This analysis explores the very likely possibility that staff, patients, and the NHS as a whole are being mismanaged due to the significant proportion of positive COVID-19 cases in Pillar 1 that are false (where Pillar 1 represents the data from tests carried out in Public Health England (PHE) labs and NHS hospital settings).
Limitations regarding the widespread use of PCR tests in diagnostics have been well-documented, and can be summarised as follows…
- PCR tests offer the capacity to detect viral material in very small quantities. However, the test cannot explicitly determine whether this viral material is infectious or not.
- If a high cycle threshold (Ct) limit is used, the testing process will be skewed towards detecting non-infectious levels of viral material.
- PCR tests are not 100% accurate, since results can include false-positives (the false detection of viral material in the original swab) and false-negatives (the false omission of viral material in the original swab).
There are several indicators which suggest that we should expect the current implementation of PCR tests to be problematic, and that a significant proportion of positive COVID-19 cases may be false…
- Ct values higher than 24–34 are associated with non-infectious samples. Infectivity declines eight days after symptom onset, despite continued high levels of viral load. However, Public Health England (PHE) have advised that a maximum of 40 cycles should be used. As such, testing labs following PHE’s guidance are using a Ct limit higher than that which is associated with infectious disease.
- Evidence suggests that people who re-test positive for SARS-CoV-2 after having previously suffered from COVID-19 are extremely unlikely to be suffering from active re-infection. This is supported by evidence which shows that immunity is certain for at least six months following COVID-19 infection.
- The publication which provided the PCR protocol for the detection and diagnostics of SARS-CoV-2 has been heavily criticised and faces possible retraction.
- The proportion of incorrectly categorised COVID-19 admissions increased to over 85% at Imperial College Healthcare NHS Trust (ICHT) in May, demonstrating that as prevalence decreases, the impact of falsely categorised COVID-19 patients can become extremely significant.
- Contamination and human error are likely to be primary causes of false-positives. This would suggest that the false-positive rate may change based on viral prevalence, which is observed over summer. Furthermore, human error may be a significant problem now compared to March-April because testing capacity has increased by more than ten-fold, largely through the creation of large private testing labs — a.k.a. Lighthouse Labs — rather than via the NHS, and concerns have been raised regarding the training, processes, and workloads of those working at these Lighthouse Labs.
- There have been cases in the past where the use of mass PCR testing in response to a disease has created the false appearance of an epidemic — a “pseudo-epidemic”.
- Many experts have echoed concerns regarding the problem of false-positives, including Carl Heneghan (Director of the Centre for Evidence-Based Medicine at Oxford), Martin Kulldorf (Professor of Medicine at Harvard, with expertise in biostatistics and epidemiology), John Ioannidis (Professor of Medicine and Epidemiology at Stanford), and many more.
Estimating the impact of false-positives on the NHS…
In lab settings, the false-positive rates for SARS-CoV-2 are consistent with those associated with other RNA viruses, for which the median false-positive rate has been found to be 2.3% and the interquartile range (IQR) was 0.8–4.0%.
False-negative rates in the detection of SARS-CoV-2 appear to vary over time, decreasing from 100% on day 1 of infection to 38% on day 5 (average day of symptom onset), to a low of 20% on day 8, after which the false-negative rate gradually increases again. On average, most tests may be occurring on day 8, although observed evidence quality is low.
In the four weeks leading up to Christmas — 26 November to 23 December, before testing and other data was affected by bank holidays — there were 1,783,360 tests conducted in Pillar 1, and 102,000 positive results.
Given a false-positive rate of 0.8%-4.0% and a false-negative rate of 20%, the following simultaneous equations can be solved to estimate the number of real positives and negatives:
For a false-positive rate of 0.8%…
102,000 = P₁ + 0.008*N₁
1,783,360 = N₁ + 0.2*P₁
where P₁ represents the number of real positives, and N₁ represents the number of real negatives.
These calculations suggest that 14,126–68,667 (16–67%) of all 102,000 positive COVID-19 cases in Pillar 1 through this period were false.
This high significance of false-positives is expected because the relationship between false-positives and positivity rate is well-understood: the lower the proportion of positive results, the higher the significance of false-positives.
Is the hypothesis of “false-positives are significant” reflected via other metrics?
If such a significant number of positive cases are false, then we would expect to see low numbers of people suffering from COVID-19 symptoms, normal levels of emergency hospital admissions, and normal mortality levels…
- The number of assessments made relating to coronavirus symptoms, triaged through NHS pathways, remains at roughly 10% of levels seen during the peak in March-April.
- Emergency admissions in December 2020 were 17.9% lower than in December 2019.
- As of mid-December, deaths-per-week were not increasing and remained at roughly 10% above-normal levels. Specifically, 13,011 deaths were registered in the week ending 18 December. For reference, 22,351 deaths were registered in the week ending 17 April, at which point they were at 221% above-normal levels. (Deaths are recorded by date of registration. However, significant registration delays occur during the Christmas period, as well as on other bank holidays. As such, all-cause mortality figures do not accurately reflect deaths by date of death until the second or third week in January. Furthermore, week-on-week excess mortality is also difficult to measure during these periods, due to the misalignment of respective weeks across different years. Subsequently, all-cause mortality and excess death rates in the two weeks on either side of the new year cannot reasonably be used to gauge trends.)
The improper implementation of PCR tests is not only harming our ability to gauge the true prevalence of COVID-19, but also causing enormous and unnecessary strain on the NHS.
Patients and staff are being wrongly diagnosed as having COVID-19 and subsequently are being mismanaged (e.g. staff sent home, patients restricted to COVID-19-specific areas in hospitals, etc.), leading to unnecessarily overwhelming concentrations of patients.
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First published on georgemichael93.medium.com on October 16, 2021.