Epidemiologist Quotes

Same first name as a president and an obscure comic book character. Half-Jewish. Excellent grammar. Easily nauseated. Likes Reese's and Oreos (i.e. not an idiot). Divorced parents. Big brother to a fetus. Dad lives in Savannah. Dad's an English teacher. Mom's an epidemiologist. The problem is, I'm beginning to realize I hardly know anything about anyone. I mean I generally know who's a virgin. But I don't have a clue whether most people's parents are divorced, or what their parents do for a living. I mean, Nick's parents are doctors. But I don't know what Leah's mom does, and I don't even know what the deal is with her dad, because Leah never talks about him. I have no idea why Abby's dad and brother still live in DC. And these are my best friends. I've always thought of myself as nosy, but I guess I'm just nosy about stupid stuff. It's actually really terrible, now that I think about it.

Epidemiologists think that smallpox killed roughly one billion people during its last hundred years of activity on earth.

Epidemiologists have computed that measles requires an unvaccinated population of at least half a million people living in fairly close contact to continue to exist.

a notable bacteriologist indicated that the emergence of some new disease had always been a possibility which had worried the more far-thinking epidemiologists.

By 1991, for instance, epidemiologist surverys in populations had revealed that high cholesterol was NOT associated with heart disease or premature death in women. Rather, the higher the cholesterol in women, the longer they lived, a finding that was so consistent across populations and surveys that it prompted an editorial in the American Heart Associations journal, Circulation: "We are coming to realize," the three authors, led by UC San Francisco epidemiologist Stephen Hulley, wrote, "the the results of cardiovascular research in men, which represents the great majority of the effort thus far, may not apply to women.

Achille Adrien Proust, was a famous doctor and epidemiologist, responsible for studying and attempting to remedy the causes and movements of cholera through Europe and Asia

let’s begin with the word “vector.” It comes from the Latin root vehere, “to carry,” which also gives us words like “vehicle” and “conveyor belt.” To an epidemiologist, a vector is the carrier of a pathogen, like the mosquito that conveys malaria to your bloodstream. To a mathematician, a vector (at least in its simplest form) is a step that carries you from one place to another.

Bots are at best narrow AI, nothing that would make a cleric remotely nervous. But they would scare the hell out of epidemiologists who understand that parasites don’t need to be smart to be dangerous.

Psychiatric epidemiologists are also finding that people born in winter months—during times of heightened flu and viral infections—may be more likely to develop serious mental illness (though people with more severe forms of the illnesses are more likely to be born in the summer months, so who knows).

Doctors generally consider smallpox to be the worst human disease. It is thought to have killed more people than any other infectious pathogen, including the Black Death of the Middle Ages. Epidemiologists think that smallpox killed roughly one billion people during its last hundred years of activity onearth.

It comes and it goes. But epidemiologists have recognized that, with measles virus, as with other pathogens, there’s a critical minimum size of the host population, below which it can’t persist indefinitely as an endemic, circulating infection. This is known as the critical community size (CCS), an important parameter in disease dynamics.

It was a Nazi epidemiologist who first established the link between smoking and lung cancer, establishing a government agency to combat tobacco consumption in June 1939.

As the epidemiologist Ian Alcock put it, if you want to be happy, there is a simple, scientific formula: “get married, get a job and live near the coast.

American pollsters have officially joined economists and epidemiologists in the category of professions that will tell you tomorrow why the things they predicted yesterday didn't happen today.

In 2010, the psychiatrist Thomas Insel, then director of NIMH, called for the research community to redefine schizophrenia as “a collection of neurodevelopmental disorders,” not one single disease. The end of schizophrenia as a monolithic diagnosis could mean the beginning of the end of the stigma surrounding the condition. What if schizophrenia wasn’t a disease at all, but a symptom? “The metaphor I use is that years ago, clinicians used to look at ‘fever’ as one disease,” said John McGrath, an epidemiologist with Australia’s Queensland Centre for Mental Health Research and one of the world’s authorities on quantifying populations of mentally ill people. “Then they split it into different types of fevers. And then they realized it’s just a nonspecific reaction to various illnesses. Psychosis is just what the brain does when it’s not working very well.

The metaphor I use is that years ago, clinicians used to look at ‘fever’ as one disease,” said John McGrath, an epidemiologist with Australia’s Queensland Centre for Mental Health Research and one of the world’s authorities on quantifying populations of mentally ill people. “Then they split it into different types of fevers. And then they realized it’s just a nonspecific reaction to various illnesses. Psychosis is just what the brain does when it’s not working very well.

[D}o not ask me to choose classical philology over industrial catering when they both seem such powerful fun; I want to be a forensic epidemiologist and a floorwalker in men's hosiery-look at how those size l0-to-13's drape over their tiny 2-shaped hangers...

The best indicator of personal risk is whether you have fallen much before. Accident proneness is a slightly controversial area among stair-injury epidemiologists, but it does seem to be a reality. About four persons in ten injured in a stair fall have been injured in a stair fall before.

And there’s one other matter I must raise. The epidemic of domestic sexual violence that lacerates the soul of South Africa is mirrored in the pattern of grotesque raping in areas of outright conflict from Darfur to the Democratic Republic of the Congo, and in areas of contested electoral turbulence from Kenya to Zimbabwe. Inevitably, a certain percentage of the rapes transmits the AIDS virus. We don’t know how high that percentage is. We know only that women are subjected to the most dreadful double jeopardy. The point must also be made that there’s no such thing as the enjoyment of good health for women who live in constant fear of rape. Countless strong women survive the sexual assaults that occur in the millions every year, but every rape leaves a scar; no one ever fully heals. This business of discrimination against and oppression of women is the world’s most poisonous curse. Nowhere is it felt with greater catastrophic force than in the AIDS pandemic. This audience knows the statistics full well: you’ve chronicled them, you’ve measured them, the epidemiologists amongst you have disaggregated them. What has to happen, with one unified voice, is that the scientific community tells the political community that it must understand one incontrovertible fact of health: bringing an end to sexual violence is a vital component in bringing an end to AIDS. The brave groups of women who dare to speak up on the ground, in country after country, should not have to wage this fight in despairing and lonely isolation. They should hear the voices of scientific thunder. You understand the connections between violence against women and vulnerability to the virus. No one can challenge your understanding. Use it, I beg you, use it.

A question has to be asked: If a Level 4 emerging virus spread to a million people in North America, or in any continent, would hospitals be able to handle the patients and give them care? Would epidemiologists be able to trace and break the chains of transmission if a million people were infected?

People who possess less occupational freedom have higher cortisol levels (a higher stress response). The social epidemiologist Michael Marmot has documented the relationship between individuals’ health and the extent to which they possess control over their job responsibilities.2 More freedom equals better health.

But before we can even address the mistreatment that occurs once a woman is interacting with the health-care system, we have to address the fact that some women never get that far. We won’t get a true picture of the incidence of endometriosis until we specifically look for it in marginalized communities. And before we can do that, we have to address the disparity in access. Social epidemiologist Jhumka Gupta has said that endometriosis is a social justice issue. In her speech at the Worldwide Endo March in Washington, DC, on March 19, 2016, she said that endometriosis is a social pathology, which she defined as “gender inequality, social injustice, and attitudes of society that keep women and girls from fully reaching their potential.

Marijuana causes paranoia and psychosis. That fact is now beyond dispute. Even scientists who aren’t sure if marijuana can cause permanent psychosis agree that it can cause temporary paranoia and psychotic episodes. The risk is so obvious that marijuana dispensaries advertise certain strains as less likely to cause paranoia. Paranoia and psychosis cause violence. Overwhelming evidence links psychotic disorders and violence, especially murder. Studies have confirmed the connection, across cultures, nations, races, and eras. The definitive analysis was published in PLOS Medicine in 2009. Led by Seena Fazel, a psychiatrist and epidemiologist at Oxford University, researchers examined twenty earlier studies on people with schizophrenia and other forms of psychosis. They found that people with psychosis were 5 times as likely to commit violent crimes as

The idea of latency is worth thinking about. Biology rewards patience. Mycobacterium tuberculosis understands this. It estabishes its toeholds and then it becomes dormant. And in that restraint it demonstrates the full extend of its power. It is not necessary that every thirst be slaked. In not acting upon a desire, that desire is diminished neither in intensity nor in merit. Priests fall in love with parishioners and display it all the time--we read about this in the newspapers. What we do not read about are the times, over and over again, when those words are not said, those kisses are not offered, or solicited. But such unexpressed love does not amount to nothing. When we love it is because we have seen especially clearly. And a clear view of human beauty is a treasure that endures for as long as the possessor of such insight breathes. And endurance is the final measure of importance: of ideas and of organisms. Love lies latent sometimes, as tuberculosis does--but, as any epidemiologist will tell you, latent is nothing like gone.

When Franklin D. Roosevelt signed the Social Security Act in 1935, old age was defined as sixty-five years, yet estimated life expectancy in the United States at the time was sixty-one years for males and sixty-four years for females.62 A senior citizen today, however, can expect to live eighteen to twenty years longer. The downside is that he or she also should expect to die more slowly. The two most common causes of death in 1935 America were respiratory diseases (pneumonia and influenza) and infectious diarrhea, both of which kill rapidly. In contrast, the two most common causes of death in 2007 America were heart disease and cancer (each accounted for about 25 percent of total deaths). Some heart attack victims die within minutes or hours, but most elderly people with heart disease survive for years while coping with complications such as high blood pressure, congestive heart failure, general weakness, and peripheral vascular disease. Many cancer patients also remain alive for several years following their diagnosis because of chemo-therapy, radiation, surgery, and other treatments. In addition, many of the other leading causes of death today are chronic illnesses such as asthma, Alzheimer’s, type 2 diabetes, and kidney disease, and there has been an upsurge in the occurrence of nonfatal but chronic illnesses such as osteoarthritis, gout, dementia, and hearing loss.63 Altogether, the growing prevalence of chronic illness among middle-aged and elderly individuals is contributing to a health-care crisis because the children born during the post–World War II baby boom are now entering old age, and an unprecedented percentage of them are suffering from lingering, disabling, and costly diseases. The term epidemiologists coined for this phenomenon is the “extension of morbidity.

Epidemiologists-scientists who study the spread of disease-use a special number to describe how contagious a virus is. It's called the basic reproduction number, or R0 for short. It's complicated to calculate but simple to understand-it counts how many people one sick person is expected to infect over the course of his or her illness. If I'm sick with a cold and I make two other people sick, the R0 of my virus is 2. Colds and seasonal flus typically have R0 values of around 1.5 to 2. The 1918 flu pandemic R0 was estimated to be 2 to 3, while diseases like polio and small pox have R0 values of around 5 to 7.

Yes, our social and economic circumstances shape decisions we make about all sorts of things in life, including sex. Sometimes they rob us of the power to make any decisions at all. But of all human activity, sex is among the least likely to fit neatly into the blueprint of rational decision making favoured by economists. To quote my friend Claire in Istanbul, sex is about 'conquest, fantasy, projection, infatuation, mood, anger, vanity, love, pissing off your parents, the risk of getting caught, the pleasure of cuddling afterwards, the thrill of having a secret, feeling desirable, feeling like a man, feeling like a woman, bragging to your mates the next day, getting to see what someone looks like naked and a million-and-one-other-things.' When sex isn't fun, it is often lucrative, or part of a bargain which gives you access to something you want or need. If HIV is spread by 'poverty and gender equality', how come countries that have plenty of both, such as Bangladesh, have virtually no HIV? How come South Africa and Botswana, which have the highest female literacy and per capita incomes in Africa, are awash with HIV, while countries that score low on both - such as Guinea, Somalia, Mali, and Sierra Leone - have epidemics that are negligible by comparison? How come in country after country across Africa itself, from Cameroon to Uganda to Zimbabwe and in a dozen other countries as well, HIV is lowest in the poorest households, and highest in the richest households? And how is it that in many countries, more educated women are more likely to be infested with HIV than women with no schooling? For all its cultural and political overtones, HIV is an infectious disease. Forgive me for thinking like an epidemiologist, but it seems to me that if we want to explain why there is more of it in one place than another, we should go back and take a look at the way it is spread.

The world’s last great pandemic was the Spanish flu outbreak in 1918 that killed a hundred million people—about 5 percent of the world’s population. If a pandemic like that were to happen again, it would spread faster and might be impossible to contain. According to the Bill & Melinda Gates Foundation, in such a pandemic “the death toll could reach 360 million”—even with the full deployment of vaccines and powerful modern drugs. The Gates Foundation estimated that the pandemic would also devastate the world financially, precipitating a three-trillion-dollar economic collapse. This is not scaremongering: Most epidemiologists believe such a pandemic will eventually happen.

In fact, the entire range of human variation for some genetic traits can be found on the African continent.77 A person from the Congo, a person from South Africa, and a person from Ethiopia are more genetically different from each other than from a person from France.78 This seems astonishing because we are so used to focusing on a tiny set of physical features, especially skin color, to assign people to racial categories. It turns out that the genes contributing to these phenotypic differences represent a minute and relatively insignificant fraction of our genotypes and do not reflect the total picture of genetic variation among groups.79 What’s more, these phenotypic differences do not even fall neatly into the categories known as races. Rather, the physical features are “discordant” among groups—they are assorted randomly and do not come assembled in racial packages. “Sub-Saharan Africa is home to both the tallest (Maasai) and the shortest (pygmies) people, and dark skin is found in all equatorial populations, not just in the ‘Black race’ as defined in the United States,” writes Richard S. Cooper, a physician epidemiologist at Loyola University.80 And most genetic variation is found within any human population.81

If you can’t make a good prediction, it is very often harmful to pretend that you can. I suspect that epidemiologists, and others in the medical community, understand this because of their adherence to the Hippocratic oath. Primum non nocere: First, do no harm. Much of the most thoughtful work on the use and abuse of statistical models and the proper role of prediction comes from people in the medical profession.88 That is not to say there is nothing on the line when an economist makes a prediction, or a seismologist does. But because of medicine’s intimate connection with life and death, doctors tend to be appropriately cautious. In their field, stupid models kill people. It has a sobering effect. There is something more to be said, however, about Chip Macal’s idea of “modeling for insights.” The philosophy of this book is that prediction is as much a means as an end. Prediction serves a very central role in hypothesis testing, for instance, and therefore in all of science.89 As the statistician George E. P. Box wrote, “All models are wrong, but some models are useful.”90 What he meant by that is that all models are simplifications of the universe, as they must necessarily be. As another mathematician said, “The best model of a cat is a cat.”91 Everything else is leaving out some sort of detail. How pertinent that detail might be will depend on exactly what problem we’re trying to solve and on how precise an answer we require.

A highly regarded infectious-disease epidemiologist named Donald S. Burke, presently dean of the Graduate School of Public Health at the University of Pittsburgh, gave a lecture (later published) back in 1997 in which he listed the criteria that might implicate certain kinds of viruses as likeliest candidates to cause a new pandemic. “The first criterion is the most obvious: recent pandemics in human history,” Burke told his audience. That would point to the orthomyxoviruses (including the influenzas) and the retroviruses (including the HIVs), among others. “The second criterion is proven ability to cause major epidemics in non-human animal populations.” This would again spotlight the orthomyxoviruses, but also the family of paramyxoviruses, such as Hendra and Nipah, and the coronaviruses, such as that virus later known as SARS-CoV. Burke’s third criterion was “intrinsic evolvability,” meaning readiness to mutate and to recombine (or reassort), which “confers on a virus the potential to emerge into and to cause pandemics in human populations.” As examples he returned to retroviruses, orthomyxoviruses, and coronaviruses. “Some of these viruses,” he warned, citing coronaviruses in particular, “should be considered as serious threats to human health. These are viruses with high evolvability and proven ability to cause epidemics in animal populations.” It’s interesting in retrospect to note that he had augured the SARS epidemic six years before it occurred. Much more recently, Burke told me: “I made a lucky guess.” He laughed a self-deprecating hoot and then added that “prediction is too strong a word” for what he had been doing.

The Company We Keep So now we have seen that our cells are in relationship with our thoughts, feelings, and each other. How do they factor into our relationships with others? Listening and communicating clearly play an important part in healthy relationships. Can relationships play an essential role in our own health? More than fifty years ago there was a seminal finding when the social and health habits of more than 4,500 men and women were followed for a period of ten years. This epidemiological study led researchers to a groundbreaking discovery: people who had few or no social contacts died earlier than those who lived richer social lives. Social connections, we learned, had a profound influence on physical health.9 Further evidence for this fascinating finding came from the town of Roseto, Pennsylvania. Epidemiologists were interested in Roseto because of its extremely low rate of coronary artery disease and death caused by heart disease compared to the rest of the United States. What were the town’s residents doing differently that protected them from the number one killer in the United States? On close examination, it seemed to defy common sense: health nuts, these townspeople were not. They didn’t get much exercise, many were overweight, they smoked, and they relished high-fat diets. They had all the risk factors for heart disease. Their health secret, effective despite questionable lifestyle choices, turned out to be strong communal, cultural, and familial ties. A few years later, as the younger generation started leaving town, they faced a rude awakening. Even when they had improved their health behaviors—stopped smoking, started exercising, changed their diets—their rate of heart disease rose dramatically. Why? Because they had lost the extraordinarily close connection they enjoyed with neighbors and family.10 From studies such as these, we learn that social isolation is almost as great a precursor of heart disease as elevated cholesterol or smoking. People connection is as important as cellular connections. Since the initial large population studies, scientists in the field of psychoneuroimmunology have demonstrated that having a support system helps in recovery from illness, prevention of viral infections, and maintaining healthier hearts.11 For example, in the 1990s researchers began laboratory studies with healthy volunteers to uncover biological links to social and psychological behavior. Infected experimentally with cold viruses, volunteers were kept in isolation and monitored for symptoms and evidence of infection. All showed immunological evidence of a viral infection, yet only some developed symptoms of a cold. Guess which ones got sick: those who reported the most stress and the fewest social interactions in their “real life” outside the lab setting.12 We Share the Single Cell’s Fate Community is part of our healing network, all the way down to the level of our cells. A single cell left alone in a petri dish will not survive. In fact, cells actually program themselves to die if they are isolated! Neurons in the developing brain that fail to connect to other cells also program themselves to die—more evidence of the life-saving need for connection; no cell thrives alone. What we see in the microcosm is reflected in the larger organism: just as our cells need to stay connected to stay alive, we, too, need regular contact with family, friends, and community. Personal relationships nourish our cells,

A 2009 study in the American Journal of Epidemiology called “Life-Course Socioeconomic Position and Incidence of Coronary Heart Disease” found that the longer a person remains in poverty, the more likely he or she is to develop heart disease.133 People who were economically disadvantaged throughout life were more likely to smoke, be obese, and have poor diets and the like. In an earlier study by epidemiologist Dr. Ralph R. Frerichs, focusing specifically on the socioeconomic divide in the city of Los Angeles, CA, found that the death rate from heart disease was 40 percent higher for poor men over all than for wealthier ones.134

In 1980, Stanford University internist and epidemiologist James Fries recognized that modern medicine was not extending the human lifespan, and yet survival curves were changing. More people were living vitally until eighty-five or ninety, and then dying quickly, like the wonderful one-hoss shay in Oliver Wendell Holmes’s poem, which ran perfectly for a hundred years and then fell apart all at once.2 Fries called this phenomenon “compression of morbidity.”3 In 1900, because most deaths were premature, the human survival “curve” was a diagonal line; now it is more of a rectangle—especially if you have no risk factors (Figure 7.1). In 2040 there will be ten times as many eighty-five-year-olds as there were in 1990. This is not because the normal human lifespan is any longer than it was, but because fewer people will die before eighty. After eighty the lifespan will reflect little increase. Medical advances like antibiotics, new cancer treatments, and kidney transplants all serve to decrease premature death. But they do not alter the fact that the bodies of most of us, like the one-hoss shay, have not evolved to live past one hundred.

While Europe experimented with legalization and regulation after WWII, the practice here was more stigmatized than perhaps it had ever been. It was also dangerous. John J. Potterat, one of the nation’s leading epidemiologists, noted in 2004 that the leading cause of death for prostitutes was homicide.

Increasingly, progressive voices in the media are shining a spotlight on the need for new businesses that serve both entrepreneurs and local communities. Yes! Magazine is a leading chronicler of independence from the global economy, with features such as “31 Ways to Jump Start the Local Economy,” “Wendell Berry’s 17 Rules for a Sustainable Economy,” “A Resilient Community,” “Small Banks, Radical Vision,” and other numerous stories on how consumers and householders can become producers of energy and food. Epidemiologist Richard Wilkinson, in his bestseller The Impact of Inequality: How to Make Sick Societies Healthier, offered both a survey of our nation’s growing economic inequalities and an eloquent argument that such inequalities will lead to increased anxiety, fear, isolation, health failures, and chronic insecurity.

A common feature of epidemiological data is that they are almost certain to be biased, of doubtful quality, or incomplete (and sometimes all three),” explained the epidemiologist John Bailar

The WHO study was immediately blasted by the authoritative British medical journal the Lancet, and by many renowned epidemiologists—some of whom charged that the United States had interfered with the study by preventing WHO researchers from surveying the most afflicted areas in Iraq. Hans

rumbling over the supposed destructive power of the H5N1 strain of avian flu and the predicted crisis had still not manifested itself. Until three days ago, Greg would have said with confidence that it was simply a case of Chicken Little and a whole bunch of epidemiologists and public health workers worried over a sky that remained perfectly intact.

By April 2014, when the epidemic was officially over, the sentinel sites had reported 8,750 patients seeking care. The health department’s epidemiologist, Dr. Henri-Pierre Mallet, calculated that 32,000 people, or about 12 percent of the country’s population, had Zika symptoms severe enough to warrant a visit to a doctor. He

Ferguson, testified about coronavirus to a committee of the British Parliament. Ferguson calls himself an epidemiologist, though he is not a physician and his doctorate is in theoretical physics.

The English mystery writer Agatha Christie often used a fictional village, St Mary Mead, as a microcosm of all mankind. Framingham is the American epidemiologist's English village. Under sharp, statistical lenses, its captive cohort has lived, reproduced, aged, and died, affording a rare glimpse of the natural history of life, disease, and death.

From the pathogen’s perspective, humans are what epidemiologists call an “accidental host” of many zoonoses, meaning that the pathogen usually fails to complete its life cycle in man alone. In other words, it can “afford” (evolutionarily speaking) to kill humans at staggering rates, because its natural reservoir is elsewhere.

What are we to do at any given moment, when we cannot say which of our current claims will be sustained and which will be rejected? This is one of the central questions that I have raised. Because we cannot know which of current claims will be sustained, the best we can do is to consider the weight of scientific evidence, the fulcrum of scientific opinion, and the trajectory of scientific knowledge. This is why consensus matters: If scientists are still debating a matter, then we may well be wise to “wait and see,” if conditions permit.26 If the available empirical evidence is thin, we may want to do more research. But the uncertainly of future scientific knowledge should not be used as an excuse for delay. As the epidemiologist Sir Austin Bradford Hill famously argued, “All scientific work is incomplete—whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us a freedom to ignore the knowledge we already have, or to postpone the action that it appears to demand at a given time.”27 At any given moment, it makes sense to make decisions on the information we have, and be prepared to alter our plans if future evidence warrants.

Epidemiologists generally agree that smallpox is the cruelest disease ever to afflict the human race.

The lowest estimate of the pandemic’s worldwide death toll is twenty-one million, in a world with a population less than one-third today’s. That estimate comes from a contemporary study of the disease and newspapers have often cited it since, but it is almost certainly wrong. Epidemiologists today estimate that influenza likely caused at least fifty million deaths worldwide, and possibly as many as one hundred million.

The army had data on 120 training camps—99 imposed quarantine and 21 did not. But there was no difference in mortality or morbidity between camps implementing quarantine and those that didn’t; there was not even any difference in how long it took influenza to pass through the camp. The story, however, isn’t quite that simple: the epidemiologist who performed the study looked not just at numbers but at actual practice, and found that out of the 99 camps that imposed quarantine, only a half dozen or so rigidly enforced it. Those few did benefit. But if the overwhelming majority of army bases in wartime could not enforce a quarantine rigidly enough to benefit, a civilian community in peacetime certainly could not.

and in particular to Durban, the major port of Natal Province. Though South Africa didn’t record a ‘herald’ wave of Spanish flu, as such, an epidemiologist named Dennis Shanks has found reports buried in the literature of cases of a mild, flu-like illness that arrived on ships in Durban

[From Spillover- Zika, Ebola, and Beyond, 2016] - Lina Moses, Epidemiologist, Sierra Leone One of the tragedies of Ebola is that it spreads through LOVE and through people taking care of who they care about. Once people start to understand how its transmitted, they learn that they can't take care of the people that they love, and that's how the disease slows down and stops.

What stands out now is the speed and efficiency with which, in retrospect, the world acted. The virus didn’t get opportunities to establish itself in countries outside China that delayed taking action to contain it, as happened with Covid-19. As the virus arrived, there was no disputing the need for containment or talk of relying on herd immunity. Because of this swift action, SARS never circulated widely enough to be called a pandemic. Maybe the virus’s high death rate scared everyone into line. Maybe its inability to spread before symptoms started, and absence of many mild cases, just made it easier and less disruptive to follow the epidemiologists’ advice. And there was more public trust in experts 17 years ago.

After the debacle of Chinese obfuscation at the start of the epidemic, national governments cooperated fully with IHR 1969. The world’s most equipped laboratories and foremost epidemiologists, working in real-time collaboration via the internet, succeeded, with unprecedented speed, in identifying the SARS corona-virus in just two weeks.

This finding was met with “surprise and chagrin,” Manning Feinleib, a National Heart, Lung, and Blood Institute (NHLBI) epidemiologist, told Science.

A common feature of epidemiological data is that they are almost certain to be biased, of doubtful quality, or incomplete (and sometimes all three),” explained the epidemiologist John Bailar in The New England Journal of Medicine in 1980. “Problems do not disappear even if one has flawless data, since the statistical associations in almost any nontrivial set of observations are subject to many interpretations. This ambiguity exists because of the difficulty of sorting out causes, effects, concomitant variables, and random fluctuations when the causes are multiple or diffuse, the exposure levels low, irregular, or hard to measure, and the relevant biologic mechanisms poorly understood. Even when the data are generally accepted as accurate, there is much room for individual judgment, and the considered conclusions of the investigators on these matters determine what they will label ‘cause’…

That very month, at the St. Louis Children’s Hospital, two young patients experienced strange and alarming symptoms. As they underwent dialysis, a lifesaving procedure to filter blood for those whose kidneys don’t work properly, the patients’ eyes started swelling, their heart rates escalated, and their blood pressure dropped. These were signs of a life-threatening allergic reaction. Dr. Anne Beck, the director of the nephrology unit, directed her staff to wash out the tubing with extra fluid before hooking the children back up to the dialysis machines. For the next two months, everything seemed fine. But in January 2008, the symptoms struck again. Beck contacted an epidemiologist specializing in children’s infectious diseases who immediately assembled a command center where a team worked around the clock to uncover the cause of the strange reactions. But as more children succumbed and the staff grew frightened, the epidemiologist notified the Centers for Disease Control and Prevention. The CDC immediately contacted dialysis centers in other states and learned of similar reactions elsewhere. As the CDC and the FDA began a joint investigation, their efforts pointed to a common denominator: all the sickened patients had been given heparin made by the brand-name company Baxter, the nation’s biggest heparin supplier. It was a drug that patients took intravenously during dialysis to ensure that they didn’t suffer blood clots. Within weeks, Baxter—at the FDA’s urging—began a sweeping series of recalls, until finally the allergic reactions stopped. Yet

FDA used the same playbook in 2002 to isolate, silence, and drive from government service its star epidemiologist, Dr. Bart Classen, when his massive epidemiologic studies, the largest ever performed, linked Hib vaccines to the juvenile diabetes epidemic. FDA ordered Dr. Classen to refrain from publishing the government-funded studies, forbade him from talking publicly about the alarming outbreak, and eventually forced him out of government service.

But venereal diseases, hepatitis, and diarrhea continued to ravage the French. In addition, recent evidence demonstrates that trench fever, a debilitating but rarely fatal disease borne by the same body lice that transmit typhus, also afflicted Napoleon’s troops. Thus multiple comorbidities compounded the misery of the retreating troops and compromised their resistance. Furthermore, typhus is well known to be especially lethal when it runs its course in populations that are undernourished. The nineteenth-century epidemiologist Rudolf Virchow reminds us that the disease fully earned yet another of its many nicknames—“famine fever.” The classic case is Ireland, where famine and typhus accompanied one another in successive crises between the end of the eighteenth century and the potato famine of 1846–1848.

For the first time, we could calculate the six-year total for the entire state. There were two ways to do it. Simply add up all the pills the pharmacies bought. Or add up each distributor’s deliveries to every county. Both methods produced the same number—780 million. That was just hydrocodone and oxycodone—in a state with fewer than 1.8 million people. During those same years, 1,728 West Virginians fatally overdosed on those two painkillers, according to data sent to me by epidemiologists at the state Health Statistics Center.

The risks of catching an infection as estimated by epidemiologists will not necessarily correspond with parents’ sense of the risks they think their children face.

For all of these reasons, a shocking amount of expert research turns out to be wrong. John Ioannidis, a Greek doctor and epidemiologist, examined forty-nine studies published in three prominent medical journals.8 Each study had been cited in the medical literature at least a thousand times. Yet roughly one-third of the research was subsequently refuted by later work. (For example, some of the studies he examined promoted estrogen replacement therapy.) Dr. Ioannidis estimates that roughly half of the scientific papers published will eventually turn out to be wrong.9 His research was published in the Journal of the American Medical Association, one of the journals in which the articles he studied had appeared. This does create a certain mind-bending irony: If Dr. Ioannidis’s research is correct, then there is a good chance that his research is wrong. Regression

I’m not really an epidemiologist, if that’s what you mean. It’s outside my area. I build mathematical models based on biological systems.

Many experts believe that a cholera-like pandemic looms. In a survey by the epidemiologist Larry Brilliant, 90 percent of epidemiologists said that a pandemic that will sicken 1 billion, kill up to 165 million, and trigger a global recession that could cost up to $3 trillion would occur sometime in the next two generations.

In 2009, an American soldier named Bowe Bergdahl slipped through a gap in the concertina wire at his combat outpost in southern Afghanistan and walked off into the night. He was quickly captured by a Taliban patrol, and his absence triggered a massive search by the US military that put thousands of his fellow soldiers at risk. The level of betrayal felt by soldiers was so extreme that many called for Bergdahl to be tried for treason when he was repatriated five years later. Technically his crime was not treason, so the US military charged him with desertion of his post—a violation that still carries a maximum penalty of death. The collective outrage at Sergeant Bergdahl was based on very limited knowledge but provides a perfect example of the kind of tribal ethos that every group—or country—deploys in order to remain unified and committed to itself. If anything, though, the outrage in the United States may not be broad enough. Bergdahl put a huge number of people at risk and may have caused the deaths of up to six soldiers. But in purely objective terms, he caused his country far less harm than the financial collapse of 2008, when bankers gambled trillions of dollars of taxpayer money on blatantly fraudulent mortgages. These crimes were committed while hundreds of thousands of Americans were fighting and dying in wars overseas. Almost 9 million people lost their jobs during the financial crisis, 5 million families lost their homes, and the unemployment rate doubled to around 10 percent. For nearly a century, the national suicide rate has almost exactly mirrored the unemployment rate, and after the financial collapse, America’s suicide rate increased by nearly 5 percent. In an article published in 2012 in The Lancet, epidemiologists who study suicide estimated that the recession cost almost 5,000 additional American lives during the first two years—disproportionately among middle-aged white men. That is close to the nation’s losses in the Iraq and Afghan wars combined. If Sergeant Bergdahl betrayed his country—and that’s not a hard case to make—surely the bankers and traders who caused the financial collapse did as well. And yet they didn’t provoke nearly the kind of outcry that Bergdahl did. Not a single high-level CEO has even been charged in connection with the financial collapse, much less been convicted and sent to prison, and most of them went on to receive huge year-end bonuses. Joseph Cassano of AIG Financial Products—known as “Mr. Credit-Default Swap”—led a unit that required a $99 billion bailout while simultaneously distributing $1.5 billion in year-end bonuses to his employees—including $34 million to himself. Robert Rubin of Citibank received a $10 million bonus in 2008 while serving on the board of directors of a company that required $63 billion in federal funds to keep from failing. Lower down the pay scale, more than 5,000 Wall Street traders received bonuses of $1 million or more despite working for nine of the financial firms that received the most bailout money from the US goverment.

What if we looked at the law as a piece of software, the operating system of the United States of America. After all, laws play the same role as software in providing instructions for a given system - if this, then that, and so on. If a team of software engineers was asked to analyze the entire body of federal law, they would see tens of thousand of pages of poorly documented code, with a multitude of complex, spaghetti-like interdependencies between the individual components. Could the principles of good software design be used to improve the way we write financial regulations? Li, William, Pablo Azar, David Larochelle, Phil Hill, and Andrew W. Lo. 2015. 'Law Is Code: A Software Engineering Approach to Analyzing the United States Code.' Journal of Business and Technology Law 10: 297. A useful feature of network graphs if the ability to model contagion. Like an epidemiologist studying the spread of a contagious disease from its point of origin, we should identify the potential linkages through which a financial crisis may travel. Billio, Monica, Mila Getmansky, Andrew W. Lo, and Loriana Pelizzon, 2012. 'Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors.' Journal of Financial Economics, 104: 535-559. This approach can also be used to measure the network of banks, insurance companies, and sovereign nations. The idea is to see how macroeconomic problems facing countries might get transmitted to the financial system and vice versa. Billio, Monica, Mila Getmansky, Dale Gray, Andrew W. Lo, Robert C. Merton, and Loriana Pelizzon. 2016. 'Granger-Causality Networks of Sovereign Risk.' Working Paper, MIT Laboratory for Financial Engineering.

asked myself, Why didn’t these epidemiologists figure it out? They didn’t figure it out because they didn’t have tools that were focused on the problem. They had tools to understand the movement of infectious disease without the purpose of trying to stop it.

An Israeli study showed that natural immunity is at least thirteen times more powerful than vaccination at preventing infection.24 The CDC countered with a study of its own looking at hospitalized patients that concluded that vaccination was five times more powerful than natural immunity. This study was admittedly highly flawed: there was a full page in the discussion section of the “limitations” of the study. Dr. Martin Kuhldorf, an epidemiologist from Harvard, offered an analysis of the two studies that is a must-read for anyone who doubts the deception of the CDC.

I also couldn’t help noticing how often news reports about some modeler’s latest findings would leave out important nuances and caveats. In March 2020, Neil Ferguson, a highly respected epidemiologist at Imperial College, predicted that there could be more than 500,000 COVID deaths in the U.K. and more than 2 million in the U.S. over the course of the pandemic. That caused quite a stir in the press, but few reporters mentioned a key point that Ferguson had been very clear about: The scenario of his that made all the headlines assumed that people wouldn’t change their behavior—that no one would wear masks or shelter in place, for instance—but of course that wouldn’t be the case in reality. He wanted to show how high the stakes were and demonstrate the value of masks and other interventions, not drive everyone into a panic.

No in-person worship anywhere in New York State. Epidemiologists and public health officials were now somehow on many institutions' Boards.

There is a kinship, between the climate scientists and the epidemiologists and the scholars of authoritarian states. The people who research worst-case scenarios are stuck breaking bad news while protectors of profit margins and purveyors of institutionalist mythologies market false assurances. The later remain successful not in spite of evidence, but to spite the evidence.

For all of these reasons, a shocking amount of expert research turns out to be wrong. John Ioannidis, a Greek doctor and epidemiologist, examined forty-nine studies published in three prominent medical journals.8 Each study had been cited in the medical literature at least a thousand times. Yet roughly one-third of the research was subsequently refuted by later work. (For example, some of the studies he examined promoted estrogen replacement therapy.) Dr. Ioannidis estimates that roughly half of the scientific papers published will eventually turn out to be wrong.9 His research was published in the Journal of the American Medical Association, one of the journals in which the articles he studied had appeared. This does create a certain mind-bending irony: If Dr. Ioannidis’s research is correct, then there is a good chance that his research is wrong.

Not surprisingly, we can’t always have the Ferrari. The research equivalent of a Toyota is a cross-sectional data set, which is a collection of data gathered at a single point in time. For example, if epidemiologists are searching for the cause of a new disease (or an outbreak of an old one), they may gather data from all those afflicted in hopes of finding a pattern that leads to the source. What have they eaten? Where have they traveled? What else do they have in common? Researchers may also gather data from individuals who are not afflicted by the disease to highlight contrasts between the two groups.

if we use electrodes to study its oddly intelligent brain, we can replicate a pack of cloned genius dogs to do our bidding.” Everyone in the room smiled along with their leader. They followed his gaze to the TV monitor, now showing a photo of Wolfe with his arm around a young woman, and talking to a smiling black couple, while the dog sat at their feet. If any of those people happened to witness Jake Wolfe’s murder, they’d be killed too. He turned to Gisela and demanded, “Is the laboratory completion on schedule?” “Yes, it’s ready now, awaiting the scientists.” She tapped the remote and played a video. Attached to the mansion, in what appeared to be a five-car garage, a secret laboratory had been prepared for two epidemiologists Belken intended to kidnap. They would be forced to mutate the 1918 influenza pathogen into an even deadlier strain to be used as an aerosolized microbe weapon sprayed from ships or planes onto targeted cities. Their other task, equally important, would be to develop a new flu shot to immunize against the threat. There were murmurs of approval around the table. Belken nodded, hearing their flattering remarks. “Any report on our team kidnapping the targets?

In 1977 a psychologist and epidemiologist named Ernest M. Gruenberg at Johns Hopkins University called the rise of these immiserating diseases the “failures of success”: the more the health care system enabled people to survive to old age, the more they developed chronic diseases that sucked the quality out of life. Gruenberg argued that we should view health care as an epidemiological force, like a pathogen, which reduces rates of death but increases rates of sickness and disability. The system’s priorities were twisted, Gruenberg believed, because it was preoccupied with extending life, not health. So research dollars went to picking off the acute causes of death, which tend to work pretty quickly, rather than to delaying or preventing chronic diseases that drag on and on, bringing whole families into their circle of pain. To Gruenberg, this went against the oath to do no harm. If cancer patients typically die of pneumonia, say, and we develop treatments for pneumonia, all we’ve done for their cancer is ensure that they spend more years dying of it. In place of a day on their deathbed, we’ve given them a month and called it progress. “Instead of enhancing the people’s health this kind of deathly thinking has been increasing the people’s sickness and disability,” he wrote. “Now that we recognize that our life-saving technology of the past four decades has outstripped our health-preserving technology and that the net effect has been to worsen the people’s health, we must begin the search for preventable causes of the chronic illnesses which we have been extending.” Yes, medicine was helping us live longer, Gruenberg said, but the extra years were added at the end, when we were too weak or sick to enjoy them.

In the fullness of time, the 2020 lockdown of the U.S. economy will be viewed as the greatest policy blunder ever. Lost wealth and income will be measured in trillions of dollars. Any gain in lives saved or damage avoided was inapposite, since equally effective policy choices were available but untried. There’s no evidence that epidemiologists considered lives lost to drugs, alcohol, suicide, and despair when they pursued policies that pushed 60 million Americans out of jobs.

Within a few years, the study of chaos gave a strong impetus to theoretical biology, bringing biologists and physicists into scholarly partnerships that were inconceivable a few years before. Ecologists and epidemiologists dug out old data that earlier scientists had discarded as too unwieldy to handle. Deterministic chaos was found in records of New York City measles epidemics and in two hundred years of fluctuations of the Canadian lynx population, as recorded by the trappers of the Hudson’s Bay Company. Molecular biologists began to see proteins as systems in motion. Physiologists looked at organs not as static structures but as complexes of oscillations, some regular and some irregular.

His days as a globe-trotting epidemiologist might be over—Dr. Levinson had made that perfectly clear—but his efforts to save Lantos, and now Nika, had reminded him of the satisfaction to be had from healing just one person. What was that old Hebrew proverb he’d once heard Dr. Levinson herself say—“If you save one life, it’s the same as saving the whole world.” Right now the only life he wanted to save, even more than his own, was Nika’s.

The main reason for my presence was to impact policy, not just try to help the president and the country accurately understand the current status of the pandemic. After all, I was a health policy expert, not an epidemiologist or virologist. My expertise, my role, was to devise a set of policies that minimized the harms of the pandemic—including the harms of the policies themselves. Americans would have been frightened if they had realized that there was no one on the Task Force with any medical background who understood, or was even concerned with, these impacts. To delegate policy to people solely concerned with stopping the infection, without any understanding of the destruction of the lockdowns, would have been reckless.

I also received dozens, hundreds, of emails from epidemiologists, medical scientists, doctors, biostatisticians—agreeing with me, sending me their own research, and sadly telling me they personally were afraid to speak out, but that I should keep going, keep citing the facts. I received pleas from parents, from teachers, from school board members begging me not to give up, to stay visible, and keep telling the truth.

As epidemiologists, we are interested in equilibria because stable equilibria tell us when a system has attained stability -- or where it will, eventually, attain stability. Epidemics are 'extraordinary events'. The term 'outbreak', beloved of the popular media when commenting on epidemics, emphasises that we are dealing with a phenomenon that goes counter to 'business as usual'. Stable equilibria are nothing more than mathematical descriptions of states in which the system can settle again and attain a measure of normalcy.

If we were to construct a similar map for society, it would have to include each person’s professional and personal interests and chart everyone she or he knew. It would make Milgram’s experiment seem clumsy and obsolete by allowing us to find, in seconds, the shortest path to any person in the world. It would be a must-use tool for everyone from politicians to salespeople and epidemiologists. Of course, such a social search engine is impossible to build, since it would take at least a lifetime to interrogate all 6 billion people on the earth to learn about their friends and acquaintances.

Good women discuss these things the way epidemiologists identify and track disease without alarming the public. This is woman’s work. Men are unfitted for it by nature and should be protected from it the same way women shouldn’t have to go down the mines. Men are so innocent.

To many a practicing geologist or epidemiologist, the claim that the very simple computational models developed in the following chapters have anything to do with real earthquakes or real epidemics may well be deemed professionally offensive, or at best dismissed as an infantile nerdy joke.

We’ve discussed two parallel adaptations to manage the sun’s dueling effects on body chemistry—the evolution of dark skin to protect our stores of folate and the evolution of a genetic trigger for increased cholesterol to maximize production of vitamin D. Both of those adaptations are common in people of African descent and are effective—in the bright, strong sun of equatorial Africa. But what happens when people with those adaptations move to New England, where the sun is much less plentiful and far less strong? Without enough sunlight to penetrate their dark skin and convert the additional cholesterol, they’re doubly vulnerable—not enough vitamin D and too much cholesterol. Sure enough, rickets—the disease caused by a vitamin D deficiency that causes poor bone growth in children—was very common in African American populations until we started routinely fortifying milk with vitamin D in the last century. And there appear to be connections among sunlight, vitamin D, and prostate cancer in African Americans as well. There is growing evidence that vitamin D inhibits the growth of cancerous cells in the prostate and in other areas, including the colon, too. Epidemiologists, who specialize in unlocking the mystery of where, why, and in whom disease occurs, have found that the risk of prostate cancer for black men in America climbs from south to north. When it comes to prostate cancer in black men, the risk is considerably lower in sunny Florida. But as you move north, the rate of prostate cancer in black men climbs until it peaks in the often cloud-covered heights of the Northeast.

In order to deeply bury reprehensible emotions, your brain can cause physical pain to distract you. The pain is real. Laboratory tests demonstrate that the pain is caused when your brain cuts off oxygen to the afflicted area. Epidemiologists call this transfer of symptoms amplification.10 Amplification prevents unacceptable ideas from surfacing.

In 2013, the Journal of the American Medical Association published the results of a study that aimed to find, once and for all, the link between mortality rates and BMI (a.k.a. is our fat really killing us?). The study was led by Katherine Flegal, an epidemiologist at the National Center for Health Statistics, and her colleagues. After analyzing ninety-seven studies of mortality rates and BMI that included almost 3 million people, Flegal found what’s known as a “U-shaped curve.” At the top ends of the curve, where death rates were the highest, are people whose BMIs categorize them as either severely underweight or severely obese. At the lowest point of the curve, where death rates are the lowest, are people whose BMI falls within the “overweight” category. Meaning that statistically, people who are overweight according to BMI had the lowest risk of death. Following the U-shaped curve, people whose BMI fell within the “mildly obese” category had no higher risk of death than people within the “normal” category. The increased mortality rate came at the extremes, either side.

From the 1950s onward, popular thinking on the link between Western lifestyles and cancer focused on industrialization and carcinogens in the environment—something Higginson himself argued against in the 1980s, noting that “only a very small part of the total cancer burden” could be laid on industrial chemicals. When cancer epidemiologists did systematic reviews of the data, they continued to conclude, as Higginson had, that some significant percentage of cancers had to be lifestyle- or diet-induced. Breast cancer may be the best example. Though it has never been the scourge among Japanese women living in Japan that it is among women in America, it takes only two generations in the United States before Japanese-Americans experience the same breast-cancer rates as any other ethnic group. This implies that something about the American lifestyle or diet is a cause of breast cancer,

In 2003, epidemiologists from the Centers for Disease Control, led by Eugenia Calle, published an analysis in The New England Journal of Medicine reporting that cancer mortality in the United States was clearly associated with obesity and overweight. The heaviest men and women, they reported, were 50 and 60 percent more likely, respectively, to die from cancer than the lean. This increased risk of death held true for a host of common cancers—esophageal, colorectal, liver, gallbladder, pancreatic, and kidney cancers, as well as, in women, cancers of the breast, uterus, cervix, and ovary. In 2004, the CDC followed up with an analysis linking cancer to diabetes, particularly pancreatic, colorectal, liver, bladder, and breast cancers. Cancer researchers trying to make sense of this association would later say that something about cancer seems to thrive on the metabolic environment of the obese and the diabetic. One conspicuous clue as to what that something might be was that the same association was seen with people who weren’t obese and diabetic (or at least not yet) but suffered only from metabolic syndrome and thus were insulin-resistant. The higher their levels of circulating insulin, and that of a related hormone known as insulin-like growth factor, the greater the likelihood that they would get cancer.

Every day, I saw the transformation of a city, from beautiful villas to filthy bottom-of-the-pit hovels where potato sacks and battered hats served as replacements for missing window panes. And so also did I transform, from the fake male bacteriologist and epidemiologist Anton Kronberg to Anna Kronberg

More thunder out of China, in the form of the coronavirus pandemic, came in early 2020. Although epidemiologists (not to mention biological weapons experts) will be studying this catastrophe long into the future; the mark of China’s authoritarian government and social-control systems is all over it. There is little doubt that China delayed, withheld, fabricated, and distorted information about the origin, timing, spread, and extent of the disease;28 suppressed dissent from physicians and others;29 hindered outside efforts by the World Health Organization and others to get accurate information; and engaged in active disinformation campaigns, actually trying to argue that the virus (SARS-CoV-2) and the disease itself (COVID-19) did not originate in China.30 Ironically, some of the worst effects of China’s cover-up were visited on its closest allies. Iran, for example, looked to be one of the worst-hit countries, with satellite photos showing the excavation of burial pits for the expected victims of COVID-19.31

More thunder out of China, in the form of the coronavirus pandemic, came in early 2020. Although epidemiologists (not to mention biological weapons experts) will be studying this catastrophe long into the future; the mark of China’s authoritarian government and social-control systems is all over it. There is little doubt that China delayed, withheld, fabricated, and distorted information about the origin, timing, spread, and extent of the disease;28 suppressed dissent from physicians and others;29 hindered outside efforts by the World Health Organization and others to get accurate information; and engaged in active disinformation campaigns, actually trying to argue that the virus (SARS-CoV-2) and the disease itself (COVID-19) did not originate in China.30 Ironically, some of the worst effects of China’s cover-up were visited on its closest allies. Iran, for example, looked to be one of the worst-hit countries, with satellite photos showing the excavation of burial pits for the expected victims of COVID-19.31 With 2020 being a presidential election year, it was inevitable that Trump’s performance in this global health emergency would become a campaign issue, which it did almost immediately. And there was plenty to criticize, starting with the Administration’s early, relentless assertion that the disease was “contained” and would have little or no economic effect. Larry Kudlow, Chairman of the National Economic Council, said, on February 25, “We have contained this. I won’t say [it’s] airtight, but it’s pretty close to airtight.”32 Market reactions to these kinds of assertions were decidedly negative, which may finally have woken the White House up to the seriousness of the problem.

The world’s last great pandemic was the Spanish flu outbreak in 1918 that killed a hundred million people—about 5 percent of the world’s population. If a pandemic like that were to happen again, it would spread faster and might be impossible to contain. According to the Bill & Melinda Gates Foundation, in such a pandemic “the death toll could reach 360 million”—even with the full deployment of vaccines and powerful modern drugs. The Gates Foundation estimated that the pandemic would also devastate the world financially, precipitating a three-trillion-dollar economic collapse. This is not scaremongering: Most epidemiologists believe such a pandemic will eventually happen. Archaeology