Social, cultural, economic, spiritual, psychological, emotional, intellectual: Everything is outside the box. And this new sheltered-in-place experience won’t fit into old containers.Photo Illustration by Africa Studio / Shutterstock

Many of us are stuck now, sheltered in our messy dwellings. A daily walk lets me appreciate the urban landscaping; but I can’t stop to smell anything because a blue cotton bandana shields my nostrils. Indoors, constant digital dispatches chirp to earn my attention. I click on memes, status updates, and headlines, but everything is more of the same. How many ways can we repackage fear and reframe optimism? I mop the wood-laminate floor of my apartment because I hope “ocean paradise” scented Fabuloso will make my home smell a little less confining. My thoughts waft toward the old cliché: Think outside the box. I’ve always hated when people say that.

To begin with, the directions are ineffectual. You can’t tell someone to think outside the box and expect them to do it. Creativity doesn’t happen on demand. Want proof? Just try to make yourself think a brilliant thought, something original, innovative, or unique. Go ahead. Do it. Right now. You can’t, no matter how hard you try. This is why ancient people believed that inspiration comes from outside. It’s external, bestowed on each of us like a revelation or prophecy—a gift from the Muses. Which means your genius does not belong to you. The word “genius” is the Latin equivalent of the ancient Greek “daemon” (δαίμονες)—like a totem animal, or a spirit companion. A genius walks beside us. It mediates between gods and mortals. It crosses over from one realm to the next. It whispers divine truth.

We are paralyzed by the prospect of chaos, uncertainty, and entropy.

In modern times, our mythology moves the daemons away from the heavens and into the human soul. We say, “Meditate and let your spirit guide you.” Now we think genius comes from someplace deep within. The mind? The brain? The heart? Nobody knows for sure. Yet, it seems clear to us that inspiration belongs to us; it’s tangibly contained within our corporeal boundaries. That’s why we celebrate famous artists, poets, physicists, economists, entrepreneurs, and inventors. We call them visionaries. We read their biographies. We do our best to emulate their behaviors. We study the five habits of highly successful people. We practice yoga. We exercise. We brainstorm, doodle, sign up for online personal development workshops. We do whatever we can to cultivate the fertile cognitive soil in which the springtime seeds of inspiration might sprout. But still, even though we believe that a genius is one’s own, we know that we cannot direct it. Therefore, no matter how many people tell me to think outside the box, I won’t do it. I can’t. 

Even if I could, I’m not sure thinking outside the box would be worthwhile. Consider the origins of the phrase. It started with an old brain teaser. Nine dots are presented in a perfect square, lined up three by three. Connect them all, using only four straight lines, without lifting your pencil from the paper. It’s the kind of puzzle you’d find on the back of a box of Lucky Charms breakfast cereal, frivolous but tricky. The solution involves letting the lines expand out onto the empty page, into the negative space. Don’t confine your markings to the dots themselves. You need to recognize, instead, that the field is wider than you’d assume. In other words, don’t interpret the dots as a square, don’t imagine that the space is constricted. Think outside the box! 

For years, pop-psychologists, productivity coaches, and business gurus have all used the nine-dot problem to illustrate the difference between “fixation” and “insight.” They say that we look at markings on a page and immediately try to find a pattern. We fixate on whatever meaning we can ascribe to the image. In this case, we assume that nine dots make a box. And we imagine we’re supposed to stay within its boundaries—contained and confined. We bring habitual assumptions with us even though we’re confronting a unique problem. Why? Because we are paralyzed by the prospect of chaos, uncertainty, and entropy. We cling to the most familiar ways of organizing things in order to mitigate the risk that new patterns might not emerge at all, the possibility that meaning itself could cease to exist. But this knee-jerk reaction limits our capacity for problem-solving. Our customary ways of knowing become like a strip of packing tape that’s accidentally affixed to itself—you can struggle to undo it, but it just tangles up even more. In other words, your loyalty to the easiest, most common interpretations is the sticky confirmation bias that prevents you from arriving at a truly insightful solution. 

At least that’s what the experts used to say. And we all liked to believe it. But our minds don’t really work that way. The box parable appeals because it reinforces our existing fantasies about an individual’s proclivity to innovate and disrupt by thinking in unexpected ways. It’s not true. 

Studies have found that solving the nine-dot problem has nothing to do with the box. Even when test subjects were told that the solution requires going outside the square’s boundaries, most of them still couldn’t solve it. There was an increase in successful attempts so tiny that it was considered statistically insignificant, proving that the ability to arrive at a solution to the nine-dot problem has nothing to do with fixation or insight. The puzzle is just difficult, no matter which side of the box you’re standing on.

Still, I bet my twelve-year-old son could solve it. Yesterday, we unpacked a set of oil paints, delivered by Amazon. He was admiring the brushes and canvases. He was thinking about his project, trying to be creative, searching for insight. “Think inside the outside of the box,” he said.  “What does that mean?” I pushed the branded, smiling A-to-Z packaging aside and I looked at him like he was crazy. “Like with cardboard, you know, with all the little holes inside.” 

He was talking about the corrugations, those ridges that are pasted between layers of fiberboard. They were originally formed on the same fluted irons used to make the ruffled collars of Elizabethan-era fashion. At first, single faced corrugated paper—smooth on one side, ridged on the other—was used to wrap fragile glass bottles. Then, around 1890, the double-faced corrugated fiberboard with which we’re familiar was developed. And it transformed the packing and shipping industries. The new paperboard boxes were sturdy enough to replace wooden crates. It doesn’t take an engineering degree to understand how it works: The flutes provide support; the empty space in between makes it lightweight. My son is right; it’s all about what’s inside the outside of the box.

Now I can’t stop saying it to myself, “Think inside the outside of the box.” It’s a perfect little metaphor. In a way, it even sums up the primary cognitive skill I acquired in graduate school. One could argue that a PhD just means you’ve been trained to think inside the outside of boxes. What do I mean by that? Consider how corrugation gives cardboard it’s structural integrity. The empty space—what’s not there—makes it strong and light enough that it’s a useful and efficient way to carry objects. Similarly, it’s the intellectual frameworks that make our interpretations and analyses of the world hold up. An idea can’t stand on its own; it needs a structure and a foundation. It needs a box. It requires a frame. And by looking at how those frames are assembled, by seeing how they carry a concept through to communication, we’re able to do our best thinking. We look at the empty spaces—the invisible, or tacit assumptions—which lurk within the fluted folds of every intellectual construction. We recognize that our conscious understanding of lived experience is corrugated just like cardboard. 

The famous sociologist Erving Goffman said as much in 1974 when he published his essay on “Frame Analysis.” He encouraged his readers to identify the principles of organization which govern our perceptions. This work went on to inspire countless political consultants, pundits, publicists, advertisers, researchers, and marketers. It’s why we now talk often about the ways in which folks “frame the conversation.” But I doubt my son has read Goffman. He just stumbled on a beautifully succinct way to frame the concept of critical thinking. Maybe he was inspired by Dr. Seuss. 

When my kids were little, they asked for the same story every night, “Read Sneetches Daddy!” I could practically recite the whole thing from memory: “Now, the Star-belly Sneetches had bellies with stars. The Plain-belly Sneetches had none upon thars.” It’s an us-versus-them story, a fable about the way a consumption economy encourages people to compete for status, and to alienate the “other.” If you think inside the outside of the box, it’s also a scathing criticism of a culture that’s obsessed with personal and professional transformation—always reinventing and rebranding. 

One day, Sylvester McMonkey McBean shows up on the Sneetches’ beaches with a peculiar box-shaped fix-it-up machine. Sneetches go in with plain-bellies and they come out with stars. Now, anyone can be anything, for a fee. McBean charges them a fortune; he exploits the Sneetches’ insecurities. He builds an urgent market demand for transformational products. He preys on their most familiar—and therefore, cozy and comforting—norms of character assessment. He disrupts their identity politics, makes it so that there’s no clear way to tell who rightfully belongs with which group. And as a result, chaos ensues. Why? Because the Sneetches discover that longstanding divisive labels and pejorative categories no longer provide a meaningful way to organize their immediate experiences. They’ve lost their frames, the structural integrity of their worldview. They feel unhinged, destabilized, unboxed, and confused.

Social, cultural, economic, spiritual, psychological, emotional, intellectual: Everything is outside the box.

It should sound familiar. After all, we’ve been living through an era in history that’s just like the Sneetches’. The patterns and categories we heretofore used to define self and other are being challenged every day—sometimes for good, sometimes for bad. How can we know who belongs where in a digital diaspora, a virtual panacea, where anyone can find “my tribe”? What do identity, allegiance, heredity, and loyalty even mean now that these ideas can be detached from biology and birthplace? Nobody knows for sure. And that’s just the beginning: We’ve got Sylvester-McMonkey-McBean-style disruption everywhere we look. Connected technologies have transformed the ways in which we make sense of our relationships, how we communicate with one another, our definitions of intimacy. 

Even before the novel coronavirus, a new global paradigm forced us to live and work in a world that’s organized according to a geopolitical model we can barely comprehend. Sure, the familiar boundaries of statehood sometimes prohibited migrant foot traffic—but information, microbes, and financial assets still moved swiftly across borders, unimpeded. Similarly, cross-national supply-chains rearranged the rules of the marketplace. High-speed transportation disrupted how we perceive the limits of time and space. Automation upset the criteria through which we understand meritocracy and self-worth. Algorithms and artificial intelligence changed the way we think about labor, employment, and productivity. Data and privacy issues blurred the boundaries of personal sovereignty. And advances in bioengineering shook up the very notion of human nature.

Our boxes were already bursting. And now, cloistered at home in the midst of a pandemic, our most mundane work-a-day routines are dissolved, making it feel like our core values and deeply-held beliefs are about to tumble out all over the place. We can already envision the mess that is to come—in fact, we’re watching it unfurl in slow motion. Soon, the world will look like the intellectual, emotional, and economic equivalent of my 14-year-old’s bedroom. Dirty laundry is strewn across the floor, empty candy wrappers linger on dresser-tops, mud-caked sneakers are tossed in the corner, and the faint yet unmistakable stench of prepubescent body odor is ubiquitous. Nothing is copasetic. Nothing is in its place. Instead, everything is outside the box. 

It’s not creative, inspiring, or insightful. No, it’s disorienting and anxiety-provoking. I want to tidy it up as quickly as possible. I want to put things back in their familiar places. I want to restore order and eliminate chaos. But no matter how hard I try, I can’t do it, because the old boxes are ripped and torn. Their bottoms have fallen out. Now, they’re useless. Social, cultural, economic, spiritual, psychological, emotional, intellectual: Everything is outside the box. And this new sheltered-in-place experience won’t fit into old containers.

Jordan Shapiro, Ph.D., is a senior fellow for the Joan Ganz Cooney Center at Sesame Workshop and Nonresident Fellow in the Center for Universal Education at the Brookings Institution. He teaches at Temple University, and wrote a column for Forbes on global education and digital play from 2012 to 2017. His book, The New Childhood, was released by Little, Brown Spark in December 2018.

Read More…

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).

Read More…

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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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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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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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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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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