A new study suggests that COVID-19 super-spreading events are more common than originally believed. Limiting gatherings to 10 or fewer people could help prevent this issue.
Scientists have spent the better part of the past year trying to make sense of the novel coronavirus, SARS-CoV-2, which causes the disease responsible for the ongoing pandemic.
As COVID-19 cases approach 49 million worldwide, researchers continue to study how the virus spreads in an effort to find ways of reducing the transmission.
A new study from researchers at the Massachusetts Institute of Technology (MIT), in Cambridge, examines the spread of COVID-19 in large gatherings. It shows that super-spreading events are more common — and have more impact on the overall spread of the virus — than previously thought.
In their study paper, published in Proceedings of the National Academy of Sciences, theresearchers explain that these events have an “outsized” role in virus transmission.
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‘Super-spreading events’ defined
On average, SARS-CoV-2 spreads from one person to two to three others. In some cases, the virus does not transmit. But it can pass to dozens of other people in a relatively short period.
A super-spreading event is a gathering where the virus transmits from one person to several others. The researchers behind the present study considered super-spreading to take place when at least six people acquired the virus.
One such event, a choir practice, took place in Skagit County, WA. Scientists tracked 53 cases of COVID-19 back to one person with a SARS-CoV-2 infection at the rehearsal.
Of the 61 people who attended the 2.5-hour event, 33 tested positive for COVID-19 and 20 others had probable cases.
Since COVID-19 primarily transmits through respiratory droplets, the choir practice was a prime environment for it to spread.
Some other notable COVID-19 super-spreading events include the White House’s Rose Garden event where 35 out of approximately 200 attendees acquired the virus and a birthday party in Westport, CT, where 20 of the 50 partygoers acquired the virus.
Fat-tail data distribution
The MIT researchers studied data from 60 super-spreading events, including some from the ongoing COVID-19 outbreak and others from the 2003 outbreak of SARS.
To determine the impact of these events on the overall transmission of the virus, the researchers created two mathematical models.
When they plotted the data, using statistical tools, they found that that the distribution of the transmission had had a “fat tail.”
“This means that the probability of extreme events decays more slowly than one would have expected,” explained lead study author Felix Wong, a postdoctoral fellow at MIT.
“These really large super-spreading events, with between 10 and 100 people infected, are much more common than we had anticipated,” he added.
Since the probability of extreme transmission events tapers off more slowly than expected, there is a high likelihood of COVID-19 being spread in large gatherings.
“Super-spreading events are likely more important than most of us had initially realized. Even though they are extreme events, they are probable and thus are likely occurring at a higher frequency than we thought. If we can control the super-spreading events, we have a much greater chance of getting this pandemic under control.”
– senior author James Collins, the Termeer Professor of Medical Engineering and Science at MIT
How does this knowledge help?
Many public health officials have recommended limiting the number of people at gatherings since the early stages of the pandemic.
Having more people at an event increases the likelihood that at least one person present has COVID-19 and that the underlying virus is transmitting to more people.
There has not been consistent agreement about what constitutes a large gathering, however.
While the actual frequency and impact of these super-spreading events may be concerning, the findings can help public health officials develop consistent recommendations.
“It gives us a handle as to how we could control the ongoing pandemic, which is by identifying strategies that target super-spreaders,” Wong says.
“One way to do that would be to, for instance, prevent anyone from interacting with over 10 people at a large gathering,” he suggests.
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