event planners, the researchers behind this study have developed a conceptual framework and model called “Event R”.
According to this concept, there is a fundamental mathematical relationship between three factors at any social event where a single person with COVID-19 infection is present:
- The number of people in contact with the infectious individual
- The precise duration of time for which they are in contact
- The risk of transmission per unit time
The researchers calculated how these factors interacted during reported events where transmission and subsequent COVID-19 infections occurred and created an equation which can be implemented in various settings to analyse their transmission risks.
The equation related the Event R to the level of crowding at the event, the level of mixing among people (meaning if they stay within their social bubble or mix with the crowd more widely) and the propensity of transmission by the infectious individual within such a setting. The greater the calculated Event R, the higher the risk of an event turning into a potential outbreak or superspreading event.
Why social settings matter
The researchers then set out to classify the types of social events into two types based on this equation:
- Linear events, where the probability of transmission is low, like outdoor events and public transport with masks and social distancing
- Saturating events, where the probability of transmission is high, like in bars, night clubs, indoor sporting events and overcrowded workplaces
The researchers determined that proper social distancing of at least one or two meters is effective in reducing COVID-19 infection spread whether an event is saturating or linear. However, in the case of mask-wearing and creating social bubbles, the efficacy of the preventive measure depends more on the setting.
The researchers reveal that during saturating events like parties, crowded workplaces or school classrooms, having small social bubbles that stick together throughout the exposure period and don’t mix with others may be more effective than only wearing masks.
This is because the researchers calculated that even if wearing masks can reduce the transmission rate by 50 percent, it won’t have the same effect on the probability of transmission at such huge events. What’s more, having social bubbles in such settings can aid in contact tracing better later, in case an outbreak does occur.
On the other hand, in linear events, social bubbles are almost ineffective, while wearing masks can have much higher efficacy. The researchers also suggest that organisers of events should assess the Event R for their setting based on a proper exploration of the transmission rates in their area.
Estimating the effects of measures such as mask-wearing and using physical barriers like plexiglass partitions or face shields in saturating events can be very difficult to calculate, so reducing the crowd size and enforcing better social distancing in these events is crucial.
This is why designing measures to target each and every type of activity is necessary for all event planners, school and university boards, sporting institutions and regional or national policymakers.
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