By Kip Hansen – Re-Blogged From WUWT
Dr. Michael Mina, an epidemiologist at the Harvard T.H. Chan School of Public Health, says that “The standard tests are diagnosing huge numbers of people who may be carrying relatively insignificant amounts of the virus… Tests with thresholds so high may detect not just live virus but also genetic fragments, leftovers from infection that pose no particular risk — akin to finding a hair in a room long after a person has left”.
My analogy would be the testing of a Motel 6 room for DNA samples, a month after a crime had been committed in it.
Just how over-sensitive does Dr. Mina think that these PCR Covid tests are? 100 to 1,000 times too sensitive for the test to return a positive result “— at least, one worth acting on.”
According to a report in the NY Times: “In three sets of testing data that include cycle thresholds, compiled by officials in Massachusetts, New York and Nevada, up to 90 percent of people testing positive carried barely any virus, a review by The Times found.” [ my bold – kh ]
The technical point is that:
“The PCR test amplifies genetic matter from the virus in cycles; the fewer cycles required, the greater the amount of virus, or viral load, in the sample. The greater the viral load, the more likely the patient is to be contagious.” “This number of amplification cycles needed to find the virus, called the cycle threshold, is never included in the results sent to doctors and coronavirus patients, although it could tell them how infectious the patients are.” “On Thursday, the United States recorded 45,604 new coronavirus cases, according to a database maintained by The Times. If the rates of contagiousness in Massachusetts and New York were to apply nationwide, then perhaps only 4,500 of those people may actually need to isolate and submit to contact tracing.” [ NY Times article ]
The New York Times math wizards have under-stated the over-estimation. If Dr. Mina is correct, the number of people who may need to isolate or submit to contact tracing could be as small as 45 of those 45,604 – 1,000 times less than the total reported.
The current number of PCR amplification cycles needed to report a Positive Test is 40.
Any test with a cycle threshold above 35 is too sensitive, agreed Juliet Morrison, a virologist at the University of California, Riverside. “I’m shocked that people would think that 40 could represent a positive,” she said.
Dr. Morrison stated that “A more reasonable cutoff would be 30 to 35.” Dr. Mina said he would set the figure at 30, or even less.
I tried and failed to create a graphic that would clearly illustrate the difference between the Real Positive Test Rate and the 100- to 1,000-times Exaggerated Positive Test Rate. The real rate is simply too small to visualize if one shows the 1,000 times error. This is the best I could do – the smallest bar is over-size due to the limits of your screen.
William Briggs recounts that the Governor of California has mandated that in order for “Most business to open with modifications” a California county must have “Less than 1 Daily New cases (per 100k)” and “Less than 2% Positive Tests”. With a 100- to 1,000-times over count of true positives, California is doomed to remain locked-down forever.
Of course, the CDC is “helping” (quoting the Times’ article): “The C.D.C.’s own calculations suggest that it is extremely difficult to detect any live virus in a sample above a threshold of 33 cycles. Officials at some state labs said the C.D.C. had not asked them to note threshold values or to share them with contact-tracing organizations.”
So, in the Mad Mad Mad World of Covid Madness, they are not only reporting Covid Deaths that are not caused by Covid; they are not only reporting all positive tests as “New Covid Cases” despite lack of illness and totally ignoring the known false positive rate; they are reporting numbers for “positive tests” that are known to be anywhere from 100 to 1,000 times too high.
One only wishes that this report had come from some nut-case conspiracy theory web site. But the Times has sourced the story well – even though it runs counter to the Times’ usual panic-driven editorial narrative on the Covid Pandemic.
Had this come from any less powerful source, Tweety, Facepalm, and Goggles would have suppressed the facts immediately, labeling it “Misinformation”.
Welcome to the world of Medicine-in-Support-of-Politics.