How dozens of men across Alaska (and their dogs) teamed up to save one town from a deadly outbreak
During the winter of 1924, Curtis Welch – the only doctor in Nome, a remote fishing town in northwest Alaska – started noticing something strange. More and more, the children of Nome were coming to his office with sore throats.
Initially, Welch dismissed the cases as tonsillitis or some run-of-the-mill virus – but when more kids started getting sick, with some even dying, he grew alarmed. It wasn’t until early 1925, after a three-year-old boy died just two weeks after becoming ill, that Welch realized that his worst suspicions were true. The boy – and dozens of other children in town – were infected with diphtheria.
A DEADLY BACTERIA
Diphtheria is nearly nonexistent and almost unheard of in industrialized countries today. But less than a century ago, diphtheria was a household name – one that struck fear in the heart of every parent, as it was extremely contagious and particularly deadly for children.
Diphtheria – a bacterial infection – is an ugly disease. When it strikes, the bacteria eats away at the healthy tissues in a patient’s respiratory tract, leaving behind a thick, gray membrane of dead tissue that covers the patient's nose, throat, and tonsils. Not only does this membrane make it very difficult for the patient to breathe and swallow, but as the bacteria spreads through the bloodstream, it causes serious harm to the heart and kidneys. It sometimes also results in nerve damage and paralysis. Even with treatment, diphtheria kills around 10 percent of people it infects. Young children, as well as adults over the age of 60, are especially at risk.
Welch didn’t suspect diphtheria at first. He knew the illness was incredibly contagious and reasoned that many more people would be sick – specifically, the family members of the children who had died – if there truly was an outbreak. Nevertheless, the symptoms, along with the growing number of deaths, were unmistakable. By 1925 Welch knew for certain that diphtheria had come to Nome.
In desperation, Welch tried treating an infected seven-year-old girl with some expired antitoxin – but she died just a few hours after he administered it.
AN INACCESSIBLE CURE
A vaccine for diphtheria wouldn’t be widely available until the mid-1930s and early 1940s – so an outbreak of the disease meant that each of the 10,000 inhabitants of Nome were all at serious risk.
One option was to use something called an antitoxin – a serum consisting of anti-diphtheria antibodies – to treat the patients. However, the town’s reserve of diphtheria antitoxin had expired. Welch had ordered a replacement shipment of antitoxin the previous summer – but the shipping port that was set to deliver the serum had been closed due to ice, and no new antitoxin would arrive before spring of 1925. In desperation, Welch tried treating an infected seven-year-old girl with some expired antitoxin – but she died just a few hours after he administered it.
Welch radioed for help to all the major towns in Alaska as well as the US Public Health Service in Washington, DC. His telegram read: An outbreak of diphtheria is almost inevitable here. I am in urgent need of one million units of diphtheria antitoxin. Mail is the only form of transportation.
FOUR-LEGGED HEROES
When the Alaskan Board of Health learned about the outbreak, the men rushed to devise a plan to get antitoxin to Nome. Dropping the serum in by airplane was impossible, as the available planes were unsuitable for flying during Alaska’s severe winter weather, where temperatures were routinely as cold as -50 degrees Fahrenheit.
In late January 1925, roughly 30,000 units of antitoxin were located in an Anchorage hospital and immediately delivered by train to a nearby city, Nenana, en route to Nome. Nenana was the furthest city that was reachable by rail – but unfortunately it was still more than 600 miles outside of Nome, with no transportation to make the delivery. Meanwhile, Welch had confirmed 20 total cases of diphtheria, with dozens more at high risk. Diphtheria was known for wiping out entire communities, and the entire town of Nome was in danger of suffering the same fate.
It was Mark Summer, the Board of Health superintendent, who suggested something unorthodox: Using a relay team of sled-racing dogs to deliver the antitoxin serum from Nenana to Nome. The Board quickly voted to accept Summer’s idea and set up a plan: The thousands of units of antitoxin serum would be passed along from team to team at different towns along the mail route from Nenana to Nome. When it reached a town called Nulato, a famed dogsled racer named Leonhard Seppala and his experienced team of huskies would take the serum more than 90 miles over the ice of Norton Sound, the longest and most treacherous part of the journey. Past the sound, the serum would change hands several times more before arriving in Nome.
Between January 27 and 31, the serum passed through roughly a dozen drivers and their dog sled teams, each of them carrying the serum between 20 and 50 miles to the next destination. Though each leg of the trip took less than a day, the sub-zero temperatures – sometimes as low as -85 degrees – meant that every driver and dog risked their lives. When the first driver, Bill Shannon, arrived at his checkpoint in Tolovana on January 28th, his nose was black with frostbite, and three of his dogs had died. The driver who relieved Bill Shannon, named Edgar Kalland, needed the owner of a local roadhouse to pour hot water over his hands to free them from the sled’s metal handlebar. Two more dogs from another relay team died before the serum was passed to Seppala at a town called Ungalik.
THE FINAL STRETCHES
Seppala and his team raced across the ice of the Norton Sound in the dead of night on January 31, with wind chill temperatures nearing an astonishing -90 degrees. The team traveled 84 miles in a single day before stopping to rest – and once rested, they set off again in the middle of the night through a raging winter storm. The team made it across the ice, as well as a 5,000-foot ascent up Little McKinley Mountain, to pass the serum to another driver in record time. The serum was now just 78 miles from Nome, and the death toll in town had reached 28.
The serum reached Gunnar Kaasen and his team of dogs on February 1st. Balto, Kaasen’s lead dog, guided the team heroically through a winter storm that was so severe Kaasen later reported not being able to see the dogs that were just a few feet ahead of him.
Visibility was so poor, in fact, that Kaasen ran his sled two miles past the relay point before noticing – and not wanting to lose a minute, he decided to forge on ahead rather than doubling back to deliver the serum to another driver. As they continued through the storm, the hurricane-force winds ripped past Kaasen’s sled at one point and toppled the sled – and the serum – overboard. The cylinder containing the antitoxin was left buried in the snow – and Kaasen tore off his gloves and dug through the tundra to locate it. Though it resulted in a bad case of frostbite, Kaasen eventually found the cylinder and kept driving.
Kaasen arrived at the next relay point on February 2nd, hours ahead of schedule. When he got there, however, he found the relay driver of the next team asleep. Kaasen took a risk and decided not to wake him, fearing that time would be wasted with the next driver readying his team. Kaasen, Balto, and the rest of the team forged on, driving another 25 miles before finally reaching Nome just before six in the morning. Eyewitnesses described Kaasen pulling up to the town’s bank and stumbling to the front of the sled. There, he collapsed in exhaustion, telling onlookers that Balto was “a damn fine dog.”
A LIVING LEGACY
Just a few hours after Balto’s heroic arrival in Nome, the serum had been thawed and was ready to administer to the patients with diphtheria. Amazingly, the relay team managed to complete the entire journey in just 127 hours – a world record at the time – without one serum vial damaged or destroyed. The serum shipment that arrived by dogsled – along with additional serum deliveries that followed in the next several weeks – were successful in stopping the outbreak in its tracks.
Balto and several other dogs – including Togo, the lead dog on Seppala’s team – were celebrated as local heroes after the race. Balto died in 1933, while the last of the human serum runners died in 1999 – but their legacy lives on: In early 2021, an all-female team of healthcare workers made the news by braving the Alaskan winter to deliver COVID-19 vaccines to people in rural North Alaska, traveling by bobsled and snowmobile – a heroic journey, and one that would have been unthinkable had Balto, Togo, and the 1925 sled runners not first paved the way.
Podcast: The Friday Five weekly roundup in health research
The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Covered in this week's Friday Five:
- Sex differences in cancer
- Promising research on a vaccine for Lyme disease
- Using a super material for brain-like devices
- Measuring your immunity to Covid
- Reducing dementia risk with leisure activities
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.