How a Deadly Fire Gave Birth to Modern Medicine
On the evening of November 28, 1942, more than 1,000 revelers from the Boston College-Holy Cross football game jammed into the Cocoanut Grove, Boston's oldest nightclub. When a spark from faulty wiring accidently ignited an artificial palm tree, the packed nightspot, which was only designed to accommodate about 500 people, was quickly engulfed in flames. In the ensuing panic, hundreds of people were trapped inside, with most exit doors locked. Bodies piled up by the only open entrance, jamming the exits, and 490 people ultimately died in the worst fire in the country in forty years.
"People couldn't get out," says Dr. Kenneth Marshall, a retired plastic surgeon in Boston and president of the Cocoanut Grove Memorial Committee. "It was a tragedy of mammoth proportions."
Within a half an hour of the start of the blaze, the Red Cross mobilized more than five hundred volunteers in what one newspaper called a "Rehearsal for Possible Blitz." The mayor of Boston imposed martial law. More than 300 victims—many of whom subsequently died--were taken to Boston City Hospital in one hour, averaging one victim every eleven seconds, while Massachusetts General Hospital admitted 114 victims in two hours. In the hospitals, 220 victims clung precariously to life, in agonizing pain from massive burns, their bodies ravaged by infection.
The scene of the fire.
Boston Public Library
Tragic Losses Prompted Revolutionary Leaps
But there is a silver lining: this horrific disaster prompted dramatic changes in safety regulations to prevent another catastrophe of this magnitude and led to the development of medical techniques that eventually saved millions of lives. It transformed burn care treatment and the use of plasma on burn victims, but most importantly, it introduced to the public a new wonder drug that revolutionized medicine, midwifed the birth of the modern pharmaceutical industry, and nearly doubled life expectancy, from 48 years at the turn of the 20th century to 78 years in the post-World War II years.
The devastating grief of the survivors also led to the first published study of post-traumatic stress disorder by pioneering psychiatrist Alexandra Adler, daughter of famed Viennese psychoanalyst Alfred Adler, who was a student of Freud. Dr. Adler studied the anxiety and depression that followed this catastrophe, according to the New York Times, and "later applied her findings to the treatment World War II veterans."
Dr. Ken Marshall is intimately familiar with the lingering psychological trauma of enduring such a disaster. His mother, an Irish immigrant and a nurse in the surgical wards at Boston City Hospital, was on duty that cold Thanksgiving weekend night, and didn't come home for four days. "For years afterward, she'd wake up screaming in the middle of the night," recalls Dr. Marshall, who was four years old at the time. "Seeing all those bodies lined up in neat rows across the City Hospital's parking lot, still in their evening clothes. It was always on her mind and memories of the horrors plagued her for the rest of her life."
The sheer magnitude of casualties prompted overwhelmed physicians to try experimental new procedures that were later successfully used to treat thousands of battlefield casualties. Instead of cutting off blisters and using dyes and tannic acid to treat burned tissues, which can harden the skin, they applied gauze coated with petroleum jelly. Doctors also refined the formula for using plasma--the fluid portion of blood and a medical technology that was just four years old--to replenish bodily liquids that evaporated because of the loss of the protective covering of skin.
"Every war has given us a new medical advance. And penicillin was the great scientific advance of World War II."
"The initial insult with burns is a loss of fluids and patients can die of shock," says Dr. Ken Marshall. "The scientific progress that was made by the two institutions revolutionized fluid management and topical management of burn care forever."
Still, they could not halt the staph infections that kill most burn victims—which prompted the first civilian use of a miracle elixir that was being secretly developed in government-sponsored labs and that ultimately ushered in a new age in therapeutics. Military officials quickly realized this disaster could provide an excellent natural laboratory to test the effectiveness of this drug and see if it could be used to treat the acute traumas of combat in this unfortunate civilian approximation of battlefield conditions. At the time, the very existence of this wondrous medicine—penicillin—was a closely guarded military secret.
From Forgotten Lab Experiment to Wonder Drug
In 1928, Alexander Fleming discovered the curative powers of penicillin, which promised to eradicate infectious pathogens that killed millions every year. But the road to mass producing enough of the highly unstable mold was littered with seemingly unsurmountable obstacles and it remained a forgotten laboratory curiosity for over a decade. But Fleming never gave up and penicillin's eventual rescue from obscurity was a landmark in scientific history.
In 1940, a group at Oxford University, funded in part by the Rockefeller Foundation, isolated enough penicillin to test it on twenty-five mice, which had been infected with lethal doses of streptococci. Its therapeutic effects were miraculous—the untreated mice died within hours, while the treated ones played merrily in their cages, undisturbed. Subsequent tests on a handful of patients, who were brought back from the brink of death, confirmed that penicillin was indeed a wonder drug. But Britain was then being ravaged by the German Luftwaffe during the Blitz, and there were simply no resources to devote to penicillin during the Nazi onslaught.
In June of 1941, two of the Oxford researchers, Howard Florey and Ernst Chain, embarked on a clandestine mission to enlist American aid. Samples of the temperamental mold were stored in their coats. By October, the Roosevelt Administration had recruited four companies—Merck, Squibb, Pfizer and Lederle—to team up in a massive, top-secret development program. Merck, which had more experience with fermentation procedures, swiftly pulled away from the pack and every milligram they produced was zealously hoarded.
After the nightclub fire, the government ordered Merck to dispatch to Boston whatever supplies of penicillin that they could spare and to refine any crude penicillin broth brewing in Merck's fermentation vats. After working in round-the-clock relays over the course of three days, on the evening of December 1st, 1942, a refrigerated truck containing thirty-two liters of injectable penicillin left Merck's Rahway, New Jersey plant. It was accompanied by a convoy of police escorts through four states before arriving in the pre-dawn hours at Massachusetts General Hospital. Dozens of people were rescued from near-certain death in the first public demonstration of the powers of the antibiotic, and the existence of penicillin could no longer be kept secret from inquisitive reporters and an exultant public. The next day, the Boston Globe called it "priceless" and Time magazine dubbed it a "wonder drug."
Within fourteen months, penicillin production escalated exponentially, churning out enough to save the lives of thousands of soldiers, including many from the Normandy invasion. And in October 1945, just weeks after the Japanese surrender ended World War II, Alexander Fleming, Howard Florey and Ernst Chain were awarded the Nobel Prize in medicine. But penicillin didn't just save lives—it helped build some of the most innovative medical and scientific companies in history, including Merck, Pfizer, Glaxo and Sandoz.
"Every war has given us a new medical advance," concludes Marshall. "And penicillin was the great scientific advance of World War II."
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