Disease Detecting

As of today, the Coronavirus pandemic in the UK seems out of control. Everyone is talking about it. Nationwide lockdowns have been imposed, mass testing of the city of Liverpool by the military is underway, anti-lockdown protests are breaking out and there are hundreds of Covid-diagnosed deaths everyday. If you Google “Coronavirus UK” this graph appears on your screen, showing tens of thousands more cases now than there were in the pandemic peak back in April to May.

It seems horrific and people are afraid. It doesn’t seem to follow the usual bell curve pattern of a pandemic, immediately raising questions. The role of public health disease surveillance and outbreak control is to investigate diseases of public health concern and determine their patterns, including who might become unwell or die and why, and how these risks might be minimised. We become disease detectives, and as such we need to remain questioning and inquisitive. When the media and politicians take over, pressure mounts to fall in line with a given narrative which is incredibly damaging to public health activities, as has been shown on a large scale through 2020.

When you go to the Office of National Statistics and read the Public Health England All Cause Mortality Surveillance Report for Week 46 (last week), you find the below graph.

Deaths persistently undulate with a rise in winter related to seasonal respiratory viruses, of which there is usually a dominant influenza strain. In 2016-2017 the dominant strain was Influenza A H3N2. In 2017-2018 there were two, being Influenza B and Influenza A H3N2. In 2018-2019 the two dominant strains were the Influenza A H1N1 2009 pandemic strain and Influenza A H3N2. The dominant strains in 2019-2020 were Influenza A H3N2 and SARS-CoV-2. The sharp peak in April of 2020 represents the Covid-19 pandemic deaths which have since come down with some small peaks and troughs, a normal transmission pattern as viruses encounter pockets of vulnerable populations.

Professor Gabriela Gomes, biomathematician at Strathclyde University who specialises in epidemiology, infectious disease spread and herd immunity, states “Typically we cross the herd immunity threshold to seasonal viruses up and down every year. Not only because R0 is seasonal but also waning immunity and birth of susceptibles. The challenge is to cross it for the first time. After that it becomes normal“. This graph strongly suggests that Covid-19 has crossed the herd immunity threshold in the UK and has become a seasonal endemic virus.

Since April 2020 none of the peaks have been as high as those seen in 2016-2017 or 2017-2018, so they are not out of the ordinary. So what explains the enormous rate of diagnosed Covid-19 cases when there are no corresponding pandemic-level deaths?

Dr Claire Craig is a consultant pathologist who has worked for the National Health Service and has studied this data in detail. She discusses it extensively including during a 55 minute podcast with Alex McCarron and the below nine minute TalkRadio interview with Julia Hartley-Brewer.

It is complicated, but Dr Craig has identified flaws in the PCR tests being used to diagnose Covid-19 which seems to be creating a corruption of data. They are flaws well known to occur in Epidemiology including the risk of a high number of false positive results occurring when excessive testing is undertaken in populations with low rates of disease.

She also discusses the testing issues that can occur in laboratories when workloads are excessive and urgent. Tests have to be manufactured and available with a quick turnover at the beginning of any epidemic. At the beginning of the pandemic, manufacturer checks were (justifiably) compromised in order to make the tests available as soon as possible.

Laboratories have three aspects to their work, but can only ever employ two of them at a time: quality (of the test); volume (of tests done); and speed (at which test results are made available). In the initial stages of a pandemic, as seen in the UK in April, speed and volume are required, making test quality less of a priority. This ensures during the emergent pandemic stage, that testing provides enough information to get a clear picture of what is going on quickly for a timely public health response.

The risks associated with prioritising volume and speed are that test quality is compromised. Dr Craig describes the situation in laboratories which quickly scaled up their testing capacity to 50,000 per day across the UK by May 2020 and then up to 200,000 per day now, with very few extra resources, placing a large strain on laboratory services.

Epidemiology 101 for pathologists during epidemic investigations, is that when you reach peak deaths, you switch strategy from high volume, fast and sensitive testing (meaning every possible case will be detected), to quality testing which is specific (meaning the results are more accurate). The only way to get quality results is to compromise either volume of daily tests, or the speed at which the results can become available. The early strategy of testing high volumes at great speed has never been scaled down in order to improve the quality of the tests according to Dr Craig.

Public Health Scotland release information about their Covid testing which includes the number of daily positive results, daily negative results and total number of tests performed. Investigation of this data found that the percentage of positive tests is twice as high on weekends than it is on Mondays. This is clearly nothing to do with the virus, and relates directly to the extraordinary pressure that laboratories are under. Dr Craig describes weekends as short staffed, busy and stressful, and outlines the ease with which tiny traces of viral contamination can occur in negative specimens in this high stress environment.

This leads to her argument that it is possible that currently the UK could be experiencing a pseudo-epidemic of false positive tests. She refers to the Pertussis pseudo-epidemic that occurred in Dartmouth-Hitchcock Medical Center, New Hampshire USA, where 142 people were diagnosed with Pertussis (whooping cough) in 2006. 1,000 staff were quarantined and thousands received antibiotics and vaccines. When confirmatory tests were done, it was found that all 142 “cases” were in fact not infected at all. Mike Hearn wrote about this in his blog posts: Pseudo-epidemics and Pseudo-epidemics Part II.

As Dr Craig points out, living through a pseudo-epidemic, everyone believes there is an epidemic because the data looks like an epidemic. But some of the data can be studied to help figure it out, as she has done. It is more complicated than this, and her interview with Alex McCarron explains in further detail, why she feels a cause for concern on this.

Interestingly, mass testing in Liverpool UK which commenced last week amidst a storm of controversy has used a different type of test than the PCR which is being used globally to “diagnose” Covid-19, often in people with no symptoms or vague and mild symptoms. The military in Liverpool are using lateral flow tests, a point of care rapid test which provides results within 20 minutes and doesn’t require specimens to be sent to the laboratory (they work much like a pregnancy test). This test detects virus protein which will only be detected if actual virus is present, unlike PCR testing which can detect scraps of viral genetic material. Lateral flow testing of many thousands in Liverpool city has shown a much smaller infection rate, about 1 person in every 200, than the rates being suggested via PCR testing.

Dr Craig argues that whilst it may not be the case that a pseudo-epidemic is at play here, it is also a possibility which needs to be excluded. She states that the UK epidemic occurred across their population before and then during the first lockdown, and that the virus is now transmitting slowly through a largely immune population. According to Dr Craig, determining whether a pseudo-epidemic is now at play can be done by re-testing hospitalised patients diagnosed as Covid positive on PCR tests, using the lateral flow test. Are these sick hospitalised patients really suffering and dying from Covid? It seems an important question given the doubts raised.

It is all much more complicated than this and I am unsure I’ve done the topic justice, but it was worth writing about because it’s an amazing phenomenon which needs further investigation and attention for a fearful public living through another devastating lockdown. Instead however, news outlets have largely dismissed it.

Regarding the issue of asymptomatic spread, which has driven the incredibly divisive issue of whether or not general public wearing masks is useful, Dr Craig states that there are two schools of thought, being 1: asymtpomatic people cannot transmit (which makes biological sense and has been standard knowledge until 2020); 2: asymptomatic transmission is a serious problem. Dr Craig states that when you look at the literature supporting the second school of thought, every paper was published in China. She suggests, with good reason, that there should be some skepticism about this when all the other literature contradicts it.

In conclusion, the UK are currently experiencing a problem with false positive Covid test results, which can be fixed by confirmatory testing of unwell people using an accurate lateral flow test or by reducing the volume of testing required by laboratories so that they may improve the quality of their results. At the moment, the numbers which are not real are overshadowing the numbers that are real.

Additionally, Dr Michael Yeadon, a doctor of respiratory pharmacology, has described the same concerns. He has also noted that when MPs in the House of Commons voted on the latest lockdown, they were not told that ICU occupancy was at 79% (normal for this time of year in UK); medical oxygen usage was at normal rates; and that there was no abnormal spike in excess deaths. He takes it one step further, stating that many of the UK’s 620,000 expected annual deaths are being incorrectly coded as Covid-19.

Dr Clare Craig interview on talkRADIO 13 November 2020.


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