Thread by @bopinion

💃At a Zumba workshop, one person infected seven others, who then passed it on to more than 100 people.

🎶At a choir practice, one singer infected as many as 52 others.

🦐At a seafood plant, one worker is said to have infected 533 co-workers. trib.al/vLSWSaZ

These “superspreading” events have become a trademark of Covid-19.

But many people who get the disease don’t pass it on to anyone at all. One new study estimates that 10% of those infected cause 80% of new transmissions trib.al/vLSWSaZ

This imbalance explains a lot about why Covid-19 has spread so unevenly and unpredictably around the world.

It also appears to make the disease easier to control than it would be if superspreaders weren’t so important trib.al/vLSWSaZ

How much can the virus spread over time?

If you start at one infected person and multiply by 2.25 (most estimates of Covid-19’s reproduction number are between two and three), here’s what you get over the next 10 periods trib.al/vLSWSaZ

In a 2005 paper focused on SARS, two epidemiologists and two mathematicians wrote:

“Using contact tracing data from eight directly transmitted diseases, we show that the distribution of individual infectiousness around R0 is often highly skewed” trib.al/vLSWSaZ

The authors devised a new variable, “k,” to reflect the distribution of individual infectiousness, with a low k meaning a more skewed spread.

🦠They assigned SARS a k of 0.16
🦠The 1918 flu’s k hovers around 1
🦠Covid-19’s k is 0.17 trib.al/vLSWSaZ

What can we do with these estimates of k?

Diseases with a k nearing 0.1 were much more likely to fizzle out on their own or be stopped by modest control measures than those with a k of 0.5 or higher
trib.al/vLSWSaZ

.@foxjust put together a model in which 9 out of 10 people have a reproduction number of 0.5 and 1 out of 10 a reproduction number of 18.

This works out to 10% of cases causing 80% of infections. Here’s how a group of series turned out trib.al/vLSWSaZ

Keep in mind, variations in infectiousness are not entirely random.

It may be possible to identify those likeliest to be superspreaders by demographics, viral load or other physical characteristics trib.al/vLSWSaZ

In the present, it’s already pretty easy to identify specific behaviors and locations that lend themselves to large-scale Covid-19 transmission:

🎶Singing
🗣️Yelling
🗨️Talking loudly
🏢Crowding in indoor spaces trib.al/vLSWSaZ

The key role of such events may help explain why the strictness of government lockdowns in different European countries did not seem to be correlated with success in slowing the spread of the disease, although their timing did trib.al/LTQnRCZ

🇰🇷As South Korea in particular has found, superspreader events can allow Covid-19 to make rapid comebacks after periods of decline.

There’s good reason to hope that this virus can be contained in a way that, say, influenza probably cannot trib.al/vLSWSaZ