On predictions and a scientific response to calamity.

On predictions and a scientific response to calamity.

We’re fast approaching flu season, which is especially harrowing this year.

We, as a people, have struggled to respond to this calamity. We have a lot of scientific data about Covid-19 now, but science is never value-neutral. The way we design experiments reflects our biases; the way we report our findings, even more so.

For example, many people know the history of Edward Jenner inventing the world’s first vaccine. Fewer are aware of the long history of inoculation in Africa (essentially, low-tech vaccination) that preceded Jenner’s work.

So it’s worthwhile taking a moment to consider the current data on Covid-19.

Data alone can’t tell us what to do – the course of action we choose will reflect our values as a society. But the data may surprise a lot of people – which is strange considering how much we all feel that we know about Covid-19.

Indeed, we may realize that our response so far goes against our professed values.

Spoiler: I think we shouldn’t close in-person school.

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Since April, I’ve written several essays about Covid-19. In these, I’ve made a number of predictions. It’s worthwhile to consider how accurate these predictions have been.

This, after all, is what science is. We use data to make an informed prediction, and then we collect more data to evaluate how good our prediction was.

Without the second step – a reckoning with our success or failure – we’re just slinging bullshit.

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I predicted that our PCR tests were missing most Covid-19 infections, that people’s immunity was likely to be short-lived (lasting for months, not years), and that Covid-19 was less dangerous than seasonal influenza for young people.

These predictions have turned out to be correct.

In my essays, I’ve tried to unpack the implications of each of these. From the vantage of the present, with much more data at our disposal, I still stand by what I’ve written.

But gloating’s no fun. So I’d rather start with what I got wrong.

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My initial predictions about Covid-19 were terrible.

I didn’t articulate my beliefs at the time, but they can be inferred from my actions. In December, January, and February, I made absolutely no changes to my usual life. I didn’t recommend that travelers be quarantined. I didn’t care enough to even follow the news, aside from a cursory glance at the headlines.

While volunteering with the high school running team, I was jogging with a young man who was finishing up his EMT training.

“That new coronavirus is really scary,” he said. “There’s no immunity, and there’s no cure for it.”

I shrugged. I didn’t know anything about the new coronavirus. I talked with him about the 1918 influenza epidemic instead.

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I didn’t make any change in my life until mid-March. And even then, what did I do?

I called my brother and talked to him about the pizza restaurant – he needed a plan in case there was no in-person dining for a few months.

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My next set of predictions were off, but in the other direction – I estimated that Covid-19 was about four-fold more dangerous than seasonal influenza. The current best estimate from the CDC is that Covid-19 is about twice as dangerous, with an infection fatality ratio of 0.25%.

But seasonal influenza typically infects a tenth of our population, or less.

We’re unlikely to see a significant disruption in the transmission of Covid-19 (this is the concept of “herd immunity”) until about 50% of our population has immunity from it, whether from vaccination or recovery. Or possibly higher – in some densely populated areas, Covid-19 has spread until 70% (in NYC) or even 90% (in prisons) of people have contracted the disease.

Population density is hugely important for the dynamics of Covid-19’s spread, so it’s difficult to predict a nation-wide threshold for herd immunity. For a ballpark estimate, we could calculate what we’d see with a herd immunity threshold of about 40% in rural areas and 60% in urban areas.

Plugging in some numbers, 330 million people, 80% urban population, 0.25% IFR, 60% herd immunity threshold in urban areas, we’d anticipate 450,000 deaths.

That’s about half of what I predicted. And you know what? That’s awful.

Each of those 450,000 is a person. Someone with friends and family. And “slow the spread” doesn’t help them, it just stretches our grieving to encompass a whole year of tragedy instead of a horrific month of tragedy.

If we don’t have a safe, effective vaccine soon enough, the only way to save some of those 450,000 people is to shift the demographics of exposure.

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Based on the initial data, I concluded that the age demographics for Covid-19 risk were skewed more heavily toward elderly people than influenza risk.

I may have been wrong.

It’s difficult to directly compare the dangers of influenza to the dangers of Covid-19. Both are deadly diseases. Both result in hospitalizations and death. Both are more dangerous for elderly or immunocompromised people, but both also kill young, healthy people.

Typically, we use an antigen test for influenza and a PCR-based test for Covid-19. The PCR test is significantly more sensitive, so it’s easier to determine whether Covid-19 is involved a person’s death. If there are any viral particles in a sample, PCR will detect them. Whereas antigen tests have a much higher “false negative” rate.

Instead of using data from these tests, I looked at the total set of pneumonia deaths. Many different viruses can cause pneumonia symptoms, but the biggest culprits are influenza and, in 2020, Covid-19.

So I used these data to ask a simple question – in 2020, are the people dying of pneumonia disproportionately more elderly than in other years?

I expected that they would be. That is, after all, the prediction from my claims about Covid-19 demographic risks.

I was wrong.

In a normal year (I used the data from 2013, 2014, and 2015, three years with “mild” seasonal influenza), 130,000 people die of flu-like symptoms.

In 2020 (at the time I checked), 330,000 people have died of flu-like symptoms. Almost three times as many people as in a “normal” year.

For people under the age of 18, we’ve seen the same number of deaths (or fewer) in 2020 as in other years. The introduction of Covid-19 appears to have caused no increased risk for these people.

But for people of all other ages, there have been almost three times as many people dying of these symptoms in 2020 compared to other years.

In most years, one thousand people aged 25-34 die of these symptoms; in 2020, three thousand have died. In most years, two thousand people aged 35-44 die of these symptoms; in 2020, six thousand have died. This same ratio holds for all ages above eighteen.

Younger people are at much less risk of harm from Covid-19 than older people are. But, aside from children under the age of eighteen, they don’t seem to be exceptionally protected.

Of course, my predictions about the age skew of risk might be less incorrect than I’m claiming here. If people’s dramatically altered behavior in 2020 has changed the demographics of exposure as compared to other years – which is what we should be doing to save the most lives – then we could see numbers like this even if Covid-19 had the risk skew that I initially predicted.

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I predicted that four or more years would pass before we’d be able to vaccinate significant numbers of people against Covid-19.

I sure hope that I was wrong!

We now know that it should be relatively easy to confer immunity to Covid-19. Infection with other coronaviruses, including those that cause common colds, induce the production of protective antibodies. This may partly explain the low risk for children – because they get exposed to common-cold-causing coronaviruses so often, they may have high levels of protective antibodies all the time.

Several pharmaceutical companies have reported great results for their vaccine trials. Protection rates over 90%.

So the problem facing us now is manufacturing and distributing enough doses. But, honestly, that’s the sort of engineering problem that can easily be addressed by throwing money at it. Totally unlike the problem with HIV vaccines, which is that the basic science isn’t there – we just don’t know how to make a vaccine against HIV. No amount of money thrown at that problem would guarantee wide distribution of an effective vaccine.

We will still have to overcome the (unfortunately significant) hurdle of convincing people to be vaccinated.

For any individual, the risk of Covid-19 is about twice the risk of seasonal influenza. But huge numbers of people choose not to get a flu vaccine each year. In the past, the United States has had a vaccination rate of about 50%. Here’s hoping that this year will be different.

Covid-19 spreads so fast – and so silently, with many cases of infected people who feel fine but are still able to spread the virus – that it will almost certainly be a permanent resident of the world we live in. We’re unlikely to eradicate Covid-19.

Which means that elderly people will always be at risk of dying from Covid-19.

The only way to protect people whose bodies have gone through “age-related immunosenence” – the inevitable weakening of an immune system after a person passes the evolutionarily-determined natural human lifespan of about 75 years – will be to vaccinate everybody else.

Depending on how long vaccine-conferred immunity lasts, we may need to vaccinate people annually. I worry, though, that it will become increasingly difficult to persuade people to get a Covid-19 vaccine once the yearly death toll drops to influenza-like levels – 50,000 to 100,000 deaths per year in the United States.

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I wrote, repeatedly, that immunity to Covid-19 is likely to be short-lived. Immunity to other coronaviruses fades within a few months.

(Note: you may have seen articles in the New York Times suggesting that we’ll have long-lasting protection. They’re addressing a different question — after recovery, or vaccination, are you likely to become severely ill with Covid-19? And the answer is “probably not,” although it’s possible. When I discuss immunity here, I mean “after recovery, or vaccination, are you likely to be able to spread the virus after re-infection?” And the answer is almost certainly “yes, within months.”)

And I wrote about the interplay between short-lived immunity and the transmission dynamics of an extremely virulent, air-born virus.

This is what the Harvard public health team got so wrong. When we slow transmission enough that a virus is still circulating after people’s immunity wanes, they can get sick again.

For this person, the consequences aren’t so dire – an individual is likely to get less sick with each subsequent infection by a virus. But the implications for those who have not yet been exposed are horrible. The virus circulates forever, and people with naive immune systems are always in danger.

It’s the same dynamics as when European voyagers traveled to the Americas. Because the European people’s ancestors lived in unsanitary conditions surrounded by farm animals, they’d cultivated a whole host of zoogenic pathogens (like influenza and this new coronavirus). The Europeans got sick from these viruses often – they’d cough and sneeze, have a runny nose, some inflammation, a headache.

In the Americas, there were fewer endemic diseases. Year by year, people wouldn’t spend much time sick. Which sounds great, honestly – I would love to go a whole year without headaches.

But then the disgusting Europeans reached the Americas. The Europeans coughed and sneezed. The Americans died.

And then the Europeans set about murdering anyone who recovered. Today, descendants of the few survivors are made to feel like second-class citizens in their ancestral homelands.

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In a world with endemic diseases, people who have never been exposed will always be at risk.

That’s why predictions made in venues such as the August New York Times editorial claiming that a six- to eight-week lockdown would stop Covid-19 were so clearly false. They wrote:

Six to eight weeks. That’s how long some of the nation’s leading public health experts say it would take to finally get the United States’ coronavirus epidemic under control.

For proof, look at Germany. Or Thailand. Or France.

Obviously, this didn’t work – in the presence of an endemic pathogen, the lockdowns preserved a large pool of people with naive immune systems, and they allowed enough time to pass that people who’d been sick lost their initial immunity. After a few months of seeming calm, case numbers rose again. For proof, look at Germany. Or France.

Case numbers are currently low in Thailand, but a new outbreak could be seeded at any time.

And the same thing is currently happening in NYC. Seven months after the initial outbreak, immunity has waned; case numbers are rising; people with mild second infections might be spreading the virus to friends or neighbors who weren’t infected previously.

All of which is why I initially thought that universal mask orders were a bad idea.

We’ve known for over a hundred years that masks would slow the spread of a virus. The only question was whether slowing the spread of Covid-19 would cause more people to die of Covid-19.

And it would – if a vaccine was years away.

But we may have vaccines within a year. Which means that I may have been wrong. Again, the dynamics of Covid-19 transmission are still poorly understood – I’ll try to explain some of this below.

In any case, I’ve always complied with our mask orders. I wear a mask – in stores, at school pickup, any time I pass within six feet of people while jogging.

To address global problems like Covid-19 and climate change, we need global consensus. One renegade polluting wantonly, or spewing viral particles into the air, could endanger the whole world. This is precisely the sort of circumstance where personal freedom is less important than community consensus.

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The transmission dynamics of Covid-19 are extremely sensitive to environment. Whether you’re indoors or outdoors. How fast the air is moving. The population density. How close people are standing. Whether they’re wearing masks. Whether they’re shouting or speaking quietly.

Because there are so many variable, we don’t have good data. My father attended a lecture and a colleague (whom he admires) said, “Covid-19 is three-fold more infectious than seasonal influenza.” Which is bullshit – the transmission dynamics are different, so the relative infectivity depends on our behaviors. You can’t make a claim like this.

It’s difficult to measure precisely how well masks are slowing the spread of this virus.

But here’s a good estimate: according to Hsiang et al., the number of cases of Covid-19, left unchecked, might have increased exponentially at a rate of about 34% per day in the United States.

That’s fast. If about 1% of the population was infected, it could spread to everyone within a week or two. In NYC, Covid-19 appear to spread to over 70% of the population within about a month.

(To estimate the number of infections in New York City, I’m looking at the number of people who died and dividing by 0.004 – this is much higher than the infection fatality rate eventually reported by the CDC, but early in the epidemic, we were treating people with hydroxychloraquine, an unhelpful poison, and rushing to put people on ventilators. We now know that ventilation is so dangerous that it should only be used as a last resort, and that a much more effective therapy is to ask people to lie on their stomachs – “proning” makes it easier to get enough oxygen even when the virus has weakened a person’s lungs.)

Masks dramatically slow the rate of transmission.

A study conducted at a military college – where full-time mask-wearing and social distancing were strictly enforced – showed that the number of cases increased from 1% to 3% of the population over the course of two weeks.

So, some math! Solve by taking ten to the power of (log 3)/14, which gives an exponential growth rate of 8% per day. Five-fold slower than without masks.

But 8% per day is still fast.

Even though we might be able to vaccinate large numbers of people by the end of next year, that’s not soon enough. Most of us will have been sick with this – at least once – before then.

I don’t mean to sound like a broken record, but the biggest benefit of wearing masks isn’t that we slow the rate of spread for everyone — exponential growth of 8% is still fast — but that we’re better able to protect the people who need to be protected. Covid-19 is deadly, and we really don’t want high-risk people to be infected with it.

I’ve tried to walk you through the reasoning here — the actual science behind mask policies — but also, in case it wasn’t absolutely clear: please comply with your local mask policy.

You should wear a mask around people who aren’t in your (small) network of close contacts.

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I’m writing this essay the day after New York City announced the end of in-person classes for school children.

This policy is terrible.

A major problem with our response to Covid-19 is that there’s a time lag between our actions and the consequences. Human brains are bad at understanding laggy data. It’s not our fault. Our ancestors lived in a world where they’d throw a spear at an antelope, see the antelope die, and then eat it. Immediate cause and effect makes intuitive sense.

Delayed cause and effect is tricky.

If somebody hosts a party, there might be an increase in the number of people who get sick in the community over the next three weeks. Which causes an increase in the number of hospitalizations about two weeks after that. Which causes people to die about three weeks after that.

There’s a two-month gap between the party and the death. The connection is difficult for our brains to grasp.

As a direct consequence, we’ve got ass-hats and hypocrites attending parties for, say, their newly appointed Supreme Court justice.

But the problem with school closures is worse. There’s a thirty year gap between the school closure and the death. The connection is even more difficult to spot.

Even if you have relatively limited experience reading scientific research papers, I think you could make your way through this excellent article from Chistakis et al.

The authors link two sets of existing data: the correlation between school closures and low educational achievement, and the correlation between low educational achievement and premature death.

The public debate has pitted “school closures” against “lives saved,” or the education of children against the health of the community. Presenting the tradeoffs in this way obscures the very real health consequences of interrupted education.

These consequences are especially dire for young children.

The authors calculate that elementary school closures in the United States might have (already!) caused 5.5 million years of life lost.

Hsiang et al. found that school closures probably gave us no benefit in terms of reducing the number of Covid-19 cases, because children under 18 aren’t significant vectors for transmission (elementary-aged children even less so), but even if school closures had reduced the number of Covid-19 cases, closing schools would have caused more total years of life to be lost than saved.

The problem – from a political standpoint – is that Covid-19 kills older people, who vote, whereas school closures kill young people, who are intentionally disenfranchised.

And, personally, as someone with far-left political views, it’s sickening for me to see “my” political party adopt policies that are so destructive to children and disadvantaged people.

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So, here’s what the scientific data can tell us so far:

  • We will eventually have effective vaccines for Covid-19. Probably within a year.
  • Covid-19 spreads even with social distancing and masks, but the spread is slower.
  • You have no way of knowing the risk status of people in a stranger’s bubble. (Please, follow your local mask orders!)
  • Schools – especially elementary schools – don’t contribute much to the spread of Covid-19.
  • School closures shorten children’s lives (and that’s not even accounting for their quality of life over the coming decades).
  • An individual case of Covid-19 is about twice as dangerous as a case of seasonal influenza (which is scary!).
  • Underlying immunity (from prior disease and vaccination) to Covid-19 is much lower than for seasonal influenza, so there will be many more cases.
  • Most people’s immunity to Covid-19 probably lasts several months, after which a person can be re-infected and spread the virus again.

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So, those are some data. But data don’t tell us what to do. Only our values can do that.

Personally, I value the lives of children.

I wouldn’t close schools.

On threat.

On threat.

At the end of “Just Use Your Thinking Pump!”, a lovely essay that discusses the evolution (and perhaps undue elevation) of a particular set of practices now known as the scientific method, Jessica Riskin writes:

Covid-19 has presented the world with a couple of powerful ultimatums that are also strikingly relevant to our subject here. The virus has said, essentially, Halt your economies, reconnect science to a whole understanding of yourself and the world, or die.

With much economic activity slowed or stopped to save lives, let us hope governments find means to sustain their people through the crisis.

Meanwhile, with the din of “innovation” partially silenced, perhaps we can also use the time to think our way past science’s branding, to see science once again as integral to a whole, evolving understanding of ourselves and the world.

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True, the world has presented us with an ultimatum. We must halt our economies, reconnect science to a whole understanding of ourselves and our world, or die.

Riskin is a professor at Stanford. Her skies are blackened with soot. In the words of Greta Thunberg, “Our house is on fire.

For many years, we’ve measured the success of our economy in terms of growth. The idea that we can maintain perpetual growth is a delusion. It’s simple mathematics. If the amount of stuff we manufacture – telephones, televisions, air conditioners – rises by 3% each and every year, we’ll eventually reach stratospheric, absurd levels.

In the game “Universal Paperclips,” you’re put in control of a capitalist system that seeks perpetual growth. If you succeed, you’ll make a lot of paperclips! And you will destroy the planet.

Here in the real world, our reckless pursuit of growth has (as yet) wrought less harm, but we’ve driven many species to extinction, destroyed ancient forests, and are teetering at the precipice of cataclysmic climate change. All while producing rampant inequality with its attendant abundance of human misery.

We must reconnect science to a whole understanding of ourselves and the world, or die.

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We are in danger. But Covid-19 isn’t the major threat we’re facing.

I consider myself to be more cautious than average – I would never ride a bicycle without a helmet – and I’m especially cautious as regards global pandemic. Antibiotic resistance is about to be a horrific problem for us. Zoogenic diseases like Covid-19 will become much more common due to climate change and increased human population.

I’m flabbergasted that these impending calamities haven’t caused more people to choose to be vegan. It seems trivial – it’s just food – but a vegan diet is one of our best hopes for staving off antibiotic resistant plagues.

A vegan diet would have prevented Covid-19. Not that eating plants will somehow turbocharge your immune system – it won’t – but this pandemic originated from a meat market.

And a vegan diet will mitigate your contribution to climate change, which has the potential to cause the full extinction of the human race.

Make our planet uninhabitable? We all die. Make our planet even a little less habitable, which leads to violent unrest, culminating in warring nations that decide to use nukes? Yup, that’s another situation where we all die.

By way of contrast, if we had made no changes in our lives during the Covid-19 pandemic – no shutdown, no masks, no social distancing, no PCR tests, no contact tracing, no quarantines – 99.8% of our population would have survived.

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Indeed, we often discuss the Covid-19 crisis in a very imprecise way. We say that Covid-19 is causing disruptions to learning, that it’s causing domestic violence or evictions. On the front page of Sunday’s New York Times business section, the headline reads, “The Other Way that Covid Kills: Hunger.

Covid-19 is a serious disease. We need to do our best to avoid exposing high-risk people to this virus, and we should feel ashamed that we didn’t prioritize the development of coronavirus vaccines years ago.

But there’s a clear distinction between the harms caused by Covid-19 (hallucinogenic fevers, cardiac inflammation, lungs filling up with liquid until a person drowns, death) and the harms caused by our response to Covid-19 (domestic violence, educational disruption, starvation, reduced vaccination, delayed hospital visits, death).

Indeed, if the harms caused by our response to Covid-19 are worse than the harms caused by Covid-19 itself, we’re doing the wrong thing.

In that New York Times business article, Satbir Singh Jatain, a third-generation farmer in northern India, is quoted: “The lockdowns have destroyed farmers. Now, we have no money to buy seeds or pay for fuel. …. soon they will come for my land. There is nothing left for us.

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Covid-19 is awful. It’s a nasty disease. I’m fairly confident that I contracted it in February (before PCR tests were available in the United States), and my spouse says it’s the sickest she’s ever seen me.

Yes, I’d done something foolish – I was feeling a little ill but still ran a kilometer repeat workout with the high school varsity track team that I volunteer with. High intensity workouts are known to cause temporary immunosuppression, usually lasting from 3 to 72 hours.

My whole family got sick, but I fared far worse than the others.

It was horrible. I could barely breathe. Having been through that, it’s easy to understand how Covid-19 could kill so many people. I wouldn’t wish that experience on anyone.

And I have very low risk. I don’t smoke. I don’t have diabetes. I’m thirty-seven.

I wish it were possible to protect people from this.

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Obviously, we should have quarantined all international travelers beginning in December 2019. Actually, ten days probably would have been enough. We needed to diecitine all international travelers.

By February, we had probably allowed Covid-19 to spread too much to stop it.

By February, there were probably enough cases that there will always be a reservoir of this virus among the human species. 80% of people with Covid-19 feel totally fine and don’t realize they might be spreading it. By talking and breathing, they put viral particles into the air.

By the end of March, we were much, much too late. If you look at the numbers from New York City, it’s pretty clear that the preventative measures, once enacted, did little. Given that the case fatality rate is around 0.4%, there were probably about 6 million cases in New York City – most of the population.

Yes, it’s possible that New York City had a somewhat higher case fatality rate. The case fatality rate depends on population demographics and standard of care – the state of New York had an idiotic policy of shunting Covid-19 patients into nursing homes, while banning nursing homes from using Covid-19 PCR tests for these patients, and many New York doctors were prescribing hydroxychloroquine during these months, which increases mortality – but even if the case fatality rate in New York City was as high as 0.6%, a majority of residents have already cleared the virus by now.

The belated public health measures probably didn’t help. And these health measures have caused harm – kids’ schooling was disrupted. Wealthy people got to work from home; poor people lost their jobs. Or were deemed “essential” and had to work anyway, which is why the toll of Covid-19 has been so heavily concentrated among poor communities.

The pandemic won’t end until about half of all people have immunity, but a shutdown in which rich people get to isolate themselves while poor people go to work is a pretty shitty way to select which half of the population bears the burden of disease.

I am very liberal. And it’s painful to see that “my” political party has been advocating for policies that hurt poor people and children during the Covid-19 pandemic.

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Because we did not act soon enough, Covid-19 won’t end until an appreciable portion of the population has immunity – at the same time.

As predicted, immunity to Covid-19 lasts for a few months. Because our public health measures have caused the pandemic to last longer than individual immunity, there will be more infections than if we’d done nothing.

The shutdowns, in addition to causing harm on their own, will increase the total death toll of Covid-19.

Unless – yes, there is a small glimmer of hope here – unless we soon have a safe, effective vaccine that most people choose to get.

This seems unlikely, though. Making vaccines is difficult. And we already know that most people don’t get the influenza vaccine, even though, for younger people, influenza is more dangerous than Covid-19.

Look – this is shitty. I get an influenza vaccine every year. It’s not just for me – vaccination protects whole communities.

Economist Gregory Mankiw believes that we should pay people for getting a Covid-19 vaccine.

Yes, there are clear positive externalities to vaccination, but I think this sounds like a terrible idea. Ethically, it’s grim – the Covid-19 vaccines being tested now are a novel type, so they’re inherently more risky than other vaccines. By paying people to get vaccinated, we shift this burden of uncertainty onto poor communities.

We already do this, of course. Drug trials use paid “volunteers.” Especially phase 1 trials – in which drugs are given to people with no chance of medical benefit, only to see how severe the side effects are – the only enrollees are people so poor that the piddling amounts of money offered seem reasonable in exchange for scarfing an unknown, possibly poisonous medication.

Just because we already do an awful thing doesn’t mean we should make the problem worse.

And, as a practical matter, paying people to do the right thing often backfires.

In An Uncertain Glory, Jean Dreze and Amartya Sen write:

To illustrate, consider the recent introduction, in many Indian states, of schemes of cash incentives to curb sex-selective abortion. The schemes typically involve cash rewards for the registered birth of a girl child, and further rewards if the girl is vaccinated, sent to school, and so on, as she gets older.

These schemes can undoubtedly tilt economic incentives in favor of girl children. But a cash reward for the birth of a girl could also reinforce people’s tendency to think about family planning in economic terms, and also their perception, in the economic calculus of family planning, that girls are a burden (for which cash rewards are supposed to compensate).

Further, cash rewards are likely to affect people’s non-economic motives. For instance, they could reduce the social stigma attached to sex-selective abortion, by making it look like some sort of ‘fair deal’ — no girl, no cash.

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What happens if it takes a few years before there are sufficient doses of an effective vaccine that people trust enough to actually get?

Well, by then the pandemic will have run its course anyway. Masks reduce viral transmission, but they don’t cut transmission to zero. Even in places where everyone wears masks, Covid-19 is spreading, just slower.

I’ve been wearing one – I always liked the Mortal Kombat aesthetic. But I’ve been wearing one with the unfortunate knowledge that masks, by prolonging the pandemic, are increasing the death toll of Covid-19. Which is crummy. I’ve chosen to behave in a way that makes people feel better, even though the science doesn’t support it.

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We, as a people, are in an awful situation right now. Many of us are confronting the risk of death in ways that we have not previously.

In The Rise and Fall of American Growth, Robert Gordon writes:

More than 37 percent of deaths in 1900 were caused by infectious diseases, but by 1955, this had declined to less than 5 percent and to only 2 percent by 2009.

Of course, this trend will still hold true in 2020. In the United States, there have been about 200,000 Covid-19 deaths so far, out of 2,000,000 deaths total this year. Even during this pandemic, less than 1% of deaths are caused by Covid-19.

And I’m afraid. Poverty is a major risk factor for death of all causes in this country. Low educational attainment is another risk factor.

My kids am lucky to live in a school district that has mostly re-opened. But many children are not so fortunate. If we shutter schools, we will cause many more deaths – not this year, but down the road – than we could possibly prevent from Covid-19.

Indeed, school closures, by prolonging the pandemic (allowing people to be infected twice and spread the infection further), will increase the death toll from Covid-19.

School closures wouldn’t just cause harm for no benefit. School closures would increase the harm caused by Covid-19 and by everything else.

On testing.

On testing.

UPDATE: Wow, this got a lot of readers! Honestly, though, I wrote a response to common questions and comments about this essay and it is probably a better read.

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My spouse recently sent me a link to the article “Concerns with that Stanford study of coronavirus prevalence” by Andrew Gelman, a statistician at Columbia University.  From reading this article, I got the impression that Gelman is a good mathematician.  And he raises some legitimate concerns. 

But I’ve noticed that many of the people criticizing the work coming out of the Ioannidis group – such as the study of how many people in Santa Clara county might have antibodies to Covid-19 – don’t seem to understand the biology underlying the numbers.

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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.

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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. 

That’s shocking. 

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. 

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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.

Many people have been put on ventilators, but that’s often the beginning of the end.  Most people put on ventilators will die.  Among patients over 70 years old, three quarters who are put on ventilators will 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.

Or, consider: cigarette smoking causes 480,000 deaths per year in the United States, including 41,000 people who die from second-hand smoke exposure.  Those 41,000 aren’t even choosing to smoke!  But cigarettes kill them anyway.

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 air quality 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.

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So, Covid-19.  We know how many people have died – already (CORRECTION AS OF APRIL 21) forty-two thousand in the United States

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.

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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.

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When we look at the age demographics for Covid-19 infections as measured by PCR test, the undercount becomes glaringly obvious.

Consider the PCR test data from the Diamond Princess cruise ship.  To date, this is our most complete set of PCR data – everyone on board was tested multiple times.  And from this data, it appears that very few children were exposed to the virus.

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.)

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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.

It can be dangerous to use antibody tests to address the wrong questions.

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.

The PCR test measured 23 cases.  The antibody test suggested there’d been at least 600.  And antibody tests, by design, will generally have a bunch of false negatives.  When a team at Stanford assessed the antibody tests manufactured by Premier Biotech in Minneapolis, they found that for every 3 people who’d been infected with Covid-19, the tests registered only 2 positives.

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.

And it’s why the data from the Stanford Santa Clara county study is so unsurprising. 

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.

If access to health care were considered a basic right in the United States, we might’ve done something like this. 

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In Italy, it seems like Covid-19 is three- or four-fold more dangerous than seasonal influenza.  My guess is that Italy might have had about 50,000 deaths if they hadn’t enacted the lockdown.

In the United States, on a population level, Covid-19 is probably also more dangerous than seasonal influenza.  But there’s a big difference in terms of the distribution of risk.

The New York Times is running a series with short biographies of people who’ve died of Covid-19.  As of noon on April 17, about 10% of the people profiled were younger than 35.

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. 

Indeed, when a team of researchers from Harvard’s School of Public Health modeled the Covid-19 epidemic, they found that social distancing was generally unhelpful.  That’s what their data show, at least – but in their abstract, they instead recommend that we continue social distancing for the better part of two years.

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.

But, unfortunately, there’s a problem.  Research done with other coronaviruses shows that immunity fades within a year.  Because the Harvard model would cause the epidemic to last longer than a year, people would have time to lose their immunity and get infected again.

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.  

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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.

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UPDATE: Wow, this got a lot of readers! Thanks if you made it this far. I’ve also written a response to common questions and comments about this essay.