Just finished a great phone call with
@POTUS
. He’s in good spirits and we talked business — especially how impressed Senators are with the qualifications of Judge Barrett. Full steam ahead with the fair, thorough, timely process that the nominee, the Court, & the country deserve.

A few weeks after settling a years-long lawsuit with Vivendi and its subsidiary StudioCanal, the This Is Spinal Tap cast will reunite for a fundraiser on Oct. 14. Christopher Guest, Rob Reiner, Harry Shearer, and Michael McKean are joining forces to help raise funds for Democrats in Pennsylvania — a state that FiveThirtyEight said is likely to be the tipping point in this year’s presidential election. Of course, being that this is 2020, it will be a virtual reunion and will be hosted by Patton Oswalt

Announcing today: “This Is Spinal Tap” cast is reuniting to benefit the Democratic Party of Pennsylvania. Join me, Christopher Guest, Harry Shearer and Michael McKean on Oct.14 for a virtual reunion and help @PADems #TakeItToEleven

Chip in to be part of PA Democrats' Spinal Tap cast reunion with Rob Reiner, Christopher Guest, Michael McKean, Harry Shearer, and host Patton Oswalt!

This one-time LIVE event is only streaming Wednesday, October 14th, and every dollar raised goes directly towards ending Trumpism by winning Pennsylvania.

MOST PEOPLE ARE CHIPPING IN $20.20. Add your donation now for your link to the livestream on 10/14!

Why, for instance, was there such an enormous death toll in northern Italy, but not the rest of the country? Just three contiguous regions in northern Italy have 25,000 of the country’s nearly 36,000 total deaths; just one region, Lombardy, has about 17,000 deaths. Almost all of these were concentrated in the first few months of the outbreak. What happened in Quito, Ecuador, in April, when so many thousands died so quickly that bodies were abandoned in the sidewalks and streets? Why, in the spring of 2020, did so few cities account for a substantial portion of global deaths, while many others with similar density, weather, age distribution, and travel patterns were spared? What can we really learn from Sweden, hailed as a great success by some because of its low case counts and deaths as the rest of Europe experiences a second wave, and as a big failure by others because it did not lock down and suffered excessive death rates earlier in the pandemic? Why did widespread predictions of catastrophe in Japan not bear out? The baffling examples go on.

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By now many people have heard about R0—the basic reproductive number of a pathogen, a measure of its contagiousness on average. But unless you’ve been reading scientific journals, you’re less likely to have encountered k, the measure of its dispersion. The definition of k is a mouthful, but it’s simply a way of asking whether a virus spreads in a steady manner or in big bursts, whereby one person infects many, all at once. After nine months of collecting epidemiological data, we know that this is an overdispersed pathogen, meaning that it tends to spread in clusters, but this knowledge has not yet fully entered our way of thinking about the pandemic—or our preventive practices.

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There are COVID-19 incidents in which a single person likely infected 80 percent or more of the people in the room in just a few hours. But, at other times, COVID-19 can be surprisingly much less contagious. Overdispersion and super-spreading of this virus are found in research across the globe. A growing number of studies estimate that a majority of infected people may not infect a single other person. A recent paper found that in Hong Kong, which had extensive testing and contact tracing, about 19 percent of cases were responsible for 80 percent of transmission, while 69 percent of cases did not infect another person. This finding is not rare: Multiple studies from the beginning have suggested that as few as 10 to 20 percent of infected people may be responsible for as much as 80 to 90 percent of transmission, and that many people barely transmit it.

This highly skewed, imbalanced distribution means that an early run of bad luck with a few super-spreading events, or clusters, can produce dramatically different outcomes even for otherwise similar countries. Scientists looked globally at known early-introduction events, in which an infected person comes into a country, and found that in some places, such imported cases led to no deaths or known infections, while in others, they sparked sizable outbreaks. Using genomic analysis, researchers in New Zealand looked at more than half the confirmed cases in the country and found a staggering 277 separate introductions in the early months, but also that only 19 percent of introductions led to more than one additional case. A recent review shows that this may even be true in congregate living spaces, such as nursing homes, and that multiple introductions may be necessary before an outbreak takes off. Meanwhile, in Daegu, South Korea, just one woman, dubbed Patient 31, generated more than 5,000 known cases in a megachurch cluster.