Tag: Covid testing

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 money, nursing home care, and Covid-19.

In April, I wrote several essays and articles about our collective response to Covid-19.

I was worried – and am still worried, honestly – that we weren’t making the best choices.

It’s hard not to feel cynical about the reasons why we’ve failed. For instance, our president seems more concerned about minimizing the visibility of disaster than addressing the disaster itself. We didn’t respond until this virus had spread for months, and even now our response has become politicized.

Also, the best plans now would include a stratified response based on risk factor. Much more than seasonal influenza, the risk of serious complications from Covid-19 increases with age. Because we didn’t act until the virus was widespread, eighty-year-olds should be receiving very different recommendations from forty- and fifty-year-olds.

Our national response is being led by an eighty-year-old physician, though, and he might be biased against imposing exceptional burdens on members of his own generation (even when their lives are at stake) and may be less sensitive to the harms that his recommendations have caused younger people.

I’m aware that this sounds prejudiced against older folks. That’s not my intent.

I care about saving lives.

Indeed, throughout April, I was arguing that our limited Covid-19 PCR testing capacity shouldn’t be used at hospitals. These tests were providing useful epidemiological data, but in most cases the results weren’t relevant for treatment. The best therapies for Covid-19 are supportive care – anti-inflammatories, inhalers, rest – delivered as early as possible, before a patient has begun to struggle for breath and further damage their lungs. Medical doctors provided this same care whether a Covid-19 test came back positive or negative.

(Or, they should have. Many patients were simply sent home and told to come back if they felt short of breath. Because they didn’t receive treatment early enough, some of these patients then died.)

Instead, our limited testing capacity should have been used at nursing homes. We should have been testing everyone before they went through the doors of a nursing home, because people in nursing homes are the most vulnerable to this virus.

I realize that it’s an imposition to make people get tested before going in, either for care or to work – even with real-time reverse-transcription PCR, you have to wait about two hours to see the results. But the inconvenience seems worthwhile, because it would save lives.

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From March 25 until May 10 – at the same time that I was arguing that our limited Covid-19 tests be used at nursing homes instead of hospitals – the state of New York had a policy stating that nursing homes were prohibited from testing people for Covid-19.

I really dislike the phrase “asymptomatic transmission” – it’s both confusing and inaccurate, because viral shedding is itself a symptom – but we knew early on that Covid-19 could be spread by people who felt fine. That’s why we should have been using PCR tests before letting people into nursing homes.

But in New York, nursing homes were “prohibited from requiring a hospitalized resident who is determined medically stable to be tested for COVID-19 prior to admission or readmission.”

This policy caused huge numbers of deaths.

Not only do nursing homes have the highest concentration of vulnerable people, they also have far fewer resources than hospitals with which to keep people safe. Nursing home budgets are smaller. Hallways are narrower. Air circulation is worse. The workers lack protective gear and training in sterile procedure. Nursing home workers are horrendously underpaid.

The low wages of nursing home workers aren’t just unethical, they’re dangerous. A recent study found that higher pay for nursing home workers led to significantly better health outcomes for residents.

This study’s result as described in the New York Times – “if every county increased its minimum wage by 10 percent, there could be 15,000 fewer deaths in nursing homes each year” – is obviously false. But even though the math doesn’t work out, raising the minimum wage is the right thing to do.

If we raised the minimum wage, we probably would have a few years in which fewer people died in nursing homes. But then we’d see just as many deaths.

Humans can’t live forever. With our current quality of care, maybe nursing home residents die at an average age of 85. If we raise the minimum wage, we’ll get better care, and then nursing home residents might die at an average age of 87. After two years, we’d reach a new equilibrium and the death rate would be unchanged from before.

But the raw number here – how many people die each year – isn’t our biggest concern. We want people to be happy, and an increase in the minimum wage would improve lives: both nursing home residents and workers. Which I’m sure that study’s lead author, economist Kristina Ruffini, also believes. The only problem is that things like “happiness” or “quality of life” are hard to quantify.

Especially when you’re dealing with an opposition party that argues that collective action can never improve the world, you have to focus on quantifiable data. Happiness is squishy. A death is unassailable.

Indeed, that’s partly why we’ve gotten our response to Covid-19 wrong. Some things are harder to measure than others. It’s easy to track the number of deaths caused by Covid-19. (Or at least, it should be – our president is still understating the numbers.)

It’s much harder to track the lives lost to fear, to domestic violence, and to despair (no link for this one – suddenly Fox News cares about “deaths of despair,” only because they dislike the shutdown even more than they dislike poor people).  It’s hard to put a number on the value of 60 million young people’s education.

But we can’t discount the parts of our lives that are hard to measure – often, they’re the most important.

Responses to “On testing.”

Responses to “On testing.”

My spouse posted my previous essay on social media, and I’d like to address some of people’s comments.  There were some excellent points! 

My apologies if I failed to address everything that people said, but I tried my best.

Scroll to find my responses to:

  1. A shutdown could have prevented the Covid-19 epidemic.
  2. We know that the current shutdown is either delaying or preventing deaths due to Covid-19. 
  3. Ending this epidemic with a vaccine would be ideal. 
  4. Ending the shutdown while requesting that at-risk people continue to self-isolate would save lives.
  5. Why is it urgent to end the shutdown soon?
  6. Why might more people die of Covid-19 just because we are slowing the spread of the virus?
  7. How is the shutdown causing harm?
  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?
  9. Don’t the antibody tests have a lot of false positives?
  10. What about the political ramifications of ending the shutdown?

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1: “A shutdown could have prevented the Covid-19 epidemic.”

If we’d acted early enough, we could have isolated all cases of Covid-19 and prevented this whole debacle.

But we didn’t.

Covid-19 is highly infectious, and we made no effort toward containment or quarantine until the virus was already widespread.  We took action in March, but we already had community transmission of Covid-19 by January.  Given where we are now, current models predict that the epidemic will continue until the level of immunity reaches somewhere near 70%.

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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.

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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.

Yes, the influenza vaccine tends to be less effective than many others – some years it gives as little as ten percent protection, other years about sixty percent protection.  By way of comparison, the HPV vaccine has over 90% efficacy.

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.

Also, the efficacy of influenza vaccines is measured in terms of the likelihood that vaccination prevents infection.  The influenza vaccine is not great at keeping people from getting sick.  But vaccination also tends to reduce the severity of your illness, even if you do catch influenza.  Because you got sick, it seems as though the vaccine “failed,” but your case might have been far more severe if you hadn’t been vaccinated.

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.

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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 air pollution 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.

Stores will need to set aside morning hours for at-risk shoppers, and undertake rigorous cleaning at night.  We know that infectious viral particles can persist for days on a variety of surfaces.

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).

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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.

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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.

We’ve seen that immunity to other coronaviruses fades within a year.  If immunity to Covid-19 is similar, we really don’t want to prolong the epidemic past a year.

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.

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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.

At the same time, I think you’d have to be pretty callous to not feel extremely concerned by the United Nations’ policy brief, “The impact of Covid-19 on children.”

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.

We know that online sex work has increased during the shutdown.  There is an increased supply of sex workers who are experiencing increasing financial insecurity.  We don’t yet have data on this, but I’d be shocked if the shutdown hasn’t led many to feel pressured into riskier acts for lower amounts of money, including meeting clients in isolated (and therefore unsafe) spaces.

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.

But any slip can kill someone recovering from addiction.  One of my friends froze to death last year.

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.

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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.

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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.

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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.

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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!

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Header image by Goran Paunovic.

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.