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Help Me Understand the Testing Percent Positive Benchmark….
I mostly lurk here, but I think this might be a good place to get help with a question. Here in Arizona, one of the three benchmarks for re-opening schools, businesses, gyms, etc. is the percent of positive tests. It is often reported that a high percentage (above 5% is the benchmark in AZ) shows that there isn’t enough testing available and that the virus is not under control. I could understand the purpose of this benchmark if the state were either a) testing everyone they could get their hands on and/or b) testing a random sample in a community, not just people who self-select to test.
In Arizona, there is surely not a lack of available testing. That may have been true six weeks ago, but not now. This is widely reported (not enough people showing up for tests), but I’ll share my own anecdote.
Over the weekend I was ill, similar to a stomach virus, and since pretty much every common symptom is linked to COVID I figured, well, why not get a test? Arizona State University has developed a saliva test, which sounded much less uncomfortable to me so I went to their site and noticed that they had many open appointments. There were multiple spots open every five minutes up until closing time. I made an appointment, drove over to the site and the huge stadium parking lot set up with serpentine lanes was all but empty. Imagine a university stadium parking lot with four cars. I pulled up at 9:25, was handed the vial, did my spit thing, and drove away at 9:35. Easy-peasy. Although they estimated a 48-hour turnaround, at 8 pm that evening I received a text that my results were in and I was negative. Obviously, they are not overwhelmed. (As a side note, I highly recommend the saliva test. It is thought to be more accurate and was by far more comfortable than a nasal swab!).
We are at about a 10% positive test rate right now. Nothing can open until we are at or below 5%. I really didn’t think I had COVID, but I thought: hey, maybe I’ll help lower the percent positives! My kids really want to go to school! If testing sites are empty like this one, which was in a very busy metro area, I assume people who do not have symptoms are not getting tested. Oh ….and it’s all free, too, so that’s not an obstacle. How in the world are we supposed to ever lower that percentage by much if only symptomatic people get tested? I suppose it will go down as the virus wanes, but should this really be a benchmark? Isn’t this statistic somewhat meaningless? Even if everyone is encouraged to get tested, why would one do that willingly? Why would I get tested when I am feeling well? It tells me nothing other than the fact that at that moment in time, I do not have COVID. Tomorrow is a different day.
Am I missing something here? I just don’t get the constant harping on the percent positive of tests benchmark and why it is being used to guide all reopenings.
Published in General
It does raise many questions, including, how many Chinese visitors did they have then? Could the sample have been contaminated later? Is China funding any universities or studies in Spain? Etc.
That’s because all of the reports of Covid detected from samples dating pre-November 2019 are almost certainly false positives due to laboratory contamination. In all of the reported cases (there were three or four in total from different countries), the level of viral RNA in the sample was very low, which is a strong indication of a false positive.
Any of those labs claiming to have found Covid from prior to late 2019 could have easily confirmed their findings by sequencing what they found. The RNA sequence of a viral isolate gives a strong hint about when/where it originated – i.e. is it more similar to the original Wuhan isolates, or more similar to isolates circulating around the time/place of detection (indicating contamination).
None of the labs that reported detecting Covid from older samples followed their findings up with sequencing. That absence suggests they probably realize it was a false alarm.
Odd that this has not been reported as a follow-up, though. (Okay, not odd. Fits perfectly with human nature.)
Precisely.
Other types of coronavirus exist-some which cause the common cold. It is likely that antibody tests could be thrown off by cross reactivity to corona viruses other than that causing COVID-19. It might also explain why some people do not get seriously ill from COVID- they have cross reacting antibodies (from a cold type corona virus)that provide some protection.
Just a little clarification:
All of the reports claiming detection of coronavirus from pre-November 2019 used PCR, not antibody tests, as the detection method. This is relevant because PCR is several orders of magnitude more sensitive than antibody tests and thus is very susceptible to laboratory contamination. All of the reports of pre-2019 Covid only had very low levels of viral RNA, which is a hallmark of laboratory contamination. So this is not cross-reactivity, but almost certainly lab contamination.
Also, to date very little antibody cross-reactivity has been found in people not infected with Covid. What has been found, though, are cross-reactive T cells. And since T cells tend to reduce the severity of infection (as opposed to antibodies, which can prevent infection in the first place), cross-reactive T cells are indeed a likely explanation as to why so many people don’t get severe disease (or sick at all).
Contrary to many theories among right-wing armchair epidemiologists, T cells are not likely to lower the “herd immunity threshold”. However, there are other factors that probably do.
Is there a way to know, or make an educated guess as to, whether any particular person has cross-reactive T cells that reduce Covid-19 severity?
Unfortunately, not really.
Several friends/former colleagues of mine are working on this topic right now and have contributed to some of the papers that made headlines. The amount of work required to determine whether somebody has Covid-reactive T cells is, without exaggeration, about 100x as much as is required to detect Covid-reactive antibodies from the same person. So this will likely never become established as a regular diagnostic method save for an unexpected intellectual and technological breakthrough.
Since the cross-reactive T cells are presumed to have been formed in response to a recent infection from another coronavirus, the simplest way to predict whether somebody might have cross-reactive T cells would therefore probably be: did they have a coronavirus infection sometime in the past, say, two years? Of course, this is hampered by the fact that the symptoms of a seasonal coronavirus infection are nearly identical to the symptoms of influenza virus, rhinovirus, adenovirus, and so many others that we lump into the “flu” or the “common cold”, and we almost never test those patients to find out which one they have.
I suppose somebody could (and maybe already is?) check whether people with cross-reactive T cells also have detectable antibodies to a seasonal coronavirus in their blood. If that were the case, we could theoretically predict the presence of cross-reactive T cells using the presence of antibodies to seasonal CoVs. That’s a lot of “ifs”, though. Not to mention the fact that we also don’t have good antibody tests against seasonal coronaviruses since nobody considered the topic important until now…
I seem to have misplaced my certificate as a right-wing armchair epidemiologist, but why wouldn’t T cells help accomplish much the same thing as moving us closer to herd immunity. If people who have those don’t get such severe cases of covid-19, and if that means those people aren’t as infectious and aren’t as infectious for as long, wouldn’t that help reduce the spread of sars-cov-2? Not the same thing as immunity, but if a good scattering of those people in the population helps lower the risks, I would call that a good thing.
We need some t-shirts.
It’s a reasonable hypothesis. The biology of T cells is pretty complex, but I’ll try to distill the most important points down:
The first issue is that pre-existing T cells typically don’t spring into action until a while (possibly a few days) after infection (in contrast to pre-existing antibodies, which can directly block infection). That’s why T cells typically can’t prevent someone from getting infected but can help them from becoming severely ill. The problem with Covid is that people appear to be most contagious right before they even get sick – only about 3 days after infection. So it’s likely that T cells wouldn’t reduce infectiousness because that happens so early during the infection.
Moreover, even if pre-existing T cells did reduce the amount of virus an infected person spreads, that reduction is already “priced in” to the previously-calculated herd immunity threshold. The primary input for the herd immunity threshold is the virus’ R0, which for Covid is likely around 2.5-3.0. Since we know that people with pre-existing Covid-reactive T cells can become infected, that means any reduction in virus spread caused by said T cells is already reflected by that 2.5-3.0 figure. In that scenario, the “natural” R0 of Covid might be, say, 6.0, but the T cells bring it down to what we have observed from day 1 of the pandemic.
But in that case, discovery of the existence of these T cells wouldn’t change our prediction of the herd immunity threshold, since we would have already (albeit unknowingly) accounted for their effects.
That snarky aside wasn’t directed toward anybody here, but rather toward several prominent figures on social media/Fox and their devoted followers.
One example would be James Todaro MD, the founder of the “America’s Frontline Doctors” group that Trump touted. He started off as a huge HCQ champion, but now that study after study has failed to confirm a major benefit for HCQ and his group’s major spokesman turned out to have some very non-mainstream medical views (i.e. constantly warning of the dangers of demon sperm), he seems to have switched to the herd immunity threshold beat.
He recently posted a big Twitter thread about how the discovery of pre-existing Covid-reactive T cells in healthy patients meant the herd immunity threshold was much lower, since these people can’t become infected. The thread went viral. But it also got the biology completely wrong, as described in my previous comment (and which is fairly embarrassing for somebody touting his [unused] MD degree). The researchers who actually made the breakthrough T-cell findings then posted their own Twitter thread explaining in detail why Todaro was getting his science completely wrong, and that rebuttal went even more viral, making Todaro look like a hack to the majority of the viewing public not already in agreement (as if partnering with the demon sperm lady didn’t already make him look like a hack).
The most frustrating part is that the herd immunity threshold almost certainly is substantially lower than the classical 60-70% calculated using R0 alone. But the reasons why are very complicated and hard to explain, and don’t involve something as simple as T cells. Moreover, it is much more difficult to calculate how much lower the herd immunity threshold actually is from the theoretical value. By going all-in on an easy-to-understand but easy-to-debunk explanation, Todardo and his ilk simply discredit themselves among the majority who weren’t already devotees.
One of the most frustrating aspects of the Covid dilemma is that many of the “counternarratives” are most certainly closer to the truth than the mainstream predictions. But the people touting those counternarratives (who, indeed, are mostly on the political right), inevitably go one step far and claim something that is so absurd or obviously incorrect that they lose the attention of anyone who might have otherwise be looking for an alternative explanation.
Yeah, I’ve noticed that.
Ah. Thanks for the explanation.
We tend to pick the “experts” we trust based on what we want to believe. So if we are offered an explanation that best fits our wishes that is the one that we hope will win out. No one is immune from this bias. But we have to learn to accept messy explanations.
@mendel; correct me if I’m wrong, please… (I see you’ve made other comments, so I’ll check those in a second). My understanding of t-cells is not that they make you immune, in the sense that the virus bounces off of you (I’m being hyperbolic), but that they enable your body to quickly defeat the virus. So, you get it, but you’re much less likely to become ill, and much less likely to spread it… in that sense, it seems reasonable to assume that t-cells make the “immunity” threshhold much lower… but I’d suggest that we have a sort of misunderstanding of “herd immunity,” in seeming to constantly assume that it means the virus literally burns out because it runs out of hosts. I haven’t looked at it that way, but rather, that what it really means is that the virus simply doesn’t have the same impact on the population as it otherwise might have had… so, I’d think of it kind of similar to “the virus mutating into a common cold,” not because it actually mutated, but because society effectively adapted to it. Also, I’m considering that as only one part of the overall picture, where the end result is the fact that, no matter how you cut it, the effect of covid on populations becomes greatly diminished, for a variety of reasons (of which t-cell “immunity” is only one).
Thank you, everyone – what a fascinating discussion!
As an update, my kids’ school opened on 9/17 due to the expectation that Maricopa County would meet the benchmarks to open that week. Other districts have followed, others are still online only. My kids are thrilled to be back in school (and I remind them daily to remember this feeling for as long as possible). I am overall very satisfied with how the school is handling the in-person situation. They also offered free testing right before opening for all families and staff in order to try and isolate any cases before opening.
Our numbers in all three areas (hospitalizations, ICU beds, positive cases) are looking pretty good these days so hopefully more schools will follow.
Again, thank you to all who shared your knowledge.