I have been reading both students’ final-year-project reports and a report commissioned by the NHS. I don’t know whether to be happy or sad that some of our students can write better reports than an august panel that includes a number of members of Royal Colleges. On the one hand it is great to see our students doing so well, but on the other hand at any one time the NHS is treating millions of patients, and you would hope that infection control in NHS hospitals would have rather more competent oversight.
The British Medical Association (BMA) – the body that represents medical doctors – is producing reports on the COVID-19 pandemic, in consultation with their members. The first report is How well protected was the medical profession from COVID-19?. Summary here. As you would expect, it makes pretty grim reading and repeats the (well founded, I think) criticisms of the UK government’s response, such as inadequate PPE.
Teaching is now almost finished for this academic year. On Friday I had my last meeting with one of my project students. It was nice, he has learnt a lot and we said we’d next meeting at graduation in July. So I have a bit more time, and a new toy: a CO2 meter*. This measures the carbon dioxide aka CO2 in the air. The concentration of CO2 in the Earth’s atmosphere is about 400 ppm** – where ppm = parts per million. Out of every million molecules in the atmosphere, 400 are CO2. There is some evidence – although I am not sure it is very strong – that at CO2 levels above 1000 ppm your brain functions a little less well. In any event, CO2 levels allow you to estimate how well ventilated a room is.
Quantifying the absolute value of the risk of catching COVID-19 is very hard, not least as it seems likely that some infected people may be breathing out a million times more virus, than others. But estimating changes in risk is a bit easier, eg a reduction in risk due to ventilating a room. If we make some assumptions (see below), we can estimate the reduction in exposure to the virus, due to ventilation turning over the air in a room. This is plotted above. The y-axis is the factor by which exposure is reduced, i.e., two means that the exposure is halved, and so on. The x-axis is the number of times an hour ventilation replaces the air in a room. So two means the air in a room is replaced by fresh air twice an hour. The solid orange line uses (a fit to) data of Oswin and workers on the how long SARS-CoV-2 survives in the air. The prediction is that turning the air over three times an hour approximately halves the exposure to virus.
Above is a plot of the concentration of carbon dioxide (C02) in a bedroom in which one person is getting about 6.5 to 7 hours of sleep. Plot is as a function of time from when they go to bed to when they get out of bed, and is from a 2013 paper by Batog and Badura. The units are parts per million (ppm). For context, the atmospheric CO2 concentration is about 400 ppm, i.e., in the Earth’s atmosphere (i.e., outside our homes) out of every 1 million molecules, 400 are carbon dioxide*. In our homes and offices, the CO2 concentration is higher because we are all breathing out CO2. We breathe in oxygen (O2), use it to burn our food for energy, then breathe out the CO2 this produces. As far as I know, there are basically no set limits on CO2 concentrations but guidance for workplaces, schools, etc is typically that it should be no more than a 1000 ppm. As you can see, this concentration is exceeded for most of the night.
A year ago I wrote – with some surprise – of the UK government’s decision to downgrade the classification of COVID-19, so that it was no longer considered a “High Consequence Infectious Disease” (HCID). This was done right at the beginning of the pandemic in the UK, spring 2020. Very early on, COVID-19 was classified in this most-dangerous HCID category, but it was then downgraded. But I don’t think I was surprised enough.
During the pandemic we are all living through, vaccines have been a triumph of scientists and medics. Vaccines have saved millions of lives, and we should all be grateful to the medics who have played their part in this. By contrast, the senior medics responsible for infection control in hospitals have, in my opinion, had a much less good pandemic. A year ago and a few months ago, I wrote about how the guidance on the wearing of masks by healthcare workers did not seem to be consistent with what we knew about how respiratory diseases, such as COVID-19, spread.
The results of the first, or at least one of the first, studies where volunteers are deliberately infected with COVID-19, have just been published. In an interesting and important paper by Killingley et al. Thirty-four volunteers were exposed to a dose of COVID-19*. As a result half of them became infected, and of these 18, 16 showed symptoms at at least one time during the infection, while 2 (11% of those infected) never showed any symptoms. One of the big advantages of studies like this, is that you know exactly when the person was exposed to virus, and can track them from that time onwards. If someone is infected in the community, you usually don’t know when they were infected, and even if you do, then you don’t know at the time, so there is a delay in studying them.
Killingley and coworkers exploited this advantage, to get some really useful data, some of which is above. It shows two measures (red and blue curves) of the concentration of the virus SARS-CoV-2, found in samples taken from the nose of the volunteers exposed to the virus. It shows the time course of the COVID-19 infection in detail.
The viral load starts off zero, and typically first becomes measurable a couple of days after exposure. Note that the y-axis is a log scale, between days two and about seven, the amount of virus increases by about a factor of ten each day. Then between days seven and say twelve it decreases, but a bit more slowly that it rose. Finally, for another five days the viral load is low but only decreases slowly. The authors found that symptoms developed two to four days after exposure.
So, this plots supports self-isolation for ten days**. If you first noticed the infection by its symptoms, that will have been around three days after exposure. As you can see from above, the viral load will then typically be appreciable for another eight to ten days. If you were in that unfortunate position during the pandemic, I hope the above plot makes you feel a bit better about being confined to home for ten long days. It looks like that is about the right length of time.
I was also struck by a couple of other things in the paper. The first is:
Results from lateral flow tests were strongly associated with viable virus, and modeling showed that twice-weekly rapid antigen tests could diagnose infection before 70–80% of viable virus had been generated.From Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge in young adults by Killingley and coworkers, Nature Medicine, March 2022
In other words, lateral flow tests work, and can pick up infections early on, when symptoms may be weak or entirely absent. They found that the two individuals who never developed symptoms had just as much virus in them, as those that did develop symptoms. Again this is consistent with individuals with no symptoms spreading the virus without know they are infected. Another argument for the use of lateral flow tests.
Today the UK government has dramatically scaled back free lateral flow tests. The day after Killingley et al.‘s paper made the case for these tests even stronger. Sigh.
The second thing that struck me about this important paper, is how elaborate was the ethical approval process the authors had to go through, and how scrupulous was the supervision of the study. All to protect the 34 young, healthy volunteers, that they deliberately exposed to COVID-19. This ethics process is normal. Any time any research is done involving people, ethical approval is required in advance of the research. The researchers must say carefully what they will do, so that any potential harms to the people can be assessed, and balanced against any benefits the research will produce.
This ethical-approval process exists to protect the brave volunteers, and it is impressive. It is good that in the past our Parliament has passed laws meaning that any trial that exposes the trial volunteers to a potentially harmful virus, has to be so carefully justified. What is less impressive is that the current government seems to be experimenting to see how many of the UK’s 60 million citizens can be exposed to COVID-19, and they don’t need to ask ethical approval from anyone. And the Parliament we elected in 2019 seems relaxed about the ethics of this.
* It is worth noting that they were infected by dropping virus into the nose, which is different to inhaling airborne virus – which is likely how most become infected naturally. This may affect the course of the infection.
** Note that plot up top is an average, there is considerable variety between one infected person and another.
University league tables are built on poor data analysis and arbitrary assumptions, but prospective students and their parents often use them. I can see the attraction of league tables, prospective students and their parents want to compare the different universities they are considering, and league tables are by far the most prominent, and easy to access, way to do that. But as someone who teaches data analysis, and has been an admissions tutor, university league tables make me wince.
Teaching this semester is 80% back to pre-pandemic teaching. I think students and staff appreciate this. It is certainly good to be back in the computing lab, teaching computational modelling to second years. Each student is doing a little research project, with results from a code they write. This is supervised by an academic, with help from a PhD-student demonstrator. COVID-19 has not gone away – the class demonstrator was off for a couple of weeks with COVID – but for healthy young adults, COVID-19 is usually mild.