Have you got COVIDITIS?

Juliet might have been right about the rose smelling just sweet by another name but what we name things is critical.  A rose by any other name is a mislabelled rose. What we label as COVID is critical to tackling the problems we face.

What is COVID? The case definitions that were set out at the beginning of the epidemic, but vary slightly by country, are excellent definitions for an epidemic. They remain excellent definitions for any area with exponential spread of infection.  What is excellent about these definitions is that they aim and succeed to capture every possible case.  This is essential to stop spread.

However, once disease falls to low levels in the community these definitions are harmful. By labelling every patient with a positive laboratory test as COVID we have caused immense harm. By mass testing a healthy population over the summer we have incorrectly labelled a huge number of individuals. The SAGE estimate of the false positive rate is 1% my own estimates are slightly lower.  We have now tested for COVID nearly 20 million times. The SAGE estimate would mean we have had 200,000 false positives out of 350,000 total positives. There is increasing evidence that these were indeed false positives.

How false positives cause harm:

  1. Life / world changing political decisions based on false data.
  2. COVID looks increasingly benign.  The current death rate of hospital admissions labelled as having COVID is only 1.5%. This is the background death rate for all hospital admissions.  COVID had a 6% death rate.
  3. By labelling patients without classic symptoms as having COVID, we have all accepted the idea that the symptoms can vary hugely.  Unpicking this mess to really understand which symptoms matter will be incredibly difficult. Does asymptomatic COVID really exist even?
  4. Test and Trace have been spread thin and have been chasing non-cases.  Over summer there were over 500 false positive results a day.  Their contacts were then reached and tested.  1% of them will have tested positive too.  This can create the illusion of spread.
  5. New and better tests may be dismissed as lacking in sensitivity because they fail to recognise all these false positive cases.
  6. Without addressing the false positive issue we will have a constant stream of cases and be unable to return to normal.

In areas with high prevalence and active spread the definition needs to capture every possible case.  In areas where prevalence is low continuing with that approach will include numerous non-cases. The problem that WHO and the USA in particular are facing is that they need different definitions for different areas.

So let’s try having new labels for different scenarios.  The key factor is that the definitions will need to be situation specific. Case definitions and testing strategy go hand in hand (I will write about that next). The percentages in these definitions are highly dependent on a sensible testing strategy.

My proposal is to have a three tier naming system with COVID; COVIDOID and COVIDITIS being separate categories.

In an area with true exponential spread defined by more than 6% of test results coming back positive:

COVID will be defined as any patient with any one of the below:

  1. Fever 
  2. Cough
  3. Sudden loss of smell
  4. COVID skin rash
  5. A single positive PCR test

When characteristic skin rashes were first documented there was no way of tracking them to see if they were significant. If there is an as yet unidentified symptom that appears to be attributed to COVID that has not yet been confirmed as such we still need a label. Anyone with this symptom and none of the above will be labelled COVIDOID (oid being latin for kinda like).

In an area with moderate disease prevalence defined by 2-9% of PCR test results coming back positive. 

COVID will be defined as any patient with any two of the below:

  1. Fever or Cough
  2. Loss of or change to sense of smell
  3. COVID skin rash
  4. A single positive PCR test

Patients with only one of the above will be labelled COVIDOID. 

In an area with low disease prevalence defined by fewer than 2% of PCR test results coming back positive.  Any positive PCR results will be assumed to be false positives and not reported unless proven otherwise.

COVID will be defined by any patient with one of the below:

  1. Positive viral culture 
  2. Ground glass changes on CT

These changes are highly specific and that it what is needed at times of low prevalence.

PCR testing could still be used to screen the nursing home and vulnerable hospital population (e.g. over 70) in order to protect them.  However, a positive PCR result alone will not be enough. Confirmation using the above criteria would be needed to reach a diagnosis. Anyone with sudden loss of smell will be tested by PCR and a positive result would be diagnostic.

That leaves the following situations in the low prevalence area:

  1. Cough or fever 
  2. Skin rash
  3. Sore throat
  4. Knowing someone with one of the above and thinking you’ve caught it.

Anyone who believes they have COVID in that situation just has COVIDITIS. 

Published by clarecraigfrcpath

I have been a pathologist since 2001 and a Consultant Pathologist since 2009. I worked for Imperial College Healthcare Trust as a cytopathologist until 2015. Subsequently I was the day to day Pathologist on the cancer arm of the 100,000 Genome Project and more recently I have worked for Panakeia, an AI digital pathology startup as Head of Pathology. I am currently between jobs and doing occasional consultancy work and crunching COVID data.

2 thoughts on “Have you got COVIDITIS?

  1. Hi Clare
    Do you think that Bayes should be used to determine the probability of being positive given that you test positive via PCR? I believe they call it Positive Predictive Value in the medical profession.
    I generally look at only the Scottish numbers on ‘testing’. They are a nightmare of incompetence and obfuscation.
    Several things bother me.
    The reported test result is not the date of swab. The daily test results cannot be attributed to that particular day. It’s unclear what the time lag is between being swabbed and the result being presented in the stats.
    I have no faith that there is an unbroken “chain of evidence” in the whole testing process.
    Are Quality procedures and controls being strictly adhered to by labs?
    Are there any data on the incidence of COVID Rash?


  2. Great questions.

    Yes, we need to be using Bayes. Combining Bayes with our knowledge on false positives there are a whole host of people you would not want to be testing at all e.g. asymptomatic people with no evidence of direct contact with real COVID.

    We have the same issue here with the data that is published. If you want to get a better handle on it though you can always ask for an FOI from NHS Scotland.

    I have great faith in our laboratory staff and there will be in lab quality controls as well as external quality control. However, I fear that the checks for false positives are not as rigorous as those for false negatives. The latter just requires dilutions of COVID sequences. The former requires samples from the pre-COVID era of other viruses and bacteria at scale.

    COVID rash is fairly well described. Given its late onset it would be hard to use it for diagnostic purposes except in retrospect.


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