Newsweek published an article by a doctor who doesn’t (so far as I know) believe that reptilians run the US government and alien DNA is being used in scientific experiments.
He does, however, claim hydroxychloroquine helps COVID-19.
As far as we know, this is false. My brief note on this is here.
And his article is terrible. If you want a point by point analysis, see here. A quote:
The rest of Prof. Risch’s AJE article is a veritable Gish gallop of cherry-picked studies. Hilariously, he relies heavily on uncontrolled “studies” and case series from two grifters, Didier Raoult and Vladimir Zelenko….
I had a hard time believing that an actual professor of epidemiology at a school as reputable as Yale could write such drivel. The study he is referring to is Gautret et al., a study so awful, so full of flaws (and maybe even fraudulent), that it was quite properly dragged on science and medical Twitter for days and weeks afterward. That Prof. Risch would cite such an abomination of science tells you all you need to know about him.
A video is making the rounds touting the merits of hydroxychloroquine. The doctors in the video claim there’s evidence in helps in humans (citing a 2005) paper. That paper was in tissue culture (i.e., a petri dish), not real live humans.
You and I are not petri dishes. Bleach will kill bacteria in a test tube. You should not drink bleach to kill bacteria in you.
No current guidelines recommend the use of hydroxychloroquine in the treatment of COVID-19. Here’s Canada. And the CDC.
Hydroxychloroquine can cause heart issues, especially in combination with some other drugs. All drugs have potential side effects, and so using a drug “just because” is not always a risk-free undertaking. See here. And here. And here. That’s especially true with COVID, given that there is good evidence that at least some patients have COVID-related heart problems.
It’s bad to pour gas on a fire.
CDC recommends against its use except in a clinical trial (which I suspect will become less and less common as the evidence against it mounts).
Some have worried that COVID-19 cases are being over diagnosed. This almost certainly isn’t true. A useful tool is the excess mortality tracker that measures how many more deaths there ate currently compared to past years.
I’ve posted on this before, but there’s now a running total tracker here.
This is an interesting article on a possible approach to long-standing COVID-19 immunity here.
One of the problems with other approaches is that other coronavirus immunity is not typically long-lasting, and fades. Thus, even herd immunity may not give us long-term protection, and standard vaccine approaches might need to be repeated frequently.
This approach, if feasible, would be a game changer. And its written by someone who actually knows what they’re talking about.
Many people have shared two ER docs’ claims about coronavirus.
Despite their claims, they are not experts. They misrepresent the data, and their professional college has condemned their actions. (They also lie about what their local public health department believes, see here.)
ER docs (and family docs) are not the experts in this. Epidemiologists are. You don’t ask epidemiologists to read your chest x-ray or put in your chest tube.
We’ve talked here about the problems and limitations of antibody tests. We’ve seen others discuss it. And a primer on the mathematical whys and wherefores is available here.
Today some pre-publication data on a variety of US antibody tests were released, and they aren’t great–and they illustrate precisely the problems discussed above:
Note: If you or someone you know is feeling suicidal, help and hope is available and effective. Please call the resources here. [Hotline: 1-833-456-4566] If you or someone else is in immediate danger, call 911 immediately.
All medications have potential side effects. All treatments have potential downsides. Even a decision to do nothing is a decision–and it has a potential negative effects.
As we head into yet another week of lockdown with no clear end in sight, unemployment climbs and GDP continues to drop. This is a “side effect,” if you will, of the public health “treatment” for the COVID-19 outbreak. And it is a not insignificant question to ask when those side effects begin to outweigh the benefits (or if they already have).
I don’t think anyone knows this for certain. There’s more we could say, but that’s a subject for another time.
As we continue in lockdown, the costs mount in human and economic terms.
One problem which we’ve noted frequently is that it is difficult to get a true sense of the virus’ fatality rate, since knowing how many cases there are depends very much on widespread testing. Do less testing, and you’ll find less virus. But if you find less virus, then the fatality rate (% of people with the disease who die) will appear higher than it truly is. (And, since we’re unlikely to ever measure every single case, fatality rates should be treated as a sort of “upper bound”–the actual rate will almost always be at least somewhat lower.)
I ran onto an interesting and useful way to think about such things, published in The Economist this week.
It takes the approach of calculating “excess deaths.” That is, with historical statistics you can know what the typical rate of death at any time of the year is from all causes. Those numbers might fluctuate a bit (say in a bad flu season) but from year to year in a given country, they stay remarkably consistent.
So, one approach to getting a handle on COVID-19 is to simply say, “What’s the excess rate of death?” How many more deaths are we having this year (regardless of diagnosis) than is typical?
The data is mostly from Europe. Here’s their graph for the aggregate statistics compared to the last 10 years:
You can see the peaks of the last few years’ influenza (2017, 2018, 2019). Those have been exceptionally high years compared to the average death rate over the last ten years:
Compared to the baseline average of deaths from 2009-19, the flu seasons of 2017, 2018 and 2019 were all unusually lethal. But the covid-19 pandemic, which arrived much later in the year, has already reached a higher peak—and would have been far more damaging without social-distancing measures. Compared with the baseline, EuroMOMO’s figures suggest that there were about 70,000 excess deaths between March 16th and April 12th.
This also allows them to compare the known COVID-19 deaths with these total excess deaths. So, you can get a sense of how good the testing is. In this graph, New York does very well (but one wonders if there are undiscovered deaths at home, etc., that may change this) compared to some third world countries who understandably do much worse (though the first world does not necessarily cover itself in glory either). One wonders too if New York is including deaths as a result of COVID from other causes in their stats:
Why is this useful?
I think that this has a few benefits as we try to understand COVID-19:
it is less likely that officials would miss a death than miss a COVID-19 diagnosis. Deaths are easily diagnosed with the naked eye!
It lets us access some of the “hidden deaths” that might not be COVID infections, but result if a healthcare system is overwhelmed. [These are, say, your heart attack patients who would have lived if there’d been an ICU bed, or if they weren’t afraid to go to the hospital, or if the ambulances weren’t taking 2 hours to get somewhere instead of 5 minutes.) An effort to lower these “hidden deaths” (which could affect any age group) is one big reason for the “social distancing.” So, this type of analysis can be used to determine what the costs of a health care system overload actually are.]
It could also get you a look at causes of death from lockdowns if you picked the right time window. One potential issue could be higher rates of suicide, for example, compounding because of either lack of social supports, financial strains, or fear. This is a complex subject, which I’ve treated in a separate post here.
It gets us a look at impacts on a variety of age groups. Here’s the same data separated out by age:
So, while the over-65 group (the top graph) certainly has an elevated death rate, people younger than 65 are also markedly increased. So this tells us that COVID-19 is not simply hitting old people in extended care homes–there is a cost to younger people too.
Interestingly, the 14 and under group has a lower death rate. This makes sense–COVID-19 is rarely fatal to children, and lockdowns mean that kids are doing fewer “risky” things, like riding bikes, or getting hit by cars, or driving around in cars.
This also highlights that we always accept some degree of risk. Our kids would be safer if we locked them in the house forever. But, we clearly don’t and shouldn’t do that. Some risks are worth running.
Defining where that line is for COVID-19 is one of the vexing problems currently facing citizens and governments.
I’d like to see more analysis like the above, particularly focused on Alberta and Canada–it might guide policy-makers in these types of decisions.
Critiques and analysis of John Dehlin's activities mostly focusing on his written contributions, but occasionally straying into other media and activities.
Angels in the Architecture 