What We Know About Why Some People Never Get Covid 19

Americans who haven’t had covid-19 are now officially in the minority. A study published this week from the US Centers for Disease Control and Prevention (CDC) found that 58% of randomly selected blood samples from adults contained antibodies indicating that they had previously been infected with the virus; among children, that rate was 75%.

What is different about that minority of people that hasn’t yet gotten infected? Stories abound of close calls, of situations where people are sure they could have (or should have) gotten sick, but somehow dodged infection. Not all the questions are answered yet, but the question of what distinguishes the never-covid cohort is a growing area of research even as the US moves “out of the full-blown” pandemic. Here are the possibilities that scientists are considering to explain why some people haven’t contracted the virus.

They behave differently

We’ve seen it play out time and time again—some people adhere more strictly to protocols known to reduce transmission of the virus, including wearing a mask and getting vaccinated. Some people avoid large public settings and may have even been doing so before the pandemic, says Nicholas Pullen, a biology professor at the University of Northern Colorado. Then again, that doesn’t tell the whole story; as Pullen himself notes: “Ironically, I happen to be one of those ‘never COVIDers’ and I teach in huge classrooms!”

They’ve trained their immune systems

The immune system, as any immunologist or allergist can tell you, is complicated. Though vaccination against covid-19 can make symptoms more mild for some people, it can prevent others from contracting the illness altogether.

Growing evidence suggests that there may be other ways that people are protected against the virus even without specific vaccines against it. Some could have previously been infected with other coronaviruses, which may allow their immune systems to remember and fight similarly shaped viruses. Another study suggests that strong defenses in the innate immune system, barriers and other processes that prevent pathogens from infecting a person’s body, may also prevent infection.

An innate immune system that’s already not functioning as well due to other medical conditions or lifestyle factors such as sleep or diet may put a person at higher risk of getting sick from a pathogen. There’s not single answer here yet, but initial studies are intriguing and may offer avenues for future treatments for covid-19 and other conditions.

They’re genetically different

In the past, studies have found interesting associations between certain genetic variants and people’s susceptibility to communicable diseases such as HIV, tuberculosis, and the flu. Naturally, researchers wondered if such a variant could exist for covid-19. One June 2021 study that was not peer reviewed found an association between a genetic variant and lower risk of contracting covid-19; another large-scale study, focused on couples in which one person got sick while the other didn’t, kicked off in Oct. 2021.

“My speculation is that something will be borne out there, because it has been well observed that resistance embedded in genetic variation is selected in pandemics,” Pullen says. But most experts suspect that even if they are able to identify such a variant with some certainty, it’s likely to be rare. For now, it’s best for those who haven’t gotten covid to assume they’re as susceptible as anyone else. Whatever the reasons some people haven’t yet gotten sick, the best defense remains staying up to date with vaccinations and avoiding contact with the virus.

Source: What we know about why some people never get covid-19 — Quartz

“Being exposed to the SARS-CoV-2 virus doesn’t always result in infection, and we’ve been keen to understand why,” study author Rhia Kundu said in a statement, using the scientific name for the coronavirus. “We found that high levels of pre-existing T cells, created by the body when infected with other human coronaviruses like the common cold, can protect against COVID-19 infection.”

The study, which examined 52 people who lived with someone who contracted the coronavirus, found that those who didn’t get infected had significantly higher levels of T cells from previous common cold coronavirus infections. T cells are part of the immune system and believed to protect the body from infection. “Our study provides the clearest evidence to date that T cells induced by common cold coronaviruses play a protective role against SARS-CoV-2 infection,” study author Ajit Lalvani said in a statement.

Researchers cautioned that the findings should not be relied upon as a protection strategy. “While this is an important discovery, it is only one form of protection, and I would stress that no one should rely on this alone,” Kundu said. “Instead, the best way to protect yourself against COVID-19 is to be fully vaccinated, including getting your booster dose.” And the findings on the subject have been inconsistent, with other studies actually suggesting that previous infection with some coronaviruses have the opposite effect.

A major question that has come from the so-called ‘never COVID’ group is whether genetics plays a role in preventing infection. In fact, the question has spurred a team of international researchers to look for people who are genetically resistant to COVID-19 in the hopes that their findings could improve therapeutics. “What we are doing essentially is that we are testing the hypothesis that some people might not be able to get infected because of their genetic and inborn makeup, meaning that they might be genetically resistant to COVID,” says Spaan, who is a member of the COVID Human Genetic Effort.

The effort has sequenced genetic data from about 700 individuals so far, but enrollment is ongoing and researchers have received thousands of inquiries, according to Spaan. The study has several criteria, including laboratory test confirmation that the person has not had previous COVID-19 infection, intense exposure to the virus without access to personal protective equipment like masks and an unvaccinated status at the time of exposure, among others. So far, the group doesn’t know what the genetic difference could be – or if it even exists at all, though they believe it does.

“We do not know how frequent it is actually occurring,” Spaan says. “Is it like a super rare individual with a very, very rare mutation? Or is that something more common?” But the hypothesis is “embedded in human history,” according to Spaan. “COVID is not quite the first pandemic that we are dealing with,” Spaan says. “Humans have been exposed to viruses and other pathogens across time from the early beginning, and these infections have left an imprint on our genetic makeup.”

Those who haven’t gotten the coronavirus are “very much at risk,” says Murphy of Northwestern University. “I think every unvaccinated person is going to get it before this is over.” Experts stressed that research to determine why some people get COVID-19 while others don’t is still very much underway, and no one should rely on any of the hypotheses for protection. Instead, those who haven’t gotten the coronavirus should continue mitigation measures that have been proven to work, like vaccination and mask-wearing.

“You don’t ever want to have COVID,” Murphy says. “You just don’t know which people are going to get really sick from this and die or who’s going to get long COVID, which is hard to diagnose and difficult to treat and very real.” But with coronavirus cases on the rise and mitigation measures like mask mandates dropping left and right, it’s not an easy task.

COVID19: Face masks could return as cases spike Financial Mirror

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An Omicron Surges Spark Chain Reactions That Strain US Hospitals Everywhere

America’s hospitals and their workforces have reached and exceeded their breaking points in the last two years — and another surge of Covid-19 is already underway.

Earlier this month, with a new wave of Covid-19 cases looking likely after the omicron variant was identified, Rhode Island emergency doctors wrote their state leaders to warn that any new surge of patients would “lead to collapse of the state health care system.” In Kansas, patients in rural hospitals have been stuck in the ER for days while they wait for a transfer to a larger hospital with the capacity and resources to care for them.

With the fast-spreading omicron variant now upon us, some of the rhetoric around the pandemic has changed. Government officials, starting with President Joe Biden, are pointedly differentiating between the risks for vaccinated and unvaccinated people. This could create the perception that some places face more of a risk than others: Perhaps omicron will threaten rural communities (where vaccination rates are lowest) and their health systems, but perhaps more vaccinated cities and their hospitals will be better off.

Such thinking would be misguided. As convoluted and sometimes siloed as the US health system may seem at times, it is still a system. Patients transfer between facilities based on capacity or clinical need. If rural hospitals are shipping seriously ill patients to their urban neighbors, which already tend to run close to capacity even in normal times, a rural Covid-19 crisis could quickly become a crisis for everybody.

One hospital being overwhelmed isn’t a one-hospital problem, it’s an every-hospital problem. Even if your community is not awash with Covid-19 or if most people are vaccinated, a major outbreak in your broader region, plus all the other patients hospitals are treating in normal times, could easily fill your hospital, too. That makes it harder for the health system to treat you if you come to the ER with heart attack symptoms or appendicitis or any acute medical emergency.

Already, because of existing staffing shortages, rural hospitals are finding it difficult to find room for their patients at larger hospital systems. With omicron spreading rapidly, increasing the number of patients seeking care while sidelining health workers who have to quarantine, systemic overload may not be far off.

“When you have a Covid patient who needs ICU care, those hospitals are turning away patients,” Carrie Saia, CEO of Holton Community Hospital, located in a town of 3,000 people about 90 minutes east of the Kansas City metropolitan area, told me earlier this month. “We’re sending our patients farther away. Not because they’re full, they’re just out of staff.”

At earlier points in the crisis, large hospitals would limit transfers from smaller facilities in order to preserve their capacity to treat the most seriously ill patients. As a new wave driven by the omicron variant takes off, that could happen again.

As Karen Joynt Maddox, a practicing cardiologist and associate professor of medicine at Washington University in St. Louis, told me in August: “During Covid surges, we were told to limit transfers only to patients who had needs that could not be met at their current hospital (i.e. decline transfers because the family requested it, but equal services available at both places) because that was the only way we could make sure that we did have the ability to accept patients that only we (or another major referral center) could handle.”

The feedback loop works in reverse as well. Recently, the HCA hospital in Conroe, Texas, about 40 miles north of Houston, was dealing with such a staffing shortage in its emergency department that the facility temporarily asked ambulances to bypass it because the ED couldn’t handle any more patients, according to a spokesperson. Suddenly, hospitals in the heart of Houston were seeing an unexpected surge of patients who needed emergency care, causing long wait times at their facilities.

America’s hospitals are all in this together. So what can we do quickly to relieve the burden for all of our hospitals and prevent unnecessary deaths?

How we can all help hospitals handle a surge in omicron patients

Last week, the Biden White House detailed a new plan for helping hospitals handle the coming surge of Covid-19 patients. They are deploying emergency medical personnel to six states: Michigan, Indiana, Wisconsin, Arizona, New Hampshire, and Vermont. They are also planning to deploy another 1,000 military doctors and nurses in January and February, as well as ordering FEMA to work with states to add hospital beds. The White House also said it had 100,000 ventilators in the federal stockpile that could be deployed as needed.

Those policies could certainly help to alleviate the pressure on hospitals in places facing particularly acute crises. But the truth is, they can only do so much. US hospitals cannot suddenly grow the staff and physical capacity to handle another enormous surge of Covid-19 patients.

Infected medical workers add to the strain on hospitals. Hospitals have seen a spike in nurses and doctors testing positive; by late December, the El Centro Regional Medical Center, about two hours east of San Diego near the US-Mexico border, was seeing 5 to 10 percent of its staff either infected or being tested for exposure at any given time, according to CEO Adolphe Edward. Other hospitals have told me they are also seeing a growing number of workers test positive, which requires them to stop working and isolate.

The Centers for Disease Control and Prevention recently revised its isolation protocols for health care workers who test positive for Covid-19, shortening the standard isolation period from 10 days to 7 (if accompanied by a negative test). But that still takes doctors and nurses out of commission for several days if they contract the virus. (On Monday, the CDC released new guidelines for the general public stating that those who test positive can stop isolating after five days if they do not have symptoms.)

“You can send all the ventilators you want,” Roberta Schwartz, executive vice president at Houston Methodist Hospital, told me. “I have no one to staff them.”

Nearly 99 percent of rural hospitals said in a survey released in November they were experiencing a staffing shortage; 96 percent of them said they were having the most difficulty finding nurses. According to a September study commissioned by the American Hospital Association, the average cost of labor expenses for each discharged patient has grown by 14 percent in 2021 — even as the number of full-time employees has dropped by 4 percent.

“The only things I can think of could not be accomplished in two weeks,” Peter Viccellio, associate chief medical officer at Stony Brook University Hospital in New York, said. “We have a severe staffing shortage everywhere, and it’s not going to go away. It existed before Covid, and Covid just exacerbated it.”

Some policy changes — smoothing schedules that better distribute surgeries (and therefore patient volume) throughout the day or week, earlier discharges or more weekend discharges — could help. “But this won’t happen without a mandate,” Viccellio said.

“We won’t prevent future catastrophes because of a very simple reason. It requires that we think of the future and plan for it,” he added. “You can see how that’s working out. We can’t frigging plan for one month from now.”

More money from the federal government could also allow hospitals to beef up their staffing, said Beth Feldpush, senior vice president of policy and advocacy at America’s Essential Hospitals, which represents critical access facilities. But all of these policies targeted directly to hospitals may only help at the margins. The American health system’s capacity is what it is — the time to act was long ago. Instead, the US health care system is behind many of its wealthy peers in the number of practicing medical staff in its hospitals.

So the quickest and surest action to prevent hospitals from being overwhelmed is actually to prevent people from needing to go to the hospital with Covid-19 in the first place, hospital leaders said. Get vaccinated — with three doses. Wear masks indoors in public places. Test before you see people who don’t live in your house.

Following the pandemic playbook can make a difference for hospitals bracing for another grim winter in this pandemic.

“The more we can help keep the public protected, the more we can keep our workers here,” Schwartz said, “and lessen the burden of this.”

Dylan Scott

I grew up in Ohio, lived in Las Vegas for a year and moved to Washington in 2011. I cover health care and other domestic policy. You’ll probably see me tweeting about Cleveland sports or the last movie I watched.

Source: An omicron Covid-19 surge anywhere can strain US hospitals everywhere

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More contents:

Effects of Inadequate Sleep and Poor Sleep Quality In Athletes

1

Athletes are always looking for ways to improve performance and take goals to the next level. Efforts for doing just that are often limited to waking hours: nutrition, hydration, recovery protocols, supplement routine and, of course, training itself. And despite all this, research shows that, on average, athletes neglect a critical performance tool: sleep. So how does inadequate sleep affect athletic performance? Interestingly, the oversight of sleep can impact performance, both directly and indirectly, and the effects largely differ by sport. 

 
The impact of sleep quality on overall health
 

Before moving into the impact of sleep on performance, it is important to understand how sleep affects overall health and wellness. Both the amount and quality of sleep impacts our mood and energy levels, our metabolism, and immune system health. Inadequate quality sleep can be linked to a variety of serious health problems, including an increased risk of depression, obesity, type II diabetes, and cardiovascular disease. It can even increase an individual’s risk for illness and infection.

Athletes as a population do not get adequate sleep, contributing to overtraining syndrome

Adequate rest and recovery are considered key components of improving athletic performance and preventing sleep disturbances commonly reported in overtraining syndrome. Sleep provides the body with an opportunity to rest from both the physiological and cognitive stressors many athletes face throughout the day. However, despite the body of evidence on the benefits of sleep in athletes (and the potential for sleep to alleviate fatigue), sleep duration and quality are often neglected by athletes.

It is well-reported that, on average, athletes do in fact get less than seven hours of sleep per night, often of poor quality. This falls below the recommended eight hours to combat the negative effects of sleep deprivation. Despite some research limitations, the British Journal of Sports Medicine consensus statement on the topic states that sleep deprivation does affect recovery, training, and performance in elite athletes and that these athletes as a population do not get enough sleep.

Athletes are, in general, a highly motivated group—the type of people who may willingly restrict sleep to fit more activities into waking hours. But even if you’re someone who ‘gets by just fine’ on a restricted sleep schedule, such a lifestyle can have immediate detrimental effects; evidence shows that restricting sleep to six hours per night for just four consecutive nights can impair cognitive performance and mood, glucose metabolism, appetite regulation, and immune function.

Effects of sleep deprivation on different types of athletes

Before we jump into the research of the effects of sleep deprivation in athletes, a disclaimer: Despite the recognized importance of sleep in athletes’ routines, the research on sleep in athletic populations is sparse at this time. The available research on this topic has specific limitations, including the underrepresentation of female subjects, inconsistent research methods across studies, and small sample size.

Now, the science. Current research does show a number of potential performance implications of poor sleep that should be considered in both endurance and power sport athletes. Among the subjects that have been studied, individual sport athletes appear to be more susceptible sleep deficiency and had poorer sleep efficiency than their team sport counterparts.

Two main detrimental effects of sleep deprivation on performance in all sport types are cognitive impairments and mood disturbances. Blumert et al. looked at the effects of just 24 hours of sleep deprivation in collegiate weightlifters (so, for a single night’s sleep). While they saw no difference in performance tasks, training load or intensity, there was a significant difference in mood state including fatigue and confusion in the sleep deprived athletes.

There are also observed direct effects of sleep deprivation on physical performance. Oliver et al. studied endurance running performance in a 24 hour sleep deprived state and found that that subjects who were sleep deprived ran fewer miles in the same amount of time as well-rested athletes but with the same perception of effort.[8] Athletes should also be mindful of the non-direct consequences of sleep deprivation on their performance including but not limited to metabolism, hormone regulation, immune health, and limiting recovery.

Much like everything related to health, wellness, and performance, each individual will have different sleep requirements. These requirements may also vary depending on phase or training season, sex, training volume, intensity, and type of sport.

Biomarkers related to sleep and performance in athletes

Adequate sleep helps to regulate cortisol levels, and inadequate sleep can cause cortisol levels to rise above optimized levels. Cortisol is a catabolic steroid hormone that breaks down muscle, so chronically-elevated cortisol can directly combat progress to become stronger or faster in our athletic performance. 

Sleep also helps to regulate testosterone levels. This hormone is anabolic, meaning it helps build muscle (the opposite of cortisol). But, as you might have guessed, insufficient sleep can reduce testosterone levels.

Research shows that sleep deprivation can also cause chronic inflammation, as indicated by high hsCRP levels. As athletes, inflammation and muscle damage are to be expected with any sort of training—after all, we need to cause slight damage to our muscles to make them stronger. But chronic inflammation, the kind that’s caused by overtraining or insufficient rest, can leave an athlete prone to poor performance, illness, and injury. 

Actions for athletes to take to improve sleep

While the benefits of adequate sleep are well-documented in healthy individuals, the research specific to athletes and different athlete types continues to emerge. That being said, there are well-established actions you can take right now to improve your sleep. Here are some actions to optimize your sleep habits:

. If you have trouble getting the recommended amount of sleep at night, consider taking regular naps.

. Begin tracking your sleep with a wearable activity tracker. While research has displayed varying accuracy of these devices for sleep management, they can help you establish a healthy and regular bedtime routine.

. Work on implementing good sleep habits or a bedtime routine that reduces stress and promotes a good sleeping environment.

. Consider adjusting your exercise routine and incorporate more rest and active recovery in times of sleep deprivation or high life stress to help support your overall health and prevent injury or illness.

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Source: Effects of inadequate Sleep and Poor sleep Quality in Athletes.

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COVID-19 Vaccines Not Linked To Pregnancy Loss; Mixing Vaccines May Confer Greater Protection

The following is a summary of some recent studies on COVID-19. They include research that warrants further study to corroborate the findings and that have yet to be certified by peer review.

COVID-19 vaccines not linked with pregnancy loss

Two studies in major medical journals add to evidence that COVID-19 vaccines are safe before and during pregnancy. One study, published in The New England Journal of Medicine on Wednesday, tracked nearly 18,500 pregnant women in Norway, including about 4,500 who had miscarriages.

Researchers found no link between COVID-19 vaccines and risk of first-trimester miscarriage, regardless of whether the vaccines were from Moderna, Pfizer and BioNTech, or AstraZeneca. Overall, the women with miscarriages were 9% less likely to have been vaccinated, according to the researchers’ calculations.

In a separate study published on Thursday in The Lancet, researchers tracked 107 women who became pregnant while participating in trials of AstraZeneca’s vaccine in the UK, Brazil and South Africa. Seventy-two of the women had received the vaccine while the others got a placebo. AstraZeneca’s vaccine had no effect on the odds of safely carrying the pregnancy to term, the researchers reported.

“It is important that pregnant women are vaccinated since they have a higher risk of hospitalizations and COVID-19-complications, and their infants are at higher risk of being born too early,” the authors of the Norwegian study wrote. “Also, vaccination during pregnancy is likely to provide protection to the newborn infant against COVID-19 infection in the first months after birth.”

Vaccine combinations with different technologies may be best

Healthcare workers in France who got a first shot of AstraZeneca’s COVID-19 vaccine and then the Pfizer/BioNTech vaccine for their second shot showed stronger immune responses than those who had received two shots of the Pfizer vaccine, in a recent study. Combining different technologies is known to boost immune responses to other viruses, and the current study suggests it may be true for the coronavirus as well.

Both vaccines in the study deliver instructions that teach cells in the body to make a piece of protein that resembles the spike on the coronavirus and that triggers an immune response. But they do it in very different ways. Both protocols provided “safe and efficient” protection, said Vincent Legros of Universite de Lyon in France, coauthor of a report published on Thursday in Nature.

But combining the AstraZeneca shot with the Pfizer/BioNTech vaccine “conferred even better protection” than two doses of Pfizer’s shot, including against the Delta variant, Legros said. The two technologies combined induced an antibody response of better quality, with more neutralizing antibodies that could block the virus, and more cells that have been “trained” by the vaccine to have increased defense potential, he said.  Combination vaccination “is safe and may provide interesting options… for clinicians to prevent SARS-CoV-2 infection,” Legros concluded.

Cognitive problems seen in middle-aged COVID-19 survivors

A “substantial proportion” of middle-aged COVID-19 survivors with no previous dementia had cognitive problems more than half a year after diagnosis, researchers have found. They looked at 740 people who ranged in age from 38 to 59. About half were white, and 63% were female. On tests of thinking skills, 20% had trouble converting short-term memories to long-term memories, 18% had trouble processing information rapidly, and 16% had trouble with skills needed for planning, focusing attention, remembering instructions, and juggling multiple tasks.

The average time from diagnosis was 7.6 months. About one-in-four patients had been hospitalized, but most of them were not critically ill. “We can’t exactly say that the cognitive issues were lasting because we can’t determine when they began,” said Dr. Jacqueline Becker of the Icahn School of Medicine at Mount Sinai in New York City, who co-led the study published on Friday in JAMA Network Open. “But we can say that our cohort had higher than anticipated frequency of cognitive impairment” given that they were relatively young and healthy, Becker said.

Data support use of Pfizer vaccine in children and teens

The Pfizer/BioNTech COVID-19 vaccine showed 90.7% efficacy against the coronavirus in a trial of children ages 5 to 11, the U.S. drugmaker said on Friday in briefing documents submitted to the U.S. Food and Drug Administration but not formally published. The children were given two shots of a 10-microgram dose of the vaccine – a third of the strength given to people 12 and older.

The study was not primarily designed to measure efficacy against the virus. Instead, it compared the amount of neutralizing antibodies induced by the vaccine in the children to the response of recipients in their adult trial. Pfizer and BioNTech said the vaccine induced a robust immune response in the children. Outside advisers to the FDA are scheduled to meet on Tuesday to vote on whether to recommend authorization of the vaccine for that age group.

A separate study from Israel conducted while the Delta variant was prevalent and published on Wednesday in The New England Journal of Medicine, compared nearly 95,000 12- to -18-year-olds who had received Pfizer’s vaccine with an equal number of adolescents who had not been vaccinated. The results show the vaccine “was highly effective in the first few weeks after vaccination against both documented infection and symptomatic COVID-19 with the Delta variant” in this age group, the research team reported.

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Source: COVID-19 vaccines not linked to pregnancy loss; mixing vaccines may confer greater protection | Reuters

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The ٍٍEmpty Office: What We Lose When We Work From Home

For decades, anthropologists have been telling us that it’s often the informal, unplanned interactions and rituals that matter most in any work environment. So how much are we missing by giving them up?

n the summer of 2020, Daniel Beunza, a voluble Spanish social scientist who taught at Cass business school in London, organized a stream of video calls with a dozen senior bankers in the US and Europe. Beunza wanted to know how they had run a trading desk while working from home. Did finance require flesh-and-blood humans?

Beunza had studied bank trading floors for two decades, and had noticed a paradox. Digital technologies had entered finance in the late 20th century, pushing markets into cyberspace and enabling most financial work to be done outside the office – in theory. “For $1,400 a month you can have the [Bloomberg] machine at home.

You can have the best information, all the data at your disposal,” Beunza was told in 2000 by the head of one Wall Street trading desk, whom he called “Bob”. But the digital revolution had not caused banks’ offices and trading rooms to disappear. “The tendency is the reverse,” Bob said. “Banks are building bigger and bigger trading rooms.”

Why? Beunza had spent years watching financiers like Bob to find the answer. Now, during lockdown, many executives and HR departments found themselves dealing with the same issue: what is gained and what is lost when everyone is working from home? But while most finance companies focused on immediate questions such as whether employees working remotely would have still access to information, feel part of a team and be able to communicate with colleagues, Beunza thought more attention should be paid to different kinds of questions:

How do people act as groups? How do they use rituals and symbols to forge a common worldview? To address practical concerns about the costs and benefits of remote working, we first need to understand these deeper issues. Office workers make decisions not just by using models and manuals or rational, sequential logic – but by pulling in information, as groups, from multiple sources. That is why the rituals, symbols and space matter.

“What we do in offices is not usually what people think we do,” Beunza told me. “It is about how we navigate the world.” And these navigation practices are poorly understood by participants like financiers – especially in a digital age.The engineers who created the internet have always recognised that people and their rituals matter. Since it was founded in 1986, the Internet Engineering Task Force (IETF) has provided a place for people to meet and collectively design the architecture of the web.

Its members wanted to make design decisions using “rough consensus”, since they believed the internet should be an egalitarian community where anybody could participate, without hierarchies or coercion. “We reject: kings, presidents and voting. We believe in: rough consensus and running code” was, and still is, one of its key mantras.

To cultivate “rough consensus”, IETF members devised a distinctive ritual: humming. When they needed to make a crucial decision, the group asked everyone to hum to indicate “yay” or “nay” – and proceeded on the basis of which was loudest. The engineers considered this less divisive than voting.

Some of the biggest decisions about how the internet works have been made using this ritual. In March 2018, in a bland room of the Hilton Metropole on London’s Edgware Road, representatives from Google, Intel, Amazon, Qualcomm and others were gathered for an IETF meeting. They were debating a controversial issue: whether or not to adopt the “draft-rhrd-tls-tls13-visibility-01” protocol. To anybody outside the room, it might sound like gobbledegook, but this protocol was important.

Measures were being introduced to make it harder for hackers to attack crucial infrastructure such as utility networks, healthcare systems and retail groups. This was a mounting concern at the time – a year or so earlier, hackers seemingly from Russia had shut down the Ukrainian power system. The proposed “visibility” protocol would signal to internet users whether or not anti-hacking tools had been installed.

For an hour the engineers debated the protocol. Some opposed telling users the tools had been installed; others insisted on it. “There are privacy issues,” one said. “It’s about nation states,” another argued. “We cannot do this without consensus.” So a man named Sean Turner – who looked like a garden gnome, with a long, snowy-white beard, bald head, glasses and checked lumberjack shirt – invoked the IETF ritual.

“We are going to hum,” he said. “Please hum now if you support adoption.” A moan rose up, akin to a Tibetan chant, bouncing off the walls of the Metropole. “Thanks. Please hum now if you oppose.” There was a much louder collective hum. “So at this point there is no consensus to adopt this,” Turner declared. The protocol was put on ice.

Most people do not even know that the IETF exists, much less that computer engineers design the web by humming. That is not because the IETF hides its work. On the contrary, its meetings are open to anyone and posted online. But phrases like “draft-rhrd-tls-tls1.3” mean most people instinctively look away, just as they did with derivatives before the 2008 financial crisis. And, as with finance, this lack of external scrutiny – and understanding – is alarming, particularly given the accelerating effects of innovations such as AI.

Many of the engineers who build the technologies on which we rely are well-meaning. But they – like financiers – are prone to tunnel vision, and often fail to see that others may not share their mentality. “In a community of technological producers, the very process of designing, crafting, manufacturing and maintaining technology acts as a template and makes technology itself the lens through which the world is seen and defined,” observes Jan English-Lueck, an anthropologist who has studied Silicon Valley.

When the IETF members use humming, they are reflecting and reinforcing a distinctive worldview – their desperate hope that the internet should remain egalitarian and inclusive. That is their creation myth. But they are also signalling that human contact and context matter deeply, even in a world of computing. Humming enables them to collectively demonstrate the power of that idea. It also helps them navigate the currents of shifting opinion in their tribe and make decisions by reading a range of signals.

Humming does not sit easily with the way we imagine technology, but it highlights a crucial truth about how humans navigate the world of work, in offices, online or anywhere else: even if we think we are rational, logical creatures, we make decisions in social groups by absorbing a wide range of signals. And perhaps the best way to understand this is to employ an idea popularised by anthropologists working at companies such as Xerox during the late 20th century, and since used by Beunza and others on Wall Street: “Sense-making”.

One of the first thinkers to develop the concept of sense-making was a man named John Seely Brown. JSB, as he was usually known, was not trained as an anthropologist. He studied maths and physics in the early 60s, and finished a PhD in computer science in 1970, just as the idea of the internet was emerging, and then taught advanced computing science at the University of California, with a particular interest in AI. Around this time, after meeting some sociologists and anthropologists, he became fascinated by the question of how social patterns influence the development of digital tools, too.

He applied for a research post at Xerox’s Palo Alto Research Center (Parc), a research arm that the Connecticut-based company set up in Silicon Valley in 1969. Xerox was famous for developing the photocopier, but it also produced many other digital innovations. The authors of Fumbling the Future, a book about the history of the company, credits it with inventing “the first computer ever designed and built for the dedicated use of a single person … the first graphics-oriented monitor, the first handheld ‘mouse’ simple enough for a child, the first word-processing programme for non-expert users, the first local area communications network … and the first laser printer.”

During his application process to Parc, JSB met Jack Goldman, its chief scientist. The two men discussed Xerox’s research and development work, and its pioneering experiments with AI. Then JSB pointed to Goldman’s desk. “Jack, why two phones?” he asked. The desk contained both a “simple” phone and a newer, more sophisticated model.

“Oh my God, who the hell can use this phone?” Goldman said, referring to the new phone. “I have it on my desk because everyone has to have one, but when real work gets done I’ve got to use a regular one.”

That was exactly the kind of thing, Seely Brown said, that scientists at Xerox should also be researching: how humans were (or were not) using the dazzling innovations that Silicon Valley companies kept creating. Having started steeped in “hard” computing science, JSB realised that it paid to be a “softie” when looking at social science, or – to employ the buzzwords that were later popularised in Silicon Valley by the writer Scott Hartley – to be a techie and a “fuzzy”.

JSB joined Parc and put his new theories to work. Although the research centre had initially been dominated by scientists, by the time JSB arrived, a collection of anthropologists, psychologists and sociologists were also there. One of these anthropologists was a man named Julian Orr, who was studying the “tribe” of technical repair teams at Xerox.

By the late 20th century, copy machines were ubiquitous in offices. Work could collapse if one of these machines broke down. Xerox employed numerous people whose only job was to travel between offices, servicing and fixing machines. These technicians were routinely ignored, partly because the managers assumed that they knew what they did. But Orr and JSB suspected this was a big mistake, and that the technicians did not always think or behave as their bosses thought they should.

JSB first noticed it early in his time at Xerox, when he met a repairman known as “Mr Troubleshooter”, who said to him: “Well, Mr PhD, suppose this photocopier sitting here had an intermittent image quality fault, how would you go about troubleshooting it?”

JSB knew there was an “official” answer in the office handbook: technicians were supposed to “print out 1,000 copies, sort through the output, find a few bad ones, and compare them to the diagnostic”. It sounded logical – to an engineer.

“Here is what I do,” Mr Troubleshooter told JSB, with a “disgusted” look on his face. “I walk to the trash can, tip it upside down, and look at all the copies that have been thrown away. The trash can is a filter – people keep the good copies and throw the bad ones away. So just go to the trash can … and from scanning all the bad ones, interpret what connects them all.” In short, the engineers were ignoring protocols and using a solution that worked – but one that was “invisible … and outside [the] cognitive modelling lens” of the people running the company, JSB ruefully concluded.

How common was this kind of subversive approach? Orr set off to find out. He first enrolled in technical training school. Then he shadowed the repair teams out on service calls, at the parts depot, eating lunch and just hanging out when there was not much work to do. The fact that Orr had once worked as a technician himself helped in some respects: the repair crews welcomed him in. But it also created a trap: he sometimes had the same blind spots as the people he was studying. “I had a tendency to regard certain phenomena as unremarkable which are not really so to outsiders,” he later wrote in a report. He had to perform mental gymnastics to make “familiar” seem “strange”.

So, like many other anthropologists before him, he tried to get that sense of distance by looking at the group rituals, symbols and spatial patterns that the technicians used in their everyday life. Or quickly realized that many of the most important interactions took place in diners. “I drive to meet the members of the customer support team for breakfast at a chain restaurant in a small city on the east side,” Orr observed in one of his field notes. “Alice has a problem: her machine reports a self-test error, but she suspects there is some other problem … [so] we are going to lunch at a restaurant where many of [Alice’s] colleagues eat, to try to persuade Fred, the most experienced [technician], to go to look at the machine with her …

Fred tells her there is another component that she needs to change, according to his interpretation of the logs.” The repair teams were doing collective problem solving over coffee in those diners, using a rich body of shared narrative about the Xerox machines, and almost every other part of their lives. Their “gossip” was weaving a wide tapestry of group knowledge, and tapping into the collective views of the group – like the IETF humming.

This knowledge mattered. The company protocols assumed that “the work of technicians was the rote repair of identical broken machines,” as Lucy Suchman, another anthropologist at Parc, noted. But that was a fallacy: even if the machines seemed identical when they emerged from the Xerox factory, by the time repairmen encountered the machines they had histories shaped by humans. What engineers shared at the diner was this history and context. “Diagnosis is a narrative process,” Orr said.

The Xerox scientists eventually listened to the anthropologists – to some degree. After Orr issued his report on the technicians, the company introduced systems to make it easier for repair people to talk to one another in the field and share knowledge – even outside diners. A two-way radio system allowed tech reps in different regions to call on each other’s expertise. Xerox later supplemented these radios with a rudimentary messaging platform on the internet known as Eureka, where technicians could share tips. JSB viewed this as “an early model for social media platforms”.

Other Silicon Valley entrepreneurs became increasingly fascinated by what Parc was doing, and tried to emulate its ideas. Steve Jobs, a co-founder of Apple, toured Parc in 1979, saw the group’s efforts to build a personal computer, and then developed something similar at Apple, hiring away a key Parc researcher. Other Parc ideas were echoed at Apple and other Silicon Valley companies. But Xerox’s managers were not nearly as adept as Jobs in terms of turning brilliant ideas into lucrative gadgets, and in subsequent decades Xerox’s fortunes ailed.

That was partly because the company culture was conservative and slow-moving, but also because Parc was based on the west coast, while the main headquarters and manufacturing centres were on the other side of the country. Good ideas often fell between the cracks, to the frustration of Parc staff.

Still, as the years passed, Parc’s ideas had a big impact on social science and Silicon Valley. Their work helped to spawn the development of the “user experience” (UX) movement, prodding companies such as Microsoft and Intel to create similar teams. Their ideas about “sense-making” spread into the consumer goods world, and from there to an unlikely sphere: Wall Street.

A social scientist named Patricia Ensworth was one of the first to use sense-making in finance. Starting in the 80s, she decided to use social science to help explain why IT issues tended to generate such angst in finance. Her research quickly showed that the issues were social and cultural as much as technical. In one early project she found that American software coders were completely baffled as to why their internally developed software programmes kept malfunctioning – until she explained that office customs in other locations were different.

In the early 90s, Ensworth joined Moody’s Investors Service, and eventually became director of quality assurance for its IT systems. It sounded like a technical job. However, her key role was pulling together different tribes – software coders, IT infrastructure technicians, analysts, salespeople and external customers. Then she formed a consultancy to advise on “project management, risk analysis, quality assurance and other business issues”, combining cultural awareness with engineering.

In 2005, Ensworth received an urgent message from a managing director at a major investment bank. “We need a consultant to help us get some projects back on track!” the manager said. Ensworth was used to such appeals: she had spent more than a decade using techniques pioneered by the likes of Orr and Seely Brown in order to study how finance and tech intersected with humans.

The investment bank project was typical. Like many of its rivals, this bank had been racing to move its operations online. But by 2005 it was facing a crisis. Before 2000 it had outsourced much of its trading IT platform to India, since it was cheaper than hiring IT experts in the US. But while the Indian coders and testers were skilled at handling traditional investment products, they struggled to cope with a new derivatives business that the bank was building, since the Indian coders had formal, bureaucratic engineering methods. So the bank started to use other suppliers in Ukraine and Canada who had a more flexible style and were used to collaborating with creative mathematicians. But this made the problems even worse: deadlines were missed, defects emerged and expensive disputes erupted.

“In the New York office, tensions were running high between the onsite employees of rival outsourcing vendors,” Ensworth later wrote. “The pivot point occurred when a fight broke out: a male Canadian tester insulted a female Indian tester with X-rated profanity and she threw hot coffee in his face. Since this legally constituted a workplace assault, the female tester was immediately fired and deported. Debates about the fairness of the punishment divided the office … [and] at the same time auditors uncovered some serious operational and security violations in the outsourced IT infrastructures and processes.”

Many employees blamed the issues on inter-ethnic clashes. But Ensworth suspected another, more subtle problem. Almost all the coders at the bank, whether they were in India, Manhattan, Kyiv or Toronto, had been trained to think in one-directional sequences, driven by sequential logic, without much lateral vision. The binary nature of the software they developed also meant that they tended to have an “I’m-right-you’re-wrong” mentality. Although the coders could produce algorithms to solve specific problems, they struggled to see the whole picture or collaborate to adapt as conditions changed. “The [coders] document their research in the form of use cases, flowcharts and system architecture designs,” Ensworth observed. “These documents work well enough for version 1.0, because the cyberspace model matches the user community’s lived experience. But over time, the model and the reality increasingly diverge.”

The coders often seemed unaware of the gap between their initial plan and subsequent reality. Ensworth persuaded the suppliers in India to provide training about American office rules and customs, and tried to teach the suppliers in Ukraine and Canada about the dangers of taking an excessively freewheeling approach to IT. She showed coders videos of the noisy and chaotic conditions on bank trading floors; that was a shock, since coders typically toiled in library-like silence and calm. She explained to managers at the bank that coders felt angry that they could not access important proprietary databases and tools. The goal was to teach all “sides” to copy the most basic precept of anthropology: seeing the world from another point of view.

 Ensworth did not harbour any illusions about changing the bank’s overall culture. When the financial crisis erupted in 2008, the project was wound down and she moved on. However, she was thrilled to see that during the 18 months that she worked at the bank, some of the anthropology lessons stuck. “Delivery schedules and error rates were occasionally troublesome, but no longer a constant, pervasive worry,” she later wrote. Better still, the workers stopped throwing coffee around the office.


But what would happen to the business of sense-making at work if humans were suddenly prevented from working face to face? As he hovered like a fly on the wall of trading rooms on Wall Street and in the City of London in the early 2000s, Beunza often asked himself that question. Then, in the spring of 2020, he was unexpectedly presented with a natural experiment. As Covid-19 spread, financial institutions suddenly did what Bob had said they never would – they sent traders home with their Bloomberg terminals. So, over the course of the summer, Beunza contacted his old Wall Street contacts to ask a key question: what happened?

It was not easy to do the research. Anthropology is a discipline that prizes first-hand observations. Conducting research via video calls seemed to fly in the face of that. “A lot of my work depends on speaking to people face to face, understanding how they live their lives on their own terms and in their own spaces,” said Chloe Evans, an anthropologist at Spotify, to a conference convened in 2020 to discuss the challenge. “Being in the same space is vital for us to understand how people use products and services for the companies we work for.”

However, ethnographers realized there were benefits to the new world, too: they could reach people around the world on a more equal footing, and sometimes with more intimacy. “We see people in contexts not available to us in lab situations,” observed an ethnographer named Stuart Henshall, who was doing research among poor communities in India. Before the pandemic, most of the Indian people he interviewed were so ashamed of their domestic spaces that they preferred to meet in a research office, he explained. But after lockdown, his interviewees started talking to him via video calls from their homes and rickshaws, which enabled him to gain insight into a whole new aspect of their lives. “Participants are simply more comfortable at home in their environment. They feel more in control,” he observed. It was a new of type of ethnography.

When Beunza interviewed bankers remotely, he found echoes of this pattern: respondents were more eager to engage with him from home than in the office, and it felt more intimate. The financiers told him that they had found it relatively simple to do some parts of their job remotely, at least in the short term: working from home was easy if you were writing computer code or scanning legal documents. Teams that had already been working together for a long time also could interact well through video links.

The really big problem was incidental information exchange. “The bit that’s very hard to replicate is the information you didn’t know you needed,” observed Charles Bristow, a senior trader at JP Morgan. “[It’s] where you hear some noise from a desk a corridor away, or you hear a word that triggers a thought. If you’re working from home, you don’t know that you need that information.” Working from home also made it hard to teach younger bankers how to think and behave; physical experiences were crucial for conveying the habits of finance or being an apprentice.

Beunza was not surprised to hear that the financiers were eager to get traders back to the office as soon as they could; nor that most had quietly kept some teams working in the office throughout the crisis. Nor was he surprised that when banks such as JPMorgan started to bring some people back in – initially at 50% capacity – they spent a huge amount of time devising systems to “rotate” people; the trick seemed not to be bringing in entire teams, but people from different groups. This was the best way to get that all-important incidental information exchange when the office was half-full.

But one of the most revealing details from Beunza’s interviews concerned performance. When he asked the financiers at the biggest American and European banks how they had fared during the wild market turmoil of spring 2020, “the bankers said that their trading teams in the office did much, much better than those at home,” Beunza told me in the autumn of 2020. “The Wall Street banks kept more teams in the office, so they seem to have done a lot better than Europeans.” That may have been due to malfunctions on home-based tech platforms. But Beunza attributed it to something else: in-person teams had more incidental information exchange and sense-making, and at times of stress this seemed doubly important.

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The bankers that Beunza observed were not the only ones to realize the value of being together in the same physical space. The same pattern was playing out at the IETF. When the pandemic hit, the IETF organizers decided to replace in-person conventions with virtual summits. A few months later they polled about 600 members to see how they felt about this switch. More than half said they considered online meetings less productive than in-person, and only 7% preferred meeting online. Again, they missed the peripheral vision and incidental information exchange that happened with in-person meetings. “[Online] doesn’t work. In person is NOT just about the meeting sessions – it is about meeting people outside the meetings, at social events,” complained one member. “The lack of serendipitous meetings and chats is a significant difference,” said another. Or as one of them put it: “We need to meet in person to get meaningful work done.”

They also missed their humming rituals. As the meetings moved online, two-thirds of the respondents said they wanted to explore new ways to create rough consensus. “We need to figure out how to ‘hum’ online,” said one member. So the IETF organizers experimented with holding online polls. But members complained that virtual polls were too crude and one-dimensional; they crave a more nuanced, three-dimensional way to judge the mood of their tribe. “The most important thing to me about a hum is some idea of how many people present hummed at all, or how loudly. Exact numbers don’t matter, proportionality does,” said one.

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Source: The empty office: what we lose when we work from home | Anthropology | The Guardian

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