I wrote about half of this May 18th. I had stayed up all night reading medical research papers as I kept finding questions that needed to be answered and assumptions of mine that needed to be challenged. Stupidly I wrote it as a Facebook status update and was just ready to hit “Post” when my browser tab crashed and I lost it all except the first part which I had copied and pasted into a WordPress draft. I took this as a sign at 7 am that I was not supposed to post it in the week or so before my wedding, so I saved it as a draft and fell into a disappointed, espresso-tinged sleep.
Fast-forward to last night, our church was considering what actions to take with services going forward in light of the ongoing Covid19 situation. I put together an email that highlighted the least controversial, most authoritative research that showed how objectively and comparatively non-deadly Covid19 actually is, in direct contrast to the media hype that 65% of folks believe.
This post is a combination of those two documents.
However, in the meantime my Uncle N. sent me this fantastic, well-referenced summary of available evidence by a Swiss doctor. It is far more concise and comprehensive and is much more up to date than my knowledge of the body of medical research, which is about 1.5 months old. (You probably should just read it instead of my ramblings.) As I penned in my email this morning, I expect the evidence to keep pushing the IFR downwards because that’s been the trajectory all along. Literally a few hours after writing that, that evidence came to my attention.
I was wrong.
My process wasn’t wrong. My thinking wasn’t wrong. Playing it safe wasn’t wrong. My realization that this was going to be a big deal before most people realized it was a big deal wasn’t wrong–in fact I take small solace in that little nugget of foresight among the vast mountain of wrongness, but the bottom line is that I was incorrect and massively incorrect by a full order of magnitude (that means 10x off, which in small percentages is HUGE) because I assumed–along with most of the medical community–that Covid19 was similar to our simplistic understanding of most other diseases (especially respiratory and flu-like viruses) in one critical aspect. It turns out that in this critical aspect, it was *not* the same as most of the other diseases; in this aspect it was novel. You might even call it a novel coronavirus.
Our layperson understanding is that most viruses and bacterial infections have one unifying feature: when you are infected by them, you get sick. When I first posted about Covid19, we had already accidentally noticed that Covid19 didn’t quite follow this pattern the way we understand most other diseases to do and it was a cause for worry because it might have allowed Covid19 to spread undetected in stealth mode (I mentioned this worry in my linked Facebook status update). But what we had no clue of was how many more people were asymptomatic than we thought possible. (See section Asymptomatic Infection immediately below.)
If you want the bottom-line conclusion, Covid19’s infection fatality rate, according to the CDC’s best guess way back on May 20th, is only 2.6x as bad as seasonal flu. (Their best-case scenario estimate is the exactly same as seasonal flu and their worst-case scenario is 8x seasonal flu.) However, additional info suggests that even 2.6x is high.
Hooboy, this is a rabbit hole that needs a full-length blogpost of its own, but I’ll try to limit it to one tangential section of this post. You can feel free to skip this section unless you’re the curious, sciency sort.
A crucial part of thinking well is testing one’s most basic “duh, everyone knows that” presumptions about the way the world works. For me in researching this post, the testing of such a notion that bore fruit was, “When you get the viruses we’re familiar with, you get sick.” I Googled for asymptomatic viruses and found a couple of common STDs (chlamydia, HepB, HepC) that are mostly (70-99%) asymptomatic. I slapped my forehead because I did know chlamydia was asymptomatic due to a friend’s Facebook post a while back (thanks, FM!). My next assumption was that it must be that respiratory viruses and flu-like viruses are mostly symptomatic. Mostly wrong again! (On this point, I would LOVE to see a poll of MDs and epidemiologists on what they think the percentage of asymptomatic cases are for this category of viruses. I’m intensely curious whether these studies I found are widely known; I certainly hope they are, but I’m afraid they’re less known than they should be.)
Asymptomatic/Presymptomatic Transmission and Pandemic Response
The truth appears to be best summed up and applied to our current situation by some INCREDIBLY prescient remarks in a medical study I found from 2009:
“A better understanding of transmission dynamics is essential in influenza pandemic planning. If a substantial proportion of transmissions were to occur during the presymptomatic phase or from asymptomatic individuals, then infection control measures such as contact tracing and quarantine of exposures would be of limited value.”https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646474/
WOW. Eleni Patrozou and Leonard Mermel, I salute you. You are brilliant and prescient. You recognized a huge hole in our medical knowledge and you knew how that hole would impact our attempts to battle pandemics. I know there are some big concepts in that paragraph and I needed to read it a few times slowly to get it, but basically they’re saying the medical community has done a poor job studying asymptomatic and presymptomatic stages of viruses, especially how it relates to virus transmission. The failure to understand this has led to advocacy for possibly ineffective infection control measures like quarantine and contact tracing. (Wow. They wrote this is 2009, not 2020.) They looked for all the experiments they could find on asymptomatic/presymptomatic transmission (to do a meta-study) and found them all flawed and inconclusive. Their conclusion was more studies were needed.
(Ironically, they guessed that there was LESS asymptomatic/presymptomatic virus spreading than is commonly assumed, but because they stuck to the objective facts and highlighting the holes in the experimental data and the objective ways those holes would affect our planning, they look brilliant even though their guess was the opposite of the truth. So many people fail to distinguish the facts they know from the guesses they have about those facts. That is the biggest failure in both medical pros’ and laypersons’ thinking/opining/teaching through this pandemic.)
Percent of Infections that are Asymptomatic
I also found this fantastic study from 2015 that is a meta-analysis of many studies that sought to determine the asymptomatic rates of various influenza strains, which are far, far higher than widely believed due to a focus on CFR (and then very rough attempts to model IFR with likely shaky assumptions) with obvious selection bias in testing of those symptomatic. Among the serologic studies adjusted for other illnesses, they found 65-85% of those infected were asymptomatic. Here are the two key paragraphs from this meta-analysis:
We conducted a systematic review and meta-analysis of published estimates of the asymptomatic fraction of influenza virus infections. We found that estimates of the asymptomatic fraction were reported from two different types of studies: first, outbreak investigations with short-term follow-up of potentially exposed persons and virologic confirmation of infections; second, studies conducted across epidemics typically evaluating rates of acute respiratory illness among persons with serologic evidence of infection, in some cases adjusting for background rates of illness from other causes. […]
In conclusion, the true asymptomatic fraction of influenza virus infections may depend on how infections are identified, and we found quite different estimates of the asymptomatic fraction in two different types of studies. In outbreak investigations where infections were virologically confirmed, we found a pooled mean of 16% (95% CI: 13%, 19%) of infections were asymptomatic, whereas in longitudinal studies in which infections were identified using serology the point estimates of the asymptomatic fraction adjusted for illness from other causes fell in the range 65%–85%. We could not fully explain the differences in the scale of estimates from these two types of studies, although features of the respective analyses would have led to under- and over-estimation of the asymptomatic fraction respectively. A study in Vietnam did include both of these strategies, estimating the asymptomatic fraction as 45% (17%–77%) in outbreak investigations versus 86% (82%–89%) in the longitudinal serologic analysis (27, 35). One potential approach to resolve these differences would be a hybrid study, where intensive follow-up with frequent virologic testing regardless of illness throughout an influenza season is used to ascertain all infections and illnesses in a cohort.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586318/
A later 2019 cohort study found this excellent info:
Respiratory viral infections are a leading cause of disease worldwide. A variety of respiratory viruses produce infections in humans with effects ranging from asymptomatic to life-treathening. Standard surveillance systems typically only target severe infections (ED outpatients, hospitalisations, deaths) and fail to track asymptomatic or mild infections. Here we performed a large-scale community study across multiple age groups to assess the pathogenicity of 18 respiratory viruses. We enrolled 214 individuals at multiple New York City locations and tested weekly for respiratory viral pathogens, irrespective of symptom status, from fall 2016 to spring 2018. We combined these test results with participant-provided daily records of cold and flu symptoms and used this information to characterise symptom severity by virus and age category. Asymptomatic infection rates exceeded 70% for most viruses, excepting influenza and human metapneumovirus, which produced significantly more severe outcomes. Symptoms were negatively associated with infection frequency, with children displaying the lowest score among age groups. Upper respiratory manifestations were most common for all viruses, whereas systemic effects were less typical. These findings indicate a high burden of asymptomatic respiratory virus infection exists in the general population.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518513/
Here are a few more noteworthy studies on this topic (and related ones), keeping in mind SARS is a close cousin of Covid19:
- Asymptomatic SARS Coronavirus Infection among Healthcare Workers, Singapore
- Asymptomatic Severe Acute Respiratory Syndrome–associated Coronavirus Infection
One of the key metrics that has grabbed my attention from the very beginning of Covid19 was the death rate. What percent of folks that get Covid19 die? We started out with estimates of 3-5%. That was horrifying and would be a plague of Biblical proportions if the whole world got it. However, the key flaw in that estimate was that it was the CFR (case fatality rate) which is the number of folks who died divided by the number of confirmed cases. That made some perhaps logical, but ultimately very flawed, assumptions about this brand-new virus that we knew very little about. It basically assumed that if you were infected by the virus, you got sick, and got tested. (In fact, as I studied this to see if this was a reasonable assumption, I found out that we are only discovering through some excellent medical research in the past decade that a huge proportion of those infected with various respiratory viruses (and also some who get flu viruses) are also totally asymptomatic. So our understanding of that is very… fresh… as well. See previous section “Asymptomatic Infection” for more details of that.)
The proper metric to figure out how serious a virus is, is the IFR (infection fatality rate) which is the number of deaths divided by how many folks actually got infected by the virus, not just the ones who were tested and confirmed (which suffers from a selection bias of those that feel sick and misses most of the folks who were asymptomatic or with mild symptoms). The only way to get an accurate number for the IFR is to get that denominator of how many folks actually got infected, correct. The only way to do that is to test everyone in a geographic area with an antibody test (it turns out that antibody tests likely undercount those infected by 5x: this, this, and this indicate how) to see how many have had the virus in the present or past. Then you have an accurate denominator and you take everyone that died in that geographic area as your numerator and you finally, finally have an accurate death rate.
It turns out that somewhere between 30-90% of folks who are infected by Covid19 have zero symptoms and have no idea they were ever sick.
Dr. James Todaro with the help of some other researchers gathered all the geographic antibody studies done through May 13th. They ranged widely in IFR, but the average was 0.34%. That’s ~3x the IFR of flu (which is generally understood to be about 0.10%, though some say as high as 0.16%).
I’m sure some of you are thinking that he is just some crackpot doctor on Twitter who is way off base but seeking attention and influence. But he’s been right on every count long before the medical establishment has admitted it. (He even led the way in getting The Lancet, the leading medical journal, to withdraw a peer-reviewed study of Covid that was based on likely faked, and certainly inaccurate, data.) The CDC finally said the same thing (though it was a week after Dr. Todaro said it) on May 20th. The CDC’s current best estimate is a 0.4% sCFR (symptomatic CFR) which comes to 0.26% IFR (even lower than Dr. Todaro’s average!) when adjusted for that CDC scenario’s 35% asymptomatic rate (which I believe is low, but if you trust the CDC, my opinion is irrelevant). The CDC has five total scenarios that integrate their best upper/lower bound guesses on a number of virus variables. Two of the best/better-case scenarios actually have a 0.2% sCFR (which is a 0.16% or 0.1% IFR after being adjusted for that scenario’s asymptomatic rate). Their two worst-case scenarios have an IFR of 0.5% and 0.8%, 5x and 8x flu respectively.
That’s the current, medical bottom line if you wish to rely upon the pre-eminent governmental medical authority: 0.1% is the currently accepted IFR of seasonal flu. The CDC is saying in their best guess, most likely scenario the IFR is 0.26% which is 2.6x that of seasonal flu, with worst-case scenario being 8x flu and best-case being 1x or same as flu. Needless to say, as I’ve watched Dr. Todaro’s prescient and early accuracy and the continued failure of early, mainstream, scare models devolve into embarrassed corrections, I have little question on which of their estimates I’m betting on.
Since writing that last sentence, I’ve found the studies that say antibody studies undercount infections by 5x linked above and I’ve found this meta-analysis that calculates an IFR of below 0.1%.
I’ve also found based on that same meta-analysis of CDC data that the median age of death of Covid patients in the US is 80 years old while the US life expectancy is only 78.6 years old. It appears (I say very sarcastically) that getting Covid is good for your health, because it raises your life expectancy. In actuality, this highlights the HUGE role that comorbidities play in Covid deaths, with Covid mostly killing folks who likely would have had similar risks of dying from any of hundreds of other exacerbating illnesses working in concert with pre-existing comorbidities. It also reminds us that we should ALWAYS be more careful in protecting the elderly who have comorbidites like heart trouble, lung trouble, blood clot trouble, etc from any little illness we may be carrying. Covid is by far from the only exacerbating illness like this. A full 42% of all US Covid deaths are from nursing homes. It is a tragedy that Governors Cuomo and Wolf in NY and PA fumbled this key insight so badly by forcing Covid patients back into nursing homes which helped cause NY and PA to be the 2nd and 11th leading states of Covid death per capita in the US.
Questions, Fears, and a Vaccine
Is it worth neglecting the assembling of ourselves together for something that is very conservatively 3x as bad as flu? Is it worth living in stress and fear and worry and extreme life modification over something 3x as bad as flu? I think we’d all very clearly answer “No!” to that. It’s only been media hype that makes us think it’s way, way worse than the flu.
I don’t think it’s productive to assume negative motivations (fearfulness) for our brothers and sisters who have a different understanding of the facts. I am NOT a fan of all the accusations of fear without a reasonable, fact-based, science-based explanation of why the fears are ill-founded. However, I do think there is healthy fear and unhealthy fear. I think even the folks who are on the more cautious end of the spectrum would agree that they themselves are living in healthy fear. Whether that fear is healthy or not depends upon your understanding of what the facts are and your analysis of them. Hopefully this post will give those folks an alternative and fuller perspective on the underlying medical facts, though obviously my understanding is far from infallible.
I would add that some people are holding out hope for a vaccine, but that’s a rather… chancy hope. HIV has been around for decades and there’s little hope for a vaccine despite billions of dollars of research. Flu has some vaccines, but they’ve mutated into so many different strains, choosing which to include in the annual cocktail is educated guesswork. Dengue is another extremely severe virus that has been around forever and still has a big impact on our world, but for which there exists no vaccine despite lots of motivation. The idea that a vaccine is around the corner is perhaps true (and there have been recent promising preliminary results, presumably on a single strain), but there is no guarantee.
So my question for us is: what’s the end-game here? I think (and many mainstream experts concur including Dr. Fauci) that Covid19 is here to stay, just like the seasonal flu. It’s already mutated into at least 14 strains (some researchers say 30 strains). It’s mutated to become more contagious. We cannot hide in our houses and behind our masks forever. We’re all going to eventually get it over a series of seasons, just like the flu, unless by some miracle a vaccine is developed that works for all strains. We have to think long-term of likely scenarios; we cannot put life on hold forever.
History Rhymes: The Influenza Pandemic of 1918
I’d like to just end with a historical comparison that stunned me with its applicability. It is incredibly striking the headlines, signs, and photos from 1918 when the Influenza Pandemic (as they called it at the time) first thrust itself to primary attention in the public consciousness. Just take a moment to enjoy these headlines, sub-headlines, and photos and join me in laughing in disbelief that these were from 1918 rather than 2020:
Does that ring a bell?
Nowadays it’s not a pandemic, it’s just the flu. But in 1918 it was new and scary and was killing people at a faster clip at first (because they didn’t yet have herd immunity and lacked treatments to reduce severity), so it WAS noteworthy and it WAS scary. At the time, there was actually genuine reason for fear and panic because it had an actual IFR of 1.7 to 2.9% (6-11x worse than Covid and 17-29x worse than flu is now) and 28% of the US got it. But soon it became a fact of life. As herd immunity grew and medical knowledge on how to treat it grew, it slipped down to its present-day 0.1% IFR (17-29x reduction in fatality rate) and getting various strains of the flu several times is every child’s rite of passage into this sin-cursed earth. (And imagine what will happen to Covid’s IFR since it is starting at ~0.3%, if it undergoes a 17-29x reduction!) So I think there is very valuable perspective to be gained by comparing notes with history because it shows us what happened with a much more severe and deadly disease called influenza. It really puts things into perspective.
In conclusion, we need to stop these misguided lockdowns. Flattening the curve turned out to be a fiction, with empty hospital beds everywhere (rural red areas have been especially hard hit) except a few hotspots and suddenly unemployed health professionals with millions of necessary medical procedures pushed off, killing untold people. Suicides spiked. Drug overdoses spiked. Mental health was greatly damaged. (WaPo: “Three months into the coronavirus pandemic, the country is on the verge of another health crisis, with daily doses of death, isolation and fear generating widespread psychological trauma. Federal agencies and experts warn that a historic wave of mental-health problems is approaching: depression, substance abuse, post-traumatic stress disorder and suicide.”) Many have made the compelling case that the lockdown is many times worse than the few lives that may have been saved.
Because of presymptomatic spread, lockdown was all in vain from the data I’ve seen. Given its extreme transmissability, trying to stop it was a laudable fantasy that resulted from insufficient knowledge. Because of asymptomatic infection and immunity, the numbers were quite skewed until some basic, hard work was done to challenge assumptions as to which antibodies were efficacious to prevent infections and to accurately establish the denominator of the death rate. Since we’ve figured that out and that it’s either little different than seasonal flu or a bit more severe than seasonal flu, it is not desirable to stem the spread. If we can protect our seniors in the short term and get herd immunity for everyone else (according to CDC, IFR for ages 0-49 is 0.03% (1/3 of the flu) and ages 50-64 is 0.13% (almost identical to flu)), we can actually get sustainable herd protection for our seniors in the long term much more quickly. (In the meantime, please feed your seniors Zinc, CQ10, and Vitamin D on a regular basis.)
I welcome corrections to fact, opposing theories, further nuance where I failed to provide it, etc, etc. I’m simply a fellow traveler who loves medical science and research. I have no medical training, just a knack for understanding science and analysis. I’m sure I’ve made mistakes and I welcome corrections.
I am disappointed in our governmental medical policy community and especially disappointed in the media that I’m forced to spend this time studying these things I’m not trained in and summarizing them. Is it really too much to ask to have rigorous medical reporting that gives an unbiased state of play without the overriding motivation of “defeat Trump”? (The media’s deep and abiding hatred of Trump and willingness to stoop to anything (only the latest and most outrageous example) to ensure he is not re-elected is obvious even to me who is voting against Trump in 2020.) How many must die before we get a press willing to get the basics right again?