There have been documented cases of “super-contagious” COVID-19, in which one person infected with SARS-CoV-2 infects many others. But how do these events play a role in the overall spread of the disease? A new study from MIT shows that they have a much larger impact than expected.
The study of about 60 super contagious events found that events in which one person infects more than six other people were much more common than would have been expected if the range of transmission rates followed the normal statistical distribution. used in epidemiology.
Based on their findings, the researchers have also developed a mathematical model of COVID-19 transmission, which they use to show that restricting concentration to 10 or less people can be reduced. significantly the number of super-contagious events and a decrease in the total number of infections.
“Super-contagious events seem more important than most of us initially realized. Although they are extreme events, they are probable and therefore more likely to happen at a higher frequency. we think. If we can control super-contagious events, James Collins, Professor of Termeer Medical Science and Engineering at MIT’s Institute of Medical Science and Engineering (IMES) and Department of Biomedical Engineering. study, at the same time is a senior author of the new study said.
MIT postdoc Felix Wong is the lead author of the article, appearing this week in Proceedings of the National Academy of Sciences.
For the SARS-CoV-2 virus, the “baseline fertility number” is about 3, meaning that on average, each person infected with the virus will spread to about three other people. However, this number varies widely from person to person. Some individuals do not infect anyone, while the “super contagious” can infect dozens of people. Wong and Collins begin to analyze statistics for these super viral events.
“We found that an analysis that stems from looking at hyper-widespread events and how they happened in the past could indicate how we should propose coping and control strategies,” Wong said. Better than the outburst.
Researchers have defined super-communicators as individuals who transmit the virus to more than six other people. Using this definition, they identified 45 hyperinfection events from the current SARS-CoV-2 pandemic and 15 additional events from the 2003 SARS-CoV outbreak, all recorded in the scientific articles. In most of these events, between 10 and 55 people were infected, but two of them, both from the 2003 outbreak, involved more than 100 people.
Given the commonly used statistical distributions in which the typical patient infects three other people, events in which the disease spreads to dozens of people would be considered highly unlikely. For example, a normal distribution would look like a bell pot with a top around three, with a tail that tapers rapidly in both directions. In this case, the probability of an extreme event decreases exponentially as the number of infections moves further than the average by three.
However, the MIT team found that this was not the case with coronavirus-induced hyperinfection events. To do their analysis, the researchers used mathematical tools from the field of extreme value theory, used to quantify the risk of events known as “fat tails”. Extreme value theory is used to model situations in which extreme events form a large tail instead of a smaller one. This theory is commonly applied in areas such as finance and insurance to model the risk of extreme events, and it is also used to model the frequency of catastrophic events. like a tornado.
Using these mathematical tools, the researchers discovered that the distribution of coronavirus transmissions had a large tail, implying that even though hypercommunicable events were extreme, they still had possibility.
“This means that the probability of extreme events decreases more slowly than expected,” Wong said. “These really big really super contagious events, with between 10 and 100 people infected, are much more common than we expected.”
Many factors can contribute to someone being super contagious, including their viral load and other biological factors. The researchers did not address problems in this study, but they modeled the role of connection, which is defined as the number of people an infected person is exposed to.
To study the effects of connection, the researchers created and compared two mathematical lattice models of disease transmission. In each model, the average number of contacts per person was 10. However, they designed one with an exponentially decreasing distribution of contacts, while the other had one. the fat tail of which some people have lots of contacts. In that model, many people were infected through super contagious events. However, transmission stopped when people with more than 10 contacts were taken out of the network and deemed uninfected.
The findings suggest that suppressing super-contagious events can have a significant impact on the overall transmission of COVID-19, the researchers said.
“It helps us handle the way we can control the ongoing pandemic, which is by defining strategies that target supermass spreaders,” Wong said. “One way to do that, such as preventing anyone from interacting with more than 10 people at a large gathering.”
Researchers are now hoping to study how biological factors can also contribute to hyperinfection.
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Felix Wong et al., Evidence suggesting obese-tailed coronavirus transmission, Proceedings of the National Academy of Sciences (Year 2020). DOI: 10.1073 / pnas.2018490117
Provided by Massachusetts Institute of Technology
Quote: COVID-19 ‘super spread’ events play a big role in overall disease transmission (2020, November 3) retrieved November 4, 2020 from https://medicalxpress.com / news / 2020-11-covid-super-spreading-events- outsized-role.html
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