Spoiler: We accomplished nothing.
ASTORIA, NYC- I was sitting at a picnic table in the back patio of my local Astoria dive bar, sipping on a beer and responding to some comments on my Blackberry, when I struck up a conversation with the couple who were sitting next to me. The dude was around 40 and could have made good use of a toupée. The girl was around half his age, pleasantly chubby, and laughed a lot. My take was that they were co-workers having a beer on their lunch break.
We talked about the usual: how much the lockdown sucked and how we’re happy that things are opening up again. Then I mentioned something about how NYC now has herd immunity against Sars-Cov-2.
“Hold on,” the dude exclaimed. “We don’t have herd immunity.”
“Then why do we hardly have any cases anymore?”
“Because we’re all wearing these!” he stated proudly as he pulled the cloth bandana that was tied around his neck up over his mouth.
I had try hard to keep myself from laughing. The guy really though that his loosely woven cotton / polyester bandana was checking the flow of a 0.06 to 0.14 micron virus. Not even a properly worn N95 mask can really do that.
I did not see the point in mentioning the fact that we were also wearing face coverings in March, April, and May, when Sars-Cov-2 was raging out of control through the city. What? Did masks magically start working in June?
The fact of matter is that there is no indication that the draconian intervention methods that NY state and the city of New York began imposing in March had any impact once so ever on the spread of Sars-Cov-2. Let’s look at the data.
When the lockdown was first wrought upon us in NYC this was one of the graphics that were used to justify it. It shows what the infection curve would look like both with and without intervention methods. One shows a drastic rise and subsequent rapid fall that would supposedly overpower the healthcare system. The other shows a gradual hump that spreads cases out over a vastly longer period of time. We were told that if we followed unconstitutional orders, sheltered in place, wore masks, and didn’t gather in groups that we would get the second curve and more people would live. We followed orders and this is what we got:
Note: I use death data rather than infections because we weren’t testing properly at the beginning of the pandemic and accurate data isn’t available.
What does that look like to you? Well, it looks very much like the doomsday curve of the first scenario above. There is absolutely nothing flat about that curve. In fact, if you ask me it looks exactly like the natural curve of a virus spreading through a society without prevention methods at all, such as, say, in Sweden:
Or, better for our comparison, Stockholm:
What we are looking for here is not a comparison of the number of cases / deaths or even the case / death rate per capita, but whether or not intervention methods had an impact on the curve. We use Stockholm as our control group, as they did not lockdown and have a comparable level of development as NYC and their data is trustworthy. Many people will argue that you can’t compare the two due to the population density difference, but for what we’re comparing I feel that’s irrelevant (and Sars-Cov-2 actually hit the least dense parts of NYC the hardest).
Remember, the idea behind flattening the curve was … well, to flatten the curve. But if we compare the curves of NYC, which destroyed itself with a lockdown, and Stockholm, which didn’t, we see something very interesting: they are virtually exactly the same. The peak in NYC went from the third week of March until the middle of May, while Stockholm’s went from the third week of March until the beginning of June. What’s really remarkable is if we flesh this out a little wider we find that the rise and fall of the Covid-19 curve is extremely consistent throughout the entire world regardless of intervention method:
“After around a two-week exponential growth of cases (and, subsequently, deaths) some kind of break kicks in, and growth starts slowing down. The curve quickly becomes ‘sub-exponential.’ This may seem like a technical distinction, but its implications are profound.
From a Bloomberg report:
But, as our next chart shows, there’s little correlation between the severity of a nation’s restrictions and whether it managed to curb excess fatalities — a measure that looks at the overall number of deaths compared with normal trends.
Nothing that us humans have done has had any impact on the Sars-Cov-2 curve. The intervention methods that destroyed hundreds of thousands of livelihoods and suspended the civil liberties of millions in NYC did not come with an observable decrease in the number of deaths. Likewise, the protests and riots and subsequent phases of reopening did not come with a noticeable spike in cases, hospitalizations, or deaths. Certainly, if such drastic intervention methods did anything they would have had some kind of footprint in the data, right? Nope.
Nobel Laureate Michael Levitt of Stanford has an explanation:
Imagine I had a confirmed case of COVID. Unbeknownst to me, a declared case, I’ve also infected my friends, my kids, people near me. And this means on the first day, I can infect people, but then the next day, I can’t find people so easily to infect. In some ways, what’s happening is that visible cases are having a hard time finding people to infect, because the invisible cases have already infected them. Since then, there’s been a lot of extra findings about maybe we have some natural immunity to the virus as well.
Basically, the virus seems to burn itself out quick. This is something that’s represented almost without variation in places that have had significant spread.
Now, there are some people who may counter me by saying that even though there was clearly no flattening of the curve that maybe the curve didn’t go as high as it otherwise would have without intervention. My reply is the same as it was when I was talking to the couple in the bar: then why aren’t people getting it now. If people were spared exposure to Covid who are susceptible to it then why didn’t we have a rise in cases when the lockdown was called off? Or when tens of thousands of people packed into the streets tightly together to protest? NYC doesn’t exist in a bubble — there were people coming in and out of the city from all over the country without restriction up to June 25th (and even still after, as the quarantine order is all bark and no bite), as Sars-Cov-2 began peaking in Florida, Texas, and California. We have also been egregiously violating just about every social distancing protocol possible over the past two months — come to my neighborhood at night if you don’t believe me.
It seems overtly probable that the virus spread through the population in March and April and we now collectively have herd immunity. No matter what happens — protests, street parties, people going back to work — the cases keep going down. NYC often goes days on end without a single Covid death. But don’t take my word for it.
A new study by researchers at University of Illinois at Urbana-Champaign and Brookhaven National Laboratory and published on the preprint server medRxiv* in July 2020 discusses the effect of a factor called persistent contact heterogeneity on the final epidemic size of COVID-19. The researchers say that using estimates based on this measure reduces the herd immunity threshold (HIT) and suggests that the worst-affected areas, such as New York City (NYC), are almost at this threshold, meaning that they will not be sources of spread to other areas if a second wave of the current pandemic occurs.
From the NY Times:
At a clinic in Corona, a working-class neighborhood in Queens, more than 68 percent of people tested positive for antibodies to the new coronavirus. At another clinic in Jackson Heights, Queens, that number was 56 percent…
New York State conducted a more comprehensive survey on antibody rates, which involved testing some 28,419 people across the state. That survey suggested that roughly 21.6 percent of New York City residents had antibodies. But it also revealed a much higher rate in some neighborhoods. While the state has released little data from Queens, its numbers showed that in Flatbush, Brooklyn, for example, about 45 percent of those tested had antibodies.
From Off Guardian:
The research, conducted by a team of scientists at the University Hospital in Zurich, is titled: “Systemic and mucosal antibody secretion specific to SARS-CoV-2 during mild versus severe COVID-19”, and found that Sars-Cov-2-specific antibodies only appear in the most severe cases, or about 1 out of 5.
However, if the authors are indeed correct in their estimation, this might mean SARS-COV-2’s infection rate (IFR) would need to be revised downward yet again. If 80% of those infected really do not produce antibodies then there is a live possibility the virus is present in many more people than usually supposed. Which would in turn potentially reduce the IFR, possibly considerably.
Importantly, we detected SARS-CoV-2-reactive CD4+ T cells in ∼40%–60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating “common cold” coronaviruses and SARS-CoV-2.
Herd immunity thresholds are then calculated as 1-(1⁄R_0 )^(1⁄((1+〖CV〗^2 ) )) or 1-(1⁄R_0 )^(1⁄((1+〖2CV〗^2 ) )), depending on whether variation is on susceptibility or exposure. Our inferences result in herd immunity thresholds around 10-20%, considerably lower than the minimum coverage needed to interrupt transmission by random vaccination, which for R_0 higher than 2.5 is estimated above 60%. We emphasize that the classical formula, 1-1⁄R_0 , remains applicable to describe herd immunity thresholds for random vaccination, but not for immunity induced by infection which is naturally selective. These findings have profound consequences for the governance of the current pandemic given that some populations may be close to achieving herd immunity despite being under more or less strict social distancing measures.
However, local government officials are refusing to believe that the decline in Covid cases in NYC are due to natural causes. Preferring instead to pat themselves on the back:
But Mayor Bill de Blasio and Dr. Jay Varma attributed the city’s good numbers to everything but herd immunity — including social distancing, good hygiene and an increase in testing and tracing.
“I think that herd immunity is a very unlikely explanation for this because we know the vast major of New Yorkers actually weren’t infected, so we’re not nearly at a level where we would expect that immunity would play a major role in decreasing transmission,” Varma, the city’s senior adviser for public health, said at the mayor’s daily press briefing.
We’ve been duped. The virus did as viruses have done all through time: it tore through society until it burned itself out. It will follow this same pattern everywhere in the world, without exception, regardless of intervention method. We accomplished nothing and left our city and country in ruins.