How to make a vaccine: From chimp poo to my left arm

Today I had my first dose of the Oxford AstraZeneca vaccine. Waiting for it in the queue at the G Live vaccination centre felt a bit like Christmas morning when I was kid – the same anticipation of receiving an exciting gift, although in this case it is an 80% reduced chance of death in case of COVID-19 infection. I feel very grateful to all the people at Oxford University, AstraZeneca, the G Live vaccination centre, and in other organisations that together made it possible. The centre gave me some paperwork on the vaccine to read, with side effects etc. It also said that the dose is 0.5 ml, which contains 50 billion viral particles. This got me thinking. The world population is about 7.5 billion, and at two doses per person, we need about 10 million litres of vaccine, or about four Olympic swimming pools full of vaccine.

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Interactive plots of COVID-19 infection probability, courtesy of Streamlit and Heroku

As someone who taught himself BASIC in the 1980s and was taught Fortran 77 in the early 1990s*, I do need to try and keep up with modern developments. One of the things I have being wanting to for a while now, is find a way of putting some simple plotting/data analysis on the web, so anyone can use it. There have been solutions for this problem for a while but until yesterday I had not come across one I liked. I want to go from Python code on my local machine to a running a web app in minutes, and I want to spend a couple of hours learning how to do this at a very basic level. I am kind of busy so can’t spend a day learning this. I think I have a solution that fits these criteria, and I am pretty pleased with it.

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I hope the German public health authorities know of work on dead salmon recognising facial expressions

As numerous relatives have (delightedly!) pointed out, due to my recent 50th birthday, I am now sufficiently old to be in the next or next-but-one group to be vaccinated. Turns out the advantage of getting old is not wisdom, which I don’t appear to be acquiring, but moving up the vaccine queue. So I am following all news of vaccinations with interest. Currently in the news is the suspension of use of the Oxford-AstraZeneca vaccine in a number of European countries including Germany. There is information on the basis of this decision in Germany here.

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Has the pandemic done for medicine what Paul Ginsparg did for physics?

It occurs to me that a lot, perhaps most, of the papers I am reading on COVID-19 research, are preprints, not articles in peer-reviewed journals. These are mostly not by physicists, who have been putting preprints on arXiv for over 20 years, but by scientists in a whole range of fields, including medicine. The biomedical research equivalent of arXiv, medRxiv, is only two years old but has been publishing a lot of COVID-19 research. arXiv has to an extent democratised research in physics, if people read arXiv preprints it matters less if the paper finally appear in the more glamorous journals like Science or Nature.

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Some particles are just the right size to go through a filter, not too small and not too large

Surprisingly, it is easier to filter out (from air) particles tens of nanometres across, than it is to filter particles hundreds of nanometres across. The image above shows why. The orange and green curves show the trajectories of two particles in air flowing through a model mask. The model is a two-dimensional cross section of a mask, with cross-sections through the fibres of which surgical masks are made, shown as reddish brown discs. The blue curves with arrows show the flow of the air through the model mask. The orange trajectory illustrates one of the particles that are hardest to filter out – and so cause us some of the biggest problems when we try and stop COVID-19 transmission.

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At the same time as parts of Italy were being overwhelmed by COVID-19, the UK government was downgrading the risk from COVID-19

I have been reading a couple of reports looking at the UK government’s guidance on the use of Personal Protective Equipment (PPE) for healthcare workers whose patients may be infected with COVID-19. One report by Dinah Gould and Edward Purssell was commissioned by the Royal College of Nursing and is pretty damning of the process by which the guidance was drawn up and the (lack of) evidence cited. But it is the other report, by a Health and Safety consultant David Osborn*, that astonished me when I read it Friday evening. COVID-19, the disease that has killed over 100,000 people in the UK, and millions worldwide, is not classified by the UK government as a “high consequence infectious disease” (HCID). This surprises me. Even more remarkably, it was considered a HCID until mid-March 2020, when it was downgraded. If you don’t believe me (and I wouldn’t blame you here), the official UK government page is here. If you remember, March 2020 was about the time that COVID-19 was overwhelming the healthcare system of parts of northern Italy, forcing the Italian government to send in the army. On the face of it, downgrading the official risk classification of an infectious disease at the same time as that disease is overwhelming the healthcare system of another European country is a surprising decision.

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We successfully suppressed the virus – the flu virus

It has not been a good year for the world, but we have achieved one remarkable and good thing. Flu infections are at historic lows. We have successfully suppressed the flu virus. We have been less successful with the, more infectious, SARS-CoV-2 virus that causes COVID-19, but with flu we have been successful. Presumably this is simply because these two diseases, flu and COVID-19, spread in very similar ways.

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In scientific research you get what you pay for

We are in the middle of a global pandemic caused by a virus, SARS-CoV-2, that is transmitted in the air we breathe. Especially in the UK it is not going well, with over 1,000 people dying a day. A big part of the problem is political. But it is also true that our knowledge of how diseases that spread in the air we breathe, is very incomplete. This is, I think, contributing to both debates and decision making being poorly done. Examples I can think of include debates and decision making in important areas such as social distancing, mask wearing, and whether in the middle of a pandemic it is a good idea to encourage people to visits restaurants. So why is our knowledge of how diseases such as COVID-19 spread, so incomplete?

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Different perspectives on COVID-19’s attack rate

The attack rate of an infectious disease is the % chance that you contract it. I think it is term was introduced by epidemiologists. A high attack rate is bad of course, a lower one would be better, so we want to know what the attack rate depends on. Epidemiologists typically want to know how the attack rate depends on, for example, “age, symptom status, duration of exposure and household size” — see a recent preprint by Prof Neil Ferguson at Imperial College and coworkers. So here the questions are: Are children more likely to become infected than the elderly? Does longer contact with an infected person increase the chance of infection? And so on. Aerosol scientists such as Prof Jose Jimenez, and at least some medics, have a different perspective on what determines the attack rate. Prof Jimenez has a Google Sheets that estimates attack rates. But here the assumption (not question) is that the attack rate depends on duration, but not age, as well as on other factors such as ventilation. I am wondering about these two different perspectives on the same problem.

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