Bookmarked Why the Coronavirus Is So Confusing (The Atlantic)

A guide to making sense of a problem that is now too big for any one person to fully comprehend

Ed Yong continues his reporting of the coronavirus. In this article, he summarises the challenge associated with the current crisis into six parts: the virus, the disease, the reserach, the experts, the messaging, the information, the numbers and the narrative.

Yong begins by explaining how COVID19 is just one of many coronaviruses, each of which is different.

There isn’t just one coronavirus. Besides SARS-CoV-2, six others are known to infect humans—four are mild and common, causing a third of colds, while two are rare but severe, causing MERS and the original SARS. But scientists have also identified about 500 other coronaviruses among China’s many bat species.

This is in contrast to SARS-CoV-2, the disease that the virus induces. Something which there is still a lot of mystique and mystery around.

Prasad’s concern is that COVID-19 has developed a clinical mystique—a perception that it is so unusual, it demands radically new approaches. “Human beings are notorious for our desire to see patterns,” he says. “Put that in a situation of fear, uncertainty, and hype, and it’s not surprising that there’s almost a folk medicine emerging.”

In the rush to understand, scientists face the challenged on not only sorting through peer-reviewed research, but also the plethora of preprint research released into the public discourse.

Preprints also allow questionable work to directly enter public discourse, but that problem is not unique to them. The first flawed paper on hydroxychloroquine and COVID-19 was published in a peer-reviewed journal, whose editor in chief is one of the study’s co-authors. Another journal published a paper claiming that the new coronavirus probably originated in pangolins, after most virologists had considered and dismissed that idea.

Associated with this challenge, there are questions about those who actually has expertise and the reality that to produce the answers we may want we actually need to work together.

No one knows it all, and those who claim to should not be trusted.

In a pandemic, the strongest attractor of trust shouldn’t be confidence, but the recognition of one’s limits, the tendency to point at expertise beyond one’s own, and the willingness to work as part of a whole.

Something that confounds this is the inconsistency with the messaging from the official streams.

The impulse to be reassuring is understandable, but “the most important thing is to be as accurate as possible,” Inglesby says. “We should give people information so they can do what they think is right. We should tell people what we don’t know and when we’ll know more.”

With this confusion from those in power comes the rise of disinformation and falsehoods by those wishing to take it.

As the reality of the pandemic becomes clearer, the partisan gap is rapidly closing. But as time passes, misinformation, which refers to misleading stories that are circulated in good faith, will give way to disinformation—falsehoods deliberately seeded “to leverage the disaster for political power,” Starbird says.

One particular point of confusion is the death count associated COVID-19 and the fact that we often overlook what the numbers actually say.

If flu deaths were counted like COVID-19 deaths, the number would be substantially lower. This doesn’t mean we’re overestimating the flu. It does mean we are probably underestimating COVID-19.

This all creates for a challenging narrative. Like the Y2K bug, it is a difficult story to tell, for the success often relates to what goes untold.

I cannot read about the losses that never occurred, because they were averted. Prevention may be better than cure, but it is also less visceral.

Along with steams such as Coronacast, I have found Ed Yong’s posts useful in making sense of the current crisis.

Bookmarked Why Some People Get Sicker Than Others (The Atlantic)

COVID-19 is proving to be a disease of the immune system. This could, in theory, be controlled.

James Hamblin discusse reasons why some people crash, while others do not. He discusses the cytokine storm caused by the the immune response and the balance required between the virus and the immune system.

At this point, the priority for doctors shifts from hoping that a person’s immune system can fight off the virus to trying to tamp down the immune response so it doesn’t kill the person or cause permanent organ damage. As Cron puts it, “If you see a cytokine storm, you have to treat it.” But treating any infection by impeding the immune system is always treacherous. It is never ideal to let up on a virus that can directly kill our cells. The challenge is striking a balance where neither the cytokine storm nor the infection runs rampant.

The problem with this balance is that it requires more care and monitoring.

Deciding on the precise method of modulating the immune response—the exact drug, dose, and timing—is ideally informed by carefully monitoring patients before they are critically ill. People at risk of a storm could be monitored closely throughout their illness, and offered treatment immediately when signs begin to show. That could mean detecting the markers in a person’s blood before the process sends her into hallucinations—before her oxygen level fell at all.

Hamblin explains that the problem being faced is not those over the age of 60 etc, but rather than immunity of the community.

The immune system is a function of the communities that brought us up and the environments with which we interact every day. Its foundation is laid by genetics and early-life exposure to the world around us—from the food we eat to the air we breathe. Its response varies on the basis of income, housing, jobs, and access to health care.

The people who get the most severely sick from COVID-19 will sometimes be unpredictable, but in many cases, they will not. They will be the same people who get sick from most every other cause. Cytokines like IL-6 can be elevated by a single night of bad sleep. Over the course of a lifetime, the effects of daily and hourly stressors accumulate. Ultimately, people who are unable to take time off of work when sick—or who don’t have a comfortable and quiet home, or who lack access to good food and clean air—are likely to bear the burden of severe disease.

I would guess that this is the concern in regards to the fear in Australia of the virus getting into indigenous communities.

Bookmarked Now Is the Time to Overreact (The Atlantic)

Sometimes we do things even though they don’t make sense, or even because they don’t make sense, because our tiny minds have proven unable to grasp their consequences. In this case, Americans are not conducting this grand social experiment to make ourselves feel comfortable. We are doing it in the hope that later, and maybe even soon, we will look back and find it unreasonable. In the best-case scenario, as with Y2K, we might even look back and mock it for its excess. The point of overreacting, it turns out, is to overreact: to react excessively, but with reason. If you feel at least a little foolish right now, then you’re doing something right.

Ian Bogost reflects on the response by many Americans. Although encouraged to engage in social distancing, many are still congregating in close groups. He explains that although isolating ourselves might seem extreme, such measures can only be appreciated in the future and must be embraced in faith and hope. This is similar to the arguments of Nassim Nicholas Taleb.
Bookmarked The Problem With Feedback by Megan Ward (The Atlantic)

Companies and apps constantly ask for ratings, but all that data may just be noise in the system.

Megan Ward looks back at the history of feedback. She touches on its origins associated with improving machine efficiency and explains how it has been appropriated in recent times as a tool for managing people. Ward explains that this confuses things and in the process we risk making the activity one of noise, rather than any sort of meaning.


Traceable to antiquity, the idea of feedback roared to prominence in the 18th century when the Scottish engineer James Watt figured out how to harness the mighty but irregular power of steam. Watt’s steam governor solved the problem of wasted fuel by feeding the machine’s speed back into the apparatus to control it. When the machine ran too fast, the governor reduced the amount of steam fed to the engine. And when it slowed down, the governor could increase the flow of steam to keep the machine’s speed steady. The steam governor drove the Industrial Revolution by making steam power newly efficient and much more potent. Because it could maintain a relatively stable speed, Watt’s steam engine used up to one-third less energy than previous steam-powered engines.

Wiener broadened the definition of feedback, seeing it as a generic “method of controlling a system” by using past results to affect future performance. Any loop that connects past failures and successes to the present performance promises an improved future. But instead of energy, Wiener thought of feedback in terms of information. No matter the machine, Wiener hypothesized, it took in “information from the outer world” and, “through the internal transforming powers of the apparatus,” made information useful. Water flow, engine speed, temperature—all become information.

Positive ratings are a kind of holy grail on sites like Yelp and TripAdvisor, and negative reviews can sink a burgeoning small business or mom-and-pop restaurant. That shift has created a misunderstanding about how feedback works. The original structure of the loop’s information regulation has been lost.

Feedback may matter to the corporations that solicit it, but the nature of the feedback itself—the people who provide it, the relevance of their opinions, and the quality of the information—seems not to matter at all.