Larger retailers like Heinz and Loblaw signing up with Shopify

Dr Alex Aldren has returned to the NHS after leaving to become an opera singer

A lack of PPE is concern among nurses

No longer able to walk hundreds of miles to create his hand-drawn maps, the Beijing-based artist Fuller is charting his thoughts – and the global crisis – while stuck indoors

I’m interested in the psychology of a place and how it makes you feel. So I don’t really see myself as a map-maker – even though I draw maps. It’s about the process of travelling through a place to capture a sense of it. First, I walk for hundreds of miles and make all sorts of notes, and then take thousands of photos to use as triggers for my memory.

I walked more than 840 miles around Beijing when researching the map that became part of my Purposeful Wandering series. I circumnavigated the city and then walked around each ring road. Beijing (where I’ve lived for three years) is built on a Central Axis, and the map is, too. A lot of the drawing is literal, but I also built in personal experiences, references, visual puns and semiotics.

Publishers of several of Canada’s major newspapers signed a joint letter to the federal government this month, taking aim at the advertising revenue earned by Google and Facebook.

The new amendments allow the president to to take measures to contain the virus, but they also include expanded powers to ban public and private meetings, protests, celebrations and other forms of assembly.

The Rooms is eager to document how people are coping with the current pandemic to build a record for the future.

An investigator went to CCA Logistics Ltd. (Newsway) on April 1, where they say they found several pieces of personal protective equipment (PPE) for sale at grossly inflated prices.

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Health authorities at all levels of government have cautioned against visits to cottage country to prevent the spread of COVID-19 in more rural areas.

Justin Trudeau says there will be more support from the federal government to help certain sectors of the economy reeling from the impact of the COVID-19 pandemic.

Theresa May has hit out at world leaders for failing "to forge a coherent international response" to the coronavirus pandemic.

Needing to clear my head, I went down to the Penobscot River. There they were, swimming with the mergansers, following an early pulse of river herring to the mouth of Kenduskeag stream: two harbor seals, raising sleek round heads for a few long breaths before rolling under the waves.

Evidently it’s not uncommon for seals to swim the couple dozen miles between Bangor, Maine, and the Atlantic Ocean, but I’d never seen them here before. They were a balm to my buzzing thoughts: What happens next? Will I become a vector of death to my elderly mother? Is the economy going to implode? For a precious few minutes there were only the seals and mergansers and the fish who drew them there, arriving as the Penobscot’s winter icepack broke and flowed to sea, a ritual enacted ever since glaciers retreated from this continental shelf.

In the months ahead we can look to nature for these respites. The nonhuman world is free of charge; sunlight is a disinfectant, physical distance easily maintained, and no pandemic can suspend it. Nature offers not just escape but reassurance.

The nonhuman world is free of charge; sunlight is a disinfectant, and physical distance is easily maintained.

In 1946, in the aftermath of World War II, with the Nazi threat vanquished but the Cold War looming, George Orwell welcomed spring’s arrival in London’s bombed-out heart. “After the sorts of winters we have had to endure recently, the spring does seem miraculous, because it has become gradually harder and harder to believe that it is actually going to happen,” he wrote in “Some Thoughts on the Common Toad.” “Every February since 1940 I have found myself thinking that this time Winter is going to be permanent. But Persephone, like the toads, always rises from the dead at about the same moment.”

So she does. And so the slumbering earth warms to life. Two nights before the seals, two nights before World Health Organization declared a pandemic, before the NBA shut down with teams on the floor and fans in the seats, before the fright went beyond viral into logarithmic, was the Worm Moon: the full moon named for the imminent stir of earthworms in thawing soil.

In burrows beneath leaf litter, hibernating toads prepare to open what Orwell called “the most beautiful eye of any living creature,” resembling “the golden-colored semi-precious stone which one sometimes sees in signet rings, and which I think is called a chrysoberyl.” Nearly as beautiful are the eyes of painted turtles waiting on pond bottoms here in eastern Maine, the ice above now retreating from shore, mallard couples dabbling in newly open water.

The birds are the surest sign of spring’s imminence. Downtown the house finches are holding daily concerts. Starlings are starting to replace their gold-streaked winter plumes with more iridescent garb. In the street today I saw two male mockingbirds joust above the pavement, their white wing-bars fluttering territorial semaphores, abandoning the contest only when a car nearly ran them down. 

There are many quieter signs, too: pale tips of shrubs poised to grow, a spider rappelling off a low branch, fresh fox scat in the driveway. It’s red from apples preserved under snow and lined with the fur of field mice and meadow voles whose secret winter tunnels are now revealed in the grass. Somewhere soon mother fox will give birth, nursing her blind hairless charges in underground peace.

Eastern comma butterflies will gather on the trunks of those apple trees and sip their rising sap. Not long after the first orange-belted bumblebee queens will appear, inspecting potential nest sites under fallen leaves and decomposing logs. Warm rainy nights will bring salamanders and newts, just a few spotted glistening inches long, some of them decades old, out from woodland hidey-holes and down ancient paths to vernal pool bacchanals held amidst a chorus of spring peepers. Woodland ephemerals will bloom in sunshine unfiltered by still-bare treetops. My favorite are trout lilies, colonies of which illuminate forest floors with a sea of bright yellow blossoms, petals falling once the canopy unfurls.

“The atom bombs are piling up in the factories, the police are prowling through the cities, the lies are streaming from the loudspeakers,” Orwell wrote, “but the earth is still going round the sun.”

At this point there’s no end of studies showing how nature is good for our health, how patients recover faster in hospital rooms with windows overlooking trees, how a mindful walk in the woods will lower stress and raise moods. All true, but at this moment something deeper and more urgent is offered. An affirmation of life.

Will the nightmare scenes out of Italy and Spain and now New York City spread across the land? How long will the pandemic last? Will it completely rend our already tattered social fabric? When can I again play hockey or go to a coffee shop or use a credit card machine without feeling like I’m risking my own and other lives? Who will die? Nobody knows for sure, but in a few weeks the swallows will arrive, and tonight above the fields at dusk I heard the cries of woodcock.

Secretive, ground-dwelling birds with limpid black eyes and long, slender beaks attuned to the frequencies of earthworm-rustles, their feathers blend perfectly with leaf litter and old grass. They rely on this camouflage, going still rather than fleeing a walker’s approach, taking wing only as a last resort.

When they do, their flight is notable for its slowness and the quavering whistle of their wings. At no other time than in spring do they dare draw attention, much less put on a show: calling out, with an urgent nasal buzz best described as a peent, and flying straight upward before spiraling against a darkening sky.

Brandon Keim is a freelance nature and science journalist. The author of The Eye of the Sandpiper: Stories from the Living World, he’s now writing Meet the Neighbors, forthcoming from W.W. Norton & Company, about what it means to think of wild animals as fellow persons—and what that means for the future of nature.

Lead image: Tim Zurowski / Shutterstock

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).

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

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

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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