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The province is reporting 346 new cases of COVID-19 Saturday, bringing the total number of confirmed cases to 19,944. There were 59 more deaths reported, for a total of 1,599. Of those, 775 involved residents in the troubled long-term care system. There are now 237 outbreaks in the province’s care facilities, increase of three. After […]

It’s chilly out there this morning. The temperature at 7 a.m. Saturday morning sat at -3 C. Making it feel more like March than May. Clouds shouldroll in later this morning, bringing a 40 per cent chance of flurries, the high reaching only 4 C. Yep, more like March than May. The wind kicks up […]

Ottawa Fire Services received a 911 call from the homeowner at 6183 Carp Rd., reporting a detached garage was on fire. That was followed by a number of 911 calls reported heavy smoke coming from the area of Carp and Styles Side roads. While on route to the scene, crews spotted the heavy smoke and […]

Chris Labelle has a hard time getting through his latest song, Frontliners, without becoming emotional.  The Ottawa country singer wrote the tune — an unabashedly sentimental anthem of gratitude for front-line workers — during one of the sleepless nights leading up to the birth of his first child with wife Julie. Their baby boy, Grayson, […]

To mark our 175th anniversary year, we feature a different front page each week from past editions of the Ottawa Citizen.

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Saturday, May 9: Some odd musical instruments, the Official Plan and the pandemic -- you can write to us too, on these or any topics, at: letters@ottawacitizen.com

Ottawa police received a call that a residence on St. Catherine near Percy Street had been shot at on March 26. No one was injured.

Starting Monday, “park ambassadors” will be stationed at Ottawa’s busiest parks to provide information about what's permitted under pandemic rules.

The National Capital Commission has backed down from a decision to install signs to discourage people from taking pictures or – even stopping to admire – the Canadian Tulip Festival blooms. “Dear all: our bad!” the NCC tweeted Friday night after the move attracted controversy — and the ire of Mayor Jim Watson. The signs […]

When the season opened on April 11 after a three-week delay, only players, team personnel and cheerleaders were allowed in the stadium.

The Washington Capitals announced in a statement Friday morning that Brendan Leipsic has been placed on unconditional waivers for the purposes of terminating his contract.

The team says that after working closely with the local government, infectious disease experts and public health authorities, players will be allowed to access the OVO Athletic Centre starting next week.

"Our best-case scenario for this year is a drastically truncated season," Randy Ambrosie said. "And our most likely scenario is no season at all.''

Winnipeg-born NHL player Brendan Leipsic is facing massive criticism after private messages degrading women were exposed online.

Premier John Horgan has written to NHL Commissioner Gary Bettman pledging the government's support for Vancouver as a hub city if hockey returns this season.

The country’s professional soccer leagues will kick off Friday, also without spectators in the stadiums.

Prime Minister Justin Trudeau said Sunday that players would — at a minimum — need to follow quarantine protocols if they were to arrive in Canada while the border remains closed due to the pandemic.

Team training facilities have been closed, other than for approved rehab, since the league suspended play March 12 due to the global pandemic.

The veteran of 695 NHL games said: "I guess I'm not invincible, just got diagnosed with Covid, since I'm asthmatic, not the best news, will fight it off!''

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Immigrants in the U.S. sent an estimated $150 billion to their home countries in 2019 — half to Latin America and the Caribbean. The World Bank is predicting a sharp decline in remittances this year.

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NPR's Mary Louise Kelly talks with Jean-Michel Blanquer, French minister of education, about how France is planning to reopen primary schools on May 11.

As a longtime Paris resident, at first I feared Dirt might be yet another expat tale of moving to France en famille, with all its tedious clichés. I should have known better.

Belarusian President Alexander Lukashenko has dismissed the pandemic as mass "psychosis" — a disease easily cured with a bit of vodka, a hot sauna or spending time playing hockey or doing farm work.

Visitors' health status will be checked on a smartphone app before they enter the park. Once inside, they will be required to wear face masks at all times unless they are eating.

Steve Inskeep talks to Gen. Mark Milley, chairman of the Joint Chiefs of Staff, about the coronavirus threat within the ranks of the military, and guarding against a power competition with China.

The Trump administration says China poses a risk for its lack of transparency about COVID-19. China says the U.S. is trying to shift blame for the Trump administration's failings.

With hospitals and cemeteries overwhelmed by the coronavirus, the mayor of Manaus, Brazil's hardest hit city, has appealed to world leaders, including President Trump, for help.

The version published in China Daily omitted a reference to the illness originating in China and spreading to the rest of the world. The piece was published in full on the authors' websites.

Three doctors in Russia have fallen out of hospital windows during the coronavirus pandemic. Two of them died, and the third one is in serious condition.

 

The officials deciding what to open, and when, seldom offer thoughtful rationales. Clearly, risk communication about COVID-19 is failing with potentially dire consequences.Photograph by michael_swan / Flickr

When I worked as a TV reporter covering health and science, I would often be recognized in public places. For the most part, the interactions were brief hellos or compliments. Two periods of time stand out when significant numbers of those who approached me were seeking detailed information: the earliest days of the pandemic that became HIV/AIDS and during the anthrax attacks shortly following 9/11. Clearly people feared for their own safety and felt their usual sources of information were not offering them satisfaction. Citizens’ motivation to seek advice when they feel they aren’t getting it from official sources is a strong indication that risk communication is doing a substandard job. It’s significant that one occurred in the pre-Internet era and one after. We can’t blame a public feeling misinformed solely on the noise of the digital age.

America is now opening up from COVID-19 lockdown with different rules in different places. In many parts of the country, people have been demonstrating, even rioting, for restrictions to be lifted sooner. Others are terrified of loosening the restrictions because they see COVID-19 cases and deaths still rising daily. The officials deciding what to open, and when, seldom offer thoughtful rationales. Clearly, risk communication about COVID-19 is failing with potentially dire consequences.

A big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do.

Peter Sandman is a foremost expert on risk communication. A former professor at Rutgers University, he was a top consultant with the Centers for Disease Control in designing crisis and emergency risk-communication, a field of study that combines public health with psychology. Sandman is known for the formula Risk = Hazard + Outrage. His goal is to create better communication about risk, allowing people to assess hazards and not get caught up in outrage at politicians, public health officials, or the media. Today, Sandman is a risk consultant, teamed with his wife, Jody Lanard, a pediatrician and psychiatrist. Lanard wrote the first draft of the World Health Organization’s Outbreak Communications Guidelines. “Jody and Peter are seen as the umpires to judge the gold standard of risk communications,” said Michael Osterholm of the Center for Infectious Disease Research and Policy at the University of Minnesota. Sandman and Lanard have posted a guide for effective COVID-19 communication on the center’s website.

I reached out to Sandman to expand on their advice. We communicated through email.

Sandman began by saying he understood the protests around the country about the lockdown. “It’s very hard to warn people to abide by social-distancing measures when they’re so outraged that they want to kill somebody and trust absolutely nothing people say,” he told me. “COVID-19 outrage taps into preexisting grievances and ideologies. It’s not just about COVID-19 policies. It’s about freedom, equality, too much or too little government. It’s about the arrogance of egghead experts, left versus right, globalism versus nationalism versus federalism. And it’s endlessly, pointlessly about Donald Trump.”

Since the crisis began, Sandman has isolated three categories of grievance. He spelled them out for me, assuming the voices of the outraged:

• “In parts of the country, the response to COVID-19 was delayed and weak; officials unwisely prioritized ‘allaying panic’ instead of allaying the spread of the virus; lockdown then became necessary, not because it was inevitable but because our leaders had screwed up; and now we’re very worried about coming out of lockdown prematurely or chaotically, mishandling the next phase of the pandemic as badly as we handled the first phase.”

• “In parts of the country, the response to COVID-19 was excessive—as if the big cities on the two coasts were the whole country and flyover America didn’t need or didn’t deserve a separate set of policies. There are countless rural counties with zero confirmed cases. Much of the U.S. public-health profession assumes and even asserts without building an evidence-based case that these places, too, needed to be locked down and now need to reopen carefully, cautiously, slowly, and not until they have lots of testing and contact-tracing capacity. How dare they destroy our economy (too) just because of their mishandled outbreak!”

• “Once again the powers-that-be have done more to protect other people’s health than to protect my health. And once again the powers-that-be have done more to protect other people’s economic welfare than to protect my economic welfare!” (These claims can be made with considerable truth by healthcare workers; essential workers in low-income, high-touch occupations; residents of nursing homes; African-Americans; renters who risk eviction; the retired whose savings are threatened; and others.)

In their article for the Center for Infectious Disease Research and Policy, Sandman and Lanard point out that coping with a pandemic requires a thorough plan of communication. This is particularly important as the crisis is likely to enter a second wave of infection, when it could be more devastating. The plan starts with six core principles: 1) Don’t over-reassure, 2) Proclaim uncertainty, 3) Validate emotions—your audience’s and your own, 4) Give people things to do, 5) Admit and apologize for errors, and 6) Share dilemmas. To achieve the first three core principles, officials must immediately share what they know, even if the information may be incomplete. If officials share good news, they must be careful not to make it too hopeful. Over-reassurance is one of the biggest dangers in crisis communication. Sandman and Lanard suggest officials say things like, “Even though the number of new confirmed cases went down yesterday, I don’t want to put too much faith in one day’s good news.” 

Sandman and Lanard say a big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do. They caution against invoking “science” as a sole reason for action, as science in the midst of a crisis is “incremental, fallible, and still in its infancy.” Expressing empathy, provided it’s genuine, is important, Sandman and Lanard say. It makes the bearer more human and believable. A major tool of empathy is to acknowledge the public’s fear as well as your own. There is good reason to be terrified about this virus and its consequences on society. It’s not something to hide.

Sandman and Lanard say current grievances with politicians, health officials, and the media, about how the crisis has been portrayed, have indeed been contradictory. But that makes them no less valid. Denying the contradictions only amplifies divisions in the public and accelerates the outrage, possibly beyond control. They strongly emphasize one piece of advice. “Before we can share the dilemma of how best to manage any loosening of the lockdown, we must decisively—and apologetically—disabuse the public of the myth that, barring a miracle, the COVID-19 pandemic can possibly be nearing its end in the next few months.”

Robert Bazell is an adjunct professor of molecular, cellular, and developmental biology at Yale. For 38 years, he was chief science correspondent for NBC News.

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The coronavirus news from Mozambique is mixed, as it is in much of sub-Saharan Africa. Many experts fear chaos is inevitable.Photograph by gaborbasch / Shutterstock

We called Greg Carr the other day to talk about the spread of the coronavirus in Africa. Carr, who has been featured in Nautilus, is the founder of the Gorongosa Restoration Project, a partnership with the Mozambique government to revive Gorongosa National Park, that environmental treasure trove at the southern end of the Rift Valley. The 1,500 square-mile park, about the size of Rhode Island, was first given animal refuge status in the 1920s by the Portuguese, and for years was a favorite of European tourists. But in 1983 civil war broke out and the park became a no-man’s land. The place was poached to death, closed up and didn’t reopen until 1992.

Renewal began in 2004 and in 2008 the government signed a restoration agreement with Carr’s foundation. The agreement, which lasts through 2043, envisions a “human rights park” that will restore both ecosystems and economic vitality. After 11 years of rebuilding infrastructure, reintroducing animals, including hippos and wildebeests, and working with local communities, Gorongosa is thriving again. The park now serves as a model for future conservation. Today some 200,000 people live around the park in a “sustainable development zone” that includes education, employment opportunities, and health service. About 700 people have full time jobs in the park; another 300, part time. Naturalist E.O. Wilson calls Gorongosa “a window on eternity.”

“If there’s one thing the rest of the world can learn from Africans, it would be their resilience.”

Carr is a 60-year-old entrepreneur and philanthropist who grew up in Idaho and in his mid twenties co-founded Boston Technology, a voice mail company. By the time he turned 40 he had amassed his fortune and couldn’t see the fun in doing it all over again, and so turned to philanthropy. These days he’s in Idaho Falls, on the phone six hours a day, getting the latest reports from his staff in the park, now closed until further notice.

The coronavirus news from Mozambique is mixed, as it is in much of sub-Saharan Africa. With the exception of South Africa, with over 7,500 confirmed cases of COVID-19 and 148 deaths, some countries below the Equator have fewer than 100 cases. As of May 6, there were just 81 cases in Mozambique and no deaths. If these numbers don’t blow up, the quick explanation might hold that the median age in Sub Saharan Africa is under 20, just 17.6 in Mozambique; population density is low (103 people per square mile); and there’s relatively limited direct contact with heavily infected countries in other parts of the world. 

Still, many experts fear chaos is inevitable. Underlying conditions in Mozambique include implacable poverty and a 60-year history of colonial and civil wars. On another front, in early April, in northern Mozambique, an Isis group shot or beheaded 52 young people because they refused to be recruited. Add a 48 percent literacy rate for women, 60 percent for men. The country also suffers the world’s eighth-highest incidence of HIV; 1.5 million people have contracted the virus and nearly 40,000 people have died. Finally, a large number of Mozambicans go to South Africa for work and then return. Testing is rare in the entire country.

In March, CDC Africa sent out a national directive requiring social distancing. “People are going to pay more attention to that in the cities than they are in rural Mozambique, at least until the virus really comes,” Carr said the other day. “Now, if you live in rural Mozambique, you don’t have the luxury of saying, ‘I’m isolating at home.’ People have to go out every day, to get food and water, from 40 to 60 liters a day, they have to tend to their farms. The idea of social distancing is a bit impossible for these folks.” He added, “Schools are closed and we are making our own masks for people. We all know there’s no treatment per se or certainly vaccine. If this hits, we’ll only be able to offer people Tylenol and soup.”

Cases in Mozambique could shoot up as mine workers continue to return home from their jobs in South Africa. “In my opinion,” said Carr, “Mozambique does not have the capacity to deal with this type of pandemic, as there are few qualified health personnel and the high level of poverty leads people to resist isolating themselves, as they look for alternatives to take care of their families. Our Gorongosa teams are in the field, spreading prevention messages, distributing masks and water purification.” 

Berta Barros, head nurse at Gorongosa, told Carr recently she has three main worries: lack of COVID-19 test kits, lack of healthcare professionals to respond to sick patients, and shortage of medications for treatment. “Mozambique has a population close to 30 million and we only have 34 ventilators,” Barros said. “It’s beyond impossible to work and choose who to save.”

Carr often talks about Mozambique as though he was Mozambican. “We’re very practical people,” he’ll say. “We’re not really theoretical. We’re just going to work our way through this.” He shies away from broad, open-ended questions about Africa, much less cultural comparisons and grand conclusions. “Africa is more than 1 billion people in 54 countries with, what, 2,500 languages? To make a statement like, ‘Africa is this…’ Frankly, I just think a lot of it is complete baloney.”

At the same time, says Carr, “If there’s one thing the rest of the world can learn from Africans, it would be their resilience. We’ve had five years of war in Mozambique and then last year we had a cyclone that killed nearly 1,000 people. I didn’t even mention the two droughts we had in the last seven years and the armyworm that came through and ate everybody’s maize. These people had their homes washed away in a flood last year, lost everything. So they rebuild their homes and then someone says, ‘Hey, there might be a virus coming through.’ It’s just one thing after another.”

What impact might the pandemic have on animals in the park? What effect will it have on just recovered antelope populations, for example, and the inevitable increase in poaching as tourism subsides? How many resources will need to be taken away from the war on other diseases to fight this? Impossible to say. But an anecdote came to Carr’s mind that suggests the vagaries of death in Southern Africa. “I got a call from a dear friend of mine yesterday, a Mozambique good friend, who said her aunt had just died. I said, ‘Wow, do you think it was COVID?’ She goes, ‘No, she’d been suffering for a while with a bad kidney.’ Life is tough in Africa. Do we know for sure this woman didn’t also have COVID and that contributed? Maybe. The truth about Africa is that disaster is hardly news. Malaria is the most prolific killer. And when they turn 50, people die and often no one knows exactly what the cause was. It’s just the way life is.”

Mark MacNamara is an Asheville, North Carolina-based writer. His articles for Nautilus include “We Need to Talk About Peat” and “The Artist of the Unbreakable Code.”

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You probably know my robot. I’ve been inventing autonomous machines for over 30 years and one of them, Roomba from iRobot, is quite popular. During my career, I’ve learned a lot about what makes robots valuable, and formed some strong opinions about what we can expect from them in the future. I can also tell you why, contrary to popular apocalyptic Hollywood images, robots won’t be taking over the world anytime soon. But that’s getting ahead of myself. Let me back up.

My love affair with robots began in the early 1980s when I joined the research staff at MIT’s Artificial Intelligence Lab. Physics was my college major but after a short time at the lab the potential of the developing technology seduced me. I became a roboticist.

Such an exhilarating place to work! A host of brilliant people were researching deep problems and fascinating algorithms. Amazingly clever mechanisms were being developed, and it was all converging in clever and capable mobile robots. The future seemed obvious. So, I made a bold prediction and told all my friends, “In three to five years, robots will be everywhere doing all sorts of jobs.”

But I was wrong.

Again and again in those early years, news stories teased: “Big Company X has demonstrated a prototype of Consumer Robot Y. X says Y will be available for sale next year.” But somehow next year didn’t arrive. Through the 1980s and 1990s, robots never managed to find their way out of the laboratory. This was distressing to a committed robot enthusiast. Why hadn’t all the journal papers, clever prototypes, and breathless news stories culminated in a robot I could buy in a store?

Let me answer with the story of the first consumer robot that did achieve marketplace stardom.

RUG WARRIOR: Joe Jones built his “Rug Warrior” (above) in 1989. He calls it “the earliest conceptual ancestor of Roomba.” It included bump sensors and a carpet sweeper mechanism made from a bottle brush. It picked up simulated dirt at a demonstration but, Jones says, “was not robust enough to actually clean my apartment as I had hoped.”Courtesy of Joe Jones

In the summer of 1999, while working at iRobot, a colleague, Paul Sandin, and I wrote a proposal titled “DustPuppy, A Near-Term, Breakthrough Product with High Earnings Potential.” We described an inexpensive little robot, DustPuppy, that would clean consumers’ floors by itself. Management liked the idea and gave us $10,000 and two weeks to build a prototype.

Using a cylindrical brush, switches, sensors, motors, and a commonplace microprocessor, we assembled our vision. At the end of an intense fortnight we had it—a crude version of a robot that conveyed a cleaning mechanism around the floor and—mostly—didn’t get stuck. Management saw the same promise in DustPuppy as Paul and me.

We called our robot DustPuppy for a reason. This was to be the world’s first significant consumer robot and the team’s first attempt at a consumer product. The risk was that customers might expect too much and that we might deliver too little. We were sure that—like a puppy—our robot would try very hard to please but that also—like a puppy—it might sometimes mess up. Calling it DustPuppy was our way of setting expectations and hoping for patience if our robot wasn’t perfect out of the gate. Alas, iRobot employed a firm to find a more commercial name. Many consumer tests later, DustPuppy became Roomba. The thinking was the robot’s random motion makes it appear to be dancing around the room—doing the Rumba.

Paul and I knew building a robotic floor cleaner entails fierce challenges not apparent to the uninitiated. Familiar solutions that work well for people can prove problematic when applied to a robot.

Your manual vacuum likely draws 1,400 watts or 1.9 horsepower from the wall socket. In a Roomba-sized robot, that sort of mechanism would exhaust the battery in about a minute. Make the robot bigger, to accommodate a larger battery, and the robot won’t fit under the furniture. Also, batteries are expensive—the cost of a big one might scuttle sales. We needed innovation.

Melville Bissell, who patented the carpet sweeper in 1876, helped us out. We borrowed from his invention to solve Roomba’s energy problem. A carpet sweeper picks up dirt very efficiently. Although you supply all the power, you won’t work up a sweat pushing one around. (If you supplied the entire 1.9 horsepower a conventional vacuum needs, you’d do a lot of sweating!)

When designers festoon their robots with anthropomorphic features, they are making a promise no robot can keep.

We realized that our energy-efficient carpet sweeper would not clean as quickly or as deeply as a powerful vacuum. But we thought, if the robot spends enough time doing its job, it can clean the surface dirt just as well. And if the robot runs every day, the surface dirt won’t work into the carpet. Roomba matches a human-operated vacuum by doing the task in a different way.

Any robot vacuum must do two things: 1) not get stuck, and 2) visit every part of the floor. The first imperative we satisfied in part by making Roomba round with its drive wheels on the diameter. The huge advantage of this shape is that Roomba can always spin in place to escape from an object. No other shape enables such a simple, reliable strategy. The second imperative, visiting everywhere, requires a less obvious plan.

You move systematically while cleaning, only revisiting a spot if that spot is especially dirty. Conventional wisdom says our robot should do the same—drive in a boustrophedon pattern. (This cool word means writing lines in alternate directions, left to right, right to left, like an ox turns in plowing.) How to accomplish this? We received advice like, “Just program the robot to remember where it’s been and not go there again.”

Such statements reveal a touching faith that software unaided can solve any technical problem. But try this exercise (in a safe place, please!). While standing at a marked starting point, pick another point, say, six feet to your left. Now keep your eyes closed while you walk in a big circle around the central point. How close did you come to returning to your starting point? Just like you, a robot can’t position itself in the world without appropriate sensors. Better solutions are available today, but circa 2000 a position-sensing system would have added over $1,000 to Roomba’s cost. So, boustrophedon paths weren’t an option. We had to make Roomba do its job without knowing where it was.

I design robots using a control scheme called behavior-based programming. This approach is robot-appropriate because it’s fast, responsive, and runs on low-cost computer hardware. A behavior-based program structures a robot’s control scheme as a set of simple, understandable behaviors.

Remember that Roomba’s imperative is to apply its cleaning mechanism to all parts of the floor and not get stuck. The program that accomplishes this needs a minimum of two behaviors. Call them Cruise and Escape. Cruise is single-minded. It ignores all sensor inputs and constantly outputs a signal telling the robot’s motors to drive forward.

Escape watches the robot’s front bumper. Whenever the robot collides with something, one or both of the switches attached to the bumper activate. If the left switch closes, Escape knows there’s been a collision on the left, so it tells the motors to spin the robot to the right. A collision on the right means spin left. If both switches close at once, an arbitrary decision is made. When neither switch is closed Escape sends no signal to the motors.

TEST FLOORS: “Roomba needed to function on many floor types and to transition smoothly from one type to another,” says Joe Jones. “We built this test floor to verify that Roomba would work in this way.” The sample floors include wood, various carpets, and tiles.Courtesy of Joe Jones

Occasionally Cruise and Escape try to send commands to the motors at the same time. When this happens, a bit of code called an arbiter decides which behavior succeeds—the highest priority behavior outputting a command wins. In our example, Escape is assigned the higher priority.

Watching the robot, we see a complex behavior emerge from these simple rules. The robot moves across the floor until it bumps into something. Then it stops moving forward and turns in place until the path is clear. It then resumes forward motion. Given time, this random motion lets the robot cover, and clean, the entire floor.

Did you guess so little was going on in the first Roomba’s brain? When observers tell me what Roomba is thinking they invariably imagine great complexity—imbuing the robot with intentions and intricate plans that are neither present nor necessary. Every robot I build is as simple and simple-minded as I can make it. Anything superfluous, even intelligence, works against marketplace success.

The full cleaning task contains some extra subtleties. These require more than just two behaviors for efficient operation. But the principle holds, the robot includes only the minimum components and code required for the task.

A few months from product launch, we demonstrated one of our prototypes to a focus group. The setup was classical: A facilitator presented Roomba to a cross section of potential customers while the engineers watched from a darkened room behind a one-way mirror.

The session was going well, people seemed to like the robot and it picked up test dirt effectively. Then the facilitator mentioned that Roomba used a carpet sweeper mechanism and did not include a vacuum.

The mood changed. Our test group revised the price they’d be willing to pay for Roomba, cutting in half their estimate from only minutes earlier. We designers were perplexed. We solved our energy problem by eschewing a vacuum in favor of a carpet sweeper—and it worked! Why wasn’t that enough for the focus group?

Did you guess so little was going on in Roomba’s brain? Every robot I build is as simple-minded as I can make it.

Decades of advertising have trained consumers that a vacuum drawing lots of amps means effective cleaning. We wanted customers to judge our new technology using a more appropriate metric. But there was no realistic way to accomplish that. Instead, our project manager declared, “Roomba must have a vacuum, even if it does nothing.”

No one on the team wanted a gratuitous component—even if it solved our marketing problem. We figured we could afford three watts to run a vacuum motor. But a typical vacuum burns 1,400 watts. What could we do with just three?

Using the guts of an old heat gun, some cardboard, and packing tape, I found a way. It turned out that if I made a very narrow inlet, I could achieve the same air-flow velocity as a regular vacuum but, because the volume was miniscule, it used only a tiny bit of power. We had a vacuum that actually contributed to cleaning.

DUST PUPPY: Before the marketers stepped in with the name “Roomba,” Joe Jones and his colleague Paul Sandin called their floor cleaner, “DustPuppy.” “Our robot would try very hard to please,” Jones writes. But like a puppy, “it might sometimes mess up.” Above, Sandin examines a prototype, with designer Steve Hickey (black shirt) and intern Ben Trueman.Courtesy of Joe Jones

There’s a moment in the manufacturing process called “commit to tooling” when the design must freeze so molds for the plastic can be cut. Fumble that deadline and you may miss your launch date, wreaking havoc on your sales.

About two weeks before “commit,” our project manager said, “Let’s test the latest prototype.” We put some surrogate dirt on the floor and let Roomba run over it. The dirt remained undisturbed.

Panic ensued. Earlier prototypes had seemed to work, and we thought we understood the cleaning mechanism. But maybe not. I returned to the lab and tried to identify the problem. This involved spreading crushed Cheerios on a glass tabletop and looking up from underneath as our cleaning mechanism operated.

Our concept of Mr. Bissell’s carpet sweeper went like this: As the brush turns against the floor, bristle tips pick up dirt particles. The brush rotates inside a conforming shroud carrying the dirt to the back where a toothed structure combs it from the brush. The dirt then falls into the collection bin.

That sedate description couldn’t have been more wrong. In fact, as the brush turns against the floor, a flicking action launches dirt particles into a frenetic, chaotic cloud. Some particles bounce back onto the floor, some bounce deep into the brush, some find the collection bin. The solution was to extend the shroud around the brush a little farther on the back side—that redirected the dirt that bounced out such that the brush had a second chance to pick it up. Roomba cleaned again and we could begin cutting molds with a day or two to spare.

Roomba launched in September 2002. Its success rapidly eclipsed the dreams of all involved.

Did Roomba’s nascent reign end the long robot drought? Was my hordes-of-robots-in-service-to-humanity dream about to come true?

In the years since iRobot released Roomba, many other robot companies have cast their die. Here are a few: Anki, Aria Insights, Blue Workforce, Hease Robotics, Jibo, Keecker, Kuri, Laundroid, Reach Robotics, Rethink Robotics, and Unbounded Robotics. Besides robots and millions of dollars of venture capitalist investment, what do all of these companies have in common? None are in business today.

The commercial failure of robots and robot companies is not a new phenomenon. Before Roomba, the pace was slower, but the failure rate no less disappointing. This dismal situation set me looking for ways around the fatal missteps roboticists seemed determined to make. I settled on three principles that we followed while developing Roomba.

1. Perform a Valuable Task

When a robot does a specific job, say, mowing your lawn or cleaning your grill, its value is clear and long-lasting. But over the years, I’ve seen many cool, cute, engaging robots that promised great, albeit vague, value while performing no discernable task. Often the most embarrassing question I could ask the designer of such a robot was, “What does your robot do?” In this case the blurted answer, “Everything!” is synonymous with “Nothing.” The first principle for a successful robot is: Do something people want done. When a robot’s only attribute is cuteness, value evaporates as novelty fades.

2. Do the Task Today

Many robots emerge from research labs. In the lab, researchers aspire to be first to achieve some impressive result; cost and reliability matter little. But cost and reliability are paramount for real-world products. Bleeding edge technologies are rarely inexpensive, reliable, or timely. Second principle: Use established technology. A research project on the critical path to robot completion can delay delivery indefinitely.

3. Do the Task for Less

People have jobs they want done and states they want achieved—a clean floor, a mowed lawn, fresh folded clothes in the dresser. The result matters, the method doesn’t. If a robot cannot provide the lowest cost, least arduous solution, customers won’t buy it. Third principle: A robotic solution must be cost-competitive with existing solutions. People will not pay more to have a robot do the job.

A few robots have succeeded impressively: Roomba, Kiva Systems (warehouse robots), and Husqvarna’s Automower (lawn mower). But I started this article with the question, why aren’t successful robots everywhere? Maybe the answer is becoming clearer.

Robot success is opportunistic. Not every application has a viable robotic solution. The state of the art means only select applications offer: a large market; existing technology that supports autonomy; a robotic approach that outcompetes other solutions.

There’s one more subtle aspect. Robots and people may accomplish the same task in completely different ways. This makes deciding which tasks are robot-appropriate both difficult and, from my perspective, great fun. Every potential task must be reimagined from the ground up.

My latest robot, Tertill, prevents weeds from growing in home gardens. A human gardener pulls weeds up by the roots. Why? Because this optimizes the gardeners time. Leaving roots behind isn’t a moral failure, it just means weeds will rapidly re-sprout forcing the gardener to spend more time weeding.

Tertill does not pull weeds but attacks them in two other ways. It cuts the tops off weeds and it uses the scrubbing action of the wheels to kill weeds as they sprout from seeds. These tactics work because the robot, unlike the gardener, lives in the garden. Tertill returns every day to prevent rooted weeds from photosynthesizing so roots eventually die; weed seeds that are constantly disturbed don’t sprout.

Had Tertill copied the human solution, the required root extraction mechanism and visual identification system would have increased development time, added cost, and reduced reliability. Without reimagining the task, there would be no solution.

Robots have a hard-enough time doing their jobs at all. Burdening them with unnecessary features and expectations worsens the problem. That’s one reason I’m always vexed when designers festoon their robots with anthropomorphic features—they make a promise no robot can keep. Anthropomorphic features and behaviors hint that the robot has the same sort of inner life as people. But it doesn’t. Instead the robot has a limited bag of human-mimicking tricks. Once the owner has seen all the tricks, the robot’s novelty is exhausted and along with it the reason for switching on the robot. Only robots that perform useful tasks remain in service after the novelty wears off.

No commercially successful robot I’m aware of has superfluous extras. This includes computation cycles—cycles it might use to contemplate world domination. All of the robot’s resources are devoted to accomplishing the task for which it was designed, or else it wouldn’t be successful. Working robots don’t have time to take over the world.

Robots have been slow to appear because each one requires a rare confluence of market, task, technology, and innovation. (And luck. I only described some of the things that nearly killed Roomba.) But as technology advances and costs decline, the toolbox for robot designers constantly expands. Thus, more types of robots will cross the threshold of economic viability. Still, we can expect one constant. Each new, successful robot will represent a minimum—the simplest, lowest-cost solution to a problem people want solved. The growing set of tools that let us attack ever more interesting problems make this an exciting time to practice robotics.

Joe Jones is cofounder and CTO of Franklin Robotics. A graduate of MIT, he holds more than 70 patents.

Lead image: Christa Mrgan / Flickr

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There’s an old belief that truth will always overcome error. Alas, history tells us something different. Without someone to fight for it, to put error on the defensive, truth may languish. It may even be lost, at least for some time. No one understood this better than the renowned Italian scientist Galileo Galilei.

It is easy to imagine the man who for a while almost single-handedly founded the methods and practices of modern science as some sort of Renaissance ivory-tower intellectual, uninterested and unwilling to sully himself by getting down into the trenches in defense of science. But Galileo was not only a relentless advocate for what science could teach the rest of us. He was a master in outreach and a brilliant pioneer in the art of getting his message across.

Today it may be hard to believe that science needs to be defended. But a political storm that denies the facts of science has swept across the land. This denialism ranges from the initial response to the COVID-19 pandemic to the reality of climate change. It’s heard in the preposterous arguments against vaccinating children and Darwin’s theory of evolution by means of natural selection. The scientists putting their careers, reputations, and even their health on the line to educate the public can take heart from Galileo, whose courageous resistance led the way.

STAND UP FOR SCIENCE: Participants in the annual March for Science make Galileo proud, protesting those in power who have devalued and eroded science. (Above: Washington, D.C., 2017)bakdc / Shutterstock

A crucial first step, one that took Galileo a bit of time to take, was to switch from publishing his findings in Latin, as was the custom for scientific writings at the time, to the Italian vernacular, the speech of the common people. This enabled not just the highly educated elite but anyone who was intellectually curious to hear and learn about the new scientific work. Even when risking offense (which Galileo never shied away from)—for instance, in responding to a German Jesuit astronomer who disagreed with him on the nature of sunspots (mysterious dark areas observed on the surface of the sun)—Galileo replied in the vernacular, because, as he explained, “I must have everyone able to read it.” An additional motive may have been that Galileo wanted to ensure that no one would somehow distort the meaning of what he had written.

Galileo also understood that while the Church had the pomp and magic of decades of art and music, science had the enchantment of a new invention—the telescope. Even he wasn’t immune to its seductive powers, writing in his famous booklet The Sidereal Messenger: “In this short treatise I propose great things for inspection and contemplation by every explorer of Nature. Great, I say, because of the excellence of the things themselves, because of their newness, unheard of through the ages, and also because of the instrument with the benefit of which they make themselves manifest to our sight. “ And that gave him his second plan for an ambitious outreach campaign.

With alternative facts acting like real facts, there are Galileo’s heirs, throwing up their hands and attempts to make lies sound like truth.

What if he could distribute telescopes (together with detailed instructions for their use and his booklet about the discoveries) all across Europe, so that all the influential people, that is, the patrons of scientists—dukes and cardinals, could observe with their own eyes far out into the heavens. They would see the stunning craters and mountains that cover the surface of the moon, four previously unseen satellites of Jupiter, dark spots on the surface of the sun, and the vast number of stars that make up the Milky Way.

But telescopes were both expensive and technically difficult to produce. Their lenses had to be of the highest quality, to provide both the ability to see faint objects and high resolution. “Very fine lenses that can show all observations are quite rare and, of the more than sixty I have made, with great effort and expense, I have only been able to retain a very small number,” Galileo wrote on March 19, 1610. Who would front the cost of such a monumental and risky project?

Today the papacy is arguably the single most influential and powerful religious institution in the world. But its power is mostly in the moral and religious realms. In Galileo’s time, the papacy was a political power of significance, gobbling up failed dukedoms elsewhere, merging them into what became known as the “papal states.” The persons with the greatest interest in appearing strong in front of the papacy were the heads of neighboring states at the time.

So it is not surprising that Galileo presented his grandiose scheme to the Tuscan court and the Grand Duke Cosimo II de’ Medici. Nor is it surprising that Cosimo agreed to finance the manufacturing of all the telescopes. On his own, he also instructed the Tuscan ambassadors to all the major European capitals to help publicize Galileo’s discoveries. In doing so he tied the House of Medici, ruler of the foundational city of the Renaissance, Florence, to modern science. A win-win for both the Grand Duke and Galileo.

Last, Galileo instinctively understood what modern PR specialists refer to as the “quick response.” He did not let even one unkind word be said about his discoveries without an immediate reply. And his pen could be sharp.

For example, the Jesuit mathematician Orazio Grassi (hiding behind the pseudonym of Sarsi) published a book entitled The Astronomical and Philosophical Balance, in which he criticized Galileo’s ideas on comets and on the nature of heat. In it, Grassi mistakenly thought that he would strengthen his argument by citing a legendary tale about the ancient Babylonians cooking eggs by whirling them on slings.

Really?

Galileo responded with a stupendous piece of polemic literature entitled The Assayer, in which he pounced on this fabled story like a cat on a mouse.

“If Sarsi wishes me to believe, on the word of Suidas [a Greek historian], that the Babylonians cooked eggs by whirling them rapidly in slings, I shall believe it; but I shall say that the cause of this effect is very far from the one he attributes to it,” he wrote. “ To discover the true cause, I reason as follows: ‘If we do not achieve an effect which others formerly achieved, it must be that we lack something in our operation which was the cause of this effect succeeding, and if we lack one thing only, then this alone can be the true cause. Now we do not lack eggs, or slings, or sturdy fellows to whirl them, and still they do not cook, but rather cool down faster if hot. And since we lack nothing except being Babylonians, then being Babylonian is the cause of the egg hardening.’”

Galileo understood what modern PR specialists refer to as the “quick response.” He did not let one unkind word go without an immediate reply.

Did Galileo’s efforts save science from being cast aside perhaps for decades, even centuries? Unfortunately, not quite. The trial in which he was convicted by the Inquisition for “vehement suspicion of heresy” exerted a chilling effect on progress in deciphering the laws governing the cosmos. The famous French philosopher and scientist René Descartes wrote in a letter: “I inquired in Leiden and Amsterdam whether Galileo’s World System was available, for I thought I had heard that it was published in Italy last year. I was told that it had indeed been published, but that all the copies had immediately been burnt in Rome, and that Galileo had been convicted and fined. I was so astonished at this that I almost decided to burn all my papers, or at least to let no one see them.”

I suspect that there are still too few of us who can tell exactly what Galileo discovered and why he is such an important figure to the birth of modern science. But around the world, in conversations as brittle as today’s politics, with alternative facts acting like real facts, there are Galileo’s heirs, throwing up their hands at such attempts to make lies seem like the truth and worse, the truth like a lie, responding with just four words: “And yet it moves.”

Galileo may have never really uttered these words. He surely didn’t say that phrase in front of the Inquisitors—that would have been insanely dangerous. But whether the motto came first from his own mouth, that of a supporter whom he met during the years the Church put him under house arrest after his trial, or a later historian, we know one thing for sure. That motto represents everything Galileo stood for. It conveys the clear message of: In spite of what you may believe, these are the facts! That science won at the end is not solely because of the methods and rules that Galileo set out for what we accept to be true. Science prevailed because Galileo put his life and his personal freedom on the line to defend it.

Mario Livio is an astrophysicist and author. His new book is Galileo: And the Science Deniers.

Lead image: Mario Breda / Shutterstock

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In the COVID-19 pandemic, numerous models are being used to predict the future. But as helpful as they are, they cannot make sense of themselves. They rely on epidemiologists and other modelers to interpret them. Trouble is, making predictions in a pandemic is also a philosophical exercise. We need to think about hypothetical worlds, causation, evidence, and the relationship between models and reality.1,2

The value of philosophy in this crisis is that although the pandemic is unique, many of the challenges of prediction, evidence, and modeling are general problems. Philosophers like myself are trained to see the most general contours of problems—the view from the clouds. They can help interpret scientific results and claims and offer clarity in times of uncertainty, bringing their insights down to Earth. When it comes to predicting in an outbreak, building a model is only half the battle. The other half is making sense of what it shows, what it leaves out, and what else we need to know to predict the future of COVID-19.

Prediction is about forecasting the future, or, when comparing scenarios, projecting several hypothetical futures. Because epidemiology informs public health directives, predicting is central to the field. Epidemiologists compare hypothetical worlds to help governments decide whether to implement lockdowns and social distancing measures—and when to lift them. To make this comparison, they use models to predict the evolution of the outbreak under various simulated scenarios. However, some of these simulated worlds may turn out to misrepresent the real world, and then our prediction might be off.

In his book Philosophy of Epidemiology, Alex Broadbent, a philosopher at the University of Johannesburg, argues that good epidemiological prediction requires asking, “What could possibly go wrong?” He elaborated in an interview with Nautilus, “To predict well is to be able to explain why what you predict will happen rather than the most likely hypothetical alternatives. You consider the way the world would have to be for your prediction to be true, then consider worlds in which the prediction is false.” By ruling out hypothetical worlds in which they are wrong, epidemiologists can increase their confidence that they are right. For instance, by using antibody tests to estimate previous infections in the population, public health authorities could rule out the hypothetical possibility (modeled by a team at Oxford) that the coronavirus has circulated much more widely than we think.3

One reason the dynamics of an outbreak are often more complicated than a traditional model can predict is that they result from human behavior and not just biology.

Broadbent is concerned that governments across Africa are not thinking carefully enough about what could possibly go wrong, having for the most part implemented coronavirus policies in line with the rest of the world. He believes a one-size-fits-all approach to the pandemic could prove fatal.4 The same interventions that might have worked elsewhere could have very different effects in the African context. For instance, the economic impacts of social distancing policies on all-cause mortality might be worse because so many people on the continent suffer increased food insecurity and malnutrition in an economic downturn.5 Epidemic models only represent the spread of the infection. They leave out important elements of the social world.

Another limitation of epidemic models is that they model the effect of behaviors on the spread of infection, but not the effect of a public health policy on behaviors. The latter requires understanding how a policy works. Nancy Cartwright, a philosopher at Durham University and the University of California, San Diego, suggests that “the road from ‘It works somewhere’ to ‘It will work for us’ is often long and tortuous.”6 The kinds of causal principles that make policies effective, she says, “are both local and fragile.” Principles can break in transit from one place to the other. Take the principle, “Stay-at-home policies reduce the number of social interactions.” This might be true in Wuhan, China, but might not be true in a South African township in which the policies are infeasible or in which homes are crowded. Simple extrapolation from one context to another is risky. A pandemic is global, but prediction should be local.

Predictions require assumptions that in turn require evidence. Cartwright and Jeremy Hardie, an economist and research associate at the Center for Philosophy of Natural and Social Science at the London School of Economics, represent evidence-based policy predictions using a pyramid, where each assumption is a building block.7 If evidence for any assumption is missing, the pyramid might topple. I have represented evidence-based medicine predictions using a chain of inferences, where each link in the chain is made of an alloy containing assumptions.8 If any assumption comes apart, the chain might break.

An assumption can involve, for example, the various factors supporting an intervention. Cartwright writes that “policy variables are rarely sufficient to produce a contribution [to some outcome]; they need an appropriate support team if they are to act at all.” A policy is only one slice of a complete causal pie.9 Take age, an important support factor in causal principles of social distancing. If social distancing prevents deaths primarily by preventing infections among older individuals, wherever there are fewer older individuals there may be fewer deaths to prevent—and social distancing will be less effective. This matters because South Africa and other African countries have younger populations than do Italy or China.10

The lesson that assumptions need evidence can sound obvious, but it is especially important to bear in mind when modeling. Most epidemic modeling makes assumptions about the reproductive number, the size of the susceptible population, and the infection-fatality ratio, among other parameters. The evidence for these assumptions comes from data that, in a pandemic, is often rough, especially in early days. It has been argued that nonrepresentative diagnostic testing early in the COVID-19 pandemic led to unreliable estimates of important inputs in our epidemic modeling.11

Epidemic models also don’t model all the influences of the pathogen and of our policy interventions on health and survival. For example, what matters most when comparing deaths among hypothetical worlds is how different the death toll is overall, not just the difference in deaths due to the direct physiological effects of a virus. The new coronavirus can overwhelm health systems and consume health resources needed to save non-COVID-19 patients if left unchecked. On the other hand, our policies have independent effects on financial welfare and access to regular healthcare that might in turn influence survival.

A surprising difficulty with predicting in a pandemic is that the same pathogen can behave differently in different settings. Infection fatality ratios and outbreak dynamics are not intrinsic properties of a pathogen; these things emerge from the three-way interaction among pathogen, population, and place. Understanding more about each point in this triangle can help in predicting the local trajectory of an outbreak.

In April, an influential data-driven model, developed by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, which uses a curve-fitting approach, came under criticism for its volatile projections and questionable assumption that the trajectory of COVID-19 deaths in American states can be extrapolated from curves in other countries.12,13 In a curve-fitting approach, the infection curve representing a local outbreak is extrapolated from data collected locally along with data regarding the trajectory of the outbreak elsewhere. The curve is drawn to fit the data. However, the true trajectory of the local outbreak, including the number of infections and deaths, depends upon characteristics of the local population as well as policies and behaviors adopted locally, not just upon the virus.

Predictions require assumptions that in turn require evidence.

Many of the other epidemic models in the coronavirus pandemic are SIR-type models, a more traditional modelling approach for infectious-disease epidemiology. SIR-type models represent the dynamics of an outbreak, the transition of individuals in the population from a state of being susceptible to infection (S) to one of being infectious to others (I) and, finally, recovered from infection (R). These models simulate the real world. In contrast to the data-driven approach, SIR models are more theory-driven. The theory that underwrites them includes the mathematical theory of outbreaks developed in the 1920s and 1930s, and the qualitative germ theory pioneered in the 1800s. Epidemiologic theories impart SIR-type models with the know-how to make good predictions in different contexts.

For instance, they represent the transmission of the virus as a factor of patterns of social contact as well as viral transmissibility, which depend on local behaviors and local infection control measures, respectively. The drawback of these more theoretical models is that without good data to support their assumptions they might misrepresent reality and make unreliable projections for the future.

One reason why the dynamics of an outbreak are often more complicated than a traditional model can predict, or an infectious-disease epidemiology theory can explain, is that the dynamics of an outbreak result from human behavior and not just human biology. Yet more sophisticated disease-behavior models can represent the behavioral dynamics of an outbreak by modeling the spread of opinions or the choices individuals make.14,15 Individual behaviors are influenced by the trajectory of the epidemic, which is in turn influenced by individual behaviors.

“There are important feedback loops that are readily represented by disease-behavior models,” Bert Baumgartner, a philosopher who has helped develop some of these models, explains. “As a very simple example, people may start to socially distance as disease spreads, then as disease consequently declines people may stop social distancing, which leads to the disease increasing again.” These looping effects of disease-behavior models are yet another challenge to predicting.

It is a highly complex and daunting challenge we face. That’s nothing unusual for doctors and public health experts, who are used to grappling with uncertainty. I remember what that uncertainty felt like when I was training in medicine. It can be discomforting, especially when confronted with a deadly disease. However, uncertainty need not be paralyzing. By spotting the gaps in our models and understanding, we can often narrow those gaps or at least navigate around them. Doing so requires clarifying and questioning our ideas and assumptions. In other words, we must think like a philosopher.

Jonathan Fuller is an assistant professor in the Department of History and Philosophy of Science at the University of Pittsburgh. He draws on his dual training in philosophy and in medicine to answer fundamental questions about the nature of contemporary disease, evidence, and reasoning in healthcare, and theory and methods in epidemiology and medical science.

References

1. Walker, P., et al. The global impact of COVID-19 and strategies for mitigation and suppression. Imperial College London (2020).

2. Flaxman, S., et al. Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries. Imperial College London (2020).

3. Lourenco, J., et al. Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic. medRxiv:10.1101/2020.03.24.20042291 (2020).

4. Broadbent, A., & Smart, B. Why a one-size-fits-all approach to COVID-19 could have lethal consequences. TheConversation.com (2020).

5. United Nations. Global recession increases malnutrition for the most vulnerable people in developing countries. United Nations Standing Committee on Nutrition (2009).

6. Cartwright, N. Will this policy work for you? Predicting effectiveness better: How philosophy helps. Philosophy of Science 79, 973-989 (2012).

7. Cartwright, N. & Hardie, J. Evidence-Based Policy: A Practical Guide to Doing it Better Oxford University Press, New York, New York (2012).

8. Fuller, J., & Flores, L. The Risk GP Model: The standard model of prediction in medicine. Studies in History and Philosophy of Biological and Biomedical Sciences 54, 49-61 (2015).

9. Rothman, K., & Greenland, S. Causation and causal inference in epidemiology. American Journal Public Health 95, S144-S50 (2005).

10. Dowd, J. et al. Demographic science aids in understanding the spread and fatality rates of COVID-19. Proceedings of the National Academy of Sciences 117, 9696-9698 (2020).

11. Ioannidis, J. Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures. European Journal of Clinical Investigation 50, e13222 (2020).

12. COVID-19 Projections. Healthdata.org. https://covid19.healthdata.org/united-states-of-america.

13. Jewell, N., et al. Caution warranted: Using the Institute for Health metrics and evaluation model for predicting the course of the COVID-19 pandemic. Annals of Internal Medicine (2020).

14. Nardin, L., et al. Planning horizon affects prophylactic decision-making and epidemic dynamics. PeerJ 4:e2678 (2016).

15. Tyson, R., et al. The timing and nature of behavioural responses affect the course of an epidemic. Bulletin of Mathematical Biology 82, 14 (2020).

Lead image: yucelyilmaz / Shutterstock

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Plants are intelligent beings with profound wisdom to impart—if only we know how to listen. And Monica Gagliano knows how to listen. The evolutionary ecologist has done groundbreaking experiments suggesting plants have the capacity to learn, remember, and make choices. That’s not all. Gagliano, a senior research fellow at the University of Sydney in Australia, talks to plants. And they talk back. Plants summon her with instructions on how to live and work. Some of Gagliano’s conversations happened in prophetic dreams, which led her to study with a shaman in Peru while tripping on psychoactive plants.

Along with forest scientists like Suzanne Simard and Peter Wohlleben, Gagliano raises profound scientific and philosophical questions about the nature of intelligence and the possibility of “vegetal consciousness.” But what’s unusual about Gagliano is her willingness to talk about her experiences with shamans and traditional healers, along with her use of psychedelics. For someone who’d already received fierce pushback from other scientists, it was hardly a safe career move to reveal her personal experiences in otherworldly realms.

Gagliano considers her explorations in non-Western ways of seeing the world to be part of her scientific work. “Those are important doors that you need to open and you either walk through or you don’t,” she told me. “I simply decided to walk through.” Sometimes, she said, certain plants have given her precise directions on how to conduct her experiments, even telling her which plant to study. But it hasn’t been easy. “Like Alice, [I] found myself tumbling down a rather strange rabbit hole,” she wrote in a 2018 memoir, Thus Spoke the Plant. “I did doubt my own sanity many times, especially when all these odd occurrences started—and yet I know I do not suffer from psychoses.”

Shortly before the COVID-19 lockdown, I talked with Gagliano at Dartmouth College, where she was a visiting scholar. We spoke about her experiments, the new field of plant intelligence, and her own experiences of talking with plants.

PAVLOV’S PEAS: Monica Gagliano sketches a pea plant in her lab at the University of Sydney (above). She conducted experiments with pea plants to determine if, like Pavlov’s famous dogs, the plants learned to anticipate food. They did. “Although they do not salivate,” Gagliano says.Scene from the upcoming documentary, AWARE ©umbrellafilms.org

You are best known for an experiment with Mimosa pudica, commonly known as the “sensitive plant,” which instantly closes its leaves when it’s touched. Can you describe your experiment?

I built a little contraption that allowed me to drop the plants from a height of maybe 15 centimeters. So it’s not too high. When they fall, they land in a softly padded base. This plant closes its leaves when disturbed, especially if the disturbance is a potential predator. When the leaves are closed, big, spiny, pointy things stick out, so they might deter a predator. In fact, they not only close the leaf, but literally droop, like, “Look, I’m dead. No juice for you here.”

You did this over and over, dropping the plants repeatedly.

Exactly. It makes no sense for a plant or animal to repeat a behavior that is actually useless, so we learn pretty quick that whatever is useless, you don’t do anymore. You’re wasting a lot of energy trying to do something that doesn’t actually help. So, can the plant—in this case, Mimosa—learn not to close the leaves when the potential predator is not real and there are no bad consequences afterward?

After how many drops did they stop closing their leaves?

The test is for a specific type of learning that is called habituation. I decided they would be dropped continuously for 60 times. Then there was a big pause to let them rest and I did it again. But the plants were already re-opening their leaves after the first three to six drops. So within a few minutes, they knew exactly what was going on—like, “Oh my god, this is really annoying but it doesn’t mean anything, so I’m just not going to bother closing. Because when my leaves are open, I can eat light.” So there is a tradeoff between protecting yourself when the threat is real and continuing to feed and grow. I left the plants undisturbed for a month and then came back and repeated the same experiment on those individuals. And they showed they knew exactly what was going on. They were trained.

This is who I am. And nobody has the right to tell me that it’s not real.

You say these plants “understand” and “learn” that there’s no longer a threat. And you’re suggesting they “remember.” You’re not using these words metaphorically. You mean this literally?

Yes, that’s what they’re doing. This is definitely memory. It’s the same kind of experiment we do with a bee or a mouse. So using the words “memory” and “learning” feels totally appropriate. I know that some of my colleagues accuse me of anthropomorphizing, but there is nothing anthropomorphic about this. These are terms that refer to certain processes. Memory and learning are not two separate processes. You can’t learn unless you remember. So if a plant is ticking all the boxes and doing what you would expect a rat or a mouse or a bee to do, then the test is being passed.

Do you think these plants are actually making decisions about whether or not to close their leaves?

This experiment with Mimosa wasn’t designed to test that specific question. But later, I did experiments with other plants, with peas in particular, and yes, there is no doubt the plants make choices in real decision-making. This was tested in the context of a maze, where the test is actually to make a choice between left and right. The choice is based on what you might gain if you choose one side or the other. I did one study with peas that showed the plants can choose the right arm in a maze based on where the sound of water is coming from. Of course, they want water. So they will use the signal to follow that arm of the maze as they try to find the source of water.

So plants can hear water?

Oh, yeah, of course. And I’m not talking about electrical signals. We have also discovered that plants emit their own sounds. The acoustic signal comes out of the plant.

What kind of sounds do they make?

We call them clicks, but this is where language might fail because we are trying to describe something we’re not familiar enough with to create the language that really describes the picture. We worked out that, yes, plants not only produce their own sound, which is amazing, but they are listening to sounds. We are surrounded by sound, so there are studies, like my own study, of plants moving toward certain frequencies and then responding to sounds of potential predators chewing on leaves, which other plants that are not yet threatened can hear. “Oh, that’s a predator chewing on my neighbor’s leaves. I better put my defenses up.” And more recently, there was some work done in Israel on the sound of bees and how flowers prepared themselves and become very nice and sweet, literally, to be more attractive to the bee. So the level of sugars gets increased as a bee passes by.

SECRET LIFE OF PLANTS: Monica Gagliano says her experiences with indigenous people, such as the Huichol in Mexico (above), informed her view that plants have a range of feelings. “I don’t know if they would use those words to describe joy or sadness, but they are feeling bodies,” she says.Scene from the upcoming documentary, AWARE ©umbrellafilms.org

You are describing a surprising level of sophistication in these plants. Do you have a working definition of “intelligence?”

That’s one of those touchy subjects. I use the Latin etymology of the word and “intelligere” literally means something like “choosing between.” So intelligence really underscores decision-making, learning, memory, choice. As you can imagine, all those words are also loaded. They belong in the cognitive realm. That’s why I define all of this work as “cognitive ecology.”

Do you see parallels between this kind of intelligence in plants and the collective intelligence that we associate with social insects in ant colonies or beehives?

That kind of intelligence might be referred to as “distributed intelligence” or “collective intelligence.” We are testing those questions right now. Plants don’t have neurons. They don’t have a brain, which is often what we assume is the base for all of these behaviors. But like slime molds and other basal animals that don’t have neural systems, they seem to be doing the same things. So the short answer is yes.

What you’re saying is very controversial among scientists. The common criticism of your views is that an organism needs a brain or at least a nervous system to be able to learn or remember. Are you saying neurons are not required for intelligence?

Science is full of assumptions and presuppositions that we don’t question. But who said the brain and the neurons are essential for any form of intelligence or learning or cognition? Who decided that? And when I say neurons and brains are not required, it’s not to say they’re not important. For those organisms like ourselves and many animals who do have neurons and brains, it’s amazing. But if we look at the base of the animal kingdom, sponges don’t have neurons. They look like plants because when they’re adults, they settle on the bottom of the ocean and pretty much just sit there forever. Yet if you look at the sponge’s genome, they have the genetic code for the neural system. It’s almost like from an evolutionary perspective, they simply decided that developing a neural system was not useful. So they went a different way. Why would you invest that energy if you don’t need it? You can achieve the same task in different ways.

Your food is psychedelic. It changes your brain chemistry all the time.

Your critics say these are just automatic adaptive responses. This is not really learning.

You know, they just say plants do not learn and do not remember. Then you do this study and stumble on something that actually shows you otherwise. It’s the job of science to be humble enough to realize that we actually make mistakes in our thinking, but we can correct that. Science grows by correcting and modifying and adjusting what we once thought was the fact. I went and asked, can plants do Pavlovian learning? This is a higher kind of learning, which Pavlov did with his dogs salivating, expecting dinner. Well, it turns out plants actually can do it, but in a plant way. So plants do not salivate and dinner is a different kind of dinner. Can you as a scientist create the space for these other organisms to express their own, in this case, “plantness,” instead of expecting them to become more like you?

There’s an emerging field of what’s called “vegetal consciousness.” Do you think plants have minds?

What is the mind? [Laughs] You see, language is very inadequate at the moment in describing this field. I could ask you the same question in referring to humans. Do you think humans have a mind? And I could answer again, what is the mind? Of course, I have written a paper with the title “The Mind of Plants” and there is a book coming called The Mind of Plants. In this context, language is used to capture aspects of how plants can change their mind, and also whether they have agency. Is there a “person” there? These questions are relevant beyond science because they have ethical repercussions. They demand a change in our social attitude toward the environment. But I already have a problem with the language we are using because the question formulated in that way demands a yes or no answer. And what if the answer cannot be yes or no?

Let me ask the question a different way. Do you think plants have emotional lives? Can they feel pain or joy?

It’s the same question. Where do feelings arise from, and what are feelings? These are yes or no questions, usually. But to me, they are yes and no. It depends on what you mean by “feeling” and “joy.” It also depends on where you are expecting the plant to feel those things, if they do, and how you recognize them in a human way. I mean, plants might have more joy than we do. It’s just that we don’t know because we’re not plants.

We have only talked about this from the scientific perspective, which is the Western view of the world. But I’ve also had a close relationship with plants from a very different perspective, the indigenous world view. Why is that less valuable? And when you actually do explore those perspectives, they require your experience. You can’t just understand them by thinking about them. My own personal experience tells me that plants definitely feel many things. I don’t know if they would use those words to describe joy or sadness, but they are feeling bodies. We are feeling bodies.

Science is full of assumptions and presuppositions that we don’t question.

You’ve studied with shamans in indigenous cultures and you’ve taken ayahuasca and other psychoactive plants. Why did you seek out those experiences?

I didn’t. They sought me. So I just followed. They just arrived in my life. You know, those are important doors that you need to open and you either walk through or you don’t. I simply decided to walk through. I had this weird series of three dreams while I was in Australia doing my normal life. By the time the third dream came, it was very clear that the people that I was dreaming of were real people. They were waiting somewhere in this reality, in this world. And the next thing, I’m buying a ticket and going to Peru and my partner at the time is looking at me like, “What are you doing?” [laughs] I have no idea, but I need to go. As a scientist, I find this is the most scientific approach that I’ve ever had. It’s like there is something asking a question and is calling you to meet the answer. The answer is already there and is waiting for you, if you are prepared to open the door and cross through. And I did.

What did you do in Peru?

The first time I went, I found this place that was in my dream. It was just exactly the same as what I saw in my dream. It was the same man I saw in my dream, grinning in the same way as he was in my dream. So I just worked with him, trying to learn as much as I could about myself with his support.

This was a local shaman whom you identify as Don M. And there was a particular plant substance, a hallucinogen, that you took.

I did what they call a “dieta,” which is basically a quiet, intense time in isolation that you do on your own in a little hut. You are just relating with the plant that the elder is deciding on. So for me, the plant that I worked with wasn’t by itself a psychedelic in the normal way of thinking about it. But of course, all plants are psychedelic. Even your food is psychedelic because it changes your brain chemistry and your neurobiology all the time you eat. Sugars, almonds, all sorts of neurotransmitters are flying everywhere. So, again, even the idea of what a psychedelic experience is needs to be revised, because a lot of people might think that it’s only about certain plants that they have a very strong, powerful transformation. And I find that all plants are psychedelic. I can sit in my garden. I don’t have to ingest anything and I can feel very altered by that experience.

You’ve said the plant talked to you. Did you actually hear words?

When you’re trying to describe this to people haven’t had the experience, it probably doesn’t make much sense because this kind of knowledge requires your participation. I don’t hear someone talking to me as if from the outside, talking to me in words and sound. But even that is not correct because inside my head it does sound exactly like a conversation. Not only that, but I know it’s not me. There is no way that I would know about some of the information that’s been shared with me.

Are you saying these plants had specific information to tell you about your life and your work?

Yeah, I mean, some of the plants tell me exactly how wrong I was in thinking about my experiments and how I should be doing them to get them to work. And I’m like, “Really?” I’m scribbling down without really understanding. Then I go in the lab and try what they say. And even then, there is a part of me that doesn’t really believe it. For one experiment, the one on the Pavlovian pea, I was trying to address that question the year before with a different plant. I was using sunflowers. And while I was doing my dieta with a different tree back in Peru, the plant just turned up and said, “By the way, not sunflowers, peas.” And I’m like, “what?” People always think that when you have these experiences, you’re supposed to understand the secrets of the universe. No, my plants are usually quite practical. [laughs] And they were right.

Do you think you are really encountering the consciousness of that plant? Maybe your imagination has opened up to see the world in new ways, but it’s all just a projection of your own mind. How do you know you are actually encountering another intelligence?

If you had this experience of connecting with plants the way I have described—and there are plenty of people who have—the experience is so clear that you know that it’s not you; it’s someone else talking. If you haven’t had that experience, then I can totally see it’s like, “No way, it must be your mind that makes it up.” But all I can say is that I have had exchanges with plants who have shared things about topics and asked me to do things that I have really no idea about.

What have plants asked you to do?

I’m not a medical scientist, but I’ve been given information by plants about their medical properties. And these are very specific bits of information. I wrote them in my diary. I would later check and I did find them in the medical literature: “This plant is for this and we know this.” I just didn’t know. So maybe I’m tapping into the collective consciousness.

What do you do with these kinds of personal experiences? You are a scientist who’s been trained to observe and study and measure the physical world. But this is an entirely different kind of reality. Can you reconcile these two different realities?

I think there are some presuppositions that a scientist should just explore the consensus reality that most of us experience in more or less the same way. But I don’t really have a conflict because I find this is just part of experimenting and exploring. If anything, I found that it has enriched and expanded the science I do. This is a work in progress, obviously, but I think I’m getting better at it. And in the writing of my book, which for a scientist was a very scary process because it was laying bare some parts of me that I knew would likely compromise my career forever, it also became liberating because once it was written, now the world knows. And it’s my truth. This is how I operate. This is who I am. And nobody has the right or the authority to tell me that it’s not real.

Steve Paulson is the executive producer of Wisconsin Public Radio’s nationally syndicated show “To the Best of Our Knowledge.” He’s the author of Atoms and Eden: Conversations on Religion and Science. You can subscribe to TTBOOK’s podcast here.

Lead image: kmeds7 / Shutterstock

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What is this pandemic doing to our minds? Polls repeatedly show it’s having an adverse effect on our mental health. Physical distancing, for some, means social isolation, which has long been shown to encourage depression. Previous disasters have been followed by waves of depression, exacerbated by financial distress. The situation also puts us in a state of fear and anxiety—anxiety about financial strain, about being lonely, about the very lives of ourselves and our loved ones.

This fear can also bring out some of the everyday irrationalities we all struggle with. We have trouble thinking about numbers—magnitudes, probabilities, and the like—and when frightened we tend toward absolutes. Feeling powerless makes people more prone to conspiracy theories. We naturally believe that big effects should have big causes, and we see with the current coronavirus, as we did with AIDS and SARS, conspiracy theories claiming that the virus was engineered as a weapon.

We are seeing the theory of “collective resilience,” an informal solidarity among people, in action.

These psychological ramifications can make us fail to behave as well as we should. We have what psychologists call a “behavioral immune system” that makes us behave in ways that, in general, make us less likely to catch infectious disease. Things we perceive as being risky for disease makes us wary. An unfortunate side effect is that it increases prejudice against foreigners, people with visible sores or deformities, and people we perceive as simply being ugly. Politically, this can result in xenophobia and outgroup distrust. Coronavirus-related attacks, possibly encouraged by the misleading term “Chinese virus,” have plagued some ethnic Asian people.

And yet, in spite of all of the harm the pandemic seems to be wreaking on our minds, there are also encouraging acts of kindness and solidarity. In turbulent times, people come together and help each other.

A RANDOM ACT OF KINDNESS: Author Jim Davies took this photo in Centretown, Ottawa. The sign in the window reads, “Physical distancing is an act of love.”Jim Davies

In the days after the World Trade Center fell, it wasn’t just the police, hospitals, and firefighters who came forward to help, it was normal citizens who often put themselves at risk to help other people out. An equities trader named Sandler O’Neill helped rescue a dozen people and then went back to save more. A tour guide at the Pentagon helped victims outside, and then went back in the burning building to help more. We find these kinds of behaviors in every disaster.

During this pandemic, we see the same thing. Some acts are small and thoughtful, such as putting encouraging signs in windows. Others have made games out of window signs, putting up rainbows for children on walks to count. Some show support for health care and other frontline workers, applauding or banging on pots on their balconies and at windows in a nightly ritual. Others are helping in more substantial ways. In the United Kingdom, over half a million people signed up to be a National Health Volunteer, supporting the most vulnerable people, who have to stay home.

John Drury, a professor of social psychology at the University of Sussex, England, who studies people’s behavior in disasters, has seen these acts of kindness in his own neighborhood over the past month. He and his neighbors set up a WhatsApp group to help one another with shopping. “I think that translates across the country and probably across the world,” Drury says. “People are seeing themselves as an us, a new kind of we, based on the situation that we all find ourselves in. You’ve got this idea of common fate, which motivates our care and concern for others.”

We have always been a social species who rely on each other for happiness and our survival.

Drury is the pioneer of a theory known as “collective resilience,” which he describes as “informal solidarity among people in the public.” Drury’s study of the 2005 London bombing disaster found that mutual helping behaviors were more common than selfish ones. This basic finding has been replicated in other disasters, including the crash of the Ghana football stadium and the 2010 earthquake and tsunami in Chile. In disasters, Drury says, people reach heights of community and cooperation they’ve never reached before.

It turns out that being in a dangerous situation with others fosters a new social identity. Boundaries between us, which seem so salient when things are normal, disappear when we perceive we’re locked in a struggle together, with a common fate, from an external threat. People go from me thinking to we thinking. Respondents in studies about disasters often spontaneously bring up this feeling of group cohesion without being asked. The greater unity they felt, the more they helped.

Popular conceptions of how people respond in a crisis involve helplessness, selfishness, and panic. In practice, though, this rarely happens. “One of the reasons people die in emergencies isn’t overreaction, it’s underreaction,” Drury says. “People die in fires mainly because they’re too slow. They underestimate risk.” The myth of panic can lead to emergency policies that do more harm than good. At one point during Hurricane Katrina, Louisiana governor at the time Kathleen Blanco warned looters that National Guard troops “know how to shoot and kill, and they are more than willing to do so if necessary, and I expect they will.” A few days later, New Orleans police officers shot six civilians, wounding four and killing two.

People revert to selfishness when group identity starts to break down. Drury describes how people acted when the cruise ship, Costa Concordia sank off the coast of Italy in 2012. “There was cooperation until one point, when people got to the lifeboats and there was pushing,” Drury says. “Selfishness isn’t a default because many times people are cooperative. It’s only in certain conditions that people might become selfish and individualistic. Perhaps there isn’t a sense of common fate, people are positioned as individuals against individuals. After a period of time, people run out of energy, run out of emotional energy, run out of resources, and that goodwill, that support, starts to decline. They just haven’t got the resources to help each other.”

Perceptions of group behavior can shape public policy. It’s important that policymakers, rather than seeing groups as problems to be overcome, which can lead to riots and mob behavior, take account of how people in groups help one another. After all, we have always been a social species who rely on each other for happiness and our survival. And groups can achieve things that individuals cannot. This understanding couldn’t be more important than now. We can build on people’s naturally arising feelings of unity by emphasizing that we are all in this together, and celebrating the everyday heroes who, sometimes at great cost, go out of their way to make the pandemic a little less awful.

Jim Davies is a professor of cognitive science at Carleton University and author of Imagination: The Science of Your Mind’s Greatest Power. He is co-host of the Minding the Brain podcast.

Lead image: Franzi / Shutterstock

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On January 5, six days after China officially announced a spate of unusual pneumonia cases, a team of researchers at Shanghai’s Fudan University deposited the full genome sequence of the causal virus, SARS-CoV-2, into Genbank. A little more than three months later, 4,528 genomes of SARS-CoV-2 have been sequenced,1 and more than 883 COVID-related clinical trials2 for treatments and vaccines have been established. The speed with which these trials will deliver results is unknown—the delicate bаlance of efficacy and safety can only be pushed so far before the risks outweigh the benefits. For this reason, a long-term solution like vaccination may take years to come to market.3

The good news is that a lack of treatment doesn’t preclude an end to the ordeal. Viral outbreaks of Ebola and SARS, neither of which had readily available vaccines, petered out through the application of consistent public health strategies—testing, containment, and long-term behavioral adaptations. Today countries that have previously battled the 2002 SARS epidemic, like Taiwan, Hong Kong, and Singapore, have shown exemplary recovery rates from COVID. Tomorrow, countries with high fatality rates like Sweden, Belgium, and the United Kingdom will have the opportunity to demonstrate what they’ve learned when the next outbreak comes to their shores. And so will we.

The first Ebola case was identified in 1976,4 when a patient with hemorrhagic symptoms arrived at the Yambuku Mission Hospital, located in what is now the Democratic Republic of Congo (DRC). Patient samples were collected and sent to several European laboratories that specialized in rare viruses. Scientists, without sequencing technology, took about five weeks to identify the agent responsible for the illness as a new member of the highly pathogenic Filoviridae family.

The first Ebola outbreak sickened 686 individuals across the DRC and neighboring Sudan. 453 of the patients died, with a final case fatality rate (CFR)—the number of dead out of number of sickened—of 66 percent. Despite the lethality of the virus, sociocultural interventions, including lockdowns, contact-tracing, campaigns to change funeral rites, and restrictions on consumption of game meat all proved effective interventions in the long run.

That is, until 2014, when there was an exception to the pattern. Ebola appeared in Guinea, a small country in West Africa, whose population had never before been exposed to the virus. The closest epidemic had been in Gabon, 13 years before and 2,500 miles away. Over the course of two years, the infection spread from Guinea into Liberia and Sierra Leone, sickening more than 24,000 people and killing more than 10,000.

Countries that have previously battled the 2002 SARS epidemic, like Taiwan and Hong Kong, have shown exemplary recovery rates.

During the initial phase of the 2014 Ebola outbreak, rural communities were reluctant to cooperate with government directives for how to care for the sick and the dead. To help incentivize behavioral changes, sociocultural anthropologists like Mariane Ferme of the University of California, Berkeley, were brought in to advise the government. In a recent interview with Nautilus, Ferme indicated that strategies that allowed rural communities to remain involved with their loved ones increased cooperation. Villages located far from the capital, she said, were encouraged to “deputize someone to come to the hospital, to come to the burial, so they could come back to the community and tell the story of the body.” For communities that couldn’t afford to send someone to the capital, she saw public health officials adopt a savvy technological solution—tablets to record video messages that were carried between convalescent patients and their families.

However, there were also systemic failures that, in Ferme’s opinion, contributed to the severity of the 2014 West African epidemic. In Sierra Leone, she said, “the big mistake early on was to distribute [weakly causal] information about zoonotic transmission, even when it was obviously community transmission.” In other words, although there had been an instance of zoonotic transmission—the virus jumping from a bat to a human—that initiated the epidemic, the principle danger was other contagious individuals, not game meat. Eventually, under pressure from relief groups, the government changed its messaging to reflect scientific consensus.

But the retraction shook public faith in the government and bred resentment. The mismatch between messaging and reality mirrors the current pandemic. Since the COVID outbreak began, international and government health officials have issued mixed messages. Doubts initially surfaced about the certainty of the virus being capable of spreading from person to person, and the debate over the effectiveness of masks in preventing infection continues.

Despite the confused messaging, there has been general compliance with stay-at-home orders that has helped flatten the curve. Had the public been less trusting of government directives, the outcome could have been disastrous, as it was in Libera in 2014. After a two-week lockdown was announced, the Liberian army conducted house-to-house sweeps to check for the sick and collect the dead. “It was a draconian method that made people hide the sick and dead in their houses,” Ferme said. People feared their loved ones would be buried without the proper rites. A direct consequence was a staggering number of active cases, and an unknown extent of community transmission. But in the end, the benchmark for the end of Ebola and SARS was the same. The WHO declared victory when the rate of new cases slowed, then stopped. By the same measure, when an entire 14-day quarantine period passes with no new cases of COVID-19, it can be declared over.

It remains possible that even if we manage to end the epidemic, it will return again. Driven by novel zoonotic transmissions, Ebola has flared up every few years. Given the extent of COVID-19’s spread, and the potential for the kind of mutations that allow for re-infection, it may simply become endemic.

Two factors will play into the final outcome of COVID-19 are pathogenicity and virulence. Pathogenicity is the ability of an infectious agent to cause disease in the host, and is measured by R0—the number of new infections each patient can generate. Virulence, on the other hand, is the amount of harm the infectious agent can cause, and is best measured by CFR. While the pathogenicity of Ebola, SARS, and SARS-CoV-2 is on the same order—somewhere between 1 to 3 new infections for each patient, virulence differs greatly between the two SARS viruses and Ebola.

The case fatality rate for an Ebola infection is between 60 to 90 percent. The spread in CFR is due to differences in infection dynamics between strains. The underlying cause of the divergent virulence of Ebola and SARS is largely due to the tropism of the virus, meaning the cells that it attacks. The mechanism by which the Ebola virus gains entry into cells is not fully understood, but it has been shown the virus preferentially targets immune and epithelial cells.5 In other words, the virus first destroys the body’s ability to mount a defense, and then destroys the delicate tissues that line the vascular system. Patients bleed freely and most often succumb to low blood pressure that results from severe fluid loss. However, neither SARS nor SARS-CoV-2 attack the immune system directly. Instead, they enter lung epithelial cells through the ACE2 receptor, which ensures a lower CFR. What is interesting about these coronaviruses is that despite their similar modes of infection, they demonstrate a range of virulence: SARS had a final CFR of 10 percent, while SARS-CoV-2 has a pending CFR of 1.4 percent. Differences in virulence between the 2002 and 2019 SARS outbreaks could be attributed to varying levels of care between countries.

The chart above displays WHO data of the relationship between the total number of cases in a country and the CFR during the 2002-2003 SARS-CoV epidemic. South Africa, on the far right, had only a single case. The patient died, which resulted in a 100 percent CFR. China, on the other hand, had 5,327 cases and 349 deaths, giving a 7 percent CFR. The chart below zooms to the bottom left corner of the graph, so as to better resolve critically affected countries, those with a caseload of less than 1,000, but with a high CFR.

Here is Hong Kong, with 1,755 cases and a 17 percent CFR. There is also Taiwan, with 346 cases and an 11 percent CFR. Finally, nearly tied with Canada is Singapore with 238 cases and a 14 percent CFR.

With COVID-19, it’s apparent that outcome reflects experience. China has 82,747 cases of COVID, but has lowered their CFR to 4 percent. Hong Kong has 1,026 cases and a 0.4 percent CFR. Taiwan has 422 cases at 1.5 percent CFR, and Singapore with 8,014 cases, has a 0.13 percent CFR.

It was the novel coronavirus identification program established in China in the wake of the 2002 SARS epidemic that alerted authorities to SARS-CoV-2 back in November of 2019. The successful responses by Taiwan, Hong Kong, and Singapore can also be attributed to a residual familiarity with the dangers of an unknown virus, and the sorts of interventions that are necessary to prevent a crisis from spiraling out of control.

In West Africa, too, they seem to have learned the value of being prepared. When Ferme returned to Liberia on March 7, she encountered airport staff fully protected with gowns, head covers, face screens, masks, and gloves. By the time she left the country, 10 days later, she said, “Airline personnel were setting up social distancing lines, and [rural vendors] hawking face masks. Motorcycle taxis drivers, the people most at risk after healthcare workers—all had goggles and face masks.”

The sheer number of COVID-19 cases indicates the road to recovery will take some time. Each must be identified, quarantined, and all contacts traced and tested. Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars. Northwestern University economists Martin Eichenbaum et al. modeled6 the cost of a yearlong shutdown to be $4.2 trillion, a cost that proactive countries will not face. A recent Harvard study7 published in Science suggests the virus will likely make seasonal appearances going forward, potentially requiring new waves of social distancing. In other words, initial hesitancy will have repercussions for years. In the future, smart containment principles,6 where restrictions are applied on the basis of health status, may temper the impact of these measures.

Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars.

Inaction was initially framed as promoting herd immunity, where spread of the virus is interrupted once everyone has fallen sick with it. This is because getting the virus results in the same antibody production process as getting vaccinated—but doesn’t require the development of a vaccine. The Johns Hopkins Bloomberg School of Public Health estimates that 70 percent of the population will need to be infected with or vaccinated against the virus8 for herd immunity to work. Progress toward it has been slow, and can only be achieved through direct infection with the virus, meaning many will die. A Stanford University study in Santa Clara County9 suggests only 2.5 percent to 4.2 percent of the population have had the virus. Another COVID hotspot in Gangelt, Germany, suggests 15 percent10—higher, but still nowhere near the 70 percent necessary for herd immunity. Given the dangers inherent in waiting on herd immunity, our best hope is a vaccine.

A key concern for effective vaccine development is viral mutation. This is because vaccines train the immune system to recognize specific shapes on the surface of the virus—a composite structure called the antigen. Mutations threaten vaccine development because they can change the shape of the relevant antigen, effectively allowing the pathogen to evade immune surveillance. But, so far, SARS-CoV-2 has been mutating slowly, with only one mutation found in the section most accessible to the immune system, the spike protein. What this suggests is that the viral genome may be sufficiently stable for vaccine development.

What we know, though, is that Ebola was extinguished due to cooperation between public health officials and community leaders. SARS-CoV ended when all cases were identified and quarantined. The Spanish Flu in 1918 vanished after two long, deadly seasons.

The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line. With 26 million unemployed and protests erupting around the country, it seems there are many who would prefer to risk life and limb rather than face financial insolvency. Applying smart containment principles in the aftermath of the shutdown might be the best way to get the economy moving again, while maintaining the safety of those at greatest risk. Going forward, vigilance and preparedness will be the watchwords of the day, and the most efficient way to prevent social and economic ruin.

Anastasia Bendebury and Michael Shilo DeLay did their PhDs at Columbia University. Together they created Demystifying Science, a science literacy organization devoted to providing clear, mechanistic explanations for natural phenomena. Find them on Twitter @DemystifySci.

References

1. Genomic epidemiology of novel coronavirus - Global subsampling. Nextstrain www.nextstrain.org.

2. Covid-19 TrialsTracker. TrialsTracker www.trialstracker.net.

3. Struck, M. Vaccine R&D success rates and development times. Nature Biotechnology 14, 591-593 (1996).

4. Breman, J. & Johnson, K. Ebola then and now. The New England Journal of Medicine 371 1663-1666 (2014).

5. Baseler, L., Chertow, D.S., Johnson, K.M., Feldmann, H., & Morens, D.M. THe pathogenesis of Ebola virus disease. The Annual Review of Pathology 12, 387-418 (2017).

6. Eichenbaum, M., Rebell, S., & Trabandt, M. The macroeconomics of epidemics. The National Bureau of Economic Research Working Paper: 26882 (2020).

7. Kissler, S., Tedijanto, C., Goldstein, E., Grad, Y., & Lipsitch, M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science eabb5793 (2020).

8. D’ Souza, G. & Dowdy, D. What is herd immunity and how can we achieve it with COVID-19? Johns Hopkins COVID-19 School of Public Health Insights www.jhsph.edu (2020).

9. Digitale, E. Test for antibodies against novel coronavirus developed at Stanford Medicine. Stanford Medicine News Center Med.Stanford.edu (2020).

10. Winkler, M. Blood tests show 14%of people are now immune to COVID-19 in one town in Germany. MIT Technology Review (2020).

Lead image: Castleski / Shutterstock

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The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line.Castleski / Shutterstock

On January 5, six days after China officially announced a spate of unusual pneumonia cases, a team of researchers at Shanghai’s Fudan University deposited the full genome sequence of the causal virus, SARS-CoV-2, into Genbank. A little more than three months later, 4,528 genomes of SARS-CoV-2 have been sequenced,1 and more than 883 COVID-related clinical trials2 for treatments and vaccines have been established. The speed with which these trials will deliver results is unknown—the delicate bаlance of efficacy and safety can only be pushed so far before the risks outweigh the benefits. For this reason, a long-term solution like vaccination may take years to come to market.3

The good news is that a lack of treatment doesn’t preclude an end to the ordeal. Viral outbreaks of Ebola and SARS, neither of which had readily available vaccines, petered out through the application of consistent public health strategies—testing, containment, and long-term behavioral adaptations. Today countries that have previously battled the 2002 SARS epidemic, like Taiwan, Hong Kong, and Singapore, have shown exemplary recovery rates from COVID. Tomorrow, countries with high fatality rates like Sweden, Belgium, and the United Kingdom will have the opportunity to demonstrate what they’ve learned when the next outbreak comes to their shores. And so will we.

The first Ebola case was identified in 1976,4 when a patient with hemorrhagic symptoms arrived at the Yambuku Mission Hospital, located in what is now the Democratic Republic of Congo (DRC). Patient samples were collected and sent to several European laboratories that specialized in rare viruses. Scientists, without sequencing technology, took about five weeks to identify the agent responsible for the illness as a new member of the highly pathogenic Filoviridae family.

The first Ebola outbreak sickened 686 individuals across the DRC and neighboring Sudan. 453 of the patients died, with a final case fatality rate (CFR)—the number of dead out of number of sickened—of 66 percent. Despite the lethality of the virus, sociocultural interventions, including lockdowns, contact-tracing, campaigns to change funeral rites, and restrictions on consumption of game meat all proved effective interventions in the long run.

That is, until 2014, when there was an exception to the pattern. Ebola appeared in Guinea, a small country in West Africa, whose population had never before been exposed to the virus. The closest epidemic had been in Gabon, 13 years before and 2,500 miles away. Over the course of two years, the infection spread from Guinea into Liberia and Sierra Leone, sickening more than 24,000 people and killing more than 10,000.

Countries that have previously battled the 2002 SARS epidemic, like Taiwan and Hong Kong, have shown exemplary recovery rates.

During the initial phase of the 2014 Ebola outbreak, rural communities were reluctant to cooperate with government directives for how to care for the sick and the dead. To help incentivize behavioral changes, sociocultural anthropologists like Mariane Ferme of the University of California, Berkeley, were brought in to advise the government. In a recent interview with Nautilus, Ferme indicated that strategies that allowed rural communities to remain involved with their loved ones increased cooperation. Villages located far from the capital, she said, were encouraged to “deputize someone to come to the hospital, to come to the burial, so they could come back to the community and tell the story of the body.” For communities that couldn’t afford to send someone to the capital, she saw public health officials adopt a savvy technological solution—tablets to record video messages that were carried between convalescent patients and their families.

However, there were also systemic failures that, in Ferme’s opinion, contributed to the severity of the 2014 West African epidemic. In Sierra Leone, she said, “the big mistake early on was to distribute [weakly causal] information about zoonotic transmission, even when it was obviously community transmission.” In other words, although there had been an instance of zoonotic transmission—the virus jumping from a bat to a human—that initiated the epidemic, the principle danger was other contagious individuals, not game meat. Eventually, under pressure from relief groups, the government changed its messaging to reflect scientific consensus.

But the retraction shook public faith in the government and bred resentment. The mismatch between messaging and reality mirrors the current pandemic. Since the COVID outbreak began, international and government health officials have issued mixed messages. Doubts initially surfaced about the certainty of the virus being capable of spreading from person to person, and the debate over the effectiveness of masks in preventing infection continues.

Despite the confused messaging, there has been general compliance with stay-at-home orders that has helped flatten the curve. Had the public been less trusting of government directives, the outcome could have been disastrous, as it was in Libera in 2014. After a two-week lockdown was announced, the Liberian army conducted house-to-house sweeps to check for the sick and collect the dead. “It was a draconian method that made people hide the sick and dead in their houses,” Ferme said. People feared their loved ones would be buried without the proper rites. A direct consequence was a staggering number of active cases, and an unknown extent of community transmission. But in the end, the benchmark for the end of Ebola and SARS was the same. The WHO declared victory when the rate of new cases slowed, then stopped. By the same measure, when an entire 14-day quarantine period passes with no new cases of COVID-19, it can be declared over.

It remains possible that even if we manage to end the epidemic, it will return again. Driven by novel zoonotic transmissions, Ebola has flared up every few years. Given the extent of COVID-19’s spread, and the potential for the kind of mutations that allow for re-infection, it may simply become endemic.

Two factors will play into the final outcome of COVID-19 are pathogenicity and virulence. Pathogenicity is the ability of an infectious agent to cause disease in the host, and is measured by R0—the number of new infections each patient can generate. Virulence, on the other hand, is the amount of harm the infectious agent can cause, and is best measured by CFR. While the pathogenicity of Ebola, SARS, and SARS-CoV-2 is on the same order—somewhere between 1 to 3 new infections for each patient, virulence differs greatly between the two SARS viruses and Ebola.

The case fatality rate for an Ebola infection is between 60 to 90 percent. The spread in CFR is due to differences in infection dynamics between strains. The underlying cause of the divergent virulence of Ebola and SARS is largely due to the tropism of the virus, meaning the cells that it attacks. The mechanism by which the Ebola virus gains entry into cells is not fully understood, but it has been shown the virus preferentially targets immune and epithelial cells.5 In other words, the virus first destroys the body’s ability to mount a defense, and then destroys the delicate tissues that line the vascular system. Patients bleed freely and most often succumb to low blood pressure that results from severe fluid loss. However, neither SARS nor SARS-CoV-2 attack the immune system directly. Instead, they enter lung epithelial cells through the ACE2 receptor, which ensures a lower CFR. What is interesting about these coronaviruses is that despite their similar modes of infection, they demonstrate a range of virulence: SARS had a final CFR of 10 percent, while SARS-CoV-2 has a pending CFR of 1.4 percent. Differences in virulence between the 2002 and 2019 SARS outbreaks could be attributed to varying levels of care between countries.

The chart above displays WHO data of the relationship between the total number of cases in a country and the CFR during the 2002-2003 SARS-CoV epidemic. South Africa, on the far right, had only a single case. The patient died, which resulted in a 100 percent CFR. China, on the other hand, had 5,327 cases and 349 deaths, giving a 7 percent CFR. The chart below zooms to the bottom left corner of the graph, so as to better resolve critically affected countries, those with a caseload of less than 1,000, but with a high CFR.

Here is Hong Kong, with 1,755 cases and a 17 percent CFR. There is also Taiwan, with 346 cases and an 11 percent CFR. Finally, nearly tied with Canada is Singapore with 238 cases and a 14 percent CFR.

With COVID-19, it’s apparent that outcome reflects experience. China has 82,747 cases of COVID, but has lowered their CFR to 4 percent. Hong Kong has 1,026 cases and a 0.4 percent CFR. Taiwan has 422 cases at 1.5 percent CFR, and Singapore with 8,014 cases, has a 0.13 percent CFR.

It was the novel coronavirus identification program established in China in the wake of the 2002 SARS epidemic that alerted authorities to SARS-CoV-2 back in November of 2019. The successful responses by Taiwan, Hong Kong, and Singapore can also be attributed to a residual familiarity with the dangers of an unknown virus, and the sorts of interventions that are necessary to prevent a crisis from spiraling out of control.

In West Africa, too, they seem to have learned the value of being prepared. When Ferme returned to Liberia on March 7, she encountered airport staff fully protected with gowns, head covers, face screens, masks, and gloves. By the time she left the country, 10 days later, she said, “Airline personnel were setting up social distancing lines, and [rural vendors] hawking face masks. Motorcycle taxis drivers, the people most at risk after healthcare workers—all had goggles and face masks.”

The sheer number of COVID-19 cases indicates the road to recovery will take some time. Each must be identified, quarantined, and all contacts traced and tested. Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars. Northwestern University economists Martin Eichenbaum et al. modeled6 the cost of a yearlong shutdown to be $4.2 trillion, a cost that proactive countries will not face. A recent Harvard study7 published in Science suggests the virus will likely make seasonal appearances going forward, potentially requiring new waves of social distancing. In other words, initial hesitancy will have repercussions for years. In the future, smart containment principles,6 where restrictions are applied on the basis of health status, may temper the impact of these measures.

Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars.

Inaction was initially framed as promoting herd immunity, where spread of the virus is interrupted once everyone has fallen sick with it. This is because getting the virus results in the same antibody production process as getting vaccinated—but doesn’t require the development of a vaccine. The Johns Hopkins Bloomberg School of Public Health estimates that 70 percent of the population will need to be infected with or vaccinated against the virus8 for herd immunity to work. Progress toward it has been slow, and can only be achieved through direct infection with the virus, meaning many will die. A Stanford University study in Santa Clara County9 suggests only 2.5 percent to 4.2 percent of the population have had the virus. Another COVID hotspot in Gangelt, Germany, suggests 15 percent10—higher, but still nowhere near the 70 percent necessary for herd immunity. Given the dangers inherent in waiting on herd immunity, our best hope is a vaccine.

A key concern for effective vaccine development is viral mutation. This is because vaccines train the immune system to recognize specific shapes on the surface of the virus—a composite structure called the antigen. Mutations threaten vaccine development because they can change the shape of the relevant antigen, effectively allowing the pathogen to evade immune surveillance. But, so far, SARS-CoV-2 has been mutating slowly, with only one mutation found in the section most accessible to the immune system, the spike protein. What this suggests is that the viral genome may be sufficiently stable for vaccine development.

What we know, though, is that Ebola was extinguished due to cooperation between public health officials and community leaders. SARS-CoV ended when all cases were identified and quarantined. The Spanish Flu in 1918 vanished after two long, deadly seasons.

The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line. With 26 million unemployed and protests erupting around the country, it seems there are many who would prefer to risk life and limb rather than face financial insolvency. Applying smart containment principles in the aftermath of the shutdown might be the best way to get the economy moving again, while maintaining the safety of those at greatest risk. Going forward, vigilance and preparedness will be the watchwords of the day, and the most efficient way to prevent social and economic ruin.

Anastasia Bendebury and Michael Shilo DeLay did their PhDs at Columbia University. Together they created Demystifying Science, a science literacy organization devoted to providing clear, mechanistic explanations for natural phenomena. Find them on Twitter @DemystifySci.

References

1. Genomic epidemiology of novel coronavirus - Global subsampling. Nextstrain www.nextstrain.org.

2. Covid-19 TrialsTracker. TrialsTracker www.trialstracker.net.

3. Struck, M. Vaccine R&D success rates and development times. Nature Biotechnology 14, 591-593 (1996).

4. Breman, J. & Johnson, K. Ebola then and now. The New England Journal of Medicine 371 1663-1666 (2014).

5. Baseler, L., Chertow, D.S., Johnson, K.M., Feldmann, H., & Morens, D.M. THe pathogenesis of Ebola virus disease. The Annual Review of Pathology 12, 387-418 (2017).

6. Eichenbaum, M., Rebell, S., & Trabandt, M. The macroeconomics of epidemics. The National Bureau of Economic Research Working Paper: 26882 (2020).

7. Kissler, S., Tedijanto, C., Goldstein, E., Grad, Y., & Lipsitch, M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science eabb5793 (2020).

8. D’ Souza, G. & Dowdy, D. What is herd immunity and how can we achieve it with COVID-19? Johns Hopkins COVID-19 School of Public Health Insights www.jhsph.edu (2020).

9. Digitale, E. Test for antibodies against novel coronavirus developed at Stanford Medicine. Stanford Medicine News Center Med.Stanford.edu (2020).

10. Winkler, M. Blood tests show 14%of people are now immune to COVID-19 in one town in Germany. MIT Technology Review (2020).

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