Uncategorized – Page 84

October 19, 2020October 27, 2020

Leaders in Covid Death

In the vice-presidential “debate” one question asked of Mike Pence by the moderator, Susan Page, stood out in bold relief:

Vice President Pence, more than 210,000 Americans have died of COVID-19 since February. The US death toll as a percentage of our population is higher than that of almost every other wealthy nation on Earth. For instance, our death rate is two and a half times that of Canada, next door. You head the administration’s Coronavirus Task Force. Why is the U.S. death toll, as a percentage of our population, higher than that of almost every other wealthy country?

Pence had his approved talking-points ready. Rather than allow listeners to consider any international comparison of per capita death rates, Pence dove into Republican/Fox News diversion. This is the gist: Don’t compare us to other countries. No, no, no. Instead, focus on how much worse it could have been if we hadn’t taken all the marvelous and timely actions we took! Don’t look at the evidence and, if you must look, you must conclude it is flawed and untrustworthy because it conflicts with our narrative. (Read his full response, if you have the stomach for it, at 05:55 in the transcript.)

The question posed to Mike Pence is accurate. The U.S. per capita death rate from Covid is 2.5 times Canada’s rate. Canadians live next door. They speak a language we understand. We are not taught to be suspicious of their government systems. For all those reasons it is hard explain away a factor of 2.5 by claiming the statistics are flawed. (Explore more Covid per capita death statistics by country at https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/. Be sure to read the notes.)

Precisely because Canada’s numbers are pretty much unassailable, Pence deliberately sidestepped the question. He knows that the 648 Covid deaths per 1,000,000 in the U.S. is a glaring condemnation of Republican “leadership.” He also knows that Americans are trained to look inward, not outward, trained to dismiss foreign data as manufactured, trained to think of the rest of the world as backward and undeveloped. Moreover, he trusts our news media (even those outlets he and his boss label Fake News), to highlight stories of new outbreaks of coronavirus and new lockdowns while offering little if any context.

We report nearly 220,000 dead from Covid-19 to date. China reports nearly 5000. That’s 648 Covid deaths per 1,000,000 in the U.S. to 3.4 Covid deaths per 1,000,000 in China. (China has roughly four times our population.) That is a rate of death 191 times lower than ours (not just 2.5). That seems an impossible number. The Chinese must be lying, right? We Americans have been trained by a lifetime of nationalist pride and subtle propaganda, so we might be excused for making that the Chinese are lying–but we might better take off the nationalist blinders and have a critical look. After all, to equal our total dead from Covid-19, China (at four times our population) would have to be hiding 880,000 dead bodies, funerals and grieving families. In our world of electronic communication that would be no mean feat even for a country with government controlled media.

Our attention is flooded with antics Trump, his Republican sycophants, and parading militias, so flooded many of us have zero bandwidth left to look outward–and many of us have simply tuned out–just what our would-be autocratic would like. To look outward is to see what a laughingstock Trump’s failed leadership has made of us in the eyes of the world.

For a broadening of perspective take the time to read Nine Days in Wuhan, The Ground Zero of the Coronavirus Pandemic. It appears in the October 12, 2020 issue of The New Yorker. The author, Peter Kessler, is an American writer fluent in Chinese with extensive experience and a multitude of personal connections in China. He paints a personal picture of people struggling, a lot like the rest of us, through a pandemic that knocked them sideways, a pandemic which the Chinese government, with the help of its people, fought to a vigilant standstill using technology and techniques we were unable to muster. I strongly encourage reading the article, which I hope is not hidden behind a paywall (a lot of coronavirus coverage is not). The account is breathtakingly straightforward–in marked contrast to the blustery bullshit of Trump and the loudest members of his following, people who, by contrast, are clearly intent on letting Covid-19 rampage through the American population while lying and blaming their way out of any responsibility.

The Trump administration is impervious to verifiable fact. We have 220,000 dead already with no more than ten or twenty million of us carrying antibodies to the disease (a generous estimate) out of a population of 330 million. Under Republican pandemic negligence hundreds of thousands more will die than need to before we have a trusted, widely accepted, widely available, safe and effective vaccine. Vote them out.

Keep to the high ground,
Jerry

P.S. We are a long way from being done with Covid-19. There are about 7.8 billion people on our planet. Of those, the best data suggest that so far only 37 million have been infected with Covid-19. Since nearly 40% of people with Covid-19 never exhibit symptoms and would not be detected without a truly robust testing regimen, it is likely there are a lot of uncounted folks who have been infected. In a generous attempt to account for those cases let’s more than double the worldwide number of total infected to 100 million. That still leaves 7.7 billion more Covid virgins for the virus to infect. (Sure, if “herd immunity” is achieved at, say, 60% of the population having effective antibodies, then the virus has “only” 4.5 billion potential hosts to go on a worldwide basis.)

P.P.S. Check out the trajectory of cumulative cases of Covid-19 in the U.S. and China from the beginning of the pandemic.

October 14, 2020October 14, 2020

Elections and WA Judges

Ballots for the November 3rd general election ask us to chose between three pairs of Washington State judges. Electoral contests for judges in our state always seem to take me by surprise. Who are these people? What are these positions? On what basis am I supposed to chose between them? What follows is my attempt to put these three races in the context of our state judicial system.

For the Washington State Court of Appeals (District III, i.e. eastern Washington, based in Spokane):
Tracy Arlene Staab v. Marshall Casey

I encourage you to visit the campaign websites of Tracy Staab and Marshall Casey. I admit to some pre-judgement of Mr. Casey based on his 7 year partnership in the practice of law with Matt Shea, State Representative to Olympia the LD4 (Spokane Valley north to Mount Spokane). Matt Shea is credibly accused of involvement with domestic terrorism. You will not find any mention of the partnership with Shea on Casey’s campaign website. In this Spokesman article from February 18th Casey studiously avoids criticizing Shea, suggesting that Casey doesn’t want to alienate any of the militant, far right wing of the local Republican Party. While Casey’s campaign emphasis, “Protecting and Maintaining Individual Rights,” seems bland enough, his rather scant endorsements by exclusively right wing legislators suggest his leanings. Contrast that to Tracy Staub’s extremely broad based endorsements, her experience as a judge, her endorsement by seven different Bar Associations (which Casey did seek) and the choice is crystal clear: vote Staab for the Court of Appeals, District III. The tab on Staab’s website, “About Court of Appeals,” contains two short articles that I found very useful general information.

Curiously, both Staab and Casey have amassed substantial campaign contributions, $74,000 and $66,000, respectively. Staab has spent $69,000 of hers while Casey has only spent $26,000 of his (as of October 12). No other Court of Appeals candidate in this election cycle has raised more than $12,000 (pdc.wa.gov). Staab and Casey each raised more than five times that amount. Clearly, there are a lot of contributors to the Staab and Casey campaigns who think this contest is more important than most eastern Washington voters understand or appreciate. Casey filed to run almost 4 months later than Staab, in a what he must have understood would be an uphill fight. Is he hoping to capitalize on the support of Matt Shea’s followers? And another thing: Casey’s low level of spending may be a timing/reporting issue, but it also might be his acknowledgment of his underdog status. If he leaves a substantial portion of his war chest unspent, it will be worthwhile to pay attention to where it finally goes.

For the two contested seats on the Washington State Supreme Court:
Raquel Montoya-Lewis vs. Dave Larson
and
G. Helen Whitener vs. Richard S. Serns

My choices are Montoya-Lewis and Whitener. Both sit on the court by recent appointment by the governor. Both bring welcome diversity to the court. Both are experienced and highly qualified. Their challengers both appear as long shots, having raised less than half the campaign contributions of the incumbents. Perhaps they are hoping the election will play out like the 1990 election contest I detail in “#3” near the end of this post.

My process of orientation to our state’s judicial system and judicial elections is laid out below:

We are concerned here only with the Washington State Court system, a system rooted in and governed by Article IV of the Washington State Constitution and the Revised Code of Washington (RCW). See P.S. below for a short contrast to federal courts and judges.

Washington State courts are divided into appellate courts and trial courts. Appellate courts, consisting of the Supreme Court and the three Divisions of the Courts of Appeals, hear cases on appeal from the trial courts. The appellate courts do not conduct trials. All three judicial races on the November ballot are for judges to serve at the appellate level. All Washington State appellate judges serve for a six year term.

Washington State Supreme Court: 9 judges, staggered 6 year terms, age limit 75

Washington State Courts of Appeals: 22 judges divided among three Divisions: Seattle, Tacoma, and Spokane (see map) and elected by voters in the Division in which they serve. Division III, Eastern Washington, is based in Spokane. Division III has five of the 22 judgeships. Like Supreme Court judges, State Appellate Court judges serve 6 year terms with an age limit of 75.

The trial courts consist of the Superior and District Courts of the counties and Municipal Courts, i.e. courts established within municipalities that chose to establish a municipal court system (like the City of Spokane). These county and municipal court systems often have explanatory webpages. See Spokane County Superior Court, Spokane County District Court, and the City of Spokane Municipal Court. (Note that each “Court” is really a whole court system with many judges, court rooms, and staff.) The judges that sit on the trial courts of the county and city serve four year terms.

All the judges in the Washington State court system from municipal courts to the Supreme Court are elected. If you are a voter in the City of Spokane you will eventually see on successive ballots candidates for a total of 32 judgeships in five different parts of the court system: 3 City of Spokane Municipal, 8 Spokane County District, 12 Spokane County Superior, 5 Court of Appeals (Division III), and 9 Supreme Court. No wonder I was puzzled!

Since these are all “non-partisan” positions, choosing among these judgeship candidates is (at least officially) neither aided by nor made complicated by party politics and affiliations. Once elected, a Washington State judge often remains in office without opposition, their names appearing on the ballot alone. When two judges vie for an elected seat it usually means one of three things: 1) A judge has just retired from that seat (the Staub/Marshall contest for the seat on the District III Court of Appeals from which Kevin Korsmo is retiring), 2) A judge that was recently appointed to a seat from which a judge has retired/died/aged-out in mid-term, a replacement judge has been appointed, and this is the first time they actually stand for election (the Whitener/Serns and the Montoya-Lewis/Larson races for a Supreme Court seat), or 3) A candidate files and wins in something that looks like a complete fluke.

The number 3 option, the fluke, happened at least once in a Washington State Supreme Court judicial election (in 1990). A then mostly unknown attorney, Charles Johnson, apparently got a wild hair to declare candidacy, didn’t campaign, and still unseated Justice Keith M. Callow, a highly respected judge who had risen to the Supreme Court from the Court of Appeals six years earlier. That Johnson won was a complete surprise, so much so that the event resulted in a panelto study the state’s system for filling judgeships. Nothing changed. However, today voters can better inform themselves about the candidates for judgeships using information on the internet. (It turns out that Justice Charles Johnson did well after his surprise victory in 1990. He is now the longest serving member of the Washington State Supreme Court.)

In Washington State we elect our judges. It behooves us to pay close attention to whom we elect. I hope this post shines some light on that system.

Keep to the high ground,
Jerry

October 12, 2020October 14, 2020

Law, Norms, Mandates, and Masks

There is a big difference in mask wear between Idaho and Washington. Just visit a town on the other side of the border. (Of course, with the recent object lesson provided by the spread of Covid-19 among the national Republican leadership, mask wear is becoming more common everywhere–for good reason.)

Back in July the sensible majority on the Panhandle Health District Board voted 4-2 to mandate mask wear in Kootenai County (the Idaho County directly east of Spokane County). The Panhandle Health District (PHD) is authorized by law to protect the health of the citizens of all five north Idaho counties. The mask mandate applies only to Kootenai County, the most densely populated of the five counties. To attend the meetings or read the news coverage of this vote you would think that mandating mask wear were a terrible, grave endangerment to life, not the straightforward public health measure it clearly is.

If the openly armed (why?) protesters outside the meeting in July weren’t enough, the far right Idaho State legislators from the northern counties recently waded in with a doozy of a letter, part of which was quoted in the Bonner County Daily Bee on October 1.

“We, the majority of state legislators from the five northern counties, are concerned about the continuing mask mandate in Kootenai County,” the letter dated Sept. 29 reads. “This order, first passed by your board in July, carries the force of law and is highly upsetting to many of the citizens we represent.”

God knows, you’d better not “upset” a far right Republican with an AR-15 and a bandolier. The eleven state legislators who signed wrote: “Idahoans value their freedom to make decisions for themselves…Treating adults like children results in defiance of the orders and diminishes the credibility of the health board in future concerns.” It strikes me that these legislators, apparently thinking they have nothing better with which to occupy their time, are acting the part of children, not adults. No, no, no, nobody can tell me I have to wear a mask! …Even if I know it is the right thing to do!

At least one of these legislators doesn’t object to mask wear when it is “required by an institution,” except when that institution is an arm of government. [Idaho State Senator [(R) Coeur d’Alene] Mary Souza: “I personally wear a mask when I’m in an institution that requires it, but I think it’s an individual choice. The situation we have here is: Where is the line between government telling people what they have to do for their health and people making their own choice?”

This is asinine, but not so asinine as this argument:

[Idaho State Rep (R) Coeur d’Alene] Jim Addis said he signed the letter because local law officials say the size and scope of the [mask] mandate is impossible to enforce.

Think about that. A mandate or a law ought to be rescinded because it “is impossible to enforce.” The dictionary defines “enforce” as “compel observance of or compliance with.” I have a “No Trespassing” sign on my property. There are laws against trespass. Since there isn’t a law enforcement officer immediately available to arrest each person who sets foot on my property in clear violation of my sign and trespass law, by Addis’ logic we need to toss out such laws. While we’re at it, we’d best rescind laws against rape and murder, since law enforcement is clearly incapable of “compelling observance” of these laws as well.

A mask mandate or a mask requirement is more an expression of decency, a societal norm, a recognition that we’re all in this together; we need to wear masks for now in order protect each other; mask wear is a sign of mutual respect. Most citizens of Washington aren’t chaffing against the state’s mask requirement. The mask requirement is a public health tool. The fact of its enactment commands attention. That is the purpose of the requirement. No one expects law officers to arrest every person who forgets their mask any more than we expect law officers to cite every person who exceeds the speed limit or walks across a lawn in violation of a No Trespassing sign. On the other hand, those who flout the mandate, by grandstanding their refusal, those people are asking to be cited–and they can spend their time dealing with the consequences in court, just like others who flout regulations.

I cannot believe that the general attitudes toward public health on the two sides of the Idaho/Washington border explain the difference in mask wear in the two areas. The difference is the mandated recognition of the public health importance of wearing masks. The mandate is an educational tool, not a cudgel.

Large segments of the Republican Party–from Trump right on down–display their adolescent disdain for common sense regulation by wasting the time of the rest of us as they parade their belligerence. They don’t deserve the dignity of public office. Keep the Ammon Bundys, Loren Culps and Rob Chases out of public office and vote out the McCaslin Juniors and Jenny Grahams currently wasting our time there. Let’s get on with addressing real problems.

Keep to the high ground,
Jerry

P.S. Doug Muder: Many political movements fail by believing their own rhetoric, and Trump has been saying for a long time that the virus isn’t a big deal; we should all just get back to normal as fast as possible. Among Trumpists, mask-wearing and other good public-health practices are looked on as wimpy, as “living in fear“. (Packing heat at the supermarket, on the other hand, is just a reasonable precaution.)

October 9, 2020October 14, 2020

Venue, Ventilation, and Vocalization

Our understanding of the transmission of Covid-19 is steadily improving as scientists gather and analyze more data. That’s the way science works. Keeping up with the insights gleaned from published, peer-reviewed studies is greatly aided by scientists and science writers who are the gifted communicators that many scientists themselves are not. This post is an unsolicited advertisement for The Atlantic Magazine and a writer whose articles appear there, Zaynep Tufekci. (Ed Yong, who also writes for The Atlantic is another stand-out. See: America Is Trapped in a Pandemic Spiral. Both these writers do brilliant work capturing and explaining complex ideas.)

Zaynep Tufekci is a true polymath. She was recently lauded in a NYTimes article entitled, “How Zeynep Tufekci Keeps Getting the Big Things Right.” She has been a source of clarity about the pandemic on masks, on ventilation, and now on super spreaders–and epidemiology is not even her primary area of expertise.

If you prefer the six minute version of Prof. Tufekci’s take on our current situation, here is the interview she gave on NPR last Sunday morning: https://www.npr.org/2020/10/04/920038820/what-we-should-learn-from-the-white-house-coronavirus-cluster The take-away line is her summary of the “Three Vs”, what we need to focus on in this pandemic: Venue, Ventilation, and Vocalization–lessons first hinted at by the Skagit Chorale incident in March, lessons Tufekci brings into sharp focus.

Tufekci’s latest article in The Atlantic is “This Overlooked Variable Is the Key to the Pandemic, It’s not R.” It is long–and it may be hidden behind a paywall at The Atlantic. I have taken the liberty to copy and paste the entire article below as a sample of what Tufecki, Yong, and The Atlantic offer the reader. Consider a subscription.

Keep to the high ground,
Jerry

This Overlooked Variable Is the Key to the Pandemic, It’s not R.

ZEYNEP TUFEKCI

SEPTEMBER 30, 2020

There’s something strange about this coronavirus pandemic. Even after months of extensive research by the global scientific community, many questions remain open.

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 Guayaquil, Ecuador, in April, when so many 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.

I’ve heard many explanations for these widely differing trajectories over the past nine months—weather, elderly populations, vitamin D, prior immunity, herd immunity—but none of them explains the timing or the scale of these drastic variations. But there is a potential, overlooked way of understanding this pandemic that would help answer these questions, reshuffle many of the current heated arguments, and, crucially, help us get the spread of COVID-19 under control.

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.

Read: Herd immunity is not a strategy

The now-famed R0 (pronounced as “r-naught”) is an average measure of a pathogen’s contagiousness, or the mean number of susceptible people expected to become infected after being exposed to a person with the disease. If one ill person infects three others on average, the R0 is three. This parameter has been widely touted as a key factor in understanding how the pandemic operates. News media have produced multiple explainers and visualizations for it. Movies praised for their scientific accuracy on pandemics are lauded for having characters explain the “all-important” R0. Dashboards track its real-time evolution, often referred to as R or Rt, in response to our interventions. (If people are masking and isolating or immunity is rising, a disease can’t spread the same way anymore, hence the difference between R0 and R.)

Unfortunately, averages aren’t always useful for understanding the distribution of a phenomenon, especially if it has widely varying behavior. If Amazon’s CEO, Jeff Bezos, walks into a bar with 100 regular people in it, the average wealth in that bar suddenly exceeds $1 billion. If I also walk into that bar, not much will change. Clearly, the average is not that useful a number to understand the distribution of wealth in that bar, or how to change it. Sometimes, the mean is not the message. Meanwhile, if the bar has a person infected with COVID-19, and if it is also poorly ventilated and loud, causing people to speak loudly at close range, almost everyone in the room could potentially be infected—a pattern that’s been observed many times since the pandemic begin, and that is similarly not captured by R. That’s where the dispersion comes in.

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.

Read: The pastors already planning to rebel against future shutdowns

Unsurprisingly, SARS-CoV, the previous incarnation of SARS-CoV-2 that caused the 2003 SARS outbreak, was also overdispersed in this way: The majority of infected people did not transmit it, but a few super-spreading events caused most of the outbreaks. MERS, another coronavirus cousin of SARS, also appears overdispersed, but luckily, it does not—yet—transmit well among humans.

This kind of behavior, alternating between being super infectious and fairly noninfectious, is exactly what k captures, and what focusing solely on R hides. Samuel Scarpino, an assistant professor of epidemiology and complex systems at Northeastern, told me that this has been a huge challenge, especially for health authorities in Western societies, where the pandemic playbook was geared toward the flu—and not without reason, because pandemic flu is a genuine threat. However, influenza does not have the same level of clustering behavior.

We can think of disease patterns as leaning deterministic or stochastic: In the former, an outbreak’s distribution is more linear and predictable; in the latter, randomness plays a much larger role and predictions are hard, if not impossible, to make. In deterministic trajectories, we expect what happened yesterday to give us a good sense of what to expect tomorrow. Stochastic phenomena, however, don’t operate like that—the same inputs don’t always produce the same outputs, and things can tip over quickly from one state to the other. As Scarpino told me, “Diseases like the flu are pretty nearly deterministic and R0 (while flawed) paints about the right picture (nearly impossible to stop until there’s a vaccine).” That’s not necessarily the case with super-spreading diseases.

Nature and society are replete with such imbalanced phenomena, some of which are said to work according to the Pareto principle, named after the sociologist Vilfredo Pareto. Pareto’s insight is sometimes called the 80/20 principle—80 percent of outcomes of interest are caused by 20 percent of inputs—though the numbers don’t have to be that strict. Rather, the Pareto principle means that a small number of events or people are responsible for the majority of consequences. This will come as no surprise to anyone who has worked in the service sector, for example, where a small group of problem customers can create almost all the extra work. In cases like those, booting just those customers from the business or giving them a hefty discount may solve the problem, but if the complaints are evenly distributed, different strategies will be necessary. Similarly, focusing on the R alone, or using a flu-pandemic playbook, won’t necessarily work well for an overdispersed pandemic.

Hitoshi Oshitani, a member of the National COVID-19 Cluster Taskforce at Japan’s Ministry of Health, Labour and Welfare and a professor at Tohoku University who told me that Japan focused on the overdispersion impact from early on, likens his country’s approach to looking at a forest and trying to find the clusters, not the trees. Meanwhile, he believes, the Western world was getting distracted by the trees, and got lost among them. To fight a super-spreading disease effectively, policy makers need to figure out why super-spreading happens, and they need to understand how it affects everything, including our contact-tracing methods and our testing regimes.

There may be many different reasons a pathogen super-spreads. Yellow fever spreads mainly via the mosquito Aedes aegypti, but until the insect’s role was discovered, its transmission pattern bedeviled many scientists. Tuberculosis was thought to be spread by close-range droplets until an ingenious set of experiments proved that it was airborne. Much is still unknown about the super-spreading of SARS-CoV-2. It might be that some people are super-emitters of the virus, in that they spread it a lot more than other people. Like other diseases, contact patterns surely play a part: A politician on the campaign trail or a student in a college dorm is very different in how many people they could potentially expose compared with, say, an elderly person living in a small household. However, looking at nine months of epidemiological data, we have important clues to some of the factors.

In study after study, we see that super-spreading clusters of COVID-19 almost overwhelmingly occur in poorly ventilated, indoor environments where many people congregate over time—weddings, churches, choirs, gyms, funerals, restaurants, and such—especially when there is loud talking or singing without masks. For super-spreading events to occur, multiple things have to be happening at the same time, and the risk is not equal in every setting and activity, Muge Cevik, a clinical lecturer in infectious diseases and medical virology at the University of St. Andrews and a co-author of a recent extensive review of transmission conditions for COVID-19, told me.

Read: I have seen the future—and it’s not the life we knew

Cevik identifies “prolonged contact, poor ventilation, [a] highly infectious person, [and] crowding” as the key elements for a super-spreader event. Super-spreading can also occur indoors beyond the six-feet guideline, because SARS-CoV-2, the pathogen causing COVID-19, can travel through the air and accumulate, especially if ventilation is poor. Given that some people infect others before they show symptoms, or when they have very mild or even no symptoms, it’s not always possible to know if we are highly infectious ourselves. We don’t even know if there are more factors yet to be discovered that influence super-spreading. But we don’t need to know all the sufficient factors that go into a super-spreading event to avoid what seems to be a necessary condition most of the time: many people, especially in a poorly ventilated indoor setting, and especially not wearing masks. As Natalie Dean, a biostatistician at the University of Florida, told me, given the huge numbers associated with these clusters, targeting them would be very effective in getting our transmission numbers down.

Overdispersion should also inform our contact-tracing efforts. In fact, we may need to turn them upside down. Right now, many states and nations engage in what is called forward or prospective contact tracing. Once an infected person is identified, we try to find out with whom they interacted afterward so that we can warn, test, isolate, and quarantine these potential exposures. But that’s not the only way to trace contacts. And, because of overdispersion, it’s not necessarily where the most bang for the buck lies. Instead, in many cases, we should try to work backwards to see who first infected the subject.

Because of overdispersion, most people will have been infected by someone who also infected other people, because only a small percentage of people infect many at a time, whereas most infect zero or maybe one person. As Adam Kucharski, an epidemiologist and the author of the book The Rules of Contagion, explained to me, if we can use retrospective contact tracing to find the person who infected our patient, and then trace the forward contacts of the infecting person, we are generally going to find a lot more cases compared with forward-tracing contacts of the infected patient, which will merely identify potential exposures, many of which will not happen anyway, because most transmission chains die out on their own.

The reason for backward tracing’s importance is similar to what the sociologist Scott L. Feld called the friendship paradox: Your friends are, on average, going to have more friends than you. (Sorry!) It’s straightforward once you take the network-level view. Friendships are not distributed equally; some people have a lot of friends, and your friend circle is more likely to include those social butterflies, because how could it not? They friended you and others. And those social butterflies will drive up the average number of friends that your friends have compared with you, a regular person. (Of course, this will not hold for the social butterflies themselves, but overdispersion means that there are much fewer of them.) Similarly, the infectious person who is transmitting the disease is like the pandemic social butterfly: The average number of people they infect will be much higher than most of the population, who will transmit the disease much less frequently. Indeed, as Kucharski and his co-authors show mathematically, overdispersion means that “forward tracing alone can, on average, identify at most the mean number of secondary infections (i.e. R)”; in contrast, “backward tracing increases this maximum number of traceable individuals by a factor of 2-3, as index cases are more likely to come from clusters than a case is to generate a cluster.”

Even in an overdispersed pandemic, it’s not pointless to do forward tracing to be able to warn and test people, if there are extra resources and testing capacity. But it doesn’t make sense to do forward tracing while not devoting enough resources to backward tracing and finding clusters, which cause so much damage.

Another significant consequence of overdispersion is that it highlights the importance of certain kinds of rapid, cheap tests. Consider the current dominant model of test and trace. In many places, health authorities try to trace and find forward contacts of an infected person: everyone they were in touch with since getting infected. They then try to test all of them with expensive, slow, but highly accurate PCR (polymerase chain reaction) tests. But that’s not necessarily the best way when clusters are so important in spreading the disease.

PCR tests identify RNA segments of the coronavirus in samples from nasal swabs—like looking for its signature. Such diagnostic tests are measured on two different dimensions: Are they good at identifying people who are not infected (specificity), and are they good at identifying people who are infected (sensitivity)? PCR tests are highly accurate for both dimensions. However, PCR tests are also slow and expensive, and they require a long, uncomfortable swab up the nose at a medical facility. The slow processing times means that people don’t get timely information when they need it. Worse, PCR tests are so responsive that they can find tiny remnants of coronavirus signatures long after someone has stopped being contagious, which can cause unnecessary quarantines.

Meanwhile, researchers have shown that rapid tests that are very accurate for identifying people who do not have the disease, but not as good at identifying infected individuals, can help us contain this pandemic. As Dylan Morris, a doctoral candidate in ecology and evolutionary biology at Princeton, told me, cheap, low-sensitivity tests can help mitigate a pandemic even if it is not overdispersed, but they are particularly valuable for cluster identification during an overdispersed one. This is especially helpful because some of these tests can be administered via saliva and other less-invasive methods, and be distributed outside medical facilities.

In an overdispersed regime, identifying transmission events (someone infected someone else) is more important than identifying infected individuals. Consider an infected person and their 20 forward contacts—people they met since they got infected. Let’s say we test 10 of them with a cheap, rapid test and get our results back in an hour or two. This isn’t a great way to determine exactly who is sick out of that 10, because our test will miss some positives, but that’s fine for our purposes. If everyone is negative, we can act as if nobody is infected, because the test is pretty good at finding negatives. However, the moment we find a few transmissions, we know we may have a super-spreader event, and we can tell all 20 people to assume they are positive and to self-isolate—if there are one or two transmissions, there are likely more, exactly because of the clustering behavior. Depending on age and other factors, we can test those people individually using PCR tests, which can pinpoint who is infected, or ask them all to wait it out.

Read: The plan that could give us our lives back

Scarpino told me that overdispersion also enhances the utility of other aggregate methods, such as wastewater testing, especially in congregate settings like dorms or nursing homes, allowing us to detect clusters without testing everyone. Wastewater testing also has low sensitivity; it may miss positives if too few people are infected, but that’s fine for population-screening purposes. If the wastewater testing is signaling that there are likely no infections, we do not need to test everyone to find every last potential case. However, the moment we see signs of a cluster, we can rapidly isolate everyone, again while awaiting further individualized testing via PCR tests, depending on the situation.

Unfortunately, until recently, many such cheap tests had been held up by regulatory agencies in the United States, partly because they were concerned with their relative lack of accuracy in identifying positive cases compared with PCR tests—a worry that missed their population-level usefulness for this particular overdispersed pathogen.

To return to the mysteries of this pandemic, what did happen early on to cause such drastically different trajectories in otherwise similar places? Why haven’t our usual analytic tools—case studies, multi-country comparisons—given us better answers? It’s not intellectually satisfying, but because of the overdispersion and its stochasticity, there may not be an explanation beyond that the worst-hit regions, at least initially, simply had a few unlucky early super-spreading events. It wasn’t just pure luck: Dense populations, older citizens, and congregate living, for example, made cities around the world more susceptible to outbreaks compared with rural, less dense places and those with younger populations, less mass transit, or healthier citizenry. But why Daegu in February and not Seoul, despite the two cities being in the same country, under the same government, people, weather, and more? As frustrating at it may be, sometimes, the answer is merely where Patient 31 and the megachurch she attended happened to be.

Overdispersion makes it harder for us to absorb lessons from the world, because it interferes with how we ordinarily think about cause and effect. For example, it means that events that result in spreading and non-spreading of the virus are asymmetric in their ability to inform us. Take the highly publicized case in Springfield, Missouri, in which two infected hairstylists, both of whom wore masks, continued to work with clients while symptomatic. It turns out that no apparent infections were found among the 139 exposed clients (67 were directly tested; the rest did not report getting sick). While there is a lot of evidence that masks are crucial in dampening transmission, that event alone wouldn’t tell us if masks work. In contrast, studying transmission, the rarer event, can be quite informative. Had those two hairstylists transmitted the virus to large numbers of people despite everyone wearing masks, it would be important evidence that, perhaps, masks aren’t useful in preventing super-spreading.

Comparisons, too, give us less information compared with phenomena for which input and output are more tightly coupled. When that’s the case, we can check for the presence of a factor (say, sunshine or Vitamin D) and see if it correlates with a consequence (infection rate). But that’s much harder when the consequence can vary widely depending on a few strokes of luck, the way that the wrong person was in the wrong place sometime in mid-February in South Korea. That’s one reason multi-country comparisons have struggled to identify dynamics that sufficiently explain the trajectories of different places.

Once we recognize super-spreading as a key lever, countries that look as if they were too relaxed in some aspects appear very different, and our usual polarized debates about the pandemic are scrambled, too. Take Sweden, an alleged example of the great success or the terrible failure of herd immunity without lockdowns, depending on whom you ask. In reality, although Sweden joins many other countries in failing to protect elderly populations in congregate-living facilities, its measures that target super-spreading have been stricter than many other European countries. Although it did not have a complete lockdown, as Kucharski pointed out to me, Sweden imposed a 50-person limit on indoor gatherings in March, and did not remove the cap even as many other European countries eased such restrictions after beating back the first wave. (Many are once again restricting gathering sizes after seeing a resurgence.) Plus, the country has a small household size and fewer multigenerational households compared with most of Europe, which further limits transmission and cluster possibilities. It kept schools fully open without distancing or masks, but only for children under 16, who are unlikely to be super-spreaders of this disease. Both transmission and illness risks go up with age, and Sweden went all online for higher-risk high-school and university students—the opposite of what we did in the United States. It also encouraged social-distancing, and closed down indoor places that failed to observe the rules. From an overdispersion and super-spreading point of view, Sweden would not necessarily be classified as among the most lax countries, but nor is it the most strict. It simply doesn’t deserve this oversize place in our debates assessing different strategies.

Although overdispersion makes some usual methods of studying causal connections harder, we can study failures to understand which conditions turn bad luck into catastrophes. We can also study sustained success, because bad luck will eventually hit everyone, and the response matters.

The most informative case studies may well be those who had terrible luck initially, like South Korea, and yet managed to bring about significant suppression. In contrast, Europe was widely praised for its opening early on, but that was premature; many countries there are now experiencing widespread rises in cases and look similar to the United States in some measures. In fact, Europe’s achieving a measure of success this summer and relaxing, including opening up indoor events with larger numbers, is instructive in another important aspect of managing an overdispersed pathogen: Compared with a steadier regime, success in a stochastic scenario can be more fragile than it looks.

Once a country has too many outbreaks, it’s almost as if the pandemic switches into “flu mode,” as Scarpino put it, meaning high, sustained levels of community spread even though a majority of infected people may not be transmitting onward. Scarpino explained that barring truly drastic measures, once in that widespread and elevated mode, COVID-19 can keep spreading because of the sheer number of chains already out there. Plus, the overwhelming numbers may eventually spark more clusters, further worsening the situation.

As Kucharski put it, a relatively quiet period can hide how quickly things can tip over into large outbreaks and how a few chained amplification events can rapidly turn a seemingly under-control situation into a disaster. We’re often told that if Rt, the real-time measure of the average spread, is above one, the pandemic is growing, and that below one, it’s dying out. That may be true for an epidemic that is not overdispersed, and while an Rt below one is certainly good, it’s misleading to take too much comfort from a low Rt when just a few events can reignite massive numbers. No country should forget South Korea’s Patient 31.

That said, overdispersion is also a cause for hope, as South Korea’s aggressive and successful response to that outbreak—with a massive testing, tracing, and isolating regime—shows. Since then, South Korea has also been practicing sustained vigilance, and has demonstrated the importance of backward tracing. When a series of clusters linked to nightclubs broke out in Seoul recently, health authorities aggressively traced and tested tens of thousands of people linked to the venues, regardless of their interactions with the index case, six feet apart or not—a sensible response, given that we know the pathogen is airborne.

Perhaps one of the most interesting cases has been Japan, a country with middling luck that got hit early on and followed what appeared to be an unconventional model, not deploying mass testing and never fully shutting down. By the end of March, influential economists were publishing reports with dire warnings, predicting overloads in the hospital system and huge spikes in deaths. The predicted catastrophe never came to be, however, and although the country faced some future waves, there was never a large spike in deaths despite its aging population, uninterrupted use of mass transportation, dense cities, and lack of a formal lockdown.

It’s not that Japan was better situated than the United States in the beginning. Similar to the U.S. and Europe, Oshitani told me, Japan did not initially have the PCR capacity to do widespread testing. Nor could it impose a full lockdown or strict stay-at-home orders; even if that had been desirable, it would not have been legally possible in Japan.

Oshitani told me that in Japan, they had noticed the overdispersion characteristics of COVID-19 as early as February, and thus created a strategy focusing mostly on cluster-busting, which tries to prevent one cluster from igniting another. Oshitani said he believes that “the chain of transmission cannot be sustained without a chain of clusters or a megacluster.” Japan thus carried out a cluster-busting approach, including undertaking aggressive backward tracing to uncover clusters. Japan also focused on ventilation, counseling its population to avoid places where the three C’s come together—crowds in closed spaces in close contact, especially if there’s talking or singing—bringing together the science of overdispersion with the recognition of airborne aerosol transmission, as well as presymptomatic and asymptomatic transmission.

Oshitani contrasts the Japanese strategy, nailing almost every important feature of the pandemic early on, with the Western response, trying to eliminate the disease “one by one” when that’s not necessarily the main way it spreads. Indeed, Japan got its cases down, but kept up its vigilance: When the government started noticing an uptick in community cases, it initiated a state of emergency in April and tried hard to incentivize the kinds of businesses that could lead to super-spreading events, such as theaters, music venues, and sports stadiums, to close down temporarily. Now schools are back in session in person, and even stadiums are open—but without chanting.

It’s not always the restrictiveness of the rules, but whether they target the right dangers. As Morris put it, “Japan’s commitment to ‘cluster-busting’ allowed it to achieve impressive mitigation with judiciously chosen restrictions. Countries that have ignored super-spreading have risked getting the worst of both worlds: burdensome restrictions that fail to achieve substantial mitigation. The U.K.’s recent decision to limit outdoor gatherings to six people while allowing pubs and bars to remain open is just one of many such examples.”

Could we get back to a much more normal life by focusing on limiting the conditions for super-spreading events, aggressively engaging in cluster-busting, and deploying cheap, rapid mass tests—that is, once we get our case numbers down to low enough numbers to carry out such a strategy? (Many places with low community transmission could start immediately.) Once we look for and see the forest, it becomes easier to find our way out.

* This article originally stated that, in April, coronavirus deaths spiked in Quito, Ecuador. In fact, they spiked in Guayaquil, Ecuador.

We want to hear what you think about this article. Submit a letter to the editor or write to letters@theatlantic.com.ZEYNEP TUFEKCI is a contributing writer at The Atlantic and an associate professor at the University of North Carolina. She studies the interaction between digital technology, artificial intelligence, and society.

October 7, 2020October 14, 2020

Covid and Republicans

The President deserves the best of care. So does the country. Vote Biden and the Democratic ticket in November.

If Republicans at the highest levels aren’t smart enough to protect themselves, the greater fool we to imagine they know how to protect the country.

This last week there was a paradigm shift in our understanding of the transmission of Covid-19, and, as if on cue, the President and many prominent Republicans rushed in to to illustrate the new paradigm.

A huge, peer-reviewed contact tracing study of Covid-19 in two Indian states, published in Science, confirmed and quantified what many have long suspected. Quoted in an article on NPR, one of the lead authors of the study said, “We found that 8% of the people who were infected were responsible for 60% of the infections that grew out of these primary cases.”

Mr. Trump and prominent Republicans relied too much on the Abbott Labs Covid-testing-protection-bubble they erected around White House. They fostered a cavalier attitude about social distancing and mask wearing inside their bubble. They extended their disdain for masks and social distancing in the Rose Garden reception for their new Supreme Court favorite on Saturday, September 26.

At least eight people who attended the Rose Garden event have tested positive, eight Republicans and the President of Notre Dame. All of them were seated in the first three rows and only one is seen the photographs wearing a mask. Was the diseases transmitted in the Rose Garden or, perhaps, in the jubilant, indoor, unmasked hugging and back-slapping that occurred around the event, or at some other event entirely? It is impossible to know, but the new transmission paradigm offers some hints.

We already know that Covid-19 is quite good at spreading from infected individuals who 1) never develop symptoms, 2) who develop symptoms only later, or 3) are minimally symptomatic. The Indian study reveals that infected hosts vary widely in the number of contacts they infect. A few infected hosts, for reasons unknown, spread the virus widely, while many don’t spread it to anyone at all. We already knew (and a prudent President should have known) from the Skagit Chorale incident last March that one person can infect a high percentage of contacts in an indoor venue. What we didn’t know until the Indian study (and other smaller studies) is that some 80% of infections occur from super-spreading events.

The Republican Party shameful hubris around testing, masks, and social distancing was on blatant display on national television at the presidential debate held at the Cleveland Clinic last Tuesday, September 29th. The entire Trump retinue walked in to the hall with masks in place and then flouted the rules by removing their masks once they sat down–and then refused to replace them.

What are the implications of the new paradigm? No regimen for testing for Covid-19 can offer ironclad protection. It only takes one asymptomatic or minimally symptomatic super-spreader to upend any gathering–and the upending is all the more likely if the gathering is indoors, not socially distanced, maskless, and/or involves a lot of vocalization. A group can get away with flouting the rules. A group can gain false confidence by doing so and not paying a price, as long as no one in their midst is infected or is infected and is not a spreader. But woe betide them after a super spreader unknowingly participates. (One hopes that Trump, with his incessant interruptions at the debate on last Tuesday, does not prove to be a super spreader himself.)

We see this locally, especially in churches, some of which seem to take flouting safety measures as an article of faith. The Candlelight Christian Fellowship is a glaring example. Another virus cluster was recently reported in Old Town, ID, also in a Fundamentalist Church. (Read in the Bonner County Daily Bee).

The Party of Denial and their most ardent supporters can get away with flouting the best medical advice (See Loren Culp rally, handful out of hundreds wore masks or Idaho high school football game stopped at halftime after dispute involving Ammon Bundy or candidates Rob Chase or Jenny Graham questioning mask wear)–until, like their President, one day their lack of caution is one step too far.

Let’s move past this. Send the Republican Party to the wilderness from the November elections.

Keep to the high ground,
Jerry

October 5, 2020October 5, 2020

Republicans-A.W.O.L. on Climate

This Wednesday, October 7, at 7PM Gonzaga University is holding a candidate forum on Zoom on the topic of climate change. (Sign up here.) Invitations went out soon after the August primary election to nearly all candidates on the November ballot anywhere in Spokane County for county, state legislative, and U.S. congressional offices. I have copied the invitation list in the box below. Note that the asterisk by a name indicates “Did not accept invitation.” Twenty-two invitations went out to candidates. Thirteen candidates indicate they will attend. Nine of the eleven “Prefers Republican” candidates declined to appear.Laura D Carder and Bob Apple, both running for office in LD3, deserve honorable mention as “Prefers Republican” candidates who plan to attend.

From their local leader, Cathy McMorris Rodgers, right on down, most Republican candidates refuse to show up to discuss what a growing majority of Americans rightly believe is the gravest long term threat we face as a nation and as a world. Why is that? You would have to ask them–but you won’t get a straight answer–except from the man who leads the national Republican Party. From him, a man without a filter who is accustomed to saying the quiet part out loud you hear, “Climate change is a hoax!”

McMorris Rodgers’ dodge on climate change is honed to fine art, a system of political messaging that would lull a charging grizzly into oblivious slumber. Along with all other local Republicans, CMR has just two pivots when asked about climate change, Forest Management! and Hydropower!. Ask her a direct question, “Do you understand the science that underpins concerns about global warming?” and you will get a brief flash of signature toothy smile and a pivot. “Save the dams!” is her go-to response when the region is not on fire and blanketed in smoke. Then she briefly murmurs the words “carbon free” as if to suggest she understands climate science. When we’re wheezing in a pall of smoke as we’ve done frequently in the last five years, CMR’s preferred pivot turns to forest management and blame aimed at historical fire suppression, evil “environmentalists,” and regulation. If one presses her to acknowledge that the climate has already changed so much that grassland, forests, and whole towns are on fire, I suppose CMR might turn for help to Sue Lani Madsen’s recently published idea, “Could cows help fight western wildfires?” Like all such responses there may exist a kernel of truth in that argument, but as a substantive “help” such a response should be greeted with derision.

Not one of these local Republicans who declined the forum invitation has the educational background to comprehend the science on which our understanding of climate is built. Many current Republican candidates and their supporters accept as a matter of doctrine that the earth is only a few thousand years old. With that time frame taught as a matter of faith, it is a real challenge to interpret evidence from ice cores that gives us a window on climate and atmospheric carbon dioxide concentrations that go back hundreds of thousands of years. “Young earth ‘theory'” is common among Evangelicals, those christians for whom the Bible is considered wholly inerrant. A young earth is by no means universal Christian doctrine. After all, this climate forum is sponsored by Gonzaga University, a Roman Catholic institution. Conversely, Cathy McMorris Rodgers’ education was entirely at institutions (except for a late stint at U of WA) that teach the young earth as a tenet of faith.

These nine Republicans’ unwillingness to attend this forum is a glaring statement of science denial. Do not let them dodge this, as McMorris Rodgers has dodged it her entire career. These are the same people who often squirm in response to the growing scientific evidence around the Covid-19 pandemic. We risk our very lives and the lives of grandchildren by letting these Republicans off the hook on these issues.

Sign up and attend the climate forum on Wednesday. It should be interesting. As you watch keep in mind these are the candidates willing to discuss climate change in a public forum. The nine Republicans (check the asterisked names in the box below) acknowledge by their absence that they have nothing to contribute. Either they deny the existence of the problem and do not understand the science that underpins it or, as members of a Republican Party that is beholden to myth, they dare not let on that they understand. They hope we won’t notice. None of these nine Republicans can be trusted to represent us.

Here’s the link to sign up: https://www.gonzaga.edu/college-of-arts-sciences/departments/environmental-studies/events

Keep to the high ground,
Jerry

Category: Uncategorized

Vote! It’s Not Over

Leaders in Covid Death

Elections and WA Judges

Law, Norms, Mandates, and Masks

Venue, Ventilation, and Vocalization

Covid and Republicans

Republicans-A.W.O.L. on Climate