Americans Fell for a Theranos-Style Scam 100 Years Ago. Will We Ever Learn?
The huckster understands what people want – an easy route to good health -- and figures out just how to provide it as long as no one asks too many questions.
"Americans are very much prone to this sort of thinking: Give me a pill or give me a magical bean that can make me lose weight!"
The keys to success: Hoopla, fancy technology, and gullibility. And oh yes, one more thing: a blood sample. Well, lots and lots of blood samples. Every testing fee counts.
Sound familiar? It could be the story of the preternaturally persuasive Elizabeth Holmes, the disgraced founder of Theranos who stands accused of perpetrating a massive blood-testing fraud. But this is a different story from a different time, one that dates back 100 years but sounds almost like it could unfold on the front page of The Wall Street Journal today.
The main difference: Back then, watchdogs thought they'd be able to vanquish fake medicine and scam science. Fat chance, it turned out. It seems like we're more likely to lose-weight-quick than make much of a dent into quackery and health fraud.
Why? Have we learned anything at all over the past century? As we sweep into a new decade, experts says we're not as advanced as we'd like to think. But the fight against fraud and fakery continues.
Quackery: As American As America Itself
In the 17th century, British healers of questionable reputation got a new name -- "quack," from the Dutch word "quacksalver," which originally referred to someone who treats others with home remedies but developed a new meaning along the lines of "charlatan." And these quacks got a new place to sell their wares: the American colonies.
By 1692, a Boston newspaper advertised a patent medicine that promised to cure "the Griping of the Guts, and the Wind Cholick" and – for good measure – "preventeth that woeful Distemper of the Dry Belly Ach." A couple centuries later, the most famous woman in the United States wasn't a first lady or feminist but a hawker of nostrums named Lydia Estes Pinkham whose "vegetable compound" promised to banish "female complaints." One advertisement suggested that the "sure cure" would have saved the life of a Connecticut clergyman whose wife killed him after suffering from feminine maladies for 16 years.
By the early 20th century, Americans were fascinated by electricity and radiation, and both healers and hucksters embraced the new high-tech era. Men with flagging libidos, for example, could irradiate their private parts with the radioactive Radiendocrinator or buy battery-powered electric belts equipped with dangling bits to supercharge their, um, dangling bits.
The Rise of the Radio Wave 'Cure'
Enter radionics, the (supposed) science of better health via radio waves. The idea was that "healthy people radiate healthy energy," and sickness could be reversed through diagnosis and re-tuning, write Dr. Lydia Kang and Nate Pedersen in their 2017 book "Quackery: A Brief History of the Worst Ways to Cure Everything."
Detecting illness and fixing it required machinery -- Dynamizers, Radioclasts and Oscillocasts – that could cost hundreds of dollars each. Thousands of physicians bought them. Fortunately, they could work remotely, for a fee. The worried-and-potentially-unwell just needed to send a blood sample and, of course, a personal check.
Sting operations revealed radionics to be bogus. A skeptic sent a blood sample to one radionics practitioner in Albuquerque who reported back with news of an infected fallopian tube. In fact, the blood sample came from a male guinea pig. As an American Medical Association leader reported, the guinea pig "had shown no female characteristics up to that time, and a postmortem examination yielded no evidence of ladylike attributes."
When Quackery Refused to Yield
The rise of bogus medical technology in the early 20th century spawned a watchdog industry as organizations like the American Medical Association swept into action, said medical historian Eric Boyle, author of 2012's "Quack Medicine: A History of Combating Health Fraud in Twentieth-Century America."
"When quackery was recognized as a major problem, the people who campaigned for its demise were confident that they could get rid of it," he said. "A lot of people believed that increased education, the truths of science, and laws designed to protect consumers would ultimately drive quackery from the marketplace. And then throughout the century, as modern medicine developed, and more effectively treated one disease after another, many observers remained confident in that prediction."
There's a bid to "flood the information highway with truth to turn the storm of fake promotional stuff into a trickle."
But fake medicine persisted as Americans continued their quest to get- healthy-quick… or get-rich-quick by promising to help others to get- healthy-quick. Even radionics refused to die. It's still around in various forms. And, as the Theranos scandal reveals, we're still hoping our blood can offer the keys to longevity and good health.
Why Do We Still Fall for Scams?
In our own era, the Theranos company rose to prominence when founder and CEO Elizabeth Holmes convinced journalists and investors that she'd found a way to cheaply test drops of blood for hundreds of conditions. Then it all fell apart, famously, when the world learned that the technology didn't work. The company has folded, and Holmes faces a federal trial on fraud charges this year.
"There were a lot of prominent, very smart people who bought into the myth of Elizabeth Holmes," a former employee told "60 Minutes," even though the blood tests never actually worked as advertised.
Shouldn't "prominent, very smart people" know better? "People are gullible," said Dr. Stephen Barrett, a psychiatrist and leading quack-buster who runs the QuackWatch website. But there's more to the story. According to him, we're uniquely vulnerable as individuals to bogus medicine.
Scam artists specifically pinpoint their target audiences, such as "smart people," desperate people and alienated people, he said.
Smart people, for example, might be overconfident about their ability to detect fraud and fall for bogus medicine. Alienated people may distrust the establishment, whether it's the medical field or government watchdogs, and be more receptive to alternative sources of information.
Dr. Barrett also points a finger at magical thinking, which comes in different forms. It could mean a New Age-style belief that our minds can control the world around us. Or, as professional quack-buster Alex Berezow said, it could refer to "our cultural obsession with quick fixes."
"Americans are very much prone to this sort of thinking: Give me a pill or give me a magical bean that can make me lose weight! But complex problems need complex solutions," said Berezow, a microbiologist who debunks junk science in his job as a spokesman for the American Council on Science & Health.
American mistrust of expertise makes matters worse, he said. "When I tell people they need to get vaccinated, I'm called a shill for the pharmaceutical industry," he said. "If I say dietary supplements generally don't work, I'm a shill for doctors who want to keep people sick."
What can ordinary citizens do to protect themselves from fake medicine? "You have to have a healthy skepticism of everything," Berezow said. "When you come across something new, is someone trying to take advantage of you? It's a horrible way to think about the world, but there's some truth to it."
"Like any chronic disease, we will have to live with it while we do our best to fight it."
The government and experts have their own roles to play via regulation and education, respectively. For all the criticism it gets, the Food & Drug Administration does serve as a bulwark against fakery in prescription medicine. And while celebrities like Gwyneth "Goop" Paltrow hawk countless questionable medical products on the Internet, scientists and physicians are fighting back by using social media as a tool to promote the truth. There's a bid to "flood the information highway with truth to turn the storm of fake promotional stuff into a trickle," said Dr. Randi Hutter Epstein, a writer in residence at Yale School of Medicine and author of 2018's "Aroused: The History of Hormones and How They Control Just About Everything."
What's next? Like death, taxes and Cher, charlatans are likely to always be with us. Boyle quoted the late William Jarvis, a pioneering quack-buster in the late 20th century who believed health fraud would never be eradicated: "Like any chronic disease, we will have to live with it while we do our best to fight it."
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in 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.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers