Anthropomorphic language refers to non-human entities as if they have human experiences, perceptions, and motivations. Both non-living things and non-human organisms may be subjects of anthropomorphism. Anthropomorphism may be used deliberately as a kind of metaphorical language that will help the audience appreciate what is being described because of its similarly to some familiar human experience. In science teaching, and in public communication of science, anthropomorphic language may often be used in this way, giving technical accounts the flavour of a persuasive narrative that people will readily engage with. Anthropomorphism may therefore be useful in 'making the unfamiliar familiar', but sometimes the metaphorical nature of the language may not be recognised, and the listener/reader may think that the anthropomorphic description is meant to be taken at face value. This 'strong anthropomorphism' may be a source of alternative conceptions ('misconceptions') of science.
The first example was from the lead story about 'long COVID'.
Prof. Onur Boyman, Director of the Department of Immunology at the University Hospital, Zurich, was interviewed after his group published a paper suggesting that blood tests may help identify people especially susceptible to developing post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) – which has become colloquially known as 'long COVID'.
"We found distinct patterns of total immunoglobulin (Ig) levels in patients with COVID-19 and integrated these in a clinical prediction score, which allowed early identification of both outpatients and hospitalized individuals with COVID-19 that were at high risk for PACS ['long COVID']."
Cervia, Zurbuchen, Taeschler, et al., 2022, p.2
The study reported average patterns of immunoglobulins found in those diagnosed with COVID-19 (due to SARS-CoV-2 infection), and those later diagnosed with PACS. The levels of different types of immunoglobulins (designated as IgM, etc.) were measured,
Differentiating mild versus severe COVID-19, IgM was lower in severe compared to mild COVID-19 patients and healthy controls, both at primary infection and 6-month follow-up… IgG3 was higher in both mild and severe COVID-19 cases, compared to healthy controls …In individuals developing PACS, we detected decreased IgM, both at primary infection and 6-month follow-up… IgG3 tended to be lower in patients with PACS…which was contrary to the increased IgG3 concentrations in both mild and severe COVID-19 cases…
Cervia, Zurbuchen, Taeschler, et al., 2022, p.3
Viruses in a defensive mode
In the interview, Professor Boyman discussed how features of the immune system, and in particular immunoglobulins, were involved in responses to infection, and made the comment:
"IgG3…is smaller than IgM and therefore it is able to go into many more tissues. It is able to cross certain tissue barriers and go into those sites where viruses might actually try to go to and hide"
Prof. Onur Boyman interviewed on 'BBC Inside Science'
This is anthropomorphic as it refers to viruses trying to hide from the immune components. Of course, viruses are not sentient, so they do not try to do anything: they have no intentions. Although viruses might well pass across tissue barriers and move into tissues where they are less likely to come into contact with immunoglobulins, 'hiding' suggests a deliberate behaviour – which is not the case.
Professor Boyman is clearly aware of that, and either deliberately or otherwise was speaking metaphorically. Scientifically literate people would not be misled by this as they would know viruses are not conscious agents. However, learners are not always clear about this.
The bacteria, however, are going on the offensive
The other point I spotted was later in the same programme when the presenter, Gaia Vince, introduced an item about antibiotic resistance:
"Back in my grandparent's time, the world was a much more dangerous place with killer microbes lurking everywhere. People regularly died from toothache, in childbirth, or just a simple scratch that got infected. But at the end of the second world war, doctors had a new miracle [sic] drug called penicillin. Antibiotics have proved a game changer, taking the deadly fear away from common infections. But the microbes did not just accept defeat, they have been mounting their resistance and they are making a comeback."
Gaia Vince presenting 'Inside Science'
Antibiotics are generally ineffective against viruses, but have proved very effective treatments for many bacterial infections, including those that can be fatal when untreated. The functioning of antibiotics can be explained by science in purely natural terms, so the label of 'miracle drugs' is a rhetorical flourish: their effect must have seemed like a miracle when they first came into use, so this can also be seen as metaphoric language.
Bacteria regrouping for a renewed offensive? (Image by WikiImages from Pixabay )
However, again the framing is anthropomorphic. The suggestion that microbes could 'accept defeat' implies they are the kind of entities able to reflect on and come to terms with a situation – which of course they are not. The phrase 'mounting resistance' also has overtones of deliberate action – but again is clearly meant metaphorically.
Again, there is nothing wrong with these kinds of poetic flourishes in presenting science. Most listeners would have heard "microbes did not just accept defeat, they have been mounting their resistance and they are making a comeback" and would have spontaneously understood the metaphoric use of language without suspecting any intention to suggest microbes actually behave deliberately. Such language supports the non-specialist listener in accessing a technical science story.
Some younger listeners, however, may not have a well-established framework for thinking about the nature of an organism that is able to reflect on its situation and actively plan deliberate behaviours. After all, a good deal of children's literature relies on accepting that various organisms, indeed non-living entities such as trains, do have human feelings, motives and behavioural repertoires. (Learners may for example think that evolutionary adaptations, such as having more fur in a cold climate, are mediated by conscious deliberation.) Popular science media does a good job of engaging and enthusing a broad audience in science, but with the caveat that accessible accounts may be open to misinterpretation.
Work cited:
Cervia, C., Zurbuchen, Y., Taeschler, P. et al.(2022) Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome. Nature Communications, 13, 446. https://doi.org/10.1038/s41467-021-27797-1
Anthropomorphism is the name given treating non-human entities as if they were human actors. An example of anthropomorphic language would be "the atom wants to donate an electron so that it can get a full outer shell" (see for example: 'A sodium atom wants to donate its electron to another atom'). In an example such as that, an event that would be explained in terms of concepts such as force and energy in a scientific account (the ionisation of an atom) is instead described as if the atom is a conscious agent that is aware of its status, has preferences, and acts to bring about desired ends.
Of course, an atom is not a complex enough entity to have mental experience that allows it to act deliberately in the world, so why might someone use such language?
Perhaps, if the speaker was a young learner, because they have not been taught the science.
Perhaps a non-scientist might use such language because they can only make sense of the abstract event in more familiar terms.
But what if the speaker was a scientist – a science teacher or a research scientist?
When fellow professionals (e.g., scientists) talk to each other they may often use a kind of shorthand that is not meant to be taken literally (e.g., 'the molecule wants to be in this configuration') simply because it can shorten and simplify more technical explanations that both parties understand. But when a teacher is talking to learners or a scientist is trying to explain their ideas to the general public, something else may be going on.
Anthropomorphism in science communication and education
In science teaching or science communication (scientists communicating science to the public) there is often a need to present abstract or complex ideas in ways that are accessible to the audience. At one level, teaching is about shifting what is to be taught from being unfamiliar to learners to being familiar, and one way to 'make the unfamiliar familiar' is to show it is in some sense like something already familiar.
Therefore there is much use of simile and analogy, and of telling stories that locate the focal material to be learned within a familiar narrative. Anthropomorphism is often used in this way. Inanimate objects may be said to want or need or try (etc.) as the human audience can relate to what it is to want or need or try.
Such techniques can be very useful to introduce novel ideas or phenomena in ways that are accessible and/or memorable ('weak anthropomorphism'). However, sometimes the person receiving these accounts may not appreciate their figurative nature as pedagogic / communicative aids, and may mistake what is meant to be no more than a starting point, a way into a new topic or idea, as being the scientific account itself. That is, these familiarisation techniques can work so well that the listener (or reader) may feel satisfied with them as explanatory accounts ('strong anthropomorphism').
Evolution – it's just natural (selection)
A particular issue arises with evolution, when often science only has hypothetical or incomplete accounts of how and why specific features or traits have been selected for in evolution. It is common for evolution to be misunderstood teleologically – that is, as if evolution was purposeful and nature has specific end-points in mind.
The scientific account of evolution is natural selection, where none of genes, individual specimens, populations or species are considered to be deliberately driving evolution in particular directions (present company excepted perhaps – as humans are aware of evolutionary processes, and may be making some decisions with a view to the long-term future). 1
Yet describing evolutionary change in accord with the scientific account tends to need complex and convoluted language (Taber, 2017). Teleological and anthropomorphic shorthand is easier to comprehend – even if it puts a burden on the communicatee to translate the narrative into a more technical account.
What the virus tries to do
The first example from the recent Science in Action episode related to the COVID pandemic, and the omicron variant of the SARS-CoV-2 virus. This was the lead story on the broadcast/podcast, in particular how the travel ban imposed on Southern Africa (a case of putting the lid on the Petri dish after the variant had bolted?) was disrupting supplies of materials needed to address the pandemic in the countries concerned.
This was followed by a related item:
"Omicron contains many more mutations than previous variants. However scientists have produced models in the past which can help us understand what these mutations do. Rockefeller University virologist Theodora Hatziioannou produced one very similar to Omicron and she tells us why the similarities are cause for concern."
"When you give the virus the opportunity to infect so many people, then of course it is going to try not only every possible mutation, but every possible combination of mutations, until it finds one that really helps it overcome our defences."
Dr Theodora Hatziioannou interviewed on Science in Action
Dr Theodora Hatziioannou Research Associate Professor Laboratory of Retrovirology The Rockefeller University
I am pretty sure that Dr Hatziioannou does not actually think that 'the virus' (which of course is composed of myriad discrete virus particles) is trying out different mutations intending to stop once it finds one which will overcome human defences. I would also be fairly confident that in making this claim she was not intending her listeners to understand that the virus had a deliberate strategy and was systematically working its way through a plan of action. A scientifically literature person should readily interpret the comments in a natural selection framework (e.g., 'random' variation, fitness, differential reproduction). In a sense, Dr Hatziioannou's comments may be seen as an anthropomorphic analogy – presenting the 'behaviour' of the virus (collectively) by analogy with human behavior.
Yet, as a science educator, such comments attract my attention as I am well aware that school age learners and some adult non-scientists may well understand evolution to work this way. Alternative conceptions of natural selection are very common. Even when students have been taught about natural selection they may misunderstand the process as Lamarckian (the inheritance of acquired characteristics – see for example 'The brain thinks: grow more fur'). So, I wonder how different members of the public hearing this interview will understand Dr Hatziioannou's analogy.
Even before COVID-19 came along, there was a tendency for scientists to describe viruses in such terms as as 'smart', 'clever' and 'sneaky' (e.g., 'So who's not a clever little virus then?'). The COVID pandemic seems to have unleashed a (metaphorical) pandemic of public comments about what the virus wants, and what it tries to achieve, and so forth. When a research scientist talks this way, I am fairly sure it is intended as figurative language. I am much less sure when, for example, I hear a politician telling the public that the virus likes cold weather ('What COVID really likes').
Vulture bees have the guts for it
The other item that struck me concerned vulture bees.
"Laura Figueroa from University of Massachusetts in Amhert [sic] in the US, has been investigating bees' digestive systems. Though these are not conventional honey bees, they are Costa Rican vulture bees. They feed on rotting meat, but still produce honey."
Bees do not actually make reasoned choices about their diets (Original image by Oldiefan from Pixabay)
The background is that although bees are considered (so I learned) to have evolved from wasps, and to all have become vegetarians, there are a few groups of bees that have reverted to the more primitive habits of eating meat. To be fair to them, these bees are not cutting down the forests to set up pasture and manage livestock, but rather take advantage of the availability of dead animals in their environment as a source of protein.
These vulture bees (or carrion bees) are able to do this because their gut microbiomes consist of a mix of microbes that can support them in digesting meat, allowing them to be omnivores. This raises the usual kind of 'chicken and egg' question 1 thrown up by evolutionary developments: how did vegetarian bees manage to shift their diet: the more recently acquired microbes would not have been useful or well-resourced whilst the bees were still limiting themselves to a plant-based diet, but the vegetarian bees would not have been able to digest carrion before their microbiomes changed.
As part of the interview, Dr Figueroa explaied:
"These are more specialised bees that once they were vegetarian for a really long time and they actually decided to change their ways, there's all of this meat in the forest, why not take advantage? I find that super-fascinating as well, because how do these shifts happen?
Because the bees, really when we are thinking about them, they've got access to this incredible resource of all of the flowering plants that are all over the world, so then why switch? Why make this change?
Over evolutionary time there are these mutations, and, you know, maybe they'd have got an inkling for meat, it's hard to know how exactly that happened, but really because it is a constant resource in the forest, there's always, you know, this might sound a little morbid but there's always animals that are dying and there's always this turn over of nutrients that can happen, and so potentially this specialised group of bees realised that, and maybe there's enough competition on the flowers that they decided to switch. Or, they didn't decide, but it happened over evolutionary time.
Dr Laura Figueroa interviewed on Science in Action
Dr Figueroa does not know exactly how this happened – more research is needed. I am sure Dr Figueroa does not think the bees decided to change their ways in the way that a person might decide to change their ways – perhaps deciding to get more exercise and go to bed earlier for the sake of their health. I am also sure Dr Figueroa does not think the bees realised that there was so much competition feeding on the flowers that it might be in their interests to consider a change of diet, in the way that a person might decide to change strategy based on an evaluation of the competition. These are anthropomorphic figures of speech.
Dr Laura Figueroa, NSF Postdoctoral Research Fellow in Biology Department of Entomology, Cornell University / University of Massachusetts in Amherst
As she said "they didn't decide, but it happened over evolutionary time". Yet it seems so natural to use that kind of language, that is to frame the account in a narrative that makes sense in terms of how people experience their lives.
Again, the scientifically literate should appreciate the figurative use of language for what it is, and it is difficult to offer an accessible account without presenting evolutionary change as purposive and the result of deliberation and strategy. Yet, I cannot help wondering if this kind of language may reinforce some listeners' alternative conceptions about how natural selection works.
Work cited:
Dawkins, R. (1976/1989). The Selfish Gene (New ed.). Oxford: Oxford University Press.
1 The 'selfish' gene made famous by Dawkins (1976/1989) is not really selfish in the sense a person might be – rather this was an analogy which helped shift attention from changes at the individual or species level when trying to understand how evolution occurs, to changes in the level of distinct genes. If a mutation in a specific gene leads to a change in the carrying organism that (in turn) leads to that specimen having greater fitness then the gene itself has an increased chance of being replicated. So, from the perspective of focusing on the genes, the change at the species level can be seen as a side effect of the 'evolution' of the gene. The gene may be said to be (metaphorically) selfish because it does not change for the benefit of the organism, but to increase its own chances of being replicated. Of course, that is also an anthropomorphic narrative – actually the gene does not deliberately mutate, has no purpose, has no notion of replication, indeed, does not even 'know' it is a gene, and so forth.
2 Such either/or questions can be understood as posing false dichotomies (here, either the bees completely changed their diets before their microbiomes or their microbiomes changed dramatically before their diets shifted) when what often seems most likely is that change has been slow and gradual.
"I picked up that phrase 'almost certainly due to lack of vaccine', I mean that sounds like a bit of guesswork."
Presenter on the BBC Radio 4 Today programme
Yesterday, I was drafting a post about how a scientist had referred to a scientific theory being 'absolutely certain'. I suggested that this seemed at odds with the nature of science as producing conjectural knowledge always open to revisiting – yet might be considered necessary when seeking to communicate in public media.
Today, I sadly heard an excellent example to support that thesis.
BBC Radio 4's Today programme included an interview with Dr Raghib Ali
Robinson: "Now one of the first things we learned when the pandemic began, was that a greater proportion of Black and South Asian people were dying from corona virus. That remains the case many months on, but a new government report out today argues that the mortality gap now is mainly due, is not due, I'm sorry, to any genetic or social factor, it is, and I quote almost certainly down to vaccine take-up, or more accurately a lack of vaccine take-up. We're joined now by the government's independent expert advisor on COVID-19 and ethnicity, Dr. Raghib Ali, who is a consultant in acute medicine at Oxford University Hospitals. Morning to you"
Dr Ali: "Good morning Nick."
Robinson:"I picked up that phrase 'almost certainly due to lack of vaccine', I mean that sounds like a bit of guesswork. Do we actually know that?"
Nick Robinson interviewing Dr Raghib Ali on Today, 3rd December 2021, c.08.46
This seems to show a worrying level of ignorance (or else an odd provocation) from a senior and experienced journalist expecting scientific studies to be able to offer certain knowledge about causes in complex multivariate social situations.
How a scientific claim was understood on a prestigious news magazine programme
Sadly, if the news media are only interested in absolute certainty, then they should stop talking to scientists about their work as absolute certainty has no place in scientific discourse. Nor should it, I might suggest, have a place in serious journalism.
Could an oral Covid-19 treatment be available soon?
There was an item on the BBC radio programme/podcast 'Science in Action' (23rd September 2021) about anti-viral agents being used in response to the COVID-19 pandemic: 'Could an oral Covid-19 treatment be available soon?'
"But even after someone is infected, the host actually mounts, for all these [respiratory] viruses, a really dramatic immune and inflammatory response. So it sort of lights a fire. And even when the virus stops replicating, you know that fire continues to burn, and in a lot of cases that's what lands people in the hospital. And so you want to prevent the virus from igniting that fire, that is what really ends up causing a huge amount of damage to the patient. …
the greatest benefit [of the antiviral drug being tested] is in the outpatient setting before that fire gets ignited."
Daria Hazuda being interviewed on 'Science in Action'
A scientific simile
Science communicators, such as teachers, but also scientists and journalists presenting science in the public media, often use techniques to 'make the unfamiliar familiar', to get across abstract or difficult ideas in ways that their audience can relate to.
These techniques can include analogies, metaphors and similes. Here Dr Hazuda used an analogy between the damage to tissue that can occur in disease, and the damage a fire can do. In particular, she was suggesting that the virus may be seen as like something which ignites a fire (such as a match or a spark) but which is not needed to keep the fire going once it had taken hold.
She introduced this idea by suggesting that the virus "sort of lights a fire". This can be considered a simile, which is a figure of speech which is a kind of explicit comparison where one thing is said to be like or similar to another.2 Dr Hazuda did not suggest that the virus actually lights a fire, but rather it has an effect which can be considered somewhat like ('sort of') igniting a fire.
"We didn't start the fire It was always burning, since the world's been turning We didn't start the fire No, we didn't light it, but we tried to fight it"
Billy Joel
Viruses triggering long term disease
The symptoms we experience when ill can be the results of our immune system reacting to illness, rather than the direct effect of the disease causing agent. That does not mean the disease itself would not harm us (infectious agents may be destroying cells which would not be obvious until extensive damage was done), but that in some conditions what we notice – perhaps sneezing, coughing, a raised temperature – is due to the immune response.
The immediate context of the Science in Action interview was the current COVID-19 pandemic caused by infection with the SARS-CoV-2 virus. However, the idea that a viral infection may trigger ('ignite') a longer term immune response (the 'fire') is not new with COVID. The syndrome sometimes known as chronic fatigue syndrome has unknown cause(s), but viruses are among the suspects. Viruses have been suspected as being a possible trigger (if perhaps in combination with other factors) in a range of autoimmune conditions. In autoimmune conditions the mechanisms that usually protect a person from infectious agents such as (some) bacteria and viruses attack and destroy the person's own cells leading to inflammation and potentially serious tissue damage.
People might commonly say that the immune system is 'meant' or 'intended' to protect us from diseases and that it sometimes 'goes wrong' leading to autoimmune disease – but strictly this is not a scientific way of thinking. The immune system has no purpose as such (this would be 'teleological' thinking), but has just evolved in ways such that it has on balance increased fitness.
From that perspective, it might not seem so strange that our immune systems are sometimes insufficient to protect us from harm, and yet can also sometimes be over-sensitive and start doing damage – as that surely is what we might expect if evolution has (through natural selection) led to a system which has tendedon the whole to be protective.
The admirable HLA-B27?
"HLA B27 plays an admirable, perhaps outstanding role in the immune response to viruses, however, it is also directly involved in the pathogenesis of the spondyloarthropathies"
Bowness, 2002: 866
My late wife Philippa was diagnosed with a complex autoimmune condition – she was told that she had atypical Wegener's granulomatosis (a disease now usually called Granulomatosis with polyangiitis2), a form of vasculitis (a disease leading to inflammation in the blood vessels), and that she might have been genetically susceptible to autoimmune diseases because she produced a particular type of human leukocyte antigen, HLA-B27. HLA is an important component of human immune systems, but the precise antigens a person produces varies, depending on their genes (just as we all have blood but people can be assigned into different blood groups). It was also suggested to her that an otherwise minor infection may have acted as a trigger in setting off the autoimmune problems.
Medicine today has some effective agents such as steroids that help 'dampen down' the 'fires' that damage tissues in autoimmune diseases. But these conditions can be very serious. Fifty years ago, most people found to have Wegener's granulomatosis were dead from that damage within a year of their diagnosis.
HLA-B27 is only found in a minority of people in most populations and is associated with a higher prevalence of certain immune conditions such as ankylosing spondylitis (an inflammatory condition especially affecting the spine), inflammatory bowel disease, and some forms of arthritis. It might seem odd that evolution has not led to the elimination of HGLA-B27 if it is associated with serious medical conditions. Yet, again, it may be that something which can make people prone to some conditions may also be better at protecting them from others.
People with HLA-B27 may be better at mounting an effective immune response to some viral infections (the fire is more readily ignited, we might say) and this might be enough of an advantage to balance its unfortunate role in autoimmune conditions. Over human history, HLA-B27 might have protected a great many people from dangerous infections, if also being responsible for a smaller number becoming very ill.
"HLA-B27 appears to excel at its natural function of binding and presenting viral peptide epitopes to cytotoxic T cells. We have suggested that HLA-B27 may, however, act as a 'double-edged sword'. Thus, certain features of its peptide binding ability or cell biology (perhaps those favouring excellent antiviral responses) might also lead to autoimmunity."
McMichael & Bowness, 2002: S157
That is, what makes this immune component so good at attacking certain viruses (as if the immune system had been doused in petrol so that the slightest spark might initiate a response) may also be responsible for its association with autoimmune diseases. HLA-B27 may (metaphorically) be the can of petrol that means that a viral spark starts not just a fire, but a conflagration.
1: "the first oral, direct-acting antiviral shown to be highly effective at reducing nasopharyngeal SARS-CoV-2 infectious virus" according to a preprint reported at medRχiv). A preprint is a paper written to report scientific research but NOT yet tested through peer review and formally published, and so treated as reporting more provisional and uncertain findings than a peer-reviewed paper.
2 By comparison, a metaphor may be considered an implicit comparison presented as if an identity: e.g., the nucleus is the brain of the cell.
2. The disease was named after the German physician Friedrich Wegener who described the condition. After Wegener was identified as a Nazi and likely war criminal (suspected, but not convicted) it was decided to rename the disease.
When I was listening to the radio news I heard a clip of the Rt. Hon. Sajid Javid MP, the U.K. Secretary of State for Health and Social Care, talking about the ongoing response to the COVID pandemic:
Health Secretary Sajid Javid talking on 12th September
"Now that we are entering Autumn and Winter, something that COVID and other viruses, you know, usually like, the prime minister this week will be getting out our plans to manage COVID over the coming few months."
Sajid Javid
So, COVID and other viruses usually like Autumn and Winter (by implication, presumably, in comparison with Spring and Summer).
This got me wondering how we (or Sajid, at least) could know what the COVID virus (i.e., SARS-CoV-2 – severe acute respiratory syndrome coronavirus 2) prefers – what the virus 'likes'. I noticed that Mr Javid offered a modal qualification to his claim: usually. It seemed 'COVID and other viruses' did not always like Autumn and Winter, but usually did.
Yet there was a potential ambiguity here depending how one parsed the claim. Was he suggesting that
[COVID and other viruses]
usually
like Autumn and Winter
or
COVID
[and other viruses usually]
like Autumn and Winter
This might have been clearer in a written text as either
COVID and other viruses usually like Autumn and Winter
or
COVID, and other viruses usually, like Autumn and Winter
The second option may seem a little awkward in its phrasing, 1 but then not all viral diseases are more common in the Winter months, and some are considered to be due to 'Summer viruses':
"Adenovirus, human bocavirus (HBoV), parainfluenza virus (PIV), human metapneumovirus (hMPV), and rhinovirus can be detected throughout the year (all-year viruses). Seasonal patterns of PIV are type specific. Epidemics of PIV type 1 (PIV1) and PIV type 3 (PIV3) peak in the fall [Autumn] and spring-summer, respectively. The prevalence of some non-rhinovirus enteroviruses increases in summer (summer viruses)"
Moriyama, Hugentobler & Iwasaki, 2020: 86
Just a couple of days later Mr Javid was being interviewed on the radio, and he made a more limited claim:
Health Secretary Sajid Javid talking on BBC Radio 4's 'Today' programme, 15th September
"…because we know Autumn and Winter, your COVID is going to like that time of year"
Sajid Javid
So, this claim was just about the COVID virus, not viruses more generally, and that we knowthat COVID is going to like Autumn and Winter. No ambiguity there. But how do we know?
Coming to knowledge
Historically there have been various ways of obtaining knowledge.
Divine revelation: where God reveals the knowledge to someone, perhaps through appearing to the chosen one in a dream.
Consulting an oracle, or a prophet or some other kind of seer.
Intuiting the truth by reflecting on the nature of things using the rational power of the human intellect.
Empirical investigation of natural phenomena.
My focus in this blog is related to science, and given that we are talking about public health policy in modern Britain, I would like to think Mr Javid was basing his claim on the latter option. Of course, even empirical methods depend upon some metaphysical assumptions. For example, if one assumes the cosmos has inbuilt connections one might look for evidence in terms of sympathies or correspondences. Perhaps, if the COVID virus was observed closely and looked like a snowflake, that could (in this mindset) be taken as a sign that it liked Winter.
A snowflake – or is it a virus particle? (Image by Gerd Altmann from Pixabay)
Sympathetic magic
This kind of correspondence, a connection indicated by appearance, was once widely accepted, so that a plant which was thought to resemble some part of the anatomy might be assumed to be an appropriate medicine for diseases or disorders associated with that part of the body.
This is a kind of magic, and might seem a 'primitive' belief to many people today, but such an idea was sensible enough in the context of a common set of underlying beliefs about the nature and purposes of the world, and the place and role of people in that world. One might expect that specific beliefs would soon die out if, for example, the plant shaped like an ear turned out to do nothing for ear ache. Yet, at a time when medical practitioners could offer little effective treatment, and being sent to a hospital was likely to reduce life expectancy, herbal remedies at least often (if not always) did no harm.
Moreover, many herbs do have medicinal properties, and something with a general systemic effect might work as topical medicine (i.e., when applied to a specific site of disease). Add to that, the human susceptibility to confirmation bias (taking more notice of, and giving more weight to, instances that meet our expectations than those which do not) and the placebo effect (where believing we are taking effective medication can sometimes in itself have beneficial effects) and the psychological support offered by spending time with an attentive practitioner with a good 'bedside' manner – and we can easily see how beliefs about treatments may survive limited definitive evidence of effectiveness.
The gold standard of experimental method
Of course, today, we have the means to test such medicines by taking a large representative sample of a population (of ear ache sufferers, or whatever), randomly dividing them into two groups, and using a double-blind (or should that be double-deaf) approach, treat them with the possible medicine or a placebo, without either the patient or the practitioner knowing who was getting which treatment. (The researchers have a way to know of course – or it would difficult to deduce anything from the results.) That is, the randomised control trial (RCT).
Now, I have been very critical of the notion that these kinds of randomised experimental designs should be automatically be seen as the preferred way of testing educational innovations (Taber, 2019) – but in situations where control of variables and 'blinding' is possible, and where randomisation can be applied to samples of well-defined populations, this does deserve to be considered the gold standard. (It is when the assumptions behind a research methodology do not apply that we should have reservations about using it as a strategy for enquiry.)
So can the RCT approach be used to find out if COVID has a preference for certain times of year? I guess this depends on our conceptual framework for the research (e.g., how do we understand what a 'like' actually is) and the theoretical perspective we adopt.
So, for example, behaviourists would suggest that it is not useful to investigate what is going on in someone's mind (perhaps some behaviorists do not even think the mind concept corresponds to anything real) so we should observe behaviours that allow us to make inferences. This has to be done with care. Someone who buys and eats lots of chocolate presumably likes chocolate, and someone who buys and listens to a lot of reggae probably likes reggae, but a person who cries regularly, or someone that stumbles around and has frequent falls, does not necessary like crying, or falling over, respectively.
A viral choice chamber
So, we might think that woodlice prefer damp conditions because we have put a large number of woodlice in choice chambers with different conditions (dry and light, dry and dark, damp and light, damp and dark) and found that there was a statistically significant excess of woodlice settling down in the damp sections of the chamber.
Of course, to infer preferences from behaviour – or even to use the term 'behaviour' – for some kinds of entity is questionable. (To think that woodlice make a choice based on what they 'like' might seem to assume a level of awareness that they perhaps lack?) In a cathode ray tube electrons subject to a magnetic field may be observed (indirectly!) to move to one side of the tube, just as woodlice might congregate in one chamber, but I am not sure I would describe this as electrons liking that part of the tube. I think it can be better explained with concepts such as electrical charge, fields, forces, and momentum.
It is difficult to see how we can do double blind trials to see which season a virus might like, as if the COVID virus really does like Winter, it must surely have a way of knowing when it is Winter (making blinding impossible). In any case, a choice chamber with different sections at different times of the year would require some kind of time portal installed between its sections.
Like electrons, but unlike woodlice, COVID viral particles do not have an active form of transport available to them. Rather, they tend to be sneezed and coughed around and then subject to the breeze, or deposited by contact with surfaces. So I am not sure that observing virus 'behaviour' helps here.
So perhaps a different methodology might be more sensible.
A viral opinion poll
A common approach to find out what people like would be a survey. Surveys can sometimes attract responses from large numbers of respondents, which may seem to give us confidence that they offer authentic accounts of widespread views. However, sample size is perhaps less important than sample representativeness. Imagine carrying out a survey of people's favourite football teams at a game at Stamford Bridge; or undertaking a survey of people's favourite bands as people queued to enter a King Crimson concert! The responses may [sic, almost certainly would] not fully reflect the wider population due to the likely bias in such samples. Would these surveys give reliable results which could be replicated if repeated at the Santiago Bernabeu or at a Marillion concert?
How do we know what 'COVID 'really likes? (Original Images by OpenClipart-Vectors and Gordon Johnson from Pixabay)
A representative sample of vairants?
This might cause problems with the COVID-19 virus (SARS-CoV-2). What counts as a member of the population – perhaps a viable virus particle? Can we even know how big the population actually is at the time of our survey? The virus is infecting new cells, leading to new virus particles being produced all the time, just as shed particles become non-viable all the time. So we have no reliable knowledge of population numbers.
Moreover, a survey needs a representative sample: do the numbers of people in a sample of a human population reflect the wider population in relevant terms (be that age, gender, level of educational qualifications, earnings, etc.)? There are viral variants leading to COVID-19 infection – and quite a few of them. That is, SARS-CoV-2 is a class with various subgroups. The variants replicate to different extents under particular conditions, and new variants appear from time to time.
So, the population profile is changing rapidly. In recent months in the UK nearly all infections where the variant has been determined are due to the variant VOC-21APR-02 (or B.1.617.2 or Delta) but many people will be infected asymptotically or with mild symptoms and not be tested, and so this likely does not mean that VOC-21APR-02 dominates the SARS-CoV-2 population as a whole to the extent it currently dominates in investigated cases. Assuming otherwise would be like gauging public opinion from the views of those particular people who make themselves salient by attending a protest, e.g.:
"Shock finding – 98% of the population would like to abolish the nuclear arsenal,
according to a [hypothetical] survey taken at the recent Campaign for Nuclear Disarmament march"
In any case, surveys are often fairly blunt instruments as they need to present objectively the same questions to all respondents, and elicit responses in a format that can be readily classified into a discrete number of categories. This is why many questionnaires use Likert type items:
Would you say you like Autumn and Winter:
1
2
3
4
5
Always
Nearly always
Usually
Sometimes
Never
Such 'objective' measures are often considered to avoid the subjective nature of some other types of research. It may seem that responses do not need to be interpreted – but of course this assumes that the researchers and all the respondents understand language the same way (what exactly counts as Autumn and Winter? What does 'like' mean? How is 'usually' understood – 60-80% of the time, or 51-90% of the time or…). We can usually (sic) safely assume that those with strong language competence will have somewhat similar understandings of terms, but we cannot know precisely what survey participants meant by their responses or to what extent they share a meaning for 'usually'.
There are so-called 'qualitative surveys' which eschew this kind of objectivity to get more in-depth engagement with participants. They will usually use interviews where the researcher can establish rapport with respondents and ask them about their thoughts and feelings, observe non-verbal signals such as facial expressions and gestures, and use follow-up questions… However, the greater insight into individuals comes at a cost of smaller samples as these kinds of methods are more resource-intensive.
But perhaps Mr Javid does not actually mean that COVID likes Autumn and Winter?
So, how did the Department of Health & Social Care, or the Health Secretary's scientific advisors, find out that COVID (or the COVID virus) likes Autumn and Winter? The virus does not think, or feel, and it does not have preferences in the way we do. It does not perceive hot or cold, and it does not have a sense of time passing, or of the seasons.2 COVID does not like or dislike anything.
Mr Javid needs to make himself clear to a broad public audience, so he has to avoid too much technical jargon. It is not easy to pitch a presentation for such an audience and be pithy, accurate, and engaging, but it is easy for someone (such as me) to be critical when not having to face this challenge. Cabinet ministers, unlike science teachers, cannot be expected to have skills in communicating complex and abstract scientific ideas in simplified and accessible forms that remain authentic to the science.
It is easy and perhaps convenient to use anthropomorphic language to talk about the virus, and this will likely make the topic seem accessible to listeners, but it is less clear what is actually meant by a virus liking a certain time of year. In teaching the use of anthropomorphic language can be engaging, but it can also come to stand in place of scientific understanding when anthropomorphic statements are simply accepted uncritically at face value. For example, if the science teacher suggests "the atom wants a full shell of electrons" then we should not be surprised that students may think this is a scientific explanation, and that atoms do want to fill their shells. (They do not of course. 3)
Image by Gordon Johnson from Pixabay
Of course Mr Javid's statements cannot be taken as a literal claim about what the virus likes – my point in this posting is to provoke the question of what this might be intended to mean? This is surely intended metaphorically (at least if Mr Javid had thought about his claim critically): perhaps that there is higher incidence of infection or serious illness caused by the COVID virus in the Winter. But by that logic, I guess turkeys really would vote for Christmas (or Thanksgiving) after all.
Typically, some viruses cause more infection in the Winter when people are more likely to mix indoors and when buildings and transport are not well ventilated (both factors being addressed in public health measures and advice in regard to COVID-19). Perhaps 'likes' here simply means that the conditions associated with a higher frequency/population of virus particles occur in Autumn and Winter?
A snowflake. The conditions suitable for a higher frequency of snowflakes are more common in Winter. So do snowflakes also 'like' Winter? (Image by Gerd Altmann from Pixabay)
However, this is some way from assigning 'likes' to the virus. After all, in evolutionary terms, a virus might 'prefer', so to speak, to only be transmitted asymptomatically, as it cannot be in the virus's 'interests', so to speak, to encourage a public health response that will lead to vaccines or measures to limit the mixing of people.
If COVID could like anything (and of course it cannot), I would suggest it would like to go 'under the radar' (another metaphor) and be endemic in a population that was not concerned about it (perhaps doing so little harm it is not even noticed, such that people do not change their behaviours). It would then only 'prefer' a Season to the extent that that time of year brings conditions which allow it to go about its life cycle without attracting attention – from Mr Javid or anyone else.
The health secretary was interviewed on 1st December
"…we have always known that when it gets darker, it gets colder, the virus likes that, the flu virus likes that and we should not forget that's still lurking around as well…"
Rt. Hon. Sajid Javid MP, the U.K. Secretary of State for Health and Social Care, interviewed on BBC Radio 4 Today programme, 1st December, 2021
Works cited:
Moriyama, M., Hugentobler, W. J., & Iwasaki, A. (2020). Seasonality of Respiratory Viral Infections. Annual Review of Virology, 7(1), 83-101. doi:10.1146/annurev-virology-012420-022445
1. It would also seem to be a generalisation based on the only two Winters that the COVID-19 virus had 'experienced'
2. Strictly I cannot know what it is like to be a virus particle. But a lot of well-established and strongly evidenced scientific principles would be challenged if a virus particle is sentient.
Dampening down COVID? (Image by Iván Tamás from Pixabay)
Analogy in science
Analogy is a common technique used in science and science education. In scientific work analogy may be used as a thinking tool useful for generating hypotheses to explore – "what if X is like Y, then that might mean…". That is, we think we understand system Y, so, if for a moment we imagine that system X may be similar, then by analogy that would mean (for example) that A may be the cause of B, or that if we increase C then we might expect D to decrease… Suggesting analogies has been used as a way of introducing a creative activity into school science (Taber, 2016).
Scientists also sometimes use analogies to explain their ideas and results to other scientists. However, analogies are especially useful in explaining abstract ideas to non-experts, so they are used in the public communication of science by comparing technical topics with more familiar, everyday ('lifeworld') phenomena. In the same way, teachers use analogies as one technique for 'making the unfamiliar familiar' by suggesting that the unfamiliar curriculum focus (the target concept to be taught) is in some ways just like a familiar lifeworld phenomena (the analogue or source concept).
So, I was interested to hear Prof. Andrew Hayward, Professor of Infectious Disease Epidemiology and Inclusion Health Research at UCL (University College London), being interviewed on the radio and suggesting that COVID was like a fire:
"Sometimes I like to think of, you know, COVID as a fire, if we are the fuel, social mixing is the oxygen that allows the fuel to burn, vaccines the water that stops the fuel from burning, and COVID cases are the sparks that spread the fire. So, we are doing well on vaccines, but there's lots of dried wood left."
There's quite a lot going on in that short statement. If Prof. Hayward had stopped at "sometimes I like to think of COVID as a fire" this would have been a simile where it is simply observed that one thing is conceived as being a bit like another.
Simile offers a comparison and leaves the listener or reader to work out the nature of the similarity (whereas metaphor, where one thing is described to be another, an example would be 'COVID is a fire', leaves the audience to even appreciate a comparison is being made). Analogy goes further, as it makes a comparison between two conceptual structures (two systems), such that by mapping across them we can understand how the structure of the unfamiliar is suggested to be like the more familiar structure.
That is, there is a mapping (see the figure below) that is based on pairings across the analogy. Here fire and COVID disease are each treated as systems with components that are structured in a parallel way:
COVID (illness): fire
people: fuel
social mixing: oxygen
vaccines: water
COVID cases: sparks
A graphic representation of Prof. Hayward's use of analogy
A lot of us are like kindling
Moreover, having set up this analogy, we are offered some additional information – we are doing well on vaccines (= there is plenty of water to stop fuel burning), but there is still a lot of dried wood. The listener has to understand that the dry wood refers to fuel, and this maps (in the analogy) onto lots of people who can still become infected.
I suspect most people (science teachers perhaps excepted) listening to this interview will not have even explicitly noticed the nature of the analogy, but rather automatically processed the comparison. They would have understood the message about COVID through the analogy, rather than having to actively analyse the analogy itself.
We can stop the sparks spreading the fire
Professor Hayward was asked about contact tracing and suggested that
"…the key thing is the human discussion with somebody who has COVID to identify who their contacts are and to ask them to isolate as well, and that really stops those sparks getting into the population and really helps to dampen down the fire."
That is, that potential COVID cases (that are like sparks in the fire system) can be prevented from mixing with the wider population (who are like fuel in the fire system) and this will dampen down the fire (the illness in the COVID system). {Note 'dampen down' seems to be a metaphor here rather than a true part of the analogy (in which it is the vaccines that have the effect of 'literally' {analogously} dampening down the fire). Stopping sparks mixing with fuel will limit new areas of combustion starting rather than dampening down the existing fire.}
An argument about contact tracing made using the analogy
Again, most people listening to this would likely have taken on board the intended meaning quite automatically, without having to deliberately analyse this answer – even though the response shifts between the target topics (the COVID disease system) and the analogue (the fire system) – so the sparks (fire system – equivalent to infectious cases) are stopped from getting into the population (COVID system – equivalent to the fuel supply).
This is reminiscent of chemistry teaching which slips back and forth between macroscopic and molecular levels of description – and so where references to, for example, hydrogen could mean the substance or the molecule – and the same word may have a different referent at different points in the same utterance (Taber, 2013). Whether this is problematic depends upon the past experiences of the listener – someone with extensive experience of a domain (probably most of the audience of a serious news magazine programme understand enough about combustion and infection to not have to deliberate on the analogy discussed here) can usually make these shifts automatically without getting confused.
Fire requires…AND…AND…
An analogy can only be effective when the analogue is indeed more familiar to the audience (you cannot make the unfamiliar familiar by comparing an unfamiliar target with an analogue that is also unfamiliar) so the use of the analogy by Professor Hayward assumed some basic knowledge about fire. Indeed it seemed to assume knowledge of the so-called 'fire triangle'.
Three factors are need to initiate/maintain combustion: fire may be stopped by removing one or more of these.
This is the idea that for a fire to commence or continue there need to be three things: something combustible to act as fuel; AND oxygen (or another suitable substance – as when iron filings burn in chlorine – but in usual circumstances it will be oxygen); AND a source of energy sufficient to initiate reaction (as burning is exothermic, once a fire is underway it may generate enough heat to maintain combustion – and sparks may spread the fire to nearby combustible material). To extinguish a fire, one needs to remove at least one of these factors – water can act as a heat sink to decrease the temperature, and may also reduce the contact between the fuel and oxygen. Preventing sparks from transferring hot material that can initiate further sites of combustion (providing energy to more fuel) can also be important.
Unobtrusive pedagogy
The quotes here were part of a short interview with a broadcast journalist and intended for a general public audience. Prof. Hayward introduced and developed his analogy as just sharing a way of thinking, and indeed analogy is such a common device in conversation that it was not obviously marked as a pedagogic technique. However, when we think about how such a device works, and what is expected of the audience to make sense of it, I think it is quite impressive how we can often 'decode' and understand such comparisons without any conscious effort. Providing, of course, that the analogue is indeed familiar, and the mapping across the two conceptual structures can be seen to fit.
A few days ago WHO reported that the UK had had over 300 000 confirmed cases of COVID-19, but now WHO is reporting the cumulative total is many fewer. How come?
Keith S. Taber
I have been keeping an eye on the way the current pandemic has been developing around the world by looking at the World Health Organisation website (at https://covid19.who.int) which offers regularly updated statistics, globally, regionally, and in those countries with the most cases.
An example of the stats. reported by the WHO (June 23rd 2020) Note: on this day the UK Prime Minister reported: "In total, 306,210 people have now tested positive for coronavirus" which almost matches the figure shown by WHO (306 214) the next day.
Whilst the information is very interesting (and in view of what it represents, very saddening) there are some strange patterns in the graphs presented – reminding one that measurements can never just be assumed to precise, accurate and reliable. Some of the data looks unlikely to accurate, and in at least one case what is presented is downright impossible.
Questionable stats.
One type of anomaly that stands out is how some countries where the pandemic is active suddenly have a day with no new cases – before the level returning to trend.
This appeared to be the case in both Spain and Italy on 22nd March, and the two months later the same thing happened in Iran. One assumes this has more to do with reporting procedures than blessed days when no one was found to have the infection – although if that was the case should there not be some compensation in the following days (perhaps so in Spain above, but apparently not in Italy, and certainly not in Iran)?
Less easy to explain away is a peak found in the graph for Chile.
Suddenly for one day, 18th June, a much larger number of cases is reported: but then there is an immediate return to the baseline:
How is it possible that suddenly on one day there are seven times as many cases reported – as a blip superimposed on an otherwise fairly flat trend-line? Perhaps there is a rational explanation – but unfortunately the WHO site is rich in stats, but does not seem to offer interpretation or explanations *. Without a rationale, one wonder just how trustworthy the stats actually are.
Obviously false information
Even if there are explanations for some of these odd patterns due to the practicalities of reporting, and the ongoing development of systems of testing and reporting, in different jurisdictions, there is one anomaly that cannot be feasibly explained – where the data is surely, and clearly, wrong.
An example of the stats reported by the WHO (July 6th 2020)
So the graph above shows the nations with the most reported cases as of the last few days. This is a more recent update than the similar image at the top of this page. Yet, the cumulative total of confirmed cases for the United Kingdom in this figures is something like 20 000 cases LESS than the figure quoted in the EARLIER set of graphs. (Note that this has allowed the UK to have lower cumulative totals than either Chile or Peru – which would not have been the case without this reduction in cumulative total.)
The total number of confirmed cases in the UK is now (7th July) LESS that it was a week ago (see above). How come? Well, a close look the graph below explains this. The drop in cumulative numbers is due to the number of new cases that WHO gives as reported on 3rd July, when there were -29 726 new cases. Yes, that's right minus 29 thousand odd cases.
The WHO data show negative cases (-525 new cases) for the UK on May 21st as well, but on the 3rd July the magnitude of the negative number of confirmed cases is over three times as many as the highest daily number of positive new cases on any single day (April 12th, i.e., 8719 new cases).
I can imagine that if it was identified that a previous miscalculation had occurred it might be necessary to revise previous data. But surely an adjustment would be made to the earlier data: not the cumulative total corrected by interjecting a large negative number of cases on some arbitrary date in order to put the total right. [Note: the most recent data I can find on the UK government site cites 309,360 confirmed cases as of 26th June (2020-06-26 COVID-19 Press Conference Slides) so as of yet the UK data does not show the reduction in cumulative total being published by WHO.**]
Yet surely someone at WHO must have spotted that the anomaly is bizarre and brings their reports into question. The negative cases claimed for the UK on that one day are so great that the UK line has since burrowed into the graphics for completely different countries. (See below. On the day the UK graph was located above the graphic for Mexico, the UK line actually went down so far it actually crossed below the line for Mexico.)
Of course, each unit in these figures represents someone, a fellow human somewhere in the world, who has been found to be infected with a very serious, and sometimes fatal, virus. Fixating on the stats can distract from the real human drama that many of these cases represent. Yet, when the data reflect something so important, and when data are so valuable in understanding and responding to the global pandemic, such an obvious flaw in the data is disappointing and worrying.
*I could not find a link to send an email; a tweet did not get a response from @WHO; and an invitation to type my question on the website was met by the site bot with a suggestion to return to the data I was asking about.
** If I subsequently learn of the reason for the report of negative numbers of cases in these statistics, I will post an update here.
Update at 2020-07-12: duplicate testing
As of Saturday 11 July 2020 at 6:20pm The UK government reports Total number of lab-confirmed UK cases 288,953 Total number of people who have had a positive test result
So this is less than they were reporting a week earlier, despite their graph (for England, where most cases are because it is the most populous county of the UK) not showing any dip:
However, I did find this explanation:
"The data published on this website are constantly being reviewed and corrected. Cumulative counts can occasionally go down from one day to the next, and on some occasions there have been major revisions that have a significant effect on local, regional, National or UK totals. Data are provided daily from several different electronic data collection systems and these can experience technical issues which can affect daily figures, usually resulting in lower daily counts. The missing data are normally included in the data published the following day.
From 2 July 2020, Pillar 2 data [from "swab testing for the wider population" i.e., than just "for those with a clinical need, and health and care workers"] has been reported separately by all 4 Nations. Pillar 2 data for England has had duplicate tests for the same person removed by PHE [Public Helth England] from 2 July 2020. This means that the cumulative total number of UK lab-confirmed cases is now around 30,000 lower than reported on 1 July 2020."
So that explains the mystery – but duplicate reporting at that level seems extraordinary! It does not support confidence in official statistics. An error of c.10% suggests a systemic flaw in the methodology being used. It also makes one wonder about the accuracy of some of the figures being quoted for elsewhere in the world.
I just heard the UK Prime Minister introduce a public information message about what would be considered when deciding to ease current measures to tackle the COVID-19 pandemic.
Two particular statements in the clip played gained my attention:
"All viruses, like normal 'flu, have a rate of infection. Scientists call this R. R is the average number of people one infected person passes the virus onto."
"In March, at its peak, R was around 3, which seems to be the natural rate for this virus."
Neither of these statements seemed strictly correct to me.
To make things clearer, let's call a spade, a fork
Surely the rate of infection is the number of people who are infected in a unit time period – say per day. R is something else – the reproduction number. Now, those working in the public understanding of science, just as in science education, have to seek an optimum level of simplification when communicating with non-experts. There is no point using complex language that will be unclear to people, and so likely lead to them disengage with the message. So, simplification may indeed be needed. But not such a degree of simplification that what we say no longer adequately represents the ideas we are trying to convey.
But the term 'reproduction number' is not some really obscure and inaccessible jargon – it uses words that most people are quite familiar and comfortable with.It does not seem any more technical and frightening that the term 'rate of infection'. Now I accept that perhaps the compound phrase 'reproduction number' is itself unfamiliar, whereas 'rate of infection' is more commonly heard. BUT rate of infection already has a meaning, a different one – so is it sensible to confuse matters by defining rate of infection with a new meaning inconsistent with the existing common usage?
This seems an odd way to promote public understanding of science to me. This is a bit like deciding that the term 'electrical field' may seem a bit too technical for an audience, so it will be a good idea to instead start calling it 'gravity' from now on, because people are used to that term. Or thinking that 'water of crystallisation' sounds obscure, so deciding to refer to the copper sulphate crystal incorporating 'ice cubes' when talking to non-experts because they know what ice cubes are (i.e., something other than molecules of water of crystallisation!).
So what is natural about rates of viral infection?
I was not sure precisely what a normal 'flu was (in relation to an abnormal 'flu, presumably?), but was more surprised to the reference to a virus having a natural rate of infection – even if this actually meant a natural reproduction number.
Will this not depend on the conditions in which the virus exists?* R will surely be very different in a population that is sparsely spread with small social group sizes than in a population that is largely living in extended family groups in overcrowded slums – so what is the natural environment for that virus?
We have reduced R by social distancing and increased hygiene measures. Are we to assume what is natural is the work and social (and hygiene) habits of the UK population as it was in February 2020, rather than now? If so, were the social conditions in the UK in 1920 or 1820 'unnatural'? So, I think the reference to the rate (actually R) being 3 is not a natural rate, but the R value contingent on the specific conditions of UK social and economic activity at a particular historical moment. To believe that the way WE live NOW (or, actually, two months ago) reflects what is natural seems a very anthropocentric notion of 'natural'.
I guess I am being pedantic (one of the few things I tend to be good at – and we all need to work to our strengths) but it seems to me that if you are going to commission a public health message at a time when the public understanding of science is actually a matter of life and death, then it is worth trying to get the science right.
* This seemed intuitively obvious, but I thought I ought to check. A quick web-search led to lots of different estimates of R (or R0, that is R whilst a population is all susceptible) presented as if there was a single right value (even if we do not know it precisely) that applied across different contexts globally. Hm. So, I was reassured to come across: "Firstly, R0 is not an intrinsic variable of the infectious agent, but it is calculated through at least three parameters: the duration of contagiousness; the likelihood of infection per contact between; and the contact rate, along with economical, social and environmental factors, that may vary among studies aimed to estimate the R0", Viceconte and Petrosillo, 2020, COVID-19 R0: Magic number or conundrum?, Infectious Disease Reports, 12(1).
One of the things I have noticed in recent news reports about the current pandemic is the tendency to justify our susceptibility to the COVID-19 coronavirus by praising the virus. It is an intelligent and sneaky foe, and so we have to outwit it.
But no, it is not. It is a virus. It's a tiny collection of nucleic material packaged in a way that it can get into the cells which contain the chemical resources required for the virus to replicate. It is well suited to this, but there is nothing intelligent about the behaviour. (The virus does not enter the cell to reproduce any more than an ice cube melts to become water; or a hot cup of coffee radiates energy to cool down; or a toddler trips over to graze its knee rather than because gravity acts on it.) The virus is not clever nor sneaky. That would suggest it can adapt its behaviour, after reflecting upon feedback from its interactions with the environment. It cannot. Over generations viruses change – but with a lot of variations that fail to replicate (the thick ones in the family?)
Yet any quick internet search finds references to the claimed intellectual capacities of these deadly foes. Now of course an internet search can find references to virtually anything – but I am referring to sites we might expect to be authoritative, or at least well-informed. And this is not just a matter of a hasty response to the current public health emergency as it is not just COVID 19, but, it seems, viruses generally that are considered intellectually superior.
Those smart little viruses
The site Vaccines Today has a headline in a posting from 2014, that "Viruses are 'smart', so we must be smarter", basing its claims on a lecture by Colin Russell, Royal Society University Research Fellow at Cambridge University. It reports that "Dr Russell says understanding how 'clever' viruses are can help us to outsmart them". (At least there are 'scare quotes' in some of these examples.)
An article from 2002 in an on-line journal has the title "The contest between a clever virus and a facultatively clever host". Now I have moaned about the standard of many new internet journals, but this is the Journal of the Royal Society of Medicine, and the article is in volume 95, so I think it is safe to apply the descriptor 'well-established' to this journal.
A headline in Science news for Students (published by Society for Science & the Public) from 2016 reads "Sneaky! Virus sickens plants, but helps them multiply". I am sure it would not take long to find many other examples. An article in Science refers to a "nasty flu virus".
Sneaky viruses
COVID-19 is a sneaky virus according to a doctor writing in the Annals of Internal Medicine. Quite a few viruses seem to be sneaky – the the human papillomavirus is according to an article in the American Journal of Bioethics. The World Health Organisation considers that a virus that causes swine fever, H1N1, is sneaky according to an article in Systematic Reviews in Pharmacy, something also reported by the BMJ.
There are many references in the literature to clever viruses, such as Epstein‐Barr virus according to a piece in the American Journal of Transplantation. The Hepatitis C virus is clever according to an article in Clinical Therapeutics.
Science communication as making the unfamiliar, familiar
Science communication is a bit like teaching in that the purpose of communication is often to be informative (rather than say, social cohesion, like a lot of everyday conversation {and, by the way,it was another beautiful day here in Cambridgeshire today, blue sky – was it nice where you are?}) and indeed to make the unfamiliar, familiar. Sometimes we can make the unfamiliar familiar by showing people the unfamiliar and pointing it out. 'This is a conical flask'. Often, however, we cannot do that – it is hard to show someone hyperconjugation or hysteresis or a virus specimen. Then we resort to using what is familiar, and employing the usual teacher tricks of metaphor, analogy, simile, modelling, graphics, and so forth. What is familiar to us all is human behaviour, so personification is a common technique. What the virus is doing, we might suggest, is hijacking the cell's biochemical machinery, as if it is a carefully planned criminal operation.
Strong anthropomorphism and dead metaphors
This is fine as far as it goes – that is, if we use such techniques as initial pedagogic steps, as starting points to develop scientific understanding. But often the subsequent stage does not happen. Perhaps that is why there are so many dead metaphors in the language – words introduced as metaphors, which over time have simple come to be take on a new literal meaning. Science does its fair share of borrowing – as with charge (when filling a musket or canon). Dead metaphors are dead (that is metaphorical, of course, they were never actually alive) because we simply fail to notice them as metaphors any more.
There are probably just as many references to 'clever viruses' referring to computer viruses as to microbes – which is interesting as computer viruses were once only viruses metaphorically, but are now accepted as being another type of virus. They have become viruses by custom and practice, and social agreement.
Whoever decided to first refer to the covalent bond in terms of sharing presumably did not mean this in the usual social sense, but the term has stuck. The problem in education (and so, presumably, public communication of science) is that once people think they have an understanding, an explanation that works for them, they will no longer seek a more scientific explanation.
So if the teacher suggests an atom is looking for another electron (a weak form of anthropomorphism, clearly not meant to be taken too seriously – atoms are not entities able to look for anything) then there is a risk that students think they know what is going on, and so never seek any further explanation. Weak anthropomorphism becomes strong anthropomorphism: the atom (or virus) behaves like a person because it has needs and desires just like anyone else.
Perhaps in our current situation this is not that important – the public health emergency is a more urgent issue than the public understanding of the science. But it does matter in the long term. Viruses are not clever – they have evolved over billions of years, and a great many less successful iterations are no longer with us. The reason it matters is because evolution is often not well understood.
As an article in Evolution News and Science Today (a title that surely suggests a serious science periodical about evolution) tells us again that "Viruses are, to all appearances, very clever little machines" and asks "do they give evidence of intelligent design" (that is, rather than Darwinian natural selection, do they show evidence of having an intelligent designer?) After exploring some serious aspects of the science of viruses, the article concludes: "So it seems that viruses are intelligently designed" – that is, a position at odds with the scientific understanding that is virtually a consensus view based on current knowledge. Canonical science suggests that natural processes are able to explain evolution. But these viruses are so clever they must surely have been designed (Borg technology, perhaps?)
This is why I worry when I hear that viruses are these intelligent, deliberate agents that are our foes in some form of biological warfare. It is a dangerous way of thinking. So, I'm concerned when I read, for example, that the cytomegalovirus is not just a clever virus but a very clever virus. Indeed, according to an article in Cell Host & Microbe "CMV is a very clever virus that knows more about the host immune system and cell biology than we do". Hm.
1. The subheading was amended on 4th October 2021, after it was quite rightly pointed out to me that the original version, "COVID-19 is not a clever or sneaky virus (but it is not dumb either)", incorrectly conflated the disease with the virus.
