During the acute phase of the Covid-19 pandemic, I kept thinking of Margarita Engle’s poem “More Dangerous Air.” The title seemed particularly resonant, and its a beautiful poem about growing up in an atmosphere of fear.
Newsmen call it the Cuban Missile Crisis.
Teachers say it’s the end of the world.
Engle documents the way we might flail, attempting to protect ourselves & our loved ones. We know enough to be afraid; we don’t yet know enough to be safe.
Early in the pandemic, people left their groceries on the front steps for days before bringing the bags inside. A year in, we were still needlessly scrubbing surfaces with toxic chemicals.
During the missile crisis, school children practiced fire drills, earthquake drills, tornado drills, air raid drills. (They didn’t yet need the contemporary era’s most awful: the active shooter drills.)
Hide under a desk.
Pretend that furniture is enough
to protect us against perilous flames.
Radiation. Contamination. Toxic breath.
The blasts are dangerous. But warfare with atomic weapons is different from other forms of violence. A bomb might kill you, suddenly; the poisoned air might kill you, slowly; the poisoned ground might maim generations yet unborn.
Each air-raid drill is sheer terror,
but some kids giggle.
They don’t believe that death
Radiation is invisible. Marie Curie didn’t know that it would kill her. Rosalind Franklin didn’t know that it would kill her.
We know, now. At least, some of us do.
Others – including a perilously large cadre of politicians – still think we ought to stockpile a behemoth nuclear arsenal.
Viruses are invisible. And they act slowly. Breathe in an invisible virus; a week later, you might begin to cough; three weeks later, your cough might worsen; a month after that seemingly innocuous breath in which you sucked a microscopic package of genetic code into your lungs, you might be in the hospital, or worse.
Connecting an eventual death to that first dangerous breath is actually a tricky cognitive feat! The time lag confuses us. It’s much easier for human minds to draw conclusions about closely consecutive events – a vaccine followed within hours or days by fever or heart problems.
Greenhouse gases are also invisible. If we drive past a power plant, we might see plumes rising from the towers, but we can’t see poison spilling from our cars, our refrigerators, our air conditioners, our meals. This is just good food on a plate! It doesn’t look like danger.
But we are changing the air, dramatically, in ways that might poison us all. Or – which is perhaps worse – in ways that might not affect us so much, but might make this planet inhospitable to our unborn grandchildren. Perhaps we will be fine. It’s humans born twenty years from now, or fifty years from now, who will suffer more.
Each individual can take action. You, as an individual, could fly less, buy less, eat plants.
You, as an individual, can only do so much.
When I hide under my frail school desk,
my heart grows as rough and brittle
as the slab of wood
that fails to protect me
We aren’t the first. Go outside and look around – the vibrant bursts of summer green are delightfully entrancing.
Our minds are plastic things – we make ourselves through the ways we live – but certain scripts were sculpted by our ancestry. Over hundreds of millions of years, the bearers of certain types of brains were more likely to be successful in life.
Creatures like us – who need air to breath, water to drink, shelter from sun and cold – often feel an innate love for the way summer light plays over a heady mix of blue and green.
We need all that green. The plants, the trees, the algae: for humans to survive the climate crisis we’ve been making, we’re depending on them. We need them to eat carbon dioxide from the air, and drink in hydrogen atoms from water, and toss back oxygen for us to breathe.
We’ve been poisoning the air, and they might save us.
Which is ironic, in a way. Because all that green – they wrought our planet’s first global devastation.
Saving us all this time would be like a form of penance.
Early in our planet’s history, there was very little oxygen in the air. Which was a good thing for the organisms living then! Oxygen is a very dangerous molecule. When we fall apart with age, it’s largely because “oxidative damage” accumulates in our cells. When grocery stores market a new type of berry as a “superfood,” they often extol its abundance of “antioxidants,” small molecules that might protect us from the ravages of oxygen.
The first living organisms were anaerobic: they did not need, and could not tolerate, oxygen. They obtained energy from sulfur vents or various other chemicals.
But then a particular type of bacteria – cyanobacteria – evolved a way to eat air, pulling energy from sunlight. This was the precursor to modern photosynthesis. Cyanobacteria began to fill the air with (poisonous!) oxygen as waste.
Many years passed safely, though. There was abundant iron then, on land and in the seas – iron drew down oxygen to rust.
Approximately two billion years passed without incident. All that iron buffered our planet’s atmosphere! It must have seemed as though the cyanobacteria could excrete a nearly infinite amount!
But then they reached a tipping point. The iron had all become iron oxides. The concentration of oxygen in the air rose dramatically. This hyper-reactive poison killed almost everything alive.
Perhaps cyanobacteria were punished for what they’d done. By filling the world with oxygen, they enabled the evolution of organisms with higher metabolisms. Creatures who lived faster, shorter lives, turbocharged by all that dangerous air. And these creatures – our forebears – nearly grazed their enablers out of existence.
Cyanobacteria were once masters of the universe. Then they were food.
And they were imprisoned within the cells of plants. Look up at a tree – each green leaf is a holding cell, brimming with cyanobacteria who are no longer free to live on their own. Grasses, ferns, flowers – every photosynthetic cell home to perhaps dozens of chloroplasts, the descendants of those who caused our planet’s first mass extinction.
A few outlaws linger in the ocean. Some cyanobactera still pumping oxygen into the air, the lethal poison that’s gulped so greedily by human lungs. Their lethal poison now enables our growth, our flourishing, our reckless abasement of the world.
And we are poisoning the air in turn, albeit in a very different way. In our quest to use many years’ stored sunlight each year, we dig up & burn the subterranean remnants of long-dead plants. The prison cells in which cyanobacteria once lived and died, entombed for millions of years within the earth, now the fuel for our own self-imposed damnation. The concentration of carbon dioxide in the air is slowly rising. Our atmosphere is buffered; for a while, our world will seem unchanged. Until, suddenly, it doesn’t.
Some species, surely, will survive. Will thrive in the hotter, swingier, stormier world we’re making.
2: “We know that the current shutdown is either delaying or preventing deaths due to Covid-19.”
To date, the data suggests that the virus has only reached saturation inside a few closed environments, such as prisons. In Italy, both the timecourse of mortality and the results of antibody studies suggest that infections were still rising at the time of their lockdown.
Among the passengers of the Diamond Princess cruise ship, deaths peaked 21 days after infections peaked – if the virus had already reached saturation in Italy, we’d expect to see deaths peak sooner than 21 days after the lockdown began. They did not.
So, again, this much is clear: worldwide, there was a significant new cause of death. When we look at mortality data, we see the curves suddenly rise in many locations. Some researchers, such as John Ioannidis, have speculated that Covid-19 causes death primarily in people with low life expectancy, in which case we would expect to see these mortality curves drop to lower-than-average levels after the epidemic ends. But even then, it’s unprecedented to see a number of deaths that would usually occur over the course of a year all within a matter of weeks.
Covid-19 is killing people, and the shutdown is either delaying or preventing people’s death from Covid-19.
For the shutdown to actually prevent death, one of the following needs to happen:
1.) We create a vaccine, allowing our population to reach 70% immunity without as many people contracting the illness.
2.) We take action to change which segment of the population is exposed to the virus, allowing us to reach 70% immunity without as many at-risk people being exposed.
See #3 and #4, below.
3: “Ending this epidemic with a vaccine would be ideal.”
Vaccination is great science. Both my spouse and I love teaching about vaccines, in part because teaching the history of vaccine use is a good component of anti-racist science class.
Developing vaccines often takes a long time. I’ve read predictions of a year or two; my father, an infectious disease doctor, epidemiologist, research physician who runs vaccine trials, and co-developer of Merck’s HPV vaccine, guesses that it will take about five years.
And then, for the vaccine to end this epidemic, enough people will need to choose to be vaccinated that we reach approximately 70% immunity.
The reason it’s worthwhile to compare Covid-19 to seasonal influenza is that a vaccine will only end the epidemic if enough people choose to get it. Many people’s personal risk from Covid-19 is lower than their risk from seasonal influenza. Will those people choose to be vaccinated?
Obviously, I would be thrilled if the answer were “yes.” I’d love to live in a nation where people’s sense of altruism and civic duty compelled them to get vaccinated. My family is up-to-date on all of ours.
But many privileged families in the United States have elected to be freeloaders, declining the (well tested, quite safe) measles vaccine with the expectation that other people’s immunity will keep them safe. And, despite the well-documented dangers of influenza, only 40% of our population gets each year’s influenza vaccine.
A vaccine with low efficacy will still offer better protection when more people get it. If a higher percentage of our population were vaccinated against influenza, then influenza transmission would drop, and so each person’s immunity, whether high or low, would be less likely to be challenged.
The influenza vaccine saves lives. In Italy, where fewer people choose to get vaccinated against influenza (about 15% compared to our 40% of the population), the death rate from influenza is higher. Although it’s worth noting that this comparison is complicated by the fact that our health care system is so bad, with poor people especially having limited access to health care. In the United States, people between the ages of 18 and 49 comprise a higher proportion of influenza deaths than anywhere in Europe. Either our obesity epidemic or limited access to health care is probably to blame; possibly a combination of both.
In summary, for this plan to help us save lives, we will need to develop an effective vaccine, and then people will have to get it.
I am quite confident that we can eventually develop a vaccine against Covid-19. The virus includes a proofreading enzyme, so it should mutate more slowly than most RNA viruses. We don’t know how long it will take, but we can do it.
I am unfortunately pessimistic that people will choose to get the vaccine. And, unfortunately, when a low-risk person chooses to forgo vaccination, they’re not just putting themselves in harm’s way, they are endangering others. Most vaccines elicit a weaker immune response in elderly or immunocompromised recipients – exactly the group most at risk from Covid-19 – which is why we spend so much time harping about herd immunity.
4: “Ending the shutdown while requesting that at-risk people continue to self-isolate would save lives.“
This plan has major downsides, too. Because we didn’t take action soon enough, every plan we have now is bad.
Low-risk people can still die of Covid-19. Even if they don’t die, Covid-19 can cause permanent health effects. Covid-19 reduces your ability to get oxygen to your body and brain. Even a “mild” case can leave your breathing labored for weeks – you’re not getting enough oxygen. Your muscles will ache. Your thoughts will be sluggish.
With a more severe case, people can be looking at heart damage. Renal failure. It would be cruel to look at all these long-term consequences and blithely call them “recovery.”
If our health care system were better, we’d treat people sooner. The earlier you intervene, helping to boost people’s oxygen levels, the better outcome you’ll have. There’s a great editorial from medical doctor Richard Levitan recommending that people monitor their health with a pulse oximeter during this epidemic.
If you notice your oxygen levels declining, get help right away. Early intervention can prevent organ damage. And you’ll be helping everyone else, too – the sooner you intervene, the less medical care you will need.
Because medical debt can derail lives, many people in this country delay treatment as long as possible, hoping that their problems will go away naturally. That’s why people are often so sick when they show up at the ER. I imagine that this is yet another reason – alongside air pollution, food deserts, sleep loss, and persistent stress exacerbated by racism – that poor communities have had such a high proportion of people with severe cases of Covid-19.
And I imagine – although we don’t yet have enough data to know – that financial insecurity caused by the shutdown is making this worse. It’s a rotten situation: you have a segment of population that has to continue working during the shutdown, which means they now have the highest likelihood to be exposed to the virus, and they’re now under more financial strain, which might increase the chance that they’ll delay treatment.
We know that early treatment saves lives, and not everyone is sufficiently privileged to access that.
All this sounds awful. And it is. But, if we took action to shift exposure away from high risk groups, the likelihood that any individual suffers severe consequences is lower.
And there is another caveat with this plan – some people may be at high risk of complications for Covid-19 and not even realize it. In the United States, a lot of people either have type 2 diabetes or are pre-diabetic and don’t yet realize. These people have elevated risk. Both smoking and airpollution elevate risk, but people don’t always know which airborn pollutants they’ve been exposed to. (Which, again, is why it’s particularly awful that our administration is weakening air quality standards during this epidemic.)
Even if we recommended continued self-isolation for only those people who know themselves to have high risk from Covid-19, though, we would be saving lives. The more we can protect people in this group from being exposed to the virus – not just now, but ever – the more lives we will save.
We won’t be able to do this perfectly. It’ll be a logistical nightmare trying to do it at all. People at high risk from Covid-19 needs goods and services just like everybody else. We might have to give daily Covid-19 PCR tests to anyone visiting their homes, like doctors, dentists, and even delivery workers.
At that point, the false negative rate from Covid-19 PCR tests becomes a much bigger problem – currently, these false negatives reduce the quality of our data (but who cares?) and delay treatment (which can be deadly). A false negative that causes inadvertent exposure could cost lives.
Some people will be unable to work, either because they or a close relative has high risk of Covid-19. Some children will be unable to go to school. We will need a plan to help these people.
We will have to work very hard to keep people safe even after the shutdown ends for some.
But, again, if everyone does the same thing, then the demographics of people infected with Covid-19 will reflect our population demographics. We can save lives by skewing the demographics of the subset of our population that is exposed to Covid-19 to include more low-risk individuals, which will require that we stratify our recommendations by risk (at least as well as we can assess it).
5: “Why is it urgent to end the shutdown soon?“
1.) By delaying Covid-19 deaths, we run to risk of causing more total people to die of Covid-19.
2.) The shutdown itself is causing harm.
See #6 and #7, below.
6: “Why might more people die of Covid-19 just because we are slowing the spread of the virus?“
[EDIT: I wrote a more careful explanation of the takeaways of the Harvard study. That’s here if you would like to take a look!]
This is due to the interplay between duration of immunity and duration of the epidemic. At one point in time, seasonal influenza was a novel zoogenic disease. Human behavior allowed the influenza virus to become a perpetual burden on our species. No one wants for humans to still be dying of Covid-19 in ten or twenty years. (Luckily, because the virus that causes Covid-19 seems to mutate more slowly than influenza, it should be easier to design a single vaccine that protects people.)
In the Harvard model, we can see that there are many scenarios in which a single, finite shutdown leads to more deaths from Covid-19 than if we’d done nothing. Note the scenarios for which the colored cumulative incidence curves (shown on the right) exceed the black line representing how many critical cases we’d have if we had done nothing.
Furthermore, their model does not account for people’s immunity potentially waning over time. Currently, we do not know how long people’s immunity to Covid-19 will last. We won’t know whether people’s immunity will last at least a year until a year from now. There’s no way to test this preemptively.
If we could all go into stasis and simply not move for about a month, there’d be no new cases of Covid-19, and this virus would be gone forever. But people still need to eat during the shutdown. Many people are still working. So the virus is still spreading, and we have simply slowed the rate of transmission.
This seems good, because we’re slowing the rate at which people enter the hospital, but it’s actually bad if we’re increasing the number of people who will eventually enter the hospital.
Based on our research with other coronaviruses, we expect that re-infection will cause a person to experience symptoms less severe than their first case of Covid-19. But a re-infected person can still spread the disease to others. And we don’t know what will happen if a person’s risk factors – such as age, smoking status, diabetes status, etc. – have increased in the time since their last infection.
7: “How is the shutdown causing harm?“
If you turn on Fox News, I imagine you’d hear people talking about the damage we’re doing to our economy. They might discuss stock market numbers.
Who gives a shit? In my opinion, you’d have to be pretty callous to think that maintaining the Nasdaq bubble is more important than saving lives.
In this report, they estimate that the shutdown we’ve had so far will cause hundreds of thousands of children to die, many from malnutrition and the other health impacts of poverty. The longer the shutdown continues, the more children will die.
That’s a worldwide number, and most of those children live outside the United States. But I’d like to think that their lives matter, too.
The report also discusses the lifelong harm that will be inflicted on children from five months (or more!) of school closure. Drop-outs, teen pregnancy, drug abuse, recruitment of child soldiers, and the myriad health consequences of low educational attainment.
I live in a wealthy college town, but even here there is a significant population of students who don’t have internet access. Students with special needs aren’t getting the services they deserve. Food insecurity is worse.
You’re lucky that privacy protections prevent me from sharing a story about what can happen to poor kids when all the dentists’ offices are closed. I felt ashamed that this was the best my country had to offer.
As the shutdown continues, domestic violence is rising. We can assume that child abuse is rising, also, but we won’t know until later, when we finally have a chance to save children from it. In the past, levels of child abuse have been correlated with the amount of time that children spend in the presence of their abusers (usually close family), and reporting tends to happen during tense in-person conversations at school.
The shutdown has probably made our drug epidemic worse (and this was already killing about 70,000 people per year in the U.S.). When people are in recovery, one of the best strategies to stay sober is to spend a lot of time working, out of the house, and meeting with a supportive group in communal space. Luckily, many of the people I know who are in recovery have been categorized as essential workers.
A neighbor recently sent me a cartoon suggesting that the biggest harm caused by the shutdown is boredom. (I’m going to include it, below, but don’t worry: I won’t spend too much time rattling sabers with a straw man.) And, for privileged families like mine, it is. We’re safe, we’re healthy, we get to eat. My kids are still learning – we live in a house full of computers and books.
But many of the 75 million children in the United States don’t live in homes like mine, with the privilege we have. Many of our 50 million primary and secondary school students are not still learning academically during the shutdown.
Whether the shutdown is preventing or merely delaying the deaths of people at risk of serious complications from Covid-19, we have to remember that the benefit comes at a cost. What we’ve done already will negatively impact children for the rest of their lives. And the longer this goes on, the more we’re hurting them.
8: “What about the rate at which people get sick? Isn’t the shutdown worthwhile, despite the risks described above, if it keeps our hospitals from being overwhelmed?“
In writing this, I struggled with how best to organize the various responses. I hope it doesn’t seem too ingenuous to address this near the end, because slowing the rate of infection so that our hospitals don’t get overwhelmed is the BEST motivation for the shutdown. More than the hope that a delay will yield a new vaccine, or new therapies to treat severe cases, or even new diagnostics to catch people before they develop severe symptoms, we don’t want to overwhelm our hospitals.
If our physicians have to triage care, more people will die.
And I care a lot about what this epidemic will be like for our physicians. My father is a 67-year-old infectious disease doctor who just finished another week of clinical service treating Covid-19 patients at the low-income hospital in Indianapolis. My brother-in-law is an ER surgeon in Minneapolis. These cities have not yet had anything like the influx of severe cases in New York City – for demographic and environmental reasons, it’s possible they never will. But they might.
Based on the case fatality rate measured elsewhere, I’d estimate that only 10% of the population in Minneapolis has already been infected with Covid-19, so the epidemic may have a long way yet to go.
If we ended the shutdown today for everyone, with no recommendation that at-risk groups continue to isolate and no new measures to protect them, we would see a spike in severe cases.
If we ended the shutdown for low-risk groups, and did a better job of monitoring people’s health to catch Covid-19 at early, more-easily-treatable stages (through either PCR testing or oxygen levels), we can avoid overwhelming hospitals.
And the shutdown itself is contributing toward chaos at hospitals. Despite being on the front lines of this epidemic, ER doctors in Minneapolis have received a 30% pay cut. I imagine my brother-in-law is not the only physician who could no longer afford day care for his children after the pay cut. (Because so many people are delaying care out of fear of Covid-19, hospitals are running out of money.) Precisely when we should be doing everything in our power to make physicians’ lives easier, we’re making things more stressful.
We could end the shutdown without even needing to evoke the horrible trolley-problem-esque calculations of triage. Arguments could be made that even if it led to triage it might be worthwhile to end the shutdown – the increase in mortality would be the percentage of triaged cases that could have survived if they’d been treated, and we as a nation might decide that this number was acceptable to prevent the harms described above – but with a careful plan, we need not come to that.
9: “Don’t the antibody tests have a lot of false positives?“
False positives are a big problem when a signal is small. I happen to like a lot of John Ioannidis’s work – I think his paper “Why Most Published Research Findings Are False” is an important contribution to the literature – but I agree that the Santa Clara study isn’t particularly convincing.
When I read the Santa Clara paper, I nodded and thought “That sounds about right,” but I knew my reaction was most likely confirmation bias at work.
Which is why, in the essay, I mostly discussed antibody studies that found high percentages of the population had been infected with Covid-19, like the study in Germany and the study in the Italian town of Robbio. In these studies, the signal was sufficiently high that false positives aren’t as worrisome.
In Santa Clara, when they reported a 2% infection rate, the real number might’ve been as low as zero. When researchers in Germany reported a 15% infection rate, the real number might’ve been anywhere in the range of 13% to 17% – or perhaps double that, if the particular chips they used had a false negative rate similar to the chips manufactured by Premier Biotech in Minneapolis.
I’m aware that German response to Covid-19 has been far superior to our bungled effort in the United States, but an antibody tests is just a basic ELISA. We’ve been doing these for years.
Luckily for us, we should soon have data from good antibody studies here in the United States. And I think it’s perfectly reasonable to want to see the results of those. I’m not a sociopath – I haven’t gone out and joined the gun-toting protesters.
But we’ll have this data in a matter of weeks, so that’s the time frame we should be talking about here. Not months. Not years. And I’ll be shocked if these antibody studies don’t show widespread past infection and recovery from Covid-19.
10: “What about the political ramifications of ending the shutdown?“
I am, by nature, an extremely cautious person. And I have a really dire fear.
I’m inclined to believe that ending the shutdown is the right thing to do. I’ve tried to explain why. I’ve tried to explain what I think would be the best way to do it.
But also, I’m a scientist. You’re not allowed to be a scientist unless you’re willing to be proven wrong.
So, yes. I might be wrong. New data might indicate that writing this essay was a horrible mistake.
Still, please bear with me for a moment. If ending the shutdown soon turns out to be the correct thing to do, and if only horrible right-wing fanatics have been saying that we should end the shutdown soon, won’t that help our current president get re-elected?
There is a very high probability that his re-election would cause even more deaths than Covid-19.
Failing to address climate change could kill billions. Immigration controls against migrants fleeing war zones could kill millions. Weakened EPA protections could kill hundreds of thousands. Reduced access to health care could kill tens of thousands.
And, yes, there are horrible developments that neither major political party in the United States has talked about, like the risk that our antibiotics stop working, but I think it’s difficult to argue that one political party isn’t more dangerous than the other, here.
I feel pretty confident about all the scientific data I’ve discussed above. Not as confident as I’d like, which would require more data, but pretty confident.
I feel extremely confident that we need to avoid a situation in which the far right takes ownership of an idea that turns out to have been correct. And it’ll be dumb luck, just a bad coincidence. The only “data” they’re looking at are stock market numbers, or maybe the revenue at Trump-owned hotels.
EDIT: I also wrote a more careful explanation of the takeaways of the Harvard study. That’s here if you would like to take a look!
First, some background: in case you haven’t noticed, most of the United States is operating under a half-assed lockdown. In theory, there are stay-at-home orders, but many people, such as grocery store clerks, janitors, health care workers, construction workers, restaurant chefs, delivery drivers, etc., are still going to work as normal. However, schools have been closed, and most people are trying to stand at least six feet away from strangers.
We’re doing this out of fear that Covid-19 is an extremely dangerous new viral disease. Our initial data suggested that as many as 10% of people infected with Covid-19 would die.
That’s terrifying! We would be looking at tens of millions of deaths in the United States alone! A virus like this will spread until a majority of people have immunity to it – a ballpark estimate is that 70% of the population needs immunity before the epidemic stops. And our early data suggested that one in ten would die.
My family was scared. We washed our hands compulsively. We changed into clean clothes as soon as we came into the house. The kids didn’t leave our home for a week. My spouse went to the grocery store and bought hundreds of dollars of canned beans and cleaning supplies.
And, to make matters worse, our president was on the news saying that Covid-19 was no big deal. His nonchalance made me freak out more. Our ass-hat-in-chief has been wrong about basically everything, in my opinion. His environmental policies are basically designed to make more people die. If he claimed we had nothing to worry about, then Covid-19 was probably more deadly than I expected.
Five weeks have passed, and we now have much more data. It seems that Covid-19 is much less dangerous than we initially feared. For someone my age (37), Covid-19 is less dangerous than seasonal influenza.
Last year, seasonal influenza killed several thousand people between the ages of 18 and 49 in the United States – most likely 2,500 people, but perhaps as many as 5,800. People in this age demographic account for about 10% of total flu deaths in the United States, year after year.
Seasonal influenza also killed several hundred children last year – perhaps over a thousand.
There’s a vaccine against influenza, but most people don’t bother.
Seasonal influenza is more dangerous than Covid-19 for people between the ages of 18 and 49, but only 35% of them chose to be vaccinated in the most recently reported year (2018). And because the vaccination rate is so low, our society doesn’t have herd immunity. By choosing not to get the influenza vaccine, these people are endangering themselves and others.
Some people hope that the Covid-19 epidemic will end once a vaccine is released. I am extremely skeptical. The biggest problem, to my mind, isn’t that years might pass before there’s a vaccine. I just can’t imagine that a sufficient percentage of our population would choose to get a Covid-19 vaccine when most people’s personal risk is lower than their risk from influenza.
When I teach classes in jail, dudes often tell me about which vaccines they think are too dangerous for their kids to get. I launch into a tirade about how safe most vaccines are, and how deadly the diseases they prevent.
Seriously, get your kids vaccinated. You don’t want to watch your child die of measles.
And, seriously, dear reader – get a flu vaccine each year. Even if you’re too selfish to worry about the other people whom your mild case of influenza might kill, do it for yourself.
We already know how dangerous seasonal influenza is. But what about Covid-19?
To answer that, we need data. And one set of data is unmistakable – many people have died. Hospitals around the world have experienced an influx of patients with a common set of symptoms. They struggle to breathe; their bodies weaken from oxygen deprivation; their lungs accumulate liquid; they die.
For each of these patients saved, three others are consigned to an agonizing death in the hospital, intubated among the flashing lights, the ceaseless blips and bleeps. At home, they’d die in a day; in the hospital, their deaths will take three weeks.
And the sheer quantity of deaths sounds scary – especially for people who don’t realize how many tens of thousands die from influenza in the United States each year.
Indeed, when people die of Covid-19, it’s often because their lungs fail. Smoking is obviously a major risk factor for dying of Covid-19 – a significant portion of reported Covid-19 deaths could be considered cigarette deaths instead. Or as air pollution deaths – and yet, our current president is using this crisis as an opportunity to weaken EPA airquality regulations.
Air pollution is a huge problem for a lot of Black communities in the United States. Our racist housing policies have placed a lot of minority neighborhoods near heavily polluting factories. Now Covid-19 is turning what is already a lifelong struggle for breath into a death sentence.
I would enthusiastically support a shutdown motivated by the battle for clean air.
But if we want to know how scary this virus is, we need to know how many people were infected. If that many people died after everyone in the country had it, then Covid-19 would be less dangerous than influenza. If that many people died after only a hundred thousand had been infected, then this would be terrifying, and far more dangerous than influenza.
Initially, our data came from PCR testing.
These are good tests. Polymerase chain reaction is highly specific. If you want to amplify a certain genetic sequence, you can design short DNA primers that will bind only to that sequence. Put the whole mess in a thermocycler and you get a bunch of your target, as long as the gene is present in the test tube in the first place. If the gene isn’t there, you’ll get nothing.
PCR works great. Even our lovely but amnesiac lab tech never once screwed it up.
So, do the PCR test and you’ll know whether a certain gene is present in your test tube. Target a viral gene and you’ll know whether the virus is present in your test tube. Scoop out some nose glop from somebody to put into the test tube and you’ll know whether the virus is present in that nose glop.
The PCR test is a great test that measures whether someone is actively shedding virus. It answers, is there virus present in the nose glop?
This is not the same question as, has this person ever been infected with Covid-19?
It’s a similar question – most people infected with a coronavirus will have at least a brief period of viral shedding – but it’s a much more specific question. When a healthy person is infected with a coronavirus, the period of viral shedding can be as short as a single day.
A person can get infected with a coronavirus, and if you do the PCR test either before or after that single day, the PCR test will give a negative result. Nope, no viral RNA is in this nose glop!
And so we know that the PCR test will undercount the true number of infections.
When we look at the age demographics for Covid-19 infections as measured by PCR test, the undercount becomes glaringly obvious.
Friends, it is exceedingly unlikely that such a low percentage of children were exposed to this virus. Children are disgusting. I believe this is common knowledge. Parents of small children are pretty much always sick because children are so disgusting.
Seriously, my family has been doing the whole “social distancing” thing for over a month, and yet my nose is dripping while I type this.
Children are always touching everything, and then they rub their eyeballs or chew on their fingers. If you take them someplace, they grubble around on the floor. They pick up discarded tissues and ask, “What’s this?”
“That’s somebody’s gross kleenex, is what it is! Just, just drop it. I know it’s trash, I know we’re not supposed to leave trash on the ground, but just, just drop it, okay? Somebody will come throw it away later.”
The next day: “Dad, you said somebody would throw that kleenex away, but it’s still there!”
Bloody hell. Children are little monsters.
It seems fairly obvious that at least as high a percentage of children would be infected as any other age demographic.
But they’re not showing up from the PCR data. On the Diamond Princess cruise ship, the lockdown began on February 5th, but PCR testing didn’t begin until February 11th. Anyone who was infected but quickly recovered will be invisible to that PCR test. And even people who are actively shedding viral particles can feel totally well. People can get infected and recover without noticing a thing.
We see the same thing when we look at the PCR data from Italy. If we mistakenly assumed that the PCR data was measuring the number of infections, and not measuring the number of people who were given a PCR test while shedding viral particles, we’d conclude that elderly people went out and socialized widely, getting each other sick, and only occasionally infected their great-grandchildren at home.
Here in the United States, children are disgusting little monsters. I bet kids are disgusting in Italy, too. They’re disgusting all over the world.
A much more likely scenario is that children spread this virus at school. Many probably felt totally fine; some might’ve had a bad fever or the sniffles for a few days. But then they recovered.
When they got their great-grandparents sick – which can happen easily since so many Italian families live in multigenerational homes – elderly people began to die.
So we know that the PCR test is undercounting the true number of infections. Unless you’re testing every person, every day, regardless of whether or not they have symptoms, you’re going to undercount the number of infections.
In a moment, we can work through a way to get a more accurate count. But perhaps it’s worth mentioning that, for someone my age, Covid-19 would seem to be about as dangerous as influenza even if we assumed that the PCR data matched the true number of infections.
If you’re a healthy middle-aged or young person, you should not feel personally afraid.
That alone would not be an excuse to go out and start dancing in the street, though. Your actions might cause other people to die.
(NOTE & CORRECTION: After this post went up, my father recommended that I add something more about personal risk. No one has collected enough data on this yet, but he suspects that the next most important risk factor, after smoking and age, will be type 2 diabetes. And he reminded me that many people in their 30s & 40s in this country are diabetic or prediabetic and don’t even realize it yet. Everyone in this category probably has elevated risk of complications from Covid-19.)
After you’ve been infected with a virus, your body will start making antibodies. These protect you from being infected again.
Have you read Shel Silverstein’s Missing Piece book? Antibodies work kind of like that. They have a particular shape, and so they’ll glom onto a virus only if that virus has outcroppings that match the antibody’s shape. Then your body sees the antibodies hanging out on a virus like a GPS tracker and proceeds to destroy the virus.
So to make an antibody test, you take some stuff that looks like the outcroppings on the virus and you put it on a chip. Wash somebody’s blood over it, and if that blood contains antibodies that have the right shape to glom onto the virus, they’ll stick to the chip. All your other antibodies, the ones that recognize different viruses, will float away.
An antibody test is going to be worse than a PCR test. It’s easier to get a false positive result – antibodies are made of proteins, and they can unfold if you treat them roughly, and then they’ll stick to anything. Then you’ll think that somebody has the right antibodies, but they don’t. That’s bad.
You have to be much more careful when you’re doing an antibody test. I wouldn’t have asked our lab tech to do them for me.
An antibody test is also going to have false negatives. A viral particle is a big honking thing, and there are lots of places on its surface where an antibody might bind. If your antibodies recognize some aspect of the virus that’s different from what the test manufacturers included on their chip, your antibodies will float away. Even though they’d protect you from the actual virus if you happened to be exposed to it.
If you’re a cautious person, though – and I consider myself to be pretty cautious – you’d much rather have an antibody test with a bunch of false negatives than false positives. If you’re actually immune to Covid-19 but keep being cautious, well, so what? You’re safe either way. But if you think you’re immune when you’re not, then you might get sick. That’s bad.
Because antibody tests are designed to give more false negatives than false positives, you should know that it’d be really foolish to use them to track an infection. Like, if you’re testing people to see who is safe to work as a delivery person today, use the PCR test! The antibody test has a bunch of false negatives, and there’s a time lag between the onset of infection and when your body will start making antibodies.
If you use the antibody test on a bunch of people, though, you can tell how many were infected. And that’s useful information, too.
In the town of Robbio in Italy (pop. 6,000), the PCR test showed that only 23 people had been infected with Covid-19. But then the mayor implored everyone to get an antibody test, and 10% of people had actually been infected with – and had recovered from – Covid-19. Most of them couldn’t even recall having been sick.
I don’t know who made the tests used in Robbio – maybe they were a little better, maybe they were a little worse. Based on my experience, I wouldn’t be so surprised if the true infection rate with Covid-19 in that town was really just 10% – nor would I be surprised to hear that the chips had a high false-negative rate and that the infection rate was 20% or more.
If you calculate the fatality rate of Covid-19 in Italy by assuming that the PCR tests caught every infection, you’d get a terrifying 10%.
If you instead assume that many other towns had a similar infection rate to Robbio, you’ll instead calculate that the fatality rate was well under one percent.
Italy has higher risk than the United States due to age demographics, smoking rates, and multigenerational households – and even in Italy, the fatality rate was probably well under one percent.
When researchers in Germany randomly chose people to take a Covid-19 PCR test (many of whom had no symptoms), they found that 2% of the population was actively shedding virus – a much higher number of cases than they would have found if they tested only sick people. And when they randomly chose people to take an antibody test, they found that 15% had already recovered from the infection (again, many of whom had never felt sick). According to these numbers – which are expected to be an undercount, due to false negatives and the time lag before antibody production – they calculated a case fatality rate of 0.37%.
That would be about three-fold more dangerous than seasonal influenza.
In the United States, our bungling president gutted the CDC, leaving us without the expertise needed to address Covid-19 (or myriad other problems that might arise). During the first few months of this epidemic, very few people managed to get a PCR test. That’s why our data from the PCR tests is likely to be a dramatic undercount – indeed, when we finally started producing accurate tests, the apparent growth in Covid-19 caseload superimposed with the growth in test availability.
In the absence of good PCR data, we have to rely on antibody data to track infections after the fact. Which is why a town in Colorado with zero reported infections, as measured by PCR, had sufficiently widespread exposure that 2% of the population had already recovered from Covid-19.
Yes, there were problems with the Stanford study’s data collection – they displayed advertisements to a random selection of people, but then a self-selected subset responded. The pool of respondents were enriched for white women, but Santa Clara’s outbreak probably began among Asian-Americans. And we all know that random sampling doesn’t always give you an accurate depiction of the population at large – after all, random polling predicted that a competent president would be elected in 2016.
Now look at us.
It’s also likely that people with a poor understanding of the biology could misinterpret the result of the Stanford study. They found that PCR tests had undercounted the infection rate in Santa Clara county, at the time of this study, by 85-fold.
It would be absurd to assume that you could simply multiply all PCR results by 85 to determine the true infection rate, but some people did. And then pointed out the absurdity of their own bad math.
In places where more people are being tested by PCR, and they’re being tested more often, the PCR results will be closer to the true infection rate. If you gave everyone in the United States a PCR test, and did it every day, then the PCR data would be exactly equal to the true infection rate.
If we had data like that from the beginning, we wouldn’t have been scared. We would’ve known the true case fatality rate early on, and, also, at-risk people could’ve been treated as soon as they got infected. We’d be able to save many more lives.
10% is roughly the proportion of young people who die of seasonal influenza. But only 1% of Covid-19 deaths are people younger than 35. The news reports don’t always make clear how much the risk of Covid-19 is clustered in a small segment of the population.
This has serious implications for what we should do next. If we were dealing with a virus that was about three-fold more dangerous than seasonal influenza for everyone, we might just return to life as normal. (Indeed, we carried on as normal during the bad years when seasonal influenza killed 90,000 people instead of last year’s 30,000.)
Because the risk from Covid-19 is so concentrated, though, we can come up with a plan that will save a lot of lives.
Healthy people under retirement age should resume most parts of their lives as normal. Schools should re-open: for students, Covid-19 is much less dangerous than seasonal influenza. I think that people should still try to work from home when possible, because it’s the right thing to do to fight climate change.
At-risk people should continue to isolate themselves as much as possible.
This sounds crummy, but at-risk people would just continue to do the thing that everyone is doing currently. And the plan would save many lives because the epidemic would end in about 3 months, after the virus had spread to saturation among our nation’s low-risk cohort.
Their data are easy enough to understand. In each of these graphs, they show a blue box for how long social distancing would last, and then four colored lines to represent how many infections we’d see if we did no social distancing (black), medium quality social distancing (red), good social distancing (blue), or excellent social distancing (green).
So, from top to bottom, you’re looking at the graphs of what happens if we do a month of social distancing … or two months … or three, or four … or forever.
And you can see the outcomes in the panels on the right-hand side. The black line shows what would happen if we did nothing. Infections rise fast, then level off after the virus has reached saturation. There are two important features of this graph – the final height that it reaches, which is the total number of severe cases (and so a good proxy for the number of deaths), and the slope of the line, which is how fast the severe cases appear. A steeper hill means many people getting sick at the same time, which means hospitals might be overwhelmed.
So, okay. Looking at their graphs, we see that social distancing saves lives … if we do it forever. If you never leave your house again, you won’t die of Covid-19.
But if social distancing ends, it doesn’t help. The slopes are nearly as steep as if we’d done nothing, and the final height – the total number of people who die – is higher.
(Often, one of their curves will have a gentler slope than the others — usually the good-but-not-excellent social distancing seems best. So you’d have to pray that you were doing a precisely mediocre job of not infecting strangers. Do it a little better or a little worse and you cause people to die. This isn’t an artifact — it’s based on the density of uninfected people when social distancing ends — but let’s just say “mathematical models are wonky” and leave it at that.)
In a subsequent figure, the Harvard team tried to model what might happen if we occasionally resumed our lives for a month or so at a time, but then had another shutdown. This is the only scenario in which their model predicts that social distancing would be helpful.
Even in the extreme case that we mostly stayed in our homes for the better part of two years, social distancing would case more deaths from Covid-19 than if we had done nothing.
That’s not even accounting for all the people who would die from a greater risk of domestic violence, hunger, drug addiction, suicide, and sedentary behavior during the shutdown.
When our data was limited, the shutdown seemed reasonable. We wouldn’t be able to undo the damage we’d done by waiting.
Except, whoops, we waited anyway. We didn’t quarantine travelers in January. The shutdown didn’t begin March, when the epidemic was well underway in many places.
Now that we have more data, we should re-open schools, though. For most people, Covid-19 is no more dangerous than seasonal influenza. We already have enough data from antibody testing to be pretty confident about this, and even if we want to be extremely cautious, we should continue the shutdown for a matter of weeks while we conduct a few more antibody studies. Not months, and certainly not years.
At the same time, we need to do a better job of protecting at-risk people. This means providing health care for everyone. This means cleaning our air, staunching the pollution that plagues low-income neighborhoods. This might mean daily medical checkups and PCR tests for people who work closely with at-risk populations.
Our country will have to be different in the future, but mostly because we, as a people, have done such a shitty job of creating justice and liberty for all. We need to focus on addressing the inequities that we’ve let fester for generations. That’ll help far more than using a bandanna to cover up your smile.
been helping a friend learn the math behind optimization so that she can pass a
graduation-requirement course in linear algebra.
Optimization is a wonderful mathematical tool. Biochemists love it – progression toward an energy minimum directs protein folding, among other physical phenomena. Economists love it – whenever you’re trying to make money, you’re solving for a constrained maximum. Philosophers love it – how can we provide the most happiness for a population? Computer scientists love it – self-taught translation algorithms use this same methodology (I still believe that you could mostly replace Ludwig Wittgenstein’s Philosophical Investigations with this New York Times Magazine article on machine learning and a primer on principal component analysis).
But, even though optimization problems are useful, the math behind them can be tricky. I’m skeptical that this mathematical technique is essential for everyone who wants a B.A. to grasp – my friend, for example, is a wonderful preschool teacher who hopes to finally finish a degree in child psychology. She would have graduated two years ago except that she’s failed this math class three times.
I could understand if the university wanted her to take statistics, as that would help her understand psychology research papers … and the science underlying contemporary political debates … and value-added models for education … and more. A basic understanding of statistics might make people better citizens.
Whereas … linear algebra? This is a beautiful but counterintuitive field of mathematics. If you’re interested in certain subjects – if you want to become a physicist, for example – you really should learn this math. A deep understanding of linear algebra can enliven your study of quantum mechanics.
Werner Heisenberg, who was a brilliant physicist, had a limited grasp on linear
algebra. He made huge contributions to
our understanding of quantum mechanics, but his lack of mathematical expertise occasionally
held him back. He never quite understood
the implications of the Heisenberg Uncertainty Principle, and he failed to
provide Adolph Hitler with an atomic bomb.
retrospect, maybe it’s good that Heisenberg didn’t know more linear algebra.
doubt that Heisenberg would have made a great preschool teacher, I don’t think
that deficits in linear algebra were deterring him from that profession. After each evening that I spend working with
my friend, I do feel that she understands matrices a little better … but her
ability to nurture children isn’t improving.
yet. Somebody in an office decided that
all university students here need to pass this class. I don’t think this rule optimizes the
educational outcomes for their students, but perhaps they are maximizing
something else, like the registration fees that can be extracted.
Optimization is a wonderful mathematical tool, but it’s easy to misuse. Numbers will always do what they’re supposed to, but each such problem begins with a choice. What exactly do you hope to optimize?
wrong thing and you’ll make the world worse.
all, using graffiti to make a self-driving car interpret a stop sign as “Speed
Limit 45” is a design flaw. A car that
accelerates instead of braking in that situation is not operating as
passenger-less self-driving cars that roam the city all day, intentionally
creating as many traffic jams as possible?
That’s a feature. That’s
what self-driving cars are designed to do.
Despite my wariness about automation and algorithms run amok, I hadn’t considered this problem until I read Adam Millard-Ball’s recent research paper, “The Autonomous Vehicle Parking Problem.” Millard-Ball begins with a simple assumption: what if a self-driving car is designed to maximize utility for its owner?
This assumption seems reasonable. After all, the AI piloting a self-driving car must include an explicit response to the trolley problem. Should the car intentionally crash and kill its passenger in order to save the lives of a group of pedestrians? This ethical quandary is notoriously tricky to answer … but a computer scientist designing a self-driving car will probably answer, “no.”
the manufacturers won’t sell cars. Would
you ride in a vehicle that was programmed to sacrifice you?
the AI will not have to make that sort of life and death decision often. But here’s a question that will arise daily:
if you commute in a self-driving car, what should the car do while you’re
car was designed to maximize public utility, perhaps it would spend those hours
serving as a low-cost taxi. If demand
for transportation happened to be lower than the quantity of available,
unoccupied self-driving cars, it might use its elaborate array of sensors to
squeeze into as small a space as possible inside a parking garage.
But what if the car is designed to benefit its owner?
Perhaps the owner would still want for the car to work as a taxi, just as an extra source of income. But some people – especially the people wealthy enough to afford to purchase the first wave of self-driving cars – don’t like the idea of strangers mucking around in their vehicles. Some self-driving cars would spend those hours unoccupied.
But they won’t park. In most cities, parking costs between $2 and $10 per hour, depending on whether it’s street or garage parking, whether you purchase a long-term contract, etc.
The cost to just keep driving is generally going to be lower than $2 per hour. Worse, this cost is a function of the car’s speed. If the car is idling at a dead stop, it will use approximately 0.1 gallon per hour, costing 25 cents per hour at today’s prices. If the car is traveling at 30 mph without breaks, it will use approximately 1 gallon per hour, costing $2.50 per hour.
money, the car wants to stay on the road … but it wants for traffic to be as
close to a standstill as possible.
for the car, this is an easy optimization problem. It can consult its onboard GPS to find nearby
areas where traffic is slow, then drive over there. As more and more self-driving cars converge
on the same jammed streets, they’ll slow traffic more and more, allowing them
to consume the workday with as little motion as possible.
person sitting behind the wheel of an occupied car on those
streets. All the self-driving cars will
be having a great time stuck in that traffic jam: we’re saving money!,
they get to think. Meanwhile the human
is stuck swearing at empty shells, cursing a bevy of computer programmers who
made their choices months or years ago.
those idling engines exhale carbon dioxide.
But it doesn’t cost money to pollute, because one political party’s
worth of politicians willfully ignore the fact that capitalism, by
philosophical design, requires we set prices for scarce resources … like clean
air, or habitable planets.
“I heard there was, like, a car that runs on water … “
“Dude, no, there’ve been, like, six of them. But oil companies bought all the patents.”
A lot of the people who attend my poetry class in jail believe in freaky conspiracy theories. Somebody started telling me that the plots of various Berenstain Bears books are different from when he was a child, which is evidence that the universe bifurcated and that he’s now trapped in an alternate timeline from the path he was on before …
(New printings of some Berenstain Bears books really are different. Take Old Hat New Hat, a charming story about shopping and satisfaction: after the protagonist realizes that he prefers the old, beat-up hat he already owns to any of the newer, fancier models, a harried salesperson reacts with a mix of disgust and disbelieve. This scene has been excised from the board book version that you could buy today. Can’t have anything that tarnishes the joy of consumerism!)
I’ve written about conspiracy theories previously, but I think it’s worth re-iterating, in the interest of fairness, that the men in jail are correct when they assume that vast numbers of people are “breathing together” against them. Politicians, judges, police, corporate CEOs and more have cooperated to build a world in which men like my students are locked away. Not too long ago, it would have been fairly easy for them to carve out a meaningful existence, but advances in automation, the ease of international shipping, and changes to tax policy have dismantled the opportunities of the past.
Which means that I often find myself seriously debating misinterpretations of Hugh Everett’s “many worlds” theory (described midway through my essay, “Ashes”), or Biblical prophecies, or Jung-like burblings of the collective unconsciousness.
Or, last week, the existence of water cars.
In 2012, government officials from Pakistan announced that a local scientist had invented a process for using water as fuel. At the time, I was still running a webcomic – one week’s Evil Dave vs. Regular Dave focused on news of the invention.
When scientists argue that a water-powered car can’t exist, they typically reference the Second Law of Thermodynamics (also discussed in “Ashes”). The Second Law asserts that extremely unlikely events occur so rarely that you can safely assume their probability to be zero.
If something is disallowed by the Second Law, there’s nothing actually preventing it from happening. For an oversimplified example, imagine there are 10 molecules of a gas randomly whizzing about inside a box. The Second Law says that all 10 will never be traveling in the exact same direction at the same time. If they were, you’d get energy from nothing. They might all strike the north-facing wall at the same time, causing the box to move, instead of an equal number hitting the northern and southern facing walls.
But, just like flipping eight coins and seeing them all land heads, sometimes the above scenario will occur. It violates the Second Law, and it can happen. Perpetual motion machines can exist. They are just very, very rare. (Imagine a fraction where the denominator is a one followed by as many zeros as you could write before you die. That number will be bigger than the chance of a water-fueled car working for even several seconds.)
When chemists talk about fuel, they think about diagrams that look roughly like this:
The y axis on this graph is energy, and the x axis is mostly meaningless – here it’s labeled “reaction coordinate,” but you wouldn’t be so far off if you just think of it as time.
For a gasoline powered car, the term “reactants” refers to octane and oxygen. Combined, these have a higher amount of energy stored in their chemical bonds than an equivalent mass of the “products,” carbon dioxide and water, so you can release energy through combustion. The released energy moves your car forward.
And there’s a hill in the middle. This is generally called the “activation barrier” of the reaction. Basically, the universe thinks it’s a good idea to turn octane and oxygen into CO2 and H2O … but the universe is lazy. Left to its own devices, it can’t be bothered. Which is good – because this reaction has a high activation barrier, we rarely explode while refueling at the gas station.
Your car uses a battery to provide the energy needed to start this process, after which the energy of the first reaction can be used to activate the next. The net result is that you’re soon cruising the highway with nary a care, dribbling water from your tailpipe, pumping carbon into the air.
(Your car also uses a “catalyst” – this component doesn’t change how much energy you’ll extract per molecule of octane, but it lowers the height of the activation barrier, which makes it easier for the car to start. Maybe you’ve heard the term “cold fusion.” If we could harness a reaction combining hydrogen molecules to form helium, that would be a great source of power. Hydrogen fusion is what our sun uses. This reaction chucks out a lot of energy and has non-toxic byproducts.
But the “cold” part of “cold fusion” refers to the fact that, without a catalyst, this reaction has an extremely steep activation barrier. It works on the sun because hydrogen molecules are crammed together at high temperature and pressure. Something like millions of degrees. I personally get all sweaty and miserable at 80 degrees, and am liable to burn myself when futzing about near an oven at 500 degrees … I’d prefer not to drive a 1,000,000 degree hydrogen-fusion-powered automobile.)
With any fuel source, you can guess at its workings by comparing the energy of its inputs and outputs. Octane and oxygen have high chemical energies, carbon dioxide and water have lower energies, so that’s why your car goes forward. Our planet, too, can be viewed as a simple machine. High frequency (blue-ish) light streams toward us from the sun, then something happens here that increases the order of molecules on Earth, after which we release a bunch of low-frequency (red-ish) light.
(We release low-frequency “infrared” light as body heat – night vision goggles work by detecting this.)
Our planet is an order-creating machine fueled by changing the color of photons from the sun.
A water-fueled car is impractical because other molecules that contain hydrogen and oxygen have higher chemical energy than an equivalent mass of water. There’s no energy available for you to siphon away into movement.
If you live next to a concentrated animal feeding operation – facilities that houses thousands of farmed animals in fetid conditions – there’s no point in buying perfume. The smell of animal excrement overwhelms any scent you could wear. If you’re interested in a romantic dalliance, you’ll have to woo people with your looks. Or, sure, conversation. But a charming scent won’t do it.
In other environs, scent contributes to your allure. We humans choose our mates based on a huge number of considerations, including the way people smell. Back in 1995, zoologist Claus Wedekind proposed that human females are most attracted to the scents of men whose immune genes differ from their own.
During college, a friend tried to convince me that the best route to romantic success was Old Spice aftershave. “It reminds women of their fathers,” he said. This is, of course, the opposite theory from Wedekind’s – that females would seek out partners whose scents mirror their own genetic lineage.
But this much is uncontested – by overwhelming our sense of smell, air pollution makes humans less sexy.
We’re not the only animals who use aroma to identify attractive mates. Stick insects can have a wide range of physical appearances, and multiple species sometimes live in overlapping areas. Each subpopulation of stick insects secretes a different mix of oily aromatic chemicals from their skin. These oils protect them from scrapes and dehydration – and help them find mates of their own kind.
If stick insects couldn’t smell, they might mate wantonly.
That’s what happens with fish.
When we pollute water, fish lose the ability to recognize each other. In the same way that humans near a CAFO won’t notice each other’s scents because they can only smell ammonia and sulfurous shit, fish living near human dumping grounds – whether it be farm run-off, factory effluents, or untreated sewage – find their sense of smell overwhelmed.
Many types of fish behave the way my Old-Spice-sporting friend hoped humans would – they seek mates who smell like their forebears. Which they can’t necessarily do in polluted waters. And so fish mate across species. Their chimeric children dissolve the old boundary lines.
Perhaps you thought this couldn’t happen – the traditional definition of a “species” is a population of organisms that can produce fertile offspring only by mating with each other. But the traditional definition is wrong; scientists don’t actually know what a species is. Whatever boundaries exist seem porous. The Neanderthal genes carried by modern Homo sapiens show that humans also mated with other species, at least until we drove our relatives into extinction. Chimpanzees are the closest we have left, sharing 98% of our DNA, but now they’re endangered too.
Although – maybe that’s fine. Not murdering our relations, or endangering the chimps; maybe it’s fine for multiple lineages to merge back into one. I hate to find any virtue in pollution, but dissolving species boundaries doesn’t sound so bad.
Contemporary biology textbooks claim that species boundaries arise whenever subpopulations cease interbreeding. For the “Advanced Placement” biology test, students are expected to know that speciation can be triggered by migration, or a geographic impediment like a new highway, or even cultural barriers.
A strong preference for certain types of scent might qualify as a cultural barrier. Or tropical birds that want their mates to look or dance a certain way. And so would anti-miscegenation laws in the United States. Except for the gene flow provided by pale-skinned rapists, those biology textbooks imply that epidermal melanin concentrations marked a species boundary until the 1960s in the United States.
In the contemporary U.S., parental wealth creates a similar mating barrier. In many parts of the country, children born to rich, well-educated parents rarely even chat with children born to poor people, let alone marry them. This phenomenon has persisted for only a generation or two, which is certainly too brief to create a species division, but shows no sign of abating.
Marrying somebody who shares your interests seems fine. My spouse and I seem to be fairly similar people. And yet – should I be alarmed that my own choice inches us closer toward the world of Metropolis?
Feature image: “Character study, strong smell” by Franz Xaver Messerschmidt.
Despite being rather politically liberal, I consider myself a free market economist.
(Maybe it’s unfair to self-describe as an economist, though? I did the coursework for a master’s degree in economics… but couldn’t get a degree because I didn’t complete the residency requirement. I was enrolled as an undergraduate at the time, and apparently would’ve needed to be enrolled as a graduate student for my coursework to count.)
Sure, there are instances where free markets don’t fare so well — the free market solution to entertainment is for people to pirate whatever they’d like to watch, hear, or read, and then for producers of those media to realize they can never turn a profit. But for many types of commerce, free markets work great.
But, just like the term “pro-life” (I describe myself as pro-life, for instance, which can confuse people because I am a staunch supporter of women’s rights and lives), the words “free market” have taken on a political connotation that doesn’t always gel with actual meaning.
For instance, I promptly began to pout when I read the following paragraphs in James Surowiecki’s New York Review of Books article, “Why the Rich Are So Much Richer“:
The redistributive policies [Joseph] Stiglitz advocates look pretty much like what you’d expect. On the tax front, he wants to raise taxes on the highest earners and on capital gains, institute a carbon tax, and cut corporate subsidies. But dealing with inequality isn’t just about taxation. It’s also about investing. As he puts it, “If we spent more on education, health, and infrastructure, we would strengthen our economy, now and in the future.” So he wants more investment in schools, infrastructure, and basic research.
If you’re a free-market fundamentalist, this sounds disastrous — a recipe for taking money away from the job creators and giving it to the government, which will just waste it on bridges to nowhere. But here is where Stiglitz’s academic work and his political perspective intersect most clearly. The core insight of Stiglitz’s research has been that, left on their own, markets are not perfect, and that smart policy can nudge them in better directions.
A strange turn of phrase.
Sure, it’s reasonable to imagine a free-market fundamentalist kvetching over increased taxes on high earners and capital gains (progressive taxation means that, for anyone outside the bottom tax bracket, choosing to work one additional hour produces income taxed at a higher percentage than the average tax rate being applied to your current income. So the claim is that progressive taxation causes people to work less. This claim is unverified, though, and indeed you could make an equally plausible argument for the opposite: if people want a certain post-tax income, raising tax rates will cause them to work more in order to earn that same amount).
But it’s very strange to write that a free-market fundamentalist would consider it “disastrous” to cut corporate subsidies. How do government handouts to high-fructose corn syrup manufacturers reflect the free market?
They don’t, obviously. But it’s so ingrained in our culture to equate things like “free-market fundamentalist” and “right-wing economist” that even very bright people (I enjoyed the rest of Surowiecki’s article) sometimes make claims about one when they mean the other.
Similarly, I think that someone who self-describes as “pro-life” should be concerned about women’s well-being, would weigh the well-being of a sentient neglected child above that of a pre-sentient fetus, would be an advocate for economic & social justice, would have empathy for livestock subject to torturous existences in CAFOs (concentrated animal feeding operation), would be appalled that environmental harm & climate destabilization is aggravating armed conflict across the globe. Obviously I was thrilled to read Thomas Friedman’s editorial, “Why I Am Pro-Life.” I thought it’d mean I’d get fewer confused looks.
Producing carbon is a negative externality. That means it’s a cost of production that is not inherently paid by the producers — other well-known negative externalities are the raw sewage, bad smells, & concomitant reduced property values brought by CAFOs, or the suddenly poisonous well water in towns adjacent to certain types of coal mines.
For the free market to work properly, negative externalities must be priced through taxation. If not, too many of the associated good are produced and everyone’s utility (“happiness” is a reasonable synonym for the word “utility”) is lower than it could’ve been.
(Well, almost everyone’s — in some cases net utility is lower, and all but one person’s utility drops, but the person operating a mine at below-market rates and poisoning everyone’s water is happier. The mine owner might earn enough that he can afford to buy bottled water, a big house, & a politician or two.)
This is analogous to the well-known “tragedy of the commons,” the idea that if all shepherds have unlimited free access to a shared space, they’ll have their sheep overgraze it. After a few years, the grass is dead & everyone’s sheep starve. Similarly, if we give all corporations unlimited free access to the atmosphere as a garbage bin, each has an incentive to overpollute and kill us all.
If that sounds overdramatic, please read the Easter Island chapter of Jared Diamond’s Collapse. The book’s central message is that environmental disaster obliterates societies, and Easter Island is perhaps the best example of a once-fertile land pillaged by its inhabitants, who then could not survive minor geological shocks. To this day the island is covered by grassy hills & insouciant gods, but it was once densely forested & harbored a variety of plant life. Then the inhabitants chopped down the trees. In Diamond’s words:
I suspect that landscape amnesia provided part of the answer to my UCLA students’ question, “What did the Easter Islander who cut down the last palm tree say as he was doing it?” We unconsciously imagine a sudden change: one year, the island still covered with a forest of tall palm trees being used to produce wine, fruit, and timber to transport and erect statues; the next year, just a single tree left, which an islander proceeds to fell in an act of incredibly self-damaging stupidity. Much more likely, though, the changes in forest cover from year to year would have been almost undetectable: yes, this year we cut down a few trees over there, but saplings are starting to grow back again here on this abandoned garden site. Only the oldest islanders, thinking back to their childhoods decades earlier, could have recognized a difference. Their children could no more have comprehended their parents’ tales of a tall forest than my 17-year-old sons today can comprehend my wife’s and my tales of what Los Angeles used to be like 40 years ago. Gradually, Easter Island’s trees became fewer, smaller, and less important. At the time that the last fruit-bearing adult palm tree was cut, the species had long ago ceased to be of any economic significance. That left only smaller and smaller palm saplings to clear each year, along with other bushes and treelets. No one would have noticed the falling of the last little palm sapling.
Sure, a free-market fundamentalist would bemoan government interventions like a cap & trade system to regulate pollution. I’m a hippy-dippy liberal and I hate the idea of cap & trade, too. But assessing the cost to all for each unit of carbon production, then levying a tax so that corporations know the true consequences of their decisions? That is a free market solution.
Similarly, a free-market fundamentalist should support government subsidies to education, infrastructure, and basic research. Those are all goods with significant positive externalities, meaning each produces benefits that accrue to the population as a whole, not just to the individual who had to pay to build a road. Since the value of these goods to the economy as a whole is undercounted, the correct equilibrium amount won’t be produced unless they are subsidized.
Positive externalities are things like keeping bees. If you keep bees, you get some honey, maybe you get some pleasure by looking at your hive from time to time. But your decision to keep bees also makes all nearby farmland more productive. Because it’d be difficult to track each bee & charge each nearby farmer for every flower fertilized by one of your bees, it’s more sensible to simply subsidize beekeeping (with perhaps some restrictions on where you’re keeping bees — if you’re living in the middle of a city, your bees might not be helping much).
Similarly, if you educate children, employers gain access to a more competent workforce, citizens gain more pleasant neighbors, often less needs to be spent on policing & prisons a few years down the line. Government-funded research made possible our wireless technologies, the internet, microwave ovens — & these make everyone’s lives more efficient. The free-market solution that compensates the researchers who gave us all these near-magical technologies is to subsidize their research.
The other common solution, the one that is not a free-market approach but is favored by many right-wing politicians, is to grant patent protections, artificially disallowing all but one corporation from producing any of a good.
That type of distinction is why it saddens me to see habitual misuse of words or phrases as slogans lend them a connotation that’s so different from their actual meaning. Especially because, in the case of something like “free market” or “pro-life,” the distinction changes the world in appreciable ways. Like, okay, if everybody wants to use the word “peruse” to mean “skim,” of if everybody wants to use the word “fortuitous” to mean “fortunate,” I’ll just stop using those words. I don’t want to use them incorrectly, but I don’t want to confuse anyone, either. But “free market” and “pro-life” are such big, emotionally-charged concepts that I get upset about political efforts to commandeer them.