In popular press and social media, there’s been a misunderstanding of what is actually meant when scientists say that the Pfizer and Moderna Covid-19 vaccines have an efficacy of 94-95%. It does not mean that 95% of vaccinated people are protected from infection โ these vaccines are better than that. Dr. Piero Olliaro explains in a letter to The Lancet:
The mRNA-based Pfizer and Moderna vaccines were shown to have 94-95% efficacy in preventing symptomatic COVID-19, calculated as 100 x (1 minus the attack rate with vaccine divided by the attack rate with placebo). It means that in a population such as the one enrolled in the trials, with a cumulated COVID-19 attack rate over a period of 3 months of about 1% without a vaccine, we would expect roughly 0.05% of vaccinated people would get diseased.
Another way to put it: you’re 20 times less likely to get Covid-19 with a vaccine than without. (And again, data indicates these are safe vaccines.) Olliaro explains with some simple math:
If we vaccinated a population of 100,000 and protected 95% of them, that would leave 5000 individuals diseased over 3 months, which is almost the current overall COVID-19 case rate in the UK. Rather, a 95% vaccine efficacy means that instead of 1000 COVID-19 cases in a population of 100,000 without vaccine (from the placebo arm of the abovementioned trials, approximately 1% would be ill with COVID-19 and 99% would not) we would expect 50 cases (99.95% of the population is disease-free, at least for 3 months).
And of course if you vaccinate widely, it becomes a compounding situation because the virus just runs out of people to infect.
Over the past week or two, I’ve read a number of articles and threads about why Covid-19 cases are falling so rapidly in the US. The explanations have all been somewhat unsatisfying to me. Cases have indeed dropped off quite quickly and it happened pretty uniformly all over the country. Look at the mini state graphs on the NY Times Covid page โ they all look about the same. Hospitalizations and positivity rates have dropped too, so while the number of daily tests has fallen too, this appears to be a real drop and not just an artifact of a lack of testing. Which is great news! Imagine a February and March that looked like December โ a disaster compounded.
The vaccine explanation is the weakest one for me: not enough people outside of healthcare workers had gotten them early enough to start bending that curve sharply downward in early January. But as Thompson notes, it could be having more of an effect on hospitalizations because the folks getting shots (and therefore immunity against severe infection) are those most likely to end up in hospitals due to infection. And obviously, vaccines are going to become the dominant factor in falling case numbers as more and more people get jabbed.
I’m also skeptical of the seasonality argument, but (again, as Thompson notes) there’s a lot we don’t know about how temperature, sunlight, humidity, and this specific coronavirus interact. Obviously Covid-19 is a seasonal thing and that’s definitely a contributing factor here, but that sharp of a drop in early January? I don’t know if it’s the primary driver here. Also, the seasonal flu typically peaks in February in the US.
I think the most logical explanation is one proposed initially by @mgmgomes1 and others โ namely that we are seeing the effects of population immunity with heterogeneous mixing + strong behavioral effects. Take a(n overly) simple example. Assume 60% of a population has zero respiratory contacts, while the other 40% lives life as normal. If 75% of that high-mixing group has immunity (e.g., 30% population seroprevalence), you could easily see herd effects.
Basically, a large percentage of the folks at the greatest risk of getting Covid-19 in the US (i.e. folks who aren’t able or willing to keep from seeing other people and/or take proper precautions) have gotten it, resulting in a sort of localized “herd immunity” among those folks. After the massive holiday surge in cases (more on that in a sec), this hypothesis suggests, the virus started running out of people to infect and rates dropped quickly. This is the first explanation I read that really made sense to me.
Thompson leads off his piece with the behavioral explanation: “Maybe Americans finally got the hang of this mask and social-distancing thing.” I do not buy that people who previously weren’t doing so before suddenly started wearing masks (or better masks), keeping distant, spending less time indoors with others, and staying home from work started doing so in numbers large enough to cause such a sharp downturn. But you can’t consider the decline without also looking at how cases got so high in the first place. Here’s Steven Johnson on Twitter, zooming out a few months:
[It’s] not so much that people got the hang of social distancing, but rather that the holiday season compelled people to relax social distancing for in-person family gatherings. So the current decline is mostly reversion to where we were in Oct-Nov.
Yes, this. Without these holidays, we may have seen much more of a winter plateau than a spike. So here’s what seems plausible to me. As the cold weather made the coronavirus more effective at infection, people gathered for Halloween, Thanksgiving, Hanukkah, Christmas, and New Year’s โ each subsequent holiday building on the previous one โ and it pushed cases much higher than they would have been without those major gatherings. After two months of massive infection rates, the virus burned itself out among the high-mixing group and everyone else retreated back into their homes and pods to hunker down, resulting in the steep decline we’re seeing.
Obviously, careful scientific study will be necessary to tease out how significant each of these (and other!) causes were to the holiday spike and subsequent decline. But for now, the way forward is continuing to social distance, wear (better) masks, limit close contacts, and get people vaccinated โ before B.1.1.7 and the other variants hit.
Curiosity is about to get some company. NASA’s newest rover, Perseverance, is set to land on Mars beginning tomorrow at around 3pm EST. The video above walks us through the 7-minute landing routine in which the rover ditches its spacecraft, heat shields its way through the Martian atmosphere, deploys its parachute, uses an onboard guidance system to navigate to a good landing spot, and finally is lowered down to the surface via a sky crane. The rover’s destination is Jezero Crater, site of an ancient river delta and lakebed.
Jezero Crater tells a story of the on-again, off-again nature of the wet past of Mars. More than 3.5 billion years ago, river channels spilled over the crater wall and created a lake. Scientists see evidence that water carried clay minerals from the surrounding area into the crater lake. Conceivably, microbial life could have lived in Jezero during one or more of these wet times. If so, signs of their remains might be found in lakebed or shoreline sediments. Scientists will study how the region formed and evolved, seek signs of past life, and collect samples of Mars rock and soil that might preserve these signs.
Here’s how you can watch the landing “live” tomorrow (i.e. delayed by the 11 minutes & 22 seconds it takes for signals to travel from Mars). I’ll do a separate post tomorrow w/ the proper YouTube embeds so we can all follow along together.
It’s the result of the DESI Legacy Imagining Surveys, maps of the sky made by the three observatories (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey, in combination with the orbiting WISE infrared observatory). They mapped the northern sky in seven colors, covering a third of the entire sky โ 14,000 square degrees, or the equivalent area of 70,000 full Moons on the sky.
The ultimate goal is to better understand dark energy, the mysterious substance that’s accelerating the expansion of the Universe, by looking at the distribution of galaxies throughout the Universe. They’ll do that by picking tens of millions of the billion galaxies in the data and getting follow-up observations with the Dark Energy Spectroscopic Instrument (DESI), which will take spectra of those galaxies and find their distances.
Since we’ll know their positions on the sky, and their distances, this will make a 3D map of the Universe larger than any ever before.
The photo included at the top of the post is just a tiny tiny bit of the full image โ you can pan and zoom the whole thing in this viewer. Be sure to zoom out in increments from the default view so as to fully appreciate just how absurdly large this image (and the universe) is.
In 1959, a group of students died while on a hiking trip in the Ural Mountains. The circumstances of the incident and the way in which they died presented a mystery that has remained unsolved in the decades since.
The Dyatlov Pass incident is an intriguing unsolved mystery from the last century. In February 1959, a group of nine experienced Russian mountaineers perished during a difficult expedition in the northern Urals. A snow avalanche hypothesis was proposed, among other theories, but was found to be inconsistent with the evidence of a lower-than-usual slope angle, scarcity of avalanche signs, uncertainties about the trigger mechanism, and abnormal injuries of the victims.
The cross-country skiers had actually pitched camp on a small step in the hillside, scooping away the snow to level it out. When they cut into the snowpack, they sliced through the weak layer, essentially initiating a countdown. “When you create a cut in the slope to install the tent, it’s like when you remove a retaining wall,” says Gaume, a snow physicist at the Swiss Federal Institute of Technology. The slab of denser snow now hung precariously over the camp. “All the ingredients were there,” Gaume adds. “There was a weak layer, there was a slab, and the slope angle was locally steeper than the critical angle.”
Also from the Wired piece: the researchers were inspired by the realistic snow modeling that Disney did for Frozen. (via kottke ride home)
This guide to Covid-19 variants (SARS-CoV-2 viruses that have evolved changes to meaningfully alter their behavior) by Michaeleen Doucleff and Meredith Rizzo at NPR cleverly visualizes how mutations of the virus’s spike proteins help bind it more easily to ACE2 receptors on human cells. The key to the visualization is Meredith Miotke’s illustrations of the viruses using Lego pieces to represent the virus spikes and cell receptors. The usual SARS-CoV-2 has 1x1 Lego pieces that can bind with 1x2 pieces, like so:
But, as everyone who has ever worked with a Lego set knows, a 1x1 piece stuck to a 1x2 piece is not super stable. So when a version of the virus with a 1x2 piece shows up, it’s able to form a better connection to the 1x2 receptor:
The analogy breaks down if you look too hard at it1 but for many people, it can be a quick way to get the gist of the mechanism at work here. (via @EricTopol)
This is a huge pet peeve of mine when people try to poke holes in analogies: by definition, all analogies break down if you examine them too deeply. An analogy is a comparison of two different things that are similar in significant respects. If they were the same in every respect, it’s not an analogy…you’d just be describing one thing.โฉ
Using images from the Kaguya orbiter, Seรกn Doran has constructed a 4-hour realtime orbit of the Moon. Feel free to pair with your favorite piece of relaxing music for a meditative viewing experience.
You probably read something yesterday, maybe just a headline, about Moderna’s Covid-19 vaccine being “six times less effective” against the B.1.351 coronavirus variant first identified in South Africa. This is, to put it plainly, a bullshit take on what is actually excellent news. This is the important bit, via Stat:
Both the Moderna vaccine and the immunization from Pfizer-BioNTech produce such powerful levels of immune protection โ generating higher levels of antibodies on average than people who recover from a Covid-19 infection have โ that they should be able to withstand some drop in their potency without really losing their ability to guard people from getting sick.
“There is a very slight, modest diminution in the efficacy of a vaccine against it, but there’s enough cushion with the vaccines that we have that we still consider them to be effective,” Anthony Fauci, the top U.S. infectious diseases official, said Monday on the “Today” show.
Let’s hear that again: “Both the Moderna vaccine and the immunization from Pfizer-BioNTech produce such powerful levels of immune protection…” These vaccines are so good, so potent, that even this sixfold drop in one measure of the vaccines’ ability to neutralize this one SARS-CoV-2 variant isn’t even enough to significantly reduce their overall protective power.1 That’s the important news here, that’s the very good news, that’s what you should be taking away from this. We have miraculously developed a near-perfect medicine for a plague that has significantly disrupted all human life on Earth and we’re flipping out over some technical details that the experts assure us don’t mean much in terms of overall effectiveness?! No thank you. Not today.
In a Twitter thread, Zeynep Tufekci is tearing her hair out because of the media’s misunderstanding and sensationalization of the “sixfold drop”.
I know people are tired but needless anxiety isn’t helping us. Let’s focus on getting through these months โ better masks if indoors with others, more strict attention to our precautions โ and the real problem: making more of these amazing vaccines quickly & getting them out there!
I get it, we want to understand but not how it works. Stop worrying about Nab titers. That does NOT mean the vaccine is six times less effective. People whose job it is to worry about it are on it & we just got confirmation: it works against the variants.
Plea to media: this isn’t a good headline. It makes people think the vaccine is six times less effective against the new variants (FALSE!) when the news today is *excellent*: The vaccine continues to work well against the new variants. That’s the headline.
mRNA vaccines induce very high neutralizing antibodies after the second shot (consistently in the upper 25-30% of what we see with convalescent sera). If that activity is reduced by 10-fold, it is still decent neutralizing activity that will very likely protect. Furthermore, we know that the mRNA vaccines are already protective after the first shot when neutralizing antibody titers are low or undetectable in most individuals.
There is a concern here and it’s that B.1.351 or B.1.1.7 might mutate into variants that are significantly resistant against the vaccines’ good effects. Krammer again:
First, we need to do what every good scientist is praying for a year now: We need to cut down on virus circulation. The more the virus replicates, the more infections there are the higher are the chances for new variants to arise. Also, we need to try and contain B.1.351 and B.1.1.248/P.1 as much as possible.
That’s why, aside from preventing hundreds of thousands of deaths in the next several months, getting these vaccines into people’s arms is so important: the less the virus spreads, the less opportunity it will have to mutate into something even more dangerous. The US vaccination effort is slowly ramping up โ we’re at an average of 1.3 million doses per day right now and the trend is heading in the right direction. We can get this done!
So what can you do about this right now? 1. Stop worrying about the variants until the experts let us know we have something to worry about. 2. If you are eligible for the vaccine, get it! 3. Spread the word about vaccine availability in your area. Yesterday Vermont opened signups for vaccination appointments for all Vermonters 75 and older, and I texted/emailed everyone I could think of who was over 75 or who had parents/relatives/friends who are over 75 to urge them to sign up or spread the word. 4. Continue to wear a mask (a better one if possible), wash your hands, social distance, stay home when possible, don’t spend time indoors w/ strangers, etc. Thanks to these remarkable vaccines, real relief is in sight โ let’s keep on track and see this thing through.
Obviously, this could change! But the situation right now w/r/t variants is very good.โฉ
In response to comments about a video of him getting the Covid-19 vaccine โ “Come with me if you want to live!” โ Arnold Schwarzenegger says that if you want to build biceps, you should listen to him. He’s the expert. But if you want to know what to do about Covid-19, you should listen to epidemiologists and doctors.
Dr. Fauci and all of the virologists and epidemiologists and doctors have studied diseases and vaccines for their entire lives, so I listen to them and I urge you to do the same. None of us are going to learn more than them by watching a few hours of videos. It’s simple: if your house is on fire, you don’t go on YouTube, you call the damn fire department. If you have a heart attack, you don’t check your Facebook group, you call an ambulance. If 9 doctors tell you you have cancer and need to treat it or you will die, and 1 doctor says the cancer will disappear, you should always side with the 9. In this case, virtually all of the real experts around the world are telling us the vaccine is safe and some people on Facebook are saying it isn’t.
In general, I think if the circle of people you trust gets smaller and smaller and you find yourself more and more isolated, it should be a warning sign that you’re going down a rabbit hole of misinformation. Some people say it is weak to listen to experts. That’s bogus. It takes strength to admit you don’t know everything. Weakness is thinking you don’t need expert advice and only listening to sources that confirm what you want to believe.
Nicholas Rougeux has beautifully reproduced & remastered botanical illustrator Elizabeth Twining’s catalog of plants and flowers from 1868, Illustrations of the Natural Orders of Plants. Each of the 160 illustrations is accompanied by explanatory text from the original book and an interactive version of the image (click on the highlighted plant for more info).
In an opinion piece for the NY Times, Zeynep Tufekci and epidemiologist Michael Mina are urging for new trials of the Moderna and Pfizer/BioNTech Covid-19 vaccines to begin immediately to see how effective a single dose might be in preventing new infections. If the trials do indicate that a single dose works, that would effectively double the number of people we could vaccinate within a certain time period, saving countless lives in the US and worldwide.
Both vaccines are supposed to be administered in two doses, a prime and a booster, 21 days apart for Pfizer and 28 days for Moderna. However, in data provided to the F.D.A., there are clues for a tantalizing possibility: that even a single dose may provide significant levels of protection against the disease.
If that’s shown to be the case, this would be a game changer, allowing us to vaccinate up to twice the number of people and greatly alleviating the suffering not just in the United States, but also in countries where vaccine shortages may take years to resolve.
But to get there โ to test this possibility โ we must act fast and must quickly acquire more data.
For both vaccines, the sharp drop in disease in the vaccinated group started about 10 to 14 days after the first dose, before receiving the second. Moderna reported the initial dose to be 92.1 percent efficacious in preventing Covid-19 starting two weeks after the initial shot, when the immune system effects from the vaccine kick in, before the second injection on the 28th day
That raises the question of whether we should already be administrating only a single dose. But while the data is suggestive, it is also limited; important questions remain, and approval would require high standards and more trials.
The piece concludes: “The possibility of adding hundreds of millions to those who can be vaccinated immediately in the coming year is not something to be dismissed.”
If you crack a fertilized chicken egg into a transparent container โ in this case, plain old kitchen plastic wrap โ and incubate it, you can observe the embryo as it develops and eventually “hatches” into a chick, heartbeat and all. The process takes about 21 days from start to finish.
Spurred by the pandemic โ what he calls “the first experience we’ve had of a global disaster affecting every single person on Earth”1 โ Domain of Science’s Dominic Walliman takes stock of many of the possible catastrophes that might befall humanity, ranking possible threats based on their likelihood and the number of potential casualties.
This year was the first experience we’ve had of a global disaster affecting every single person on Earth. And also how unprepared society was to deal with it, despite plenty of people giving warnings that this was going to happen at some stage.
But in the midst of all the doom I started to wonder, what other things could threaten humanity, that we are not thinking about? So I made the Map of Doom to list all the threats to humanity in one place.
One could imagine a third dimension of this chart: what, if anything, humans can do about each of these threats. Earthquakes can be detected, buildings can be designed to withstand them, and evacuation procedures enacted and prioritized. Many effects of climate change can be mitigated. Asteroids can be detected, but doing something about them might prove difficult. We’ve lowered the threat of nuclear war โ for now. Supervolcanoes? Yikes.
In remarks to the German parliament today, German Chancellor Angela Merkel advocated for tighter Covid-19 restrictions, as cases & deaths in Germany reach new peaks. The restrictions she’s referring to were recommended by “a national academy of scientists and academics” and are intended at reducing the spread of Covid-19 over the December holidays. The impassioned argument that she makes in this short video clip (full report here) is difficult for me to find fault with (even though conservative members of her parliament and Twitter commenters disagree). Here’s a partial transcript:
If the price we pay is 590 deaths per day, then that is unacceptable in my view. And when scientists are practically begging us to reduce our contacts for a week before we see Grandma and Grandpa, grandparents and older people at Christmas, then perhaps we really should think again about whether we can’t find a way to start the school holidays on the 16th instead of the 19th. What will we say when we look back on this once-in-a-century event if we weren’t able to find a solution for these three days? And it may be the case that sending children home is the wrong thing to do, if so then it will have to be digital lessons or something else. I don’t know, this is not my area of expertise and I don’t want to interfere. I only want to say: if we have too many contacts now, in the run-up to Christmas, and it ends up being the last Christmas with our grandparents, then we will have done something wrong. She should not let this happen.
I teared up watching her talk. In the US, we are dealing with many more cases (which will turn into eventual deaths) and deaths than Germany, both in absolute and per capita terms. It’s like 10 fully-loaded passenger planes a day are crashing with no survivors and there are small things that we all can do to keep many of those people alive and … many of us just don’t want to do those things!
Like Merkel says, we are going to look back on this and be completely ashamed that we didn’t do these things and that we elected people that won’t advocate for these things on our behalf and that we let 300-400,000 Americans die and countless others lose loved ones and go bankrupt and get evicted and lose their businesses and be chronically ill and be food insecure and and and. If we aren’t ashamed, if we don’t reckon with all of this someday, then maybe nothing can redeem us and we deserved it all.
The vaccine structure is highly idealized, with spike mRNA in magenta, lipids in blue, and PEG-lipid in green. The background is blood serum or lymph.
Both the Pfizer/BioNTech and the Moderna Covid-19 vaccines are based on mRNA โ you can brush up on how they work at Stat or the CDC.
mRNA vaccines are a new type of vaccine to protect against infectious diseases. To trigger an immune response, many vaccines put a weakened or inactivated germ into our bodies. Not mRNA vaccines. Instead, they teach our cells how to make a protein โ or even just a piece of a protein โ that triggers an immune response inside our bodies. That immune response, which produces antibodies, is what protects us from getting infected if the real virus enters our bodies.
The NY Times recently surveyed 700 epidemiologists about how they are personally living during the pandemic and what they think is going to happen next. Epidemiologists should have a better idea than most of us about how to act during a viral pandemic, so there’s lots of good information in there about vaccines and high-risk behaviors. But I found their answers to a pair of speculative questions about a return to normalcy most interesting.
How and when will life go back to normal?
“For some, it has gone back to normal, and because of this, it will be two to three years before things are back to normal for the cautious, at least in the U.S.”
- Cathryn Bock, associate professor, Wayne State University
“The new normal will be continued masking for the next 12 to 18 months and possibly the next few years. This is a paradigm shift.”
- Roberta Bruhn, co-director, Vitalant Research Institute
What will never return to normal?
“My relationships with people who have taken this pandemic lightly and ignored public health messages and recommendations.”
- Victoria Holt, professor emeritus, University of Washington
“Every part of my daily life that involves interaction with anyone other than my spouse.”
- Charles Poole, associate professor, University of North Carolina
For many people, the pandemic has altered almost every aspect of their lives. If we listen to what epidemiologists are telling us (like we should have back in early 2020 to avoid much of our present hardship), it could help us accept that the pandemic will continue to affect most aspects of our lives even after it is “over”.
Zeynep Tufekci reports on a small study from Korea that has big implications on how we think about transmission of SARS-CoV-2. Scientists traced two cases back to a restaurant and discovered that transmission had occurred over quite a long distance in a very short period of time.
If you just want the results: one person (Case B) infected two other people (case A and C) from a distance away of 6.5 meters (~21 feet) and 4.8m (~15 feet). Case B and case A overlapped for just five minutes at quite a distance away. These people were well beyond the current 6 feet / 2 meter guidelines of CDC and much further than the current 3 feet / one meter distance advocated by the WHO. And they still transmitted the virus.
As Tufekci goes on to explain, the way they figured this out was quite clever: they contact traced, used CCTV footage from the restaurant, recreated the airflow in the space, and verified the transmission chain with genome sequencing. Here’s a seating diagram that shows the airflow in relation to where everyone was sitting:
Someone infecting another person 21 feet away in only five minutes while others who were closer for longer went uninfected is an extraordinary claim and they absolutely nailed it down. As Sherlock Holmes said: “Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.” And the truth is that in some cases, the recommended 6 feet of distance indoors is not sufficient when people aren’t wearing masks. Airflow matters. Ventilation matters. Which way people are facing matters. How much people are talking/laughing/yelling/singing matters. Masks matter. 6 feet of distance does not confer magical protection. All that can make it tough to figure out if certain situations are safe or not, but for me it’s an easy calculation: absolutely no time indoors with other people not wearing masks. Period. As Tufekci concludes:
I think there are three broad lessons here. One, small data can be extremely illuminating. Two, air flow and talking seem to matter a great deal. Three, sadly, indoor dining and any activity where people are either singing or huffing and puffing (like a gym) indoors, especially with poor ventilation, clearly remains high risk.
Read her whole post โ as she says, it’s “perhaps one of the finest examples of shoe-leather epidemiology I’ve seen since the beginning of the pandemic”.
The Milky Way galaxy may be home to billions or even trillions of rogue planets (planets that don’t orbit stars). In this video, Kurzgesagt considers how the Earth could go rogue (by following a nearby massive star away from the Sun) and what would happen to our oceans, atmosphere, and lives if it happened.
The first part of the video is pretty bleak โ “as the days turn dark, the final winter of humanity would begin” โ while the second part is hopeful: we’ll be able to predict our ejection thousands of years before it happens and may be able to prepare. In light of the world’s response to the pandemic and climate change, it would certainly be interesting to see if human civilization could get it together to save itself from a cold death in outer space. I have no doubt that scientist could accurately diagnose the problem and supply solutions, but the politics would be a total mess.
With the first approved Covid-19 vaccines set to roll out in the US soon, some of the focus has shifted to how the vaccine will be distributed and its equitable allocation. Part of the distribution logistics puzzle is making sure there are enough glass vials to hold and transport the vaccine around the nation to those waiting to be vaccinated. For the New Yorker, Christopher Payne took some photos of two Corning factories that are manufacturing vials as fast as they can.
But back in the early 19th century, for a colonial empire dealing with overseas smallpox epidemics, glass vials were not an option. Smallpox vaccination at that time was most reliably accomplished by transferring material from cowpox blisters on one person (or cow) to another person. The freshly inoculated person got a little sick but later proved to be immune to the much deadlier smallpox. So when Spain’s Royal Philanthropic Vaccine Expedition set sail in 1803 to inoculate the inhabitants of their overseas colonies for smallpox, they used the bodies of human beings to transport the vaccine. To be more specific, they used “twenty-two orphan boys, ages three to nine”.1
And so it was that, “in the era before refrigeration, freeze-dried vaccines, and jet aircraft,” writes medical historian John Bowers, “the successful circumnavigation of the globe with the vaccine…rested on a single medium โ little boys.” During the long crossing, approximately twenty-two orphans who had not previously contracted smallpox or cowpox were “vaccinated in pairs every ninth or tenth day,” via arm-to-arm inoculation (taking lymph from an unbroken pustule on a recently vaccinated boy and introducing it under the skin of another). This created a vaccine chain โ the vaccine remained active and viable for the entire journey.
The three-year expedition was success and an early & effective example of philanthropic healthcare, but you also have to note here that the reason the Americas were ravaged by smallpox was because Spain brought it there in the first place.
Given the era, it’s likely that no one asked the orphans whether they wanted to participate โ and some seemed too young to consent anyway. They’d been abandoned by their parents, were living in institutions, and had no power to resist. But the Spanish king, Carlos IV, decided to make them a few promises: They would be stuffed with food on the voyage over to make sure they looked hearty and hale upon arrival. After all, no one would want lymph from the arm of a sickly child. Appearance mattered. And they’d get a free education in the colonies, plus the chance at a new life there with an adoptive family. It was a far better shake than they’d get in Spain.
The article describes these children as “orphaned” but I wonder if it’s not more accurate to describe them as “enslaved”. Surely these kids didn’t have a real choice in whether they wanted to be infected with cowpox and carried overseas in a cramped ship.โฉ
In an incredible effort, science has provided the world with what looks like an incredibly effective vaccine for Covid-19. For Stat, Helen Braswell writes about the challenges of turning that vaccine into vaccinations. In the US, despite heroic work from individuals and individual groups, our public health system has proved unequal to the challenge of addressing the pandemic, and we’re now turning, in part, to that system to distribute and administer the vaccines, as well as to educate the public and drum up support for vaccination. The people that we’re counting on are public officials and healthcare workers worn out from what is essentially one 9-month-long wave of illness, hospitalizations, and death across the country. Misinformation and skepticism of science and government has sowed “justified distrust” about vaccines in many people:
Concern about the vaccines, however, cuts across ethnic and socioeconomic groups. President Trump’s overt efforts to pressure the FDA to issue EUAs before the Nov. 3 election โ before the vaccine trials were finished โ has deepened the sense of unease. The CDC’s early pandemic testing fiasco, coupled with its sidelining by the Trump administration, has eroded its standing as a trusted source of information.
Alison Buttenheim, an associate professor of nursing and health policy at the University of Pennsylvania, refers to the current situation as a perfect storm of “justified distrust.”
“People who don’t think twice about vaccinating their kids totally on time, who get their flu shot every year, are in the sort of, ‘Hmmm. Might wait six months on this one,’” Buttenheim, who works on vaccine acceptance, told STAT. “I’ve heard people say, ‘I’ll get the European one,’” she said, adding other people have said they would get vaccinated after Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, gets vaccinated.
And it’s not just the general public. A recent survey of 2,000 doctors and nurses in New Jersey found that 60% of doctors planned to take a Covid vaccine, but only 40% of nurses intended to, Health Commissioner Judith Persichilli said in a recent “60 Minutes” segment about Operation Warp Speed.
Fauci, along with other respected public health officials and workers, should get vaccinated live on CNN. Stream it on YouTube and Twitch. It won’t convert the anti-vax, anti-mask, QAnon wingnuts (nothing will) but if you can at least get healthcare workers and at-risk folks on board, it would be time well spent.
But that’s only one small piece of the puzzle. Braswell’s piece is long and comprehensive look at the challenges regarding the Covid-19 vaccines and is worth reading all the way through.
After Terri Nelson noticed people complaining online about a lack of scent from newly purchased scented candles, Kate Petrova analyzed Amazon reviews for candles from the past three years and found a drop in ratings for scented candles beginning in January 2020 (compared to a smaller ratings decline for unscented candles).
The hypothesis is that some of these buyers have lost their sense of smell due to Covid-19 infections and that’s showing up in the ratings.
With the positive news about the Covid-19 vaccine trials, I assume many of you have started to think about the potential end of the pandemic โ what we’ll do, where we’ll go, who we’ll see, and reckon with what’s changed and what’s been lost. I know I have. Alex Hutchinson has written an intriguing piece on what sports science might be able to tell us about the psychology of a situation like the pandemic, where the finish line is poorly defined, ever-changing, or even non-existent.
As it happens, there’s a whole subfield of sports science, at the intersection of physiology and psychology, that explores this terrain. It’s called teleoanticipation, a term coined in 1996 by German physiologist Hans-Volkhart Ulmer to describe how our knowledge of an eventual endpoint (or telos) influences the entirety of an experience. Using endurance sports as their medium, researchers in this subfield have probed what happens when you hide the finish line, surreptitiously move it or take it away entirely. For those of us tempted by promising vaccine updates to start fantasizing about an end to the pandemic, these researchers have some advice: don’t.
Instead, the key seems to be remaining in the moment instead of focusing on the goal.
It turns out that, if you ask yourself “Can I keep going?” rather than “Can I make it to the finish?” you’re far more likely to answer in the affirmative.
This squares with mindfulness practices from Buddhism and Stoicism but also reminds me of a motivational trick I first heard a few years ago: that you can do anything for 10 seconds โ and then you just begin a new 10 seconds. Turns out that was popularized by Unbreakable Kimmy Schmidt. Good advice can come from anywhere.
Now that the preliminary results of various Covid-19 vaccine trials are coming out (and looking promising), attention is turning to the eventual distribution of the vaccines. The logistics of getting the doses out to hospitals, clinics, and doctor’s offices is one concern but so is the question of who should get vaccinated first. Supplies of the vaccines will be limited at first, so we’ll need to decide as a society what distribution method is most fair and is of the most benefit to the greatest number of people.
In addition several recommendations โ including that the vaccine be distributed to everyone free of charge โ a central feature of the report is a four-phase system of vaccine distribution, summarized in this graphic:
I’d like to stress that this graphic does not show all groups of people included in each phase โ please consult the text of the report for that before you go sharing that graphic on social media without context. For example, here’s the full description for “high-risk health workers” in Phase 1a:
This group includes frontline health care workers (who are in hospitals, nursing homes, or providing home care) who either (1) work in situations where the risk of SARS-CoV-2 transmission is higher, or (2) are at an elevated risk of transmitting the infection to patients at higher risk of mortality and severe morbidity. These individuals โ who are themselves unable to avoid exposure to the virus โ play a critical role in ensuring that the health system can care for COVID-19 patients.
These groups include not only clinicians (e.g., nurses, physicians, respiratory technicians, dentists and hygienists) but also other workers in health care settings who meet the Phase 1a risk criteria (e.g., nursing assistants, environmental services staff, assisted living facility staff, long-term care facility staff, group home staff, and home caregivers). The health care settings employing these workers who are at increased risk of exposure to the virus may also include ambulatory and urgent care clinics; dialysis centers; blood, organ, and tissue donation facilities; and other non-hospital health care facilities. Finally, there are community and family settings where care for infected patients occurs. Not all the workers in these settings are paid for their labor, but, while they are caring for infected people, they all need to be protected from the virus.
Situations associated with higher risk of transmission include caring for COVID-19 patients, cleaning areas where COVID-19 patients are admitted, treated, and housed, and performing procedures with higher risk of aerosolization such as endotracheal intubation, bronchoscopy, suctioning, turning the patient to the prone position, disconnecting the patient from the ventilator, invasive dental procedures and exams, invasive specimen collection, and cardiopulmonary resuscitation. In addition, there are other frontline health care workers who, if they have uncontrolled exposure to the patients or the public in the course of their work, should be in this initial phase. This group includes those individuals distributing or administering the vaccine โ especially in areas of higher community transmission โ such as pharmacists, plasma and blood donation workers, public health nurses, and other public health and emergency preparedness workers. The committee also includes morticians, funeral home workers, and other death care professionals involved in handling bodies as part of this high-risk group.
The report declines to list specific industries which would be covered in Phase 2’s “critical workers in high-risk settings” but generally says:
The industries in which these critical workers are employed are essential to keeping society and the economy functioning. Since the beginning of the pandemic, millions of people have been going to work and risking exposure to the virus to ensure that markets have food; drug stores have pharmaceutical products; public safety and order are maintained; mail and packages are delivered; and buses, trains, and planes are operating.
Note also the text at the bottom of the graphic: they recommend that within each phase, priority be given to geographic areas where folks are more socially vulnerable in situations like these (e.g. as represented in the CDC’s Social Vulnerability Index).
In developing this phased approach, the committee focused on those who are at the most risk of exposure, severe illness or death, and passing along the virus to others as well as critical workers:
Risk of acquiring infection: Individuals have higher priority to the extent that they have a greater probability of being in settings where SARS-CoV-2 is circulating and of being exposed to a sufficient dose of the virus.
Risk of severe morbidity and mortality: Individuals have higher priority to the extent that they have a greater probability of severe disease or death if they acquire infection.
Risk of negative societal impact: Individuals have higher priority to the extent that societal function and other individuals’ lives and livelihood depend on them directly and would be imperiled if they fell ill.
Risk of transmitting infection to others: Individuals have higher priority to the extent that there is a higher probability of their transmitting the infection to others.
You should read (or at least skim) the full report for more information about the plan and the rationale behind it.
On a personal parting note, as someone who is squarely in the 5-15% of Americans covered in Phase 4 โ more specifically: as a 40-something straight white man who non-essentially works from home, isn’t low-income, doesn’t socialize widely even under normal circumstances, and should probably be the very last person on this whole Earth scheduled to be vaccinated under an equitable framework โ I am content to wait my turn should the US adopt this framework or something like it.1 Distributing vaccines to those who need them most is absolutely the right thing to do, both ethically and from the standpoint of getting society “back to normal” as quickly as possible and with as little additional death and suffering as possible.
Being that equity often isn’t America’s thing, especially during the pandemic, I could see this going either way. And even if this framework is adopted, those who can afford it will undoubtably be able to procure themselves a dose right alongside those medical workers in Phase 1a.โฉ
The preliminary results on the AstraZeneca vaccine were based on a total of 131 Covid-19 cases in a study involving 11,363 participants. The findings were perplexing. Two full doses of the vaccine appeared to be only 62% effective at preventing disease, while a half dose, followed by a full dose, was about 90% effective. That latter analysis was conducted on a small subset of the study participants, only 2,741.
Hopefully more study will be done on that dosage question. From the AP:
“The report that an initial half-dose is better than a full dose seems counterintuitive for those of us thinking of vaccines as normal drugs: With drugs, we expect that higher doses have bigger effects, and more side-effects,” he said. “But the immune system does not work like that.”
The seemingly lower efficacy comes with some perhaps significant benefits: this vaccine is cheaper to produce and doesn’t require any special refrigeration.
The vaccine can be transported under “normal refrigerated conditions” of 2 to 8 degrees Celsius (36 to 46 degrees Fahrenheit), AstraZeneca said. By comparison, Pfizer plans to distribute its vaccine using specially designed “thermal shippers” that use dry ice to maintain temperatures of minus-70 degrees Celsius (minus-94 degrees Fahrenheit).
The Pfizer and Moderna vaccines were pretty similar in many respects and this one seems quite different. These results were just released a few hours ago, so it will be interesting to follow the debate and expert commentary on this. Stay tuned…
Update: This is amazing: the seemingly more effective 1/2 dose + full dose regimen was a mistake.
Around the time when Astra was initiating its partnership with Oxford at the end of April, university researchers were administering doses to trial participants in Britain.
They soon noticed expected side effects such as fatigue, headaches or arm aches were milder than expected, he said.
“So we went back and checked … and we found out that they had underpredicted the dose of the vaccine by half,” said Pangalos.
A far smaller number of participants was given the initial half-dose, so more research will need to be done to determine if this mistake will be added to the long list of scientific discoveries made because of errors. There’s a good piece in Nature that talks about what we know and don’t know about the vaccine results so far along with some informed speculation.
But, if the differences are bona fide, researchers are eager to understand why. “I don’t think it’s an anomaly,” says Katie Ewer, an immunologist at Oxford’s Jenner Institute who is working on the vaccine. “I’m keen to get into the lab and start thinking about how we address that question.” She has two leading theories for why a lower first dose might have led to better protection against COVID. It’s possible that lower doses of vaccine do a better job at stimulating the subset of immune cells called T cells that support the production of antibodies, she says.
Another potential explanation is the immune system’s response against the chimpanzee virus. The vaccine triggers an immune response not only to the SARS-CoV-2 spike protein, but also to components of the viral vector. It’s possible that the full first dose blunted this reaction, says Ewer. She plans to look at antibody responses against the chimpanzee virus to help address this question.
Update:A short thread by Dr. Natalie Dean, which leads with “AstraZeneca/Oxford get a poor grade for transparency and rigor when it comes to the vaccine trial results they have reported”.
There’s a fatal flaw embedded in the basic Covid-19 test, trace, and isolate trifecta used around the world: It doesn’t account for the fact that the coronavirus is not an equal-opportunity pathogen. The people who are most likely to be tested, and to have the easiest time quarantining or isolating, are also the least likely to get sick and die from the virus.
From the United Kingdom to Sweden to Canada, we have evidence that the virus preys on people employed in “essential service” jobs (bus drivers, nurses, factory workers), which don’t allow for telecommuting or paid sick leave; people in low-income neighborhoods; and people in “congregate housing” like shelters, prisons, and retirement homes.
People of color tend to be overrepresented in these groups โ but there’s no biological reason they’re more likely to get sick and die from the virus. Simply put: They tend to work jobs that bring them outside the home and into close contact with other people, live in crowded environments ideal for coronavirus contagion, or both.
The state then directed efforts, resources, and money to nursing homes, the unhoused, prisons, and essential workers to make it easier for those folks to stay safe.
I also thought this bit was really interesting:
There’s a simple adage in public health: “Never do a test without offering something in exchange,” said Johns Hopkins’s Stefan Baral. So when a patient gets tested for HIV, for example, they’re offered treatment, support, or contact tracing. “We’re not just doing the testing to get information but also providing a clear service,” Baral added, and potentially preventing that person from spreading the virus any further. “This is basic public health.”
With Covid-19, the US has failed at basic public health. Across the country, people have been asked to get tested without anything offered in exchange.
“If we are asking people to stay home and not work, we have to make sure society is supporting them,” Baral said. “An equitable program would support people to do the right thing.”
“Never do a test without offering something in exchange.” To the extent that federal and state governments have been asking to people to stay home, get tested, and wear a mask, many of those same governments have been unwilling or unable to provide people with much in return for doing so. And so, here we are months into this, paying for that inaction with 250,000 lives.
You can access a free hotel room to safely isolate from your family, which include meals, Rx delivery, free wi-fi, medical staff on site, and transportation to and from hotel and medical appointments.
As I write this, it’s snowing outside here in Vermont and Covid-19 has finally gained a foothold in our little state. At the governor’s press conference yesterday, he and his pandemic response team announced that contact tracing done by the state showed that the rise in cases started as an outbreak in some hockey leagues. That initial outbreak wasn’t contained and subsequent non-essential, indoor, mask-less, multi-household gatherings and Halloween parties resulted in the very sharp rise we started to see here in the first week of November.
Scott explained that 71% of outbreaks reported from Oct. 1 to Nov. 13 were linked to “social events, parties and people hanging out at home or bars and clubs.” He added Vermont has not seen the virus spread widely at schools, restaurants or other businesses.
Dr. Mark Levine, the state health commissioner, said those parties came in a variety of sizes of parties โ Halloween gatherings large and small, dinner parties, baby showers, “people in the high single numbers at a deer camp.”
In states with many infections, particularly in the Midwest, contact tracing is all but impossible, so it’s instructive to pay attention to Vermont’s example here: we’re doing the tracing and the tracers say the infections are coming from people gathering indoors across multiple households. Which is exactly what public health and medical experts have been urging people not to do for months now.
And that brings us to Thanksgiving. For The Atlantic, Rachel Gutman asked her colleagues who have been writing extensively about the pandemic for some of their top safety rules and guidelines and their number one was, say it with me:
My colleagues’ guidance boils down to this winter’s golden rule for interacting with anyone outside your immediate household: Don’t spend time indoors with other people.
Here it is again in a fun font, just to make sure you got it: ๐๐ธ๐ท’๐ฝ ๐ผ๐น๐ฎ๐ท๐ญ ๐ฝ๐ฒ๐ถ๐ฎ ๐ฒ๐ท๐ญ๐ธ๐ธ๐ป๐ผ ๐๐ฒ๐ฝ๐ฑ ๐ธ๐ฝ๐ฑ๐ฎ๐ป ๐น๐ฎ๐ธ๐น๐ต๐ฎ.
Look, for some people spending time indoors with others is essential โ jobs, education, etc. โ but those who don’t have to, shouldn’t. And this goes for everywhere in the US because no states (aside from maybe Hawaii) are doing well right now โ cases are either high, rising sharply, or both. Please please don’t gather in indoor, multi-household groups for Thanksgiving if you haven’t quarantined beforehand. In the US right now, about 1-in-55 people who get Covid-19 die from it. With rates already high around the country, if many people do Thanksgiving as usual, an already horrific and deadly situation could become much much worse.
According to an unpublicized report by the Chinese government, the first documented case of Covid-19 was a 55-year-old person living in Hubei province on November 17, 2019. That makes today the first anniversary of the start of the Covid-19 pandemic. From that person (and possibly earlier or concurrent cases), the disease slowly and silently spread until it was determined to be due to a novel coronavirus.
They found that following the Nov. 17 case, about one to five new cases were reported every day and by Dec. 15, the total infections reached 27. Daily cases seem to have increased after that, with the case count reaching 60 by Dec. 20, the SCMP reported.
On Dec. 27, Dr. Zhang Jixian, head of the respiratory department at Hubei Provincial Hospital, reported to health officials in China that a novel coronavirus was causing the disease; by that day, it had infected more than 180 individuals. (Doctors may not have been aware of all of those cases at the time, but only identified those cases after going back over the records, the Morning Post reported.)
No one had any idea how much the world was going to change that day. What an awful, humbling, terrifying, ghoulish year.
The Swiss cheese model of accident causation is a framework for thinking about how to layer security measures to minimize risk and prevent failure. The idea is that when several layers of interventions, despite their weaknesses, are properly stacked up between a hazard and a potentially bad outcome, they are able to cumulatively prevent that outcome because there’s no single point of failure. During the pandemic, health care workers and public health officials have been using the Swiss cheese model to visualize how various measures can work together to help keep people safe.
Virologist Dr. Ian Mackay has visualized the Swiss cheese Covid-19 defense in a wonderful way (pictured above). Each layer of cheese represents a personal or shared intervention โ like mask wearing, limiting your time indoors w/ crowds, proper ventilation, quarantine, vaccines โ and the holes are imperfections. Applied together, these imperfect measures work like a filter and can vastly improve chances of success.1 He even added a “misinformation mouse” chewing through one of the cheese slices to represent how deceptive information can weaken these defenses.
Zeynep Tufekci says that a devastating third pandemic surge is upon us and that It’s Time to Hunker Down. She leads with the good news (vaccines, treatments, knowledge, testing capacity & quickness) but notes that with winter coming and a high baseline of cases from a summer not spent in preparation, now is the time to really knuckle down so that we can get to the finish line.
Whatever the causes, public-health experts knew a fall and winter wave was a high likelihood, and urged us to get ready.
But we did not.
The best way to prepare would have been to enter this phase with as few cases as possible. In exponential processes like epidemics, the baseline matters a great deal. Once the numbers are this large, it’s very easy for them to get much larger, very quickly โ and they will. When we start with half a million confirmed cases a week, as we had in mid-October, it’s like a runaway train. Only a few weeks later, we are already at about 1 million cases a week, with no sign of slowing down.
Americans are reporting higher numbers of contacts compared with the spring, probably because of quarantine fatigue and confusing guidance. It’s hard to keep up a restricted life. But what we’re facing now isn’t forever.
It’s time to buckle up and lock ourselves down again, and to do so with fresh vigilance. Remember: We are barely nine or 10 months into this pandemic, and we have not experienced a full-blown fall or winter season. Everything that we may have done somewhat cautiously โ and gotten away with โ in summer may carry a higher risk now, because the conditions are different and the case baseline is much higher.
On Friday, November 13, 170,792 new cases of Covid-19 were reported in the United States. About 3000 of those people will die from their disease on Dec 6 โ one day of Covid deaths equal to the number of people who died on 9/11. It’s already baked in, it’s already happened. Here’s how we know.
The case fatality rate (or ratio) for a disease is the number of confirmed deaths divided by the number of confirmed cases. For Covid-19 in the United States, the overall case fatality rate (CFR) is 2.3%. That is, since the beginning of the pandemic, 2.3% of those who have tested positive for Covid-19 in the US have died. In India, it’s 1.5%, Germany is at 1.6%, Iran 5.5%, and in Mexico it’s a terrifying 9.8%.
1. Reported deaths from Covid-19 lag behind reported cases by 22 days. Some deaths are reported sooner and some later, but in general it’s a 22-day lag.1
2. The overall CFR in the US is 2.3% but if you use the 22-day lag to calculate what Bedford calls “a lag-adjusted case fatality rate”, it’s a pretty steady average of 1.8% since August. Here’s a graph:
As you can see, in the early days of the pandemic, 4-6% of the cases ended in death and now that’s down to ~1.8%. That’s good news! The less good news is that the current case rate is high and rising quickly. Because of the lag in reported deaths, the rise in cases might not seem that alarming to some, even though those deaths will eventually happen. What Bedford’s analysis provides is a quick way to estimate the number of deaths that will occur in the future based on the number of cases today: just multiply the number of a day’s cases by 1.8% and you get an estimated number of people who will die 22 days later.2
For instance, as I said above, 170,792 cases were reported on Nov 13 โ 1.8% is 3074 deaths to be reported on December 6. Cases have been over 100,000 per day for 11 days now: here are the estimated deaths from that time period:
Date
Cases
Est. deaths (on date)
2020-11-15
145,670
2622 ย (2020-12-08)
2020-11-14
163,473
2943 ย (2020-12-07)
2020-11-13
170,792
3074 ย (2020-12-06)
2020-11-12
150,526
2709 ย (2020-12-05)
2020-11-11
144,499
2601 ย (2020-12-04)
2020-11-10
130,989
2358 ย (2020-12-03)
2020-11-09
118,708
2137 ย (2020-12-02)
2020-11-08
110,838
1995 ย (2020-12-01)
2020-11-07
129,191
2325 ย (2020-11-30)
2020-11-06
125,252
2255 ย (2020-11-29)
2020-11-05
116,153
2091 ย (2020-11-28)
2020-11-04
103,067
1855 ย (2020-11-27)
Totals
1,609,158
28,965
Starting the day after Thanksgiving, a day traditionally called Black Friday, the 1.6 million positive cases reported in the past 12 days will result in 2-3000 deaths per day from then into the first week of December. Statistically speaking, these deaths have already occurred โ as Bedford says, they are “baked in”. Assuming the lagged CFR stays at ~1.8% (it could increase due to an overtaxed medical system) and if the number of cases keeps rising, the daily death toll would get even worse. As daily case totals are reported, you can just do the math yourself:
number of cases ร 0.018
200,000 cases in a day would be ~3600 deaths. 300,000 daily cases, a number that would have been inconceivable to imagine in May but is now within the realm of possibility, would result in 5400 deaths in a single day. Vaccines are coming, there is hope on the horizon. But make no mistake: this is an absolute unmitigated catastrophe for the United States.
Tibshirani’s first finding was that the lag time between states was quite variable-and that the median lag time was 16 days, a lot shorter than the mean. Looking state by state, Tibshirani concluded, it seemed difficult to land on an exact number of days as the “right” lag “with any amount of confidence,” he told us. Because cases are rising quickly, a shorter lag time would mean a larger denominator of cases for recent days โ and a lower current case-fatality rate, something like 1.4 percent. This could mean fewer overall people are dying.
But this approach does not change the most important prediction. The country will still cross the threshold of 2,000 deaths a day, and even more quickly than Bedford originally predicted. Cases were significantly higher 16 days ago than 22 days ago, so a shorter lag time means that those higher case numbers show up in the deaths data sooner. Even with a lower case-fatality rate, deaths climb quickly. Estimating this way, the country would hit an average of 2,000 deaths a day on November 30.
The other major finding in Tibshirani’s analysis is that the individual assumptions and parameters in a Bedford-style model don’t matter too much. You can swap in different CFRs and lag-time parameters, and the outputs are more consistent than you might expect. They are all bad news. And, looking retrospectively, Tibshirani found that a reasonable, Bedford-style lagged-CFR model would have generated more accurate national-death-count predictions than the CDC’s ensemble model since July.
Courtesy of Ed Yong, the lag between cases and hospitalizations is about 11 days. So the full ICUs and packed ERs were hearing about now are going to get so much worse in the next two weeks. And just think about the potential situation a month from now if cases keep rising at the rate they are now for two more weeks…โฉ
Just to stress again: this is only an estimate. The real reported deaths from a single day’s reported cases will be spread out over several days or weeks. And case reporting is much lower on Sundays and Mondays than on other days (fewer reports on weekends). Bedford accounted for this in his analysis by using 7-day averages.โฉ
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