Unknown unknowns and Breathtaking

In the first episode of Breathtaking – ITV’s drama about the NHS in the COVID-19 pandemic – there is a scene where they suspect a patient may have COVID-19. They put the patient in a small side room, and try but fail to order a COVID-19 test. This is early in the pandemic, when tests were being rationed by the NHS/government. They suspect he has COVID as his symptoms are unusual, but are consistent with what they know about COVID. The episode shows the staff being, understandably, stressed by having to share a small room with someone who may or may not have a new, potentially fatal, disease.

This is a damning indictment of the UK government’s preparations and response to the pandemic. But even if they had had a test then in many cases tests are just a yes/no has-COVID/does-not-have-COVID test. This gives a very incomplete picture.

Above is plotted a slightly odd function called an exceedance, the y axis is the probability that the value on the x axis is exceeded. The x axis is the estimated rate at which a person infected with COVID breathes out viruses. So for example, the probability is close to 0.01 for 10⁰ = 1 viruses per minute. So about one infected person in a 100 breathes out at least 1 virus per minute. The data on amounts of virus in infected people are from Viloria Winnett and coworkers and use a technique called RT-qPCR. This is combined with estimates from Archer and coworkers on the rate at which we exhale aerosol particles of mucus we exhale.

To put it another way 99 out of a 100 infected people breathe out at most 1 virus per minute, in most cases much much less. Presumably most of these people are not very infectious at all. But without a quantitative assessment of how much virus there is in the respiratory tract, doctors and nurses will not know if a patient is potentially very infectious, or likely a very low risk.

The huge range of values – note above plot has log scales for both axes – makes assessing and mitigating the risk of infection a challenge. You could have two patients with similar symptoms, but one could be a million times as infectious as the other. This huge range of potential risks makes coming up with a mitigation strategy pretty tough.