Earlier this week, CBS News reported that New York had conducted an antibody test on a sample of its residents. Analysis of the test revealed an estimated infection rate of 14% across the state. This takes the estimated mortality rate down to .55%, far lower than what we get when deaths are compared to confirmed cases, currently in the neighborhood of 6% for New York, nearly 100x more deadly than flu.
A .55% mortality rate puts coronavirus a mere 9x more deadly.
The US is divided on how to think about all of this, half of us in favor of lockdown, the other half convinced, still, that CV = flu, now vindicated by the New York study. Understandably, my social media feed has lit up with legions of “told you so” thoughts and reflections on how stupid it is to keep our country in lockdown.
We knew it along, my friends say. Given the new data, a continued lockdown is further evidence of some level of anti-America conspiracy.
When it comes to “all of the data,” we’re all hurting – there’s tons out there, especially when it comes to antibody tests that are currently on the market and how they’re being used.
As with any story, there’s another side of the story, and you don’t have to dig deep to find it.
When a friend of mine posted the New York data, reminding us that this lockdown needs to end, I set out to prove him wrong – I’m just as biased and emotional as anyone else about all of this. Job #1 is therefore to go on the hunt for data that more closely jives with my version of reality.
I found some!!!
I still have a shot at being right.
Seriously though, if you’re looking for a fuller picture, here are some of the things I’ve looked into as I try to get my head around reality. What follows doesn’t make me right and everyone else wrong, I’m posting below because I think these are important to consider.
We’re united in our belief that testing is the only way forward. To move things along, the FDA has lifted restrictions on test providers, allowing about 90 companies, mostly from China, to sell in the US without formal federal review or approval. As you can imagine, a few folks are uncomfortable with this:
“Tests of ‘frankly dubious quality’ have flooded the American market.” ~ Scott Becker, executive director of the Association of Public Health Laboratories.
“People don’t understand how dangerous this test is… We sacrificed quality for speed, and in the end, when it’s people’s lives that are hanging in the balance, safety has to take precedence over speed.” ~ Michael T. Osterholm, infectious disease expert at the University of Minnesota.
“The problems mainly happen with rapid tests… They will never be able to tell the spread of the virus because they do not have the required sensitivity and specificity.” ~ Dr. Giorgio Palù, Italian microbiologist and former president of the European Society for Virology.
There’s also a problem with methodology, especially with regards to the New York study which was primarily conducted on the “out and abouters;” people hanging out in public places, not-so-religious about stay at home orders, more likely to carry the antibody, skewing the results. A more comprehensive study would need to include those on the other extreme, far less likely to be infected.
Again, as the number of infections increase, the mortality rate decreases. A test with artificially high (or low) infection numbers will yield artifical mortality rates. New York may ultimately prove itself to have low (or high) numbers, but their recent test is far from proof that a US lockdown is unwarranted, or conspiratorial.
A similar test was conducted in Santa Clara county in California, not yet peer reviewed, but yielding similar results; a much-higher-than-previously-reported infection rate. Statisticians and biomedical researchers weren’t happy:
“Do NOT interpret this study as an accurate estimate of the fraction of population exposed… Authors have made no efforts to deal with clearly known biases and whole study design is problematic.” ~ Marm Kilpatrick, infectious disease researcher at the University of California Santa Cruz.
“Statistician John Cherian of D. E. Shaw Research, a computational biochemistry company, made his own calculations given the test’s sensitivity and specificity — and conservatively estimated the proportion of truly positive people in the Stanford study to range from 0.2% to 2.4%.”
“Biostatistician Natalie E. Dean of the University of Florida called it a ‘consent problem.’ The Facebook ad might have attracted people who thought they were exposed to the virus and wanted testing.”
We’re in a hurry to get back to normal, and getting back to normal means testing = we’re in a hurry to test. This will naturally skew our numbers. It will be awhile before we have clear, relatively inarguable data that can help us decide how to move forward.
Until then, we’ll need to do our best to fact check, get our heads around both sides of the story/who the storytellers are, and try like hell to set our emotions aside before we take to public forums and contribute to misinformation, which is a bad thing right now.
Every perspective is biased. Before we decide what’s true and what’s not, we’re compelled to figure out what those biases are before moving forward. For example, this press conference, held by two ER docs who lean heavily towards the “CV = Flu” side of the story, is circulating around the internet:
According to their research, healthy people no longer need to shelter in place.
I don’t intend to discredit them, or try and convince you that they’re wrong, but if we’re going to allow perspectives like this into the courtroom, both lawyers get to speak. Here’s what I find missing:
- Neither are experts in the field of epidemiology, statistics, etc. Yes, they studied these in med school, like I studied Greek in seminary, but neither of us are experts.
- No mention is made of the structure of their study. Who was tested? What are the biases? How is it skewed? The method/structure/etc. isn’t published or peer reviewed – no way to know.
- They own a business that, financially speaking, according to them, is being negatively affected by this current shut down.
- They claim that, according to the “scientific minds that read this stuff everyday,” we now have the facts required to open the country. Who?
- Most importantly, the entirety of their argument hinges on data based on antibody tests, with no mention of the biases/faults mentioned above.
These guys have a right to speak and to share their perspective, and we should listen.
But I’m uncomfortable that this is represented as “expert” research, and that it jives in no way with the perspectives from the MD’s I’m surrounded by, or reccomendations from WHO, CDC, etc.
Either way, there’s not enough here to prove a conspiracy, or to lose our minds because so many in the world still stand in favor of the stay-at-home order.
Moving forward, our tests will get better, and we’ll get more data. We may very well discover that our reaction was overblown and that we were wrong to shut down the country. Until then, I’ll respect those who I don’t disagree with, while simultaneously checking their story, and staying home until I see something a bit more compelling.
Part of the issue here is the research you’re doing is for two different tests. There’s the antibody blood test (which is the results you first address) and then there’s the COVID19 infection test to test whether someone currently has the disease (which is done with a mouth swab, not blood). These are two completely different tests and the issues most of the quotes you supplied above are NOT about the antibody blood test.
You’ll have to hold my hand on this one – I show Becker, Osterholm, and Palu quotes all related to antibody tests. The quotes from Dean, Kilpatrick, and Cherian were all responses to the Santa Clara antibody study, right? If not, can you give me some links? I can’t find anything indicating otherwise.