Why Evolution is True is a blog written by Jerry Coyne, centered on evolution and biology but also dealing with diverse topics like politics, culture, and cats.
My GP, Dr. Alex Lickerman, has once again put up a coronavirus post on his practice’s website, and allowed me to reference it here. It’s timely because it’s all about the new Pfizer vaccine. (A ICU nurse in New York may have been the first to get the shot.) How effective is it, and how do we know that? Is it safe? What about kids under 16, who weren’t part of the clinical trials? And pregnant women, who also weren’t tested? Since this is a mRNA rather than a killed-virus vaccine, should we have extra concerns about safety? What adverse reactions have been reported? If you were already infected, does the vaccination also reduce your risk of getting reinfected? When will “normal” people who aren’t healthcare workers or nursing-home patients be able to get their jabs?
Alex has kindly agreed, as he has before, to answer readers’ questions about the new vaccine, so put your questions in the comments section below and he’ll address them as he has time. Alex has read all the relevant scientific literature, as well as the data from the vaccine trials, so ask away! But do read his 4-page summary beforehand, as it has a lot of information.
I’m not going to put up his whole post; you can go to his site to see it, which you can do by clicking on the screenshot below:
I’ll just post Alex’s recommendations, followed by his list of “unanswered questions” (indented). The short message: GET THE SHOT AS SOON AS YOU CAN!
CONCLUSIONS
The vaccine is highly effective in preventing symptomatic COVID-19 infection.
The vaccine is safe. Adverse reactions, both local and systemic, are mostly minor. Though the study hasn’t yet gone on long enough to prove there are no serious long-term adverse affects, such adverse affects, if they exist, are likely to be rare and non-life-threatening based on other Phase I and II studies of other RNA vaccines.
We recommend everyone who is eligible to receive the vaccine should receive it when it becomes available to them.
It very well may take all of 2021 to get everyone who’s willing to be vaccinated to receive the shots, which means it likely won’t be until early 2022 that life returns to pre-pandemic normal. In the meantime, continue to wear a mask when indoors with anyone you don’t live with, wash your hands frequently, and refrain from dining indoors at restaurants.
UNANSWERED QUESTIONS
While suggested by the study, still left unproven is whether BNT162b2 [Pfizer’s name for the vaccine] prevents severe COVID-19 infection, whether it prevents COVID-19 infection after just one dose, and whether it prevents COVID-19 infection in subjects who’ve already had COVID-19.
The study didn’t look to see if the vaccine prevents asymptomatic infection. Nor did it assess whether subjects who developed COVID-19 despite vaccination are less likely to transmit the virus. Thus, it’s not yet clear how effective the vaccine will be in containing the spread of the infection.
The study hasn’t gone on long enough to tell if subjects who were vaccinated yet still contracted COVID-19 have a lower risk of long-term effects of COVID-19.
We don’t yet know if the vaccine reduces the risk of dying from COVID-19.
There was insufficient data to draw conclusions about safety and efficacy of the vaccine in children younger than 16, pregnant or lactating women, and patients who are immunocompromised.
We don’t yet know how long immunity lasts and whether or not booster shots will be necessary.
If this is true, it’s excellent news. Click on screenshot to read the CNN report (see also the Washington Post report here):
An excerpt:
Drugmaker Pfizer said Monday an early look at data from its coronavirus vaccine shows it is more than 90% effective — a much better than expected efficacy if the trend continues.
The so-called interim analysis looked at the first 94 confirmed cases of Covid-19 among the more than 43,000 volunteers who got either two doses of the vaccine or a placebo. It found that fewer than 10% of infections were in participants who had been given the vaccine. More than 90% of the cases were in people who had been given a placebo.
Pfizer said that the vaccine provided protection seven days after the second dose and 28 days after the initial dose of the vaccine. The final goal of the trial is to reach 164 confirmed cases of coronavirus infection.
In a news release, the pharmaceutical giant said it plans to seek emergency use authorization from the US Food and Drug Administration soon after volunteers have been monitored for two months after getting their second dose of vaccine, as requested by the FDA.
I believe that 50% effectiveness is the threshold for FDA approval. And, of course, this is early days; but you can’t deny that this looks good so far.
While most cases of Covid-19 are surely contracted via interperson contact (hugging, respiratory droplets, talking next to someone, handshakes, and so on), this new article from Virology Journal, produced by five Australian researchers, suggests that the virus can linger on various surfaces substantially longer than we suspected, and those infection-bearing surfaces (called “fomites”) can carry a viral load large enough to cause infection. Remember when you thought that paper and cardboard could be “disinfected” by leaving it untouched for 24 hours, so that the virus would all die? That doesn’t seem to be the case, at least according to this paper.
Click below to read the screenshot; the pdf is here , and the reference is at the bottom.
The results can be conveyed briefly. The researchers inoculated live virus onto six types of surfaces that might be encountered by people on a daily basis: Stainless steel (cookware, etc.), polymer currency (used in Australia), paper currency (no longer used in Australia but used in many other places), a glass surface (cellphones, touchscreens, etc.), vinyl, and cotton fabric. The materials were incubated at three temperatures (20, 30, and 40 Celsius, corresponding respectively to 68, 86, and 104 degrees Fahrenheit, respectively), and incubation was in the dark, as UV light kills the virus more quickly (hint, put your envelopes and packages in the light when disinfecting them). The relative humidity was 50%, though higher humidity also decreases viral survival.
The virus titer is said by the researchers to “represent a plausible amount of virus that may be deposited on a surface”. Samples were taken over 28 days, and the amount of living (i.e., infectious) virus measured by standard methods.
The attrition of the virus due to death over time was measured in three ways: the D value (time at which only 10% of the original sample remained), the half life (time at which half the original sample remained), and Z values (the increase in temperature required to reduce the D value by 90%, in other words to kill 99% of the inoculate).
The table below tells you everything you need to know: the D values and half lives (latter in parentheses) for all six materials at three temperatures, as well as the Z values:
Now what we don’t know about these values, and what is really important, is how much virus has to remain on the surface before it loses its ability to infect you (remember, probability of getting infected is proportional to the amount of virus you pick up and transfer to your nose, mouth, or eyes). This isn’t discussed in the paper, but I’d say a reasonable precaution is the D value: 90% loss of titer. Perhaps readers in the know can tell us after they’ve read the paper.
But even if you use the half life, at 20°C, two days is a minimum for any surface save cotton (1.7 days). Paper loses half its virus load in three days, and glass in two. But remember, this is in the dark, and half-lives will be shorter in sunlight. Half-lives and Z values decrease dramatically at higher temperatures, though I think 20°C is what we should pay attention to because it’s close to room temperature. If 10% of the original titer is not enough to infect you, you’ll have to wait 10 days for paper and 6 days for glass. Surprisingly, cotton cloth was the material that retained viable virus for the shortest amount of time.
The Z values show that an increase in temperature of about 15°C is enough to kill 99% of the virus existing at a given temperature.
The researchers also found that except for cotton, viable virus was still found on all surfaces after 28 days.
What’s the lesson for us? Well I can’t say (nor do I wish to purvey public-health advice!), because the crucial information—the amount of virus normally deposited on a surface, and how much of that must remain to give you an appreciable chance of getting infected if you pick it up—is missing. What the authors conclude is this:
The data presented in this study demonstrates that infectious SARS-CoV-2 can be recovered from non-porous surfaces for at least 28 days at ambient temperature and humidity (20 °C and 50% RH). Increasing the temperature while maintaining humidity drastically reduced the survivability of the virus to as little as 24 h at 40 °C. The persistence of SARS-CoV-2 demonstrated in this study is pertinent to the public health and transport sectors. This data should be considered in strategies designed to mitigate the risk of fomite transmission during the current pandemic response.
I guess we’ll have to leave it to the “considerers”, i.e., medical researchers and public health experts, to translate these results into recommended behaviors. But I think it’s smart to disinfect paper for two days instead of one after getting it, and use as little currency as possible (currency is like a circulating Petri dish, carrying E. coli as well as coronavirus. Use your credit card instead, and wipe it off with ethanol or wash it with soap and water after you use it. Put it in the machine, and don’t hand it to anyone unless you have to. Oh, and don’t let anybody use your cellphone.
From time to time, my primary care physician Dr. Alex Lickerman posts articles on his website from about what’s going on with the pandemic, concentrating on the scientific research and what it means. The latest post on the website, below, “lays out the evidence for wearing masks, talks about the development of a vaccine, and answers questions about the validity of the rapid nasal swab test.” You can read it as a whole, or skip to the “bottom line” in each section. I’ll simply list the sections (Q&A’s) and the bottom lines.
Alex has kindly volunteered to answer readers’ questions about the pandemic, about vaccinations, about masks, and anything to do with the virus and how we should deal with it as individuals and as a society. So feel free to put your questions in the comments, and Alex will answer them as he has time.
Click on the screenshot to read the post:
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The sections and “bottom lines” (quotes are indented). Any take I have will be flush left, and of course each section below is followed in Alex’s post by an extensive discussion of the medical/scientific data.
Question: Will the wearing of masks in appropriate circumstances slow the pandemic?
Answer: Probably.
BOTTOM LINE: The only way we’ll ever know for certain if mask-wearing by asymptomatic people, in the right circumstances, will reduce the spread of SARS-CoV-2 would be to prospectively assign a region (e.g., a city) to wear masks and compare its rates of infection over the same time to another region where people were assigned not to wear masks (and measure the compliance of each). The impossibility of conducting such a study at this point is obvious. Therefore, we’ll likely never be able to conclude with 100 percent certainty that mask-wearing in the right circumstances will slow the progression of the pandemic. But when we consider the sum of the evidence above, we conclude that mask-wearing by asymptomatic people, in the right circumstances, is likely to slow the progression of the pandemic.
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Question: Who should wear masks, then?
Answer: Everybody.
. . . .When you consider this data together, you have what seems on the surface to be a good argument for not wearing masks to reduce the spread of COVID-19 if you’re asymptomatic.
BOTTOM LINE: But it’s not. Here’s why: a 21 percent prevalence of asymptomatic SARS-CoV-2 infection represents 57.9M people infected. If each of those 57.9M infected people has a 0.33 percent chance of spreading the infection without wearing a mask and does so, it would amount to roughly 191,070 transmitted infections! (Even if our estimate of the number of asymptomatic infections is off by a factor of 10, this would still amount to 19,107 infections.) We don’t know to what degree wearing a mask will decrease the risk down from 0.33 percent, but even a small amount would translate into a large number of people. Thus, while the impact of one asymptomatically infected person not wearing a mask is small, the impact of all asymptomatically infected people not wearing masks may be large. The logic of collective action requires that individuals act as if their contribution is greater than it is because only that way do enough individuals act in such a way that yields the protection society needs. We all need to tolerate inconvenience to contribute to the greater good.
Alex also discusses which masks are best. So far there are data only for which masks keep you from spreading viruses through respiratory droplets. For this N95s are the gold standard, but plebes like us can’t easily get them. He recommends using surgical masks to prevent infecting others, though most other masks seem to be about as good. And the best masks to protect YOU are probably the best masks for protecting others against you, though this isn’t 100% certain. Avoid knitted masks and single-layer cloth masks. I covered some research on this in a post a few weeks ago.
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To me, this is the most depressing part, but I can’t quarrel with the argument:
Question: Will we have a safe, effective vaccine for COVID-19, and if so, when?
Answer: Probably. But likely not until the Summer of 2021 at the very earliest.
BOTTOM LINE: Currently, there are over 140 COVID-19 vaccines in development. Given the statistics we quoted above, that means we should end up with 14 viable vaccines. There’s one RNA vaccine being tested in a Phase III trial right now with 30,000 volunteers being given the vaccine. But we predict it will take us at least until mid- or late-2021 to determine if it’s a winner because it will take at least that long to make sure the vaccine is safe and effective. Remember, the risk of adverse reactions to vaccines needs to be substantially lower than the risk of adverse reactions to medications. This is because: 1) the number of people vaccinated will be much greater than the number of people given a medication (medications for diseases are given to at most millions of people; a vaccine for COVID-19 will be given to billions of people), so even small risks of harm can mean harm is done to millions of people, and 2) the vaccines are given to healthy people, not people already suffering from a disease. Thus, the risk of adverse events from the vaccine must be compared to the risk of not just contracting the disease but of experiencing a severe adverse outcome (i.e., severe, chronic morbidity or death). So, in the case of COVID-19, if we’re considering immunizing a 12-year-old child, for example, whose risk of dying from COVID-19 is literally only 0.022 percent, the risk of a severe adverse reaction to the vaccine needs to be far below that.
Unfortunately, the history of vaccine development is replete with stories of harm. One vaccine developed against respiratory syncytial virus (RSV) in the 1960s actually caused a form of immune enhancement where the disease was worse in vaccinated children, even killing two who’d been vaccinated. In 1955, Cutter Laboratories, a small pharmaceutical company that manufactured a polio vaccine, released vaccines contaminated with fully live virus due to manufacturing errors and poor government oversight, resulting in an estimated 40,000 children being infected with polio. Two hundred victims were permanently paralyzed, and ten of them died.
We mention these cautionary tales not to add fuel the anti-vaccine movement fire, but to highlight the importance of doing the science correctly, of not rushing inadequately tested vaccines to market. The reason vaccines are among the safest of medical interventions available is because they undergo such long and rigorous safety testing. As candidates come off the pipeline, we’ll review their efficacy and safety data and make recommendations about them.
This section has a good precis on how vaccines are both developed and tested. There’s also a nice graph in this section showing the reduction of nine childhood diseases after vaccination was introduced—good ammunition against antivaxers. Alex concludes: “Immunization is one of the most effective—and safest—public health measures that exist. The prevalence of infections from diseases for which we now vaccinate children has declined by ninety percent (see chart below of effectiveness of routine childhood vaccinations). There are literally no other interventions in medicine that are as effective as vaccination.”
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Question: Are rapid tests worth doing, especially because the results are returned so much more rapidly
Answer: Only if the rapid test comes back positive can you believe it.
BOTTOM LINE: We don’t recommend people get a rapid test. Even though results take longer with the PCR test, a negative PCR test is more likely to be accurate. We know only one rapid test with a zero false-positive rate. Other rapid tests may not perform nearly as well.
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This is the tenth in Alex’s series of posts on coronavirus and the pandemic; you can see all the links at the bottom of this post. There’s a lot more to read if you’re interested.
So, if you have questions—my latest one, which I asked Alex yesterday, was “is it safe to get a haircut, and how should ensure that the experience is the safest possible?”—put them in the comments below and then check back in a while to see if they’ve been answered.
Thanks to Alex for offering his analyses and advice to the readers.
What kind of mask should you wear during the pandemic? (Yes, you should always wear one if you’re around people.) A new paper in Science Advances (click on screenshot below, free pdf here, reference at bottom) gives a tentative answer to that question, assuming that you’re wearing the mask to avoid infecting other people. And that presumes that you’re carrying the virus, symptomatic or asymptomatic. (If you’re symptomatic, you shouldn’t be going out anyway.)
Note that the question here is probably not the one many people have, which is “Which kind of mask should I wear if I don’t want to get infected by others?” This is not the same question, as some of the features of the masks that decrease their efficacy (i.e., breaking up expelled droplets into smaller droplets), might not work in reverse. In general, though, those masks that reduce the number of droplets expelled when you’re speaking should also reduce the number of droplets coming in when someone’s speaking to you. The short answer is that fitted N95 masks (which most of us can’t get) are the best at keeping your droplets in,, followed by surgical masks and then two-layer masks of polyproplylene and cotton (multiple layers, as you might guess, are important). N95 masks with valves to allow you to exhale aren’t that great, as you might also expect, and knitted or fleece masks, particularly with one layer, are pretty useless. Bandanas are dreadful—barely better than controls, yet I’ve seen many people wear them.
If you can see through your mask, it’s a clue that it’s not a good one.
Click to see the article, which I’ve summarized below:
The authors used an inexpensive setup (roughly $200) to measure expelled droplets when individuals spoke through a mask for 40 seconds, repeating the phrase, “Stay healthy, people” five times, with the protocol repeated ten times for each mask and the control (no mask) trial. Droplet size and number were measured in a dark chamber using a laser and a cellphone camera.
I’m not sure why the authors are so keen on the inexpensiveness of the apparatus, as individuals aren’t going to do this at home, and a more professional setup in a lab would surely reveal general results that wouldn’t need to be replicated on this inexpensive apparatus. At any rate, the apparatus is diagrammed below, with the diagram and caption from the paper:
(From paper): Fig. 1 Schematic of the experimental setup. A laser beam is expanded vertically by a cylindrical lens and shined through slits in the enclosure. The camera is located at the back of the box, a hole for the speaker in the front. The inset shows scattering for water particles from a spray bottle with the front of the box removed. Photo Credit: Martin Fischer, Duke University.
They used a single speaker for most of the tests to reduce variation, but also used four other speakers on 3 masks and the no-mask control (also ten replicates each) to test the replicability of the results. And they tested fourteen masks, shown below. I’ll describe them as they do in the paper, for the table they give is hard to read.
Masks marked with an asterisks were tested by four different speakers saying the same thing (one different speaker for each of three masks and the control), while the rest of the masks were tested with a single speaker. Numbers below correspond to the diagram above except for the control (no mask) and “swath” mask, which I assume is like a turtleneck pulled up.
“Surgical” mask*. 3 layer
Valved N95
Knitted
“Polyprop”: 2 layer polypropylene apron mask
“Poly/cotton: 3 later cottong/polypropylene/cotton mask
MaxAT mask: 1 layer Maxima AT mask
“Cotton2” 2-layer cotton pleated mask
“Cotton4”: 2-layer cotton, Olson-style mask
“Cotton3”: 2-layer cotton pleated style mask
“Cotton1” 1-layer cotton, pleated style mask
Fleece: Gaiter type neck fleece
“Bandana”*: Double layer bandana
Cotton5*: 2-layer cotton, pleated-style mask
Fitted n95 mask: no exhalation valve and fitted
“Swath” mask: swath of polypropylene mask material (not shown)
“None”: control
And the results in short are below, showing the number of droplet counts, relative to the control (green dot to the right). 1 means as many droplets expelled as with no mask, while close to zero means almost no droplets expelled relative to no mask. All black dots represent the means of ten replicates with a single (and the same0 speaker (lines are standard deviations), while the four colored dots represent the means for four other speakers. These are close to the single speaker using all three tested, giving confidence that the results may be general. Have a look:
(From paper): Droplet transmission through face masks. (A) Relative droplet transmission through the corresponding mask. Each solid data point represents the mean and standard deviation over 10 trials for the same mask, normalized to the control trial (no mask), and tested by one speaker. The hollow data points are the mean and standard deviations of the relative counts over four speakers. A plot with a logarithmic scale is shown in Supplementary Fig. S1.
Swath masks, which did well (fifth best) but aren’t shown, involve wearing swaths of polypropylene mask material, as shown below (source of photo is here, which gives a simpler summary of the recommendations): Even cotton masks are okay, with 1 layer being better than pleated, but when you get to the knitted masks, bandanas, and fleece masks (which produced more droplets, probably by breaking up the big ones into smaller ones), you’d best avoid them.
So what does this mean for you? Assuming that you can’t get a fitted N95 mask, your best bets are surgical masks, which are available (remember, these are designed to keep medical professionals from exhaling microbes into patients’ wounds and bodies), multilayered poly/cotton and poly/propylene (masks 4 and 5 above), or a “swath” of mask material (polypropylene), shown above. If you have a choice, get a surgical mask, or wear masks 4 or 5. But, except for fleece, some mask is better than no mask.
Caveats: Remember first that these masks are tested for EXHALED DROPLETS, not droplets inhaled, which would be harder to test. So sites that imply that these are the “best masks for you to wear” are leaving out that crucial information. I suspect there will be a correlation, but perhaps not a perfect one.
The authors offer other caveats, like the inability to measure total droplets in the chamber, and their use of a cellphone camera, which reduces sensitivity to detecting laser-reflecting particles. Even so, the droplets that could be detected in this method are half a micron: 0.001 mm or 0.00004 inches, which are small. They also emphasize the small number of speakers (five, with most masks tested using a single—and the same—speaker), and that would warrant replication, since some people speak more or less forcefully than the speaker they tested.
These are the necessary reservations, but these are valuable data nonetheless. But again, remember that these data tell you how to protect other people from your exhaled droplets. Even so, I’d suggest getting yourself some 3-layer surgical masks if you can. I believe you can re-use them if you let them disinfect for a week or so before you wear them again, but I’m not an expert here, so take that with a grain of salt and do your own checking.
Andrew Sullivan is moving to a new site, his own Daily Dish revived as the Weekly Dish. But his farewell piece in New York Magazine is not last week’s column, but today’s long article—about plagues. Well researched and engagingly written, it’s a change from Sullivan’s usual discussions of politics and sociology. It’s long (7 pages printed out in 9-point type), but well worth reading. Click on the screenshot to do so:
If you haven’t read one of the many good books on plagues and epidemics, this is a worthy substitute. Sullivan’s aim is not only to describe the many plagues that afflicted our species over recorded history, but also to explain why they happened as well as the sequelae, both good and bad. Going from smallpox in the Roman era through bubonic plague in medieval Europe and the big effect of smallpox on the American Continental Army to the “Spanish influenza” and then the viruses of today, the article is a pretty horrifying chronicle. Sullivan describes his own experiences during the AIDS epidemic (which, he argues, helped speed the acceptance of gay rights), and winds up musing about how Covid-19 might lead to a reinvention of society in ways both good and bad. The worst “bad” is the globalization and disruption of the environment that may release more plagues to come: Sullivan is pretty sure we’ll be ravaged now and again for the forseeable future. All in all, it’s not a happy piece.
A few excerpts:
Paradoxically, the Black Death also reshaped and rebuilt the rural economy to benefit the poor. With half the population suddenly wiped out by bubonic plague, food became plentiful and cheap as soon as the harvests returned, because there were so many fewer mouths to feed, and the price of labor soared because so many workers had perished. Day laborers suddenly had some leverage over the owners of land and exploited it. A manpower shortage also led to innovations. With fewer people on higher wages, for example, the cost of making a book became prohibitive — because it required plenty of scribes and copiers. And so the incentive to invent the printing press was created. Industries like fishing (new methods of curing), shipping (new kinds of ships both bigger and requiring less manpower), and mining (new water pumps) innovated to do more with fewer people. The historian David Herlihy puts it this way: “Plague … broke the Malthusian deadlock … which threatened to hold Europe in its traditional ways for the indefinite future.”
In these two bookends of European plague, in the sixth and then the 14th century, you see two ways in which epidemic disease changed society and culture. In one, the disruption and dislocation of mass disease sent the world into a long de-civilizing process; Roman society was gutted and its empire dissolved into various fiefdoms. In the other, a mass-death event triggered a revival, economic and spiritual, in a kind of cleansing process that restarted European society. They were caused by the same disease. In one case, it brought collapse; in the other, rebirth.
And:
If the 1918 flu pandemic were to occur today, one 2013 study found, it would kill between 188,000 and 337,000 Americans. The reason the death toll would be so much lower than the 675,000 Americans who actually died is that medicine has improved. Many of those who died endured bacterial co-infections, which are now far more treatable with antibiotics. Globally, somewhere around 100 million human beings perished.
The flu’s symptoms were horrifying. In her book Pandemic 1918, Catharine Arnold notes that “victims collapsed in the streets, hemorrhaging from lungs and nose. Their skin turned dark blue with the characteristic ‘heliotrope cyanosis’ caused by oxygen failure as the lungs filled with pus, and they gasped for breath from ‘air-hunger’ like landed fish.” The nosebleeds were projectile, covering the surroundings with blood. “When their lungs collapsed,” one witness recounted, “air was trapped beneath their skin. As we rolled the dead in winding sheets, their bodies crackled — an awful crackling noise which sounded like Rice Crispies [sic] when you pour milk over them.”
And:
Do we go back to where we were, or do we somehow reinvent ourselves for a new future?
You can see the potential contours of a similar response today. This plague makes a strong argument for a more aggressive approach to public health, which would mean, at a minimum, extending health insurance to everyone in the country, as well as reform and renewal for the disgraced CDC and WHO. It could unleash a new wave of infrastructure spending to repair the immense damage to the economy. It could, and absolutely should, end the argument over preventing climate change — because it is so deeply connected to new viral outbreaks, as shifts to hotter weather portend a highly dangerous upheaval in the animal and microbial worlds. And while I worry that this plague could well usher in a new era in which traditional liberalism gives way to a freshly invigorated collective leftism, particularly around identity politics, it could also deeply wound the appeal of the populist right in America, which, once in government, failed the core test of preventing an open-ended, lengthy period of infection, sickness, and death.
Some existing trends might also intensify. It’s hard to see how a policy of mass immigration or free trade will survive public scrutiny for long in a world where viruses cross borders with such surpassing ease. The U.S.-China relationship, already tense, could deteriorate still further. Living online, with all the isolation and depression and extremism that can generate, is now an even stronger and widespread norm, as we avoid physical interaction even more than we did previously. Same with working from home: The atomization of our culture, the already increasing levels of depression, loneliness, and antisocial behavior could deepen further. The collapse of small retail has been accelerated, and the power of the giant tech companies is ever greater. And the epidemic has not assuaged the yawning gap between rich and poor. While COVID relief has made a real, temporary impact, the stark social and economic inequality in the country looms as large as ever. Rates of suicide, drug abuse, and overdosing could climb even higher.
Finally:
And we are not in control. If you are still complacent that human science and technology have removed the potential for the mass extinction of humans, you should wake up. We have lucked out so far. COVID-19 is extremely transmissible but not that fatal to most people, all things considered. But even those countries that are success stories didn’t see it coming in the first place and have experienced resilient breakouts. We still have no vaccine — it may be a year or more before we get one, and we do not know how effective it will be. Imagine the next pandemic pathogen as something as devastating as Ebola and as contagious as the flu. We are as defenseless as we have ever been. This relatively mild virus shut the entire world down for a couple of months. What happens when a much worse one shuts it down for longer?
Knowledge of a brutal new virus does not prevent its spread. Only a much more profound reorientation of humankind will lower the odds: moving out of cities, curtailing global travel, ending carbon energy, mask wearing in public as a permanent feature of our lives. We either do this to lower the odds of mass death or let nature do what it does — eventually so winnowing the human stock that we are no longer a threat to the planet we live on.
That’s the sobering long view. It is hard to look at the history of plagues without reflecting on the fact that civilizations created them and that our shift from our hunter-gatherer origins into a world of globally connected city-dwelling masses has always had a time bomb attached to it. It has already gone off a few times in the past few thousand years, and we have somehow rebounded, but not without long periods, as in post-Roman Europe, of civilizational collapse. But our civilization is far bigger than Rome’s ever was: truly global and, in many ways, too big to fail. And the time bomb is still there — and its future impact could be far greater than in the past. In the strange silence of this plague, if you listen hard, you can still hear it ticking.
Let nobody say that Andrew Sullivan is an optimist.
A new article in Nature has gathered statistics from several studies to come up with an estimate of the overall death rate from coronavirus (click on screenshot below to read it, pdf here). If you’re paywalled, a judicious request might work. I’ll put the latest estimates at the bottom, as you’ll need to read the preliminary information since these figures come with many caveats.
As the article notes, when you’re estimating fatality rates, the gold standard is called the “infection fatality rate” (IFR), which is the proportion of all infected people, including those who are asymptomatic or haven’t been tested, who will die from the disease at issue. You can imagine the difficulty of estimating this. While we can get an accurate handle on the fatality rate among those known to have the disease, that’s only a part of the statistic, and may either under- or over-estimate the IFR. Further, if you have antibodies against the virus, you may have recovered from an infection without knowing you’ve had it. Yet that data must also be incorporated into the IFR, and antibody testing is not the same thing as testing for the virus. (How many of you have been antibody tested?) One study from Germany showed that 15.5% of the people in a town that had an outbreak had coronavirus antibodies—five times the proportion of people known to have had coronavirus at the time. Not doing antibody testing would have drastically overestimated the IFR.
Another complication is that some countries don’t test postmortem, and, importantly, the fatality rate in different groups (age, ethnicity, class and wealth, comorbidities, access to healthcare) haven’t been compiled thoroughly. Of course, if you’re infected or in a group that doesn’t have the average IFR, you’ll won’t care that much about the overall rate—you’ll want to know your own chance of dying.
Why do we need these data? As Nature notes:
Getting the number right is important because it helps governments and individuals to determine appropriate responses. “Calculate too low an IFR, and a community could underreact, and be underprepared. Too high, and the overreaction could be at best expensive, and at worst [could] also add harms from the overuse of interventions like lockdowns,” says Hilda Bastian, who studies evidence-based medicine, and is a PhD candidate at Bond University in the Gold Coast, Australia.
The article outlines other complications, but there’s no need to go into them here. I’ll just add that Nature presents the rate of six studies from five countries, and there isn’t much variance among them, with the first study, using data taken from a cruise ship in which everyone was tested, gives the only estimate of the true IFR. But the sample (3,711 people) was small.
So here are the data at hand, and realize that there are problems with all of the studies. But it is interesting that they tend to converge on a value of 0.5% to 1%. (Of course, if you’re old like me, or have other medical issues, this will be an underestimate):
Some scientists impute the small scatter to “luck” (whatever they mean by that) or coincidence, and virtually none of the data have been published in peer-reviewed manuscripts. Finally, of course, we need to know the death rate for different groups, which will help in figuring out individual treatment, though for epidemiological purposes the IFR is necessary—if it’s from a random sample of people. (Nature cites one study from Switzerland estimating an overall IFR of 0.6%, but a tenfold higher rate of 5.6% for people 65 or older.
The lesson: so far across several populations, one’s chance of dying should they contract the disease is about 0.5% to 1%. But your mileage may vary (I have a lot of mileage and my figure would be higher), and it’s early days for these statistics.
