A group of 239 scientists says there’s growing evidence covid-19 is airborne

The news: A group of 239 scientists from 32 countries have written an open letter to the World Health Organization arguing that covid-19 can be transmitted through the air. You might think we know that already, but most current guidance is based on the idea that covid-19 is transmitted via droplets expelled from an infected person’s nose or mouth. The thought is that these larger respiratory droplets quickly fall to the floor. That’s the position the WHO has taken from early on in the pandemic, and that’s why we have been keeping at a distance from one other. However, the signatories of the open letter say the organization is underestimating the role of airborne transmission, where much smaller droplets (called aerosols) stay suspended in the air. These aerosols can travel farther than droplets and linger in an area even when an infected person has left.

What’s the evidence? The letter says multiple studies “have demonstrated beyond any reasonable doubt that viruses are released during exhalation, talking, and coughing in microdroplets small enough to remain aloft in air.” It says these microdroplets “pose a risk of exposure at distances beyond 1 to 2 m from an infected individual.” An early laboratory study carried out by the US National Institutes of Health found that the coronavirus can linger in the air for up to four hours in aerosol form. The coronavirus was also detected in aerosols collected at two hospitals in Wuhan, China, according to a study published in Nature in April. And superspreading events add to the weight of evidence: for example, after a choir practice in the US nearly 50 people were infected even though they kept a safe distance apart.

The implications: If airborne transmission is a route for the spread of the virus, it could lead to changes in the current advice. It would suggest that social distancing may be insufficient, especially indoors. This may place yet more importance on mask-wearing around people who are not part of your household if you meet them indoors, even if you are distancing, and increasing ventilation in enclosed areas. It could make air-filtering systems more important to try to cut down on the recirculation of air. And it might mean health-care workers caring for coronavirus patients need the highest grade of mask—N95—to filter out the smallest droplets.


A group of 239 scientists says there’s growing evidence covid-19 is airborne 2020/07/07 13:28

If you’re over 75, catching covid-19 can be like playing Russian roulette

Are you hiding from covid-19? I am. The reason is simple: the high chance of death from the virus. 

I was reminded of the risk last week by this report from the New York City health department and Columbia University which estimated that on average, between March and May, the chance of dying if you get infected by SARS-CoV-2 was 1.45%.

That’s higher than your lifetime chance of getting killed in a car wreck. That’s every driver cutting you off, every corner taken too fast, every time you nearly dozed off on the highway, all crammed into one. That’s not a disease I want to get. For someone my mother’s age, the chance of death came to 13.83% but ranged as high as 17%. That’s roughly 1 in 6, or the chance you’ll lose at Russian roulette. That’s not a game I want my mother to play.

The rate at which people are dying from the coronavirus has been estimated many times and is calculated in different ways. For example, if you become an official covid-19 “case” on the government’s books, your death chance is more like 5%, because you’re sick enough to have sought out help and to have been tested. 

But this study instead calculated the “infection fatality ratio,” or IFR. That’s the chance you die if infected at all. This is the real risk to keep in view. It includes people who are asymptomatic, get only a sniffle, or tough it out at home and never get tested. 

Because we don’t know who those people who never got tested are, IFR figures are always an estimate, and the 1.45% figure calculated for New York is higher than most others, many of which fluctuate around 1%. That could be due to higher rates of diabetes and heart disease in the city, or to estimates used in the study. 

It’s also true that your personal odds of dying from covid-19 will differ from the average. Location matters—cruise ship or city—and so do your sex, your age, and whether you have preexisting health conditions. If you’re in college, your death odds are probably lower by a factor of a hundred, though if you’re morbidly obese, they go back up. Poor health—cancer, clogged arteries—also steeply increase what scientists call the “odds ratio” of dying. 

The biggest factor, though, is age.  I looked at the actuarial tables, and the chance of death for a man in my age group (I’m 51) is around 0.4% per year from all causes. So if I get covid-19, my death chance is probably three times my annual all-cause annual risk (since I am a man, my covid-19 risk is higher than the average). Is that a chance I can live with? Maybe, but the problem is that I have to take that extra risk right now, all up front, not spread out over time where I can’t see or worry about it. 

Tbh, these % don’t help me. More useful would be a list of comparable risks associated with common behaviours that I uncritically accept. Do you know of any examples?

— Andrew Harmer (@andrew_harmer) July 1, 2020

On Twitter, some readers complained that average risks don’t tell them much about how to think or act. They have a point. What’s a real-life risk that’s similar to a 1.45% chance of dying? It wasn’t easy to think of one, since mathematically, you can’t encounter such a big risk very often. Skydiving, maybe?  According to the US Parachute Association, there’s just one fatality for every 220,301 jumps. It would take 3,200 jumps to equal the average risk of death from covid. 

Risk perceptions differ, but it’s the immense difference in IFR risk for the young (under 25) and the elderly (over 75) that really should complicate the reopening discussion. Judging from the New York data, Grandpa’s death chances from infection are 1,000 times that of Junior. So yes, we need schools to keep kids occupied, learning, and healthy. And for them, thank goodness, the chances of death are very low. But reopening schools and colleges has the ugly side effect that those with the lowest risk could be, in effect,  putting a gun to the head of those with the highest (although there is still much we do not know about how transmissible the virus is among children).

Decent odds

The virus is now spreading fast again in the US, after the country failed to settle on a strong mitigation plan. At the current rate of spread—40,000 confirmed cases a day (and maybe five to 10 times that in reality)—it’s only two years until most people in the US have been infected. It means we’re pointed toward what, since the outset, has been seen as the worst-case scenario: a couple of hundred million infected and a quarter-million deaths. 

By now you might be wondering what your own death risk is. Online, you can find apps that will calculate it, like one at covid19survivalcalculator.com, which employs odds ratios from the World Health Organization.  I gave it my age, gender, body mass index, and underlying conditions and learned that my overall death risk was a bit higher than the average. But the site also wanted to account for my chance of getting infected in the first place. After I told it I was social distancing and mostly wearing a mask, and my rural zip code, the gadget thought I had only a 5% of getting infected. 

I clicked, the page paused, and the final answer appeared: “Survival Probability: 99.975%”. 

Those are odds I can live with. And that’s why I am not leaving the house.


If you’re over 75, catching covid-19 can be like playing Russian roulette 2020/07/05 10:15

Are we making spacecraft too autonomous?

When SpaceX’s Crew Dragon took NASA astronauts to the ISS near the end of May, the launch brought back a familiar sight. For the first time since the space shuttle was retired, American rockets were launching from American soil to take Americans into space.

Inside the vehicle, however, things couldn’t have looked more different. Gone was the sprawling dashboard of lights and switches and knobs that once dominated the space shuttle’s interior. All of it was replaced with a futuristic console of multiple large touch screens that cycle through a variety of displays. Behind those screens, the vehicle is run by software that’s designed to get into space and navigate to the space station completely autonomously. 

“Growing up as a pilot, my whole career, having a certain way to control a vehicle—this is certainly different,” Doug Hurley told NASA TV viewers shortly before the SpaceX mission. Instead of calling for a hand on the control stick, navigation is now a series of predetermined inputs. The SpaceX astronauts may still be involved in decision-making at critical junctures, but much of that function has moved out of their hands.

Does this matter? Software has never played a more critical role in spaceflight. It has made it safer and more efficient, allowing a spacecraft to automatically adjust to changing conditions. According to Darrel Raines, a NASA engineer leading software development for the Orion deep space capsule, autonomy is particularly key for areas of “critical response time”—like the ascent of a rocket after liftoff, when a problem might require initiating an abort sequence in just a matter of seconds. Or in instances where the crew might be incapacitated for some reason. 

And increased autonomy is practically essential to making some forms of spaceflight even work. Ad Astra is a Houston-based company that’s looking to make plasma rocket propulsion technology viable. The experimental engine uses plasma made out of argon gas, which is heated using electromagnetic waves. A “tuning” process overseen by the system’s software automatically figures out the optimal frequencies for this heating. The engine comes to full power in just a few milliseconds. “There’s no way for a human to respond to something like that in time,” says CEO Franklin Chang Díaz, a former astronaut who flew on several space shuttle missions from 1986 to 2002. Algorithms in the control system are used to recognize changing conditions in the rocket as it’s moving through the startup sequence—and act accordingly. “We wouldn’t be able to do any of this well without software,” he says.

But overrelying on software and autonomous systems in spaceflight creates new opportunities for problems to arise. That’s especially a concern for many of the space industry’s new contenders, who aren’t necessarily used to the kind of aggressive and comprehensive testing needed to weed out problems in software and are still trying to strike a good balance between automation and manual control.

  • space shuttle Atlantis
    The Space Shuttle Atlantis had a more traditional dashboard for its pilots to utilize.
  • inflight video of Dragon 2 mission
    The Crew Dragon capsule replaces the knobs and switches with large touchscreens.

Nowadays, a few errors in over one million lines of code could spell the difference between mission success and mission failure. We saw that late last year, when Boeing’s Starliner capsule (the other vehicle NASA is counting on to send American astronauts into space) failed to make it to the ISS because of a glitch in its internal timer. A human pilot could have overridden the glitch that ended up burning Starliner’s thrusters prematurely. NASA administrator Jim Bridenstine remarked soon after Starliner’s problems arose: “Had we had an astronaut on board, we very well may be at the International Space Station right now.” 

But it was later revealed that many other errors in the software had not been caught before launch, including one that could have led to the destruction of the spacecraft. And that was something human crew members could easily have overridden.

Boeing is certainly no stranger to building and testing spaceflight technologies, so it was a surprise to see the company fail to catch these problems before the Starliner test flight. “Software defects, particularly in complex spacecraft code, are not unexpected,” NASA said when the second glitch was made public. “However, there were numerous instances where the Boeing software quality processes either should have or could have uncovered the defects.” Boeing declined a request for comment.

According to Luke Schreier, the vice president and general manager of aerospace at NI (formerly National Instruments), problems in software are inevitable, whether in autonomous vehicles or in spacecraft. “That’s just life,” he says. The only real solution is to aggressively test ahead of time to find those issues and fix them: “You have to have a really rigorous software testing program to find those mistakes that will inevitably be there.”

Enter AI

Space, however, is a unique environment to test for. The conditions a spacecraft will encounter aren’t easy to emulate on the ground. While an autonomous vehicle can be taken out of the simulator and eased into lighter real-world conditions to refine the software little by little, you can’t really do the same thing for a launch vehicle. Launch, spaceflight, and a return to Earth are actions that either happen or they don’t—there is no “light” version.

This, says Schreier, is why AI is such a big deal in spaceflight nowadays—you can develop an autonomous system that is capable of anticipating those conditions, rather than requiring the conditions to be learned during a specific simulation. “You couldn’t possibly simulate on your own all the corner cases of the new hardware you’re designing,” he says. 

So for some groups, testing software isn’t just a matter of finding and fixing errors in the code; it’s also a way to train AI-driven software. Take Virgin Orbit, for example, which recently tried to send its LauncherOne vehicle into space for the first time. The company worked with NI to develop a test bench that looped together all the vehicle’s sensors and avionics with the software meant to run a mission into orbit (down to the exact length of wiring used within the vehicle). By the time LauncherOne was ready to fly, it believed it had already been in space thousands of times thanks to the testing, and it had already faced many different kinds of scenarios.

Of course, the LauncherOne’s first test flight ended in failure, for reasons that have still not been disclosed. If it was due to software limitations, the attempt is yet another sign there’s a limit to how much an AI can be trained to face real-world conditions. 

Raines adds that in contrast to the slower approach NASA takes for testing, private companies are able to move much more rapidly. For some, like SpaceX, this works out well. For others, like Boeing, it can lead to some surprising hiccups. 

Ultimately, “the worst thing you can do is make something fully manual or fully autonomous,” says Nathan Uitenbroek, another NASA engineer working on Orion’s software development. Humans have to be able to intervene if the software is glitching up or if the computer’s memory is destroyed by an unanticipated event (like a blast of cosmic rays). But they also rely on the software to inform them when other problems arise. 

NASA is used to figuring out this balance, and it has redundancy built into its crewed vehicles. The space shuttle operated on multiple computers using the same software, and if one had a problem, the others could take over. A separate computer ran on entirely different software, so it could take over the entire spacecraft if a systemic glitch was affecting the others. Raines and Uitenbroek say the same redundancy is used on Orion, which also includes a layer of automatic function that bypasses the software entirely for critical functions like parachute release. 

On the Crew Dragon, there are instances where astronauts can manually initiate abort sequences, and where they can override software on the basis of new inputs. But the design of these vehicles means it’s more difficult now for the human to take complete control. The touch-screen console is still tied to the spacecraft’s software, and you can’t just bypass it entirely when you want to take over the spacecraft, even in an emergency. 

There’s no consensus on how much further the human role in spaceflight will—or should—shrink. Uitenbroek thinks trying to develop software that can account for every possible contingency is simply impractical, especially when you have deadlines to make. 

Chang Díaz disagrees, saying the world is shifting “to a point where eventually the human is going to be taken out of the equation.” 

Which approach wins out may depend on the level of success achieved by the different parties sending people into space. NASA has no intention of taking humans out of the equation, but if commercial companies find they have an easier time minimizing the human pilot’s role and letting the AI take charge, than touch screens and pilotless flight to the ISS are only a taste of what’s to come.


Are we making spacecraft too autonomous? 2020/07/03 10:30

Another experimental covid-19 vaccine has shown promising early results

The news: An experimental covid-19 vaccine being developed by Pfizer and BioNTech provoked immune responses in 45 healthy volunteers, according to a preprint paper on medRXiv. The levels of antibodies were up to 2.8 times the level of those found in patients who have recovered. The study randomly assigned 45 people to get either one of three doses of the vaccine or a placebo. But there were side effects like fatigue, headache, and fever—especially at higher doses. The researchers decided to discontinue with the highest dose, 100 micrograms, after the first round of treatments.

Some caveats required: It’s promising news,but this is the first clinical data on this specific vaccine, and it hasn’t been through the process of peer review yet. Higher antibody levels in patients who’d received the vaccine are a useful proxy for immunity to covid-19, but we don’t yet know for sure that they guarantee immunity. In order to find out, Pfizer will start conducting studies in larger groups of patients, starting this summer. It says its goal is to have 100 million doses of a vaccine available by the end of 2020.

A common approach: Pfizer is using the same experimental technique as Moderna, one of the other pharmaceutical companies developing a vaccine. Both vaccines are designed to provoke an immune response against the coronavirus through its messenger RNA, the genetic instructions that tell the virus how to replicate inside the host. The method could provide a rapid way to develop a vaccine, but it’s yet to lead to a licensed one for sale. Currently, 178 vaccines are in various stages of development; 17 are now going through clinical trials.


Another experimental covid-19 vaccine has shown promising early results 2020/07/02 13:18

Intelligent infrastructure: How an agile, robust, and flexible IT infrastructure can make or break digital transformation

In today’s business environment, strategic technology initiatives are driven by the need to grow with greater agility and adapt to rapidly changing commercial, environmental, and regulatory conditions. A new report, sponsored by Panduit, explores how IT leaders from a variety of industries are building intelligent infrastructure that provides a platform for innovation and insights. The key findings of the report are:

  • Intelligent infrastructure provides a platform for business agility. In a highly competitive global environment, further strained by an unprecedented pandemic, businesses are increasingly looking to data and analytics to resolve operational dilemmas, highlight avenues for growth, and increase the productivity of far-flung employees. Digital transformation is well underway at many organizations, but opportunities remain. Whether it is 5G, migrating to hybrid cloud, or moving toward the edge, technology leaders are deploying network infrastructures that are reliable, scalable, and flexible.
  • IT infrastructure needs to be robust and dynamic. There is no one-size-fits-all, and IT leaders must balance cost and complexity while also monitoring risk and compliance. The infrastructure needs to be architected in a way that enables business leaders to respond to new challenges and opportunities.
  • The edge provides analytical fuel for innovation. Edge computing allows businesses to get closer to their customers and suppliers and make faster decisions. New use cases abound: AI for recognizing a customer’s pet, IoT networks that assess bushfire risk, real-time patient interactions through mobile apps, and blockchain-secured supplier tracing for palm oil commodities. Edge computing capabilities provide the backbone for innovation—allowing organizations to accelerate their quest for real-time analytics and insight.

Download the full report here.


Intelligent infrastructure: How an agile, robust, and flexible IT infrastructure can make or break digital transformation 2020/07/01 15:00

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