While I like the outside-the-box think of this piece at Wired from Christopher Cox, proposing prioritization for immunization of certain individuals that I suspect will receive exactly zero traction:
WE’VE KNOWN ABOUT Covid-19 super-spreaders since the start of the pandemic. In January, a man transmitted the virus to 23 people during a bus ride on the Chinese coast south of Shanghai; in March, a member of a choir in Washington state passed it on to as many as 52 of her fellow singers; in August, the presence of an infected guest or guests at a wedding in Maine eventually led to more than 175 positive cases; and in September, President Trump hosted perhaps the most famous super-spreading event of all—a party to celebrate the nomination of Amy Coney Barrett to the Supreme Court that may have infected dozens of the most influential Republicans in Washington, along with members of the White House staff and press corps.
This is a pandemic defined by clusters. Some cause deadly outbreaks in nursing homes, prisons, and meatpacking plants. Others overwhelm families and friend groups. Although the numbers vary from study to study, SARS-CoV-2 seems to follow the 80/20 rule: 80 percent of cases stem from just 20 percent of infected individuals. Indeed, most people who test positive—one study in Hong Kong put the number at 69 percent—don’t spread the disease at all. They get infected, remain asymptomatic or fall sick, recover or die, all without passing along the virus to anyone. And then there are the patients like the lawyer from New Rochelle.
Super-spreading makes the virus especially confounding. It explains why some places had huge outbreaks while others were spared, at least for a while, and why the same risky behavior (an indoor wedding, say) can lead to dozens of cases—or none. But it’s also the virus’s weakness: Eliminate the super-spreaders and you end the pandemic.
as well as appreciating the hat tip to network analysis, I think they’re confusing two different things: events with conditions conducive to spreading the diseases and individuals who through behavior or biology are more likely to spread the disease. I think that actual empirical evidence to support either of those two hypotheses is still, sadly, lacking.
If “super-spreading” can be linked to behaviors and those behaviors can, for example, be associated with cellphone usage, that would be fantastic. It would make it much easier to identify people who are putting others at risk. But to date policy has been heavily targeted to events rather than to behavior, presumably under the assumption that risky behaviors can be linked to certain events. It would sure be nice to have empirical evidence for that. To formulate good policy, whether for prioritizing distribution of the vaccine when we have one or for formulating mitigation policies, we need to be able to disaggregate events from behavior or biology.