You know when you’re cooking a packet of Maggi noodles in a saucepan, and you haven’t used enough water or don’t move the stuff soon enough from the pan to a plate once it’s done cooking, and you’re basically left with a hot lump of maida stuck to the bottom? That’s 2020. When you cook Maggi right, right up to mixing in a stick of butter at the end, you get a flavourful, well-lubricated, springy mass of strings that’s a pleasure to eat at the end of a long day. Once in a while you stick a fork into the plate and pull up a particularly long noodle, and you relish sucking it into your mouth from start to finish, with the masala dripping off at the end. That was probably many other years – when you had a strong sense of time moving from one event to the next, a sense of progression that helps you recall chronologies even long after you’ve forgotten what happened in March and what in September. For example, 2015 in my mind is cleanly divided into two parts – before May 11 and after May 11 – and memories of little personal accomplishments from that time are backgrounded by whether The Wire existed at the time. If it did, then I know the accomplishment happened after May 11. The Wire‘s birth effectively became an inflection in time that cut a little notch in the great noodle of 2015, a reference mark that created a before and an after. 2020 had none of this. It forsook all arrows of time; it wasn’t linear in any sense, not even non-linear in the sense of being exponential or logarithmic. It was practically anti-linear. Causality became a joke as the pandemic and its attendant restrictions on society fucked with the mind’s ability to tell one day apart from the next. So many of us beheld the world from our windows or balconies, although it wasn’t as if the world itself moved on without us. We weren’t there to world the world. Or maybe we were, but our collective grief at being imprisoned, literally and otherwise, seemed to be able to reshape our neighbourhoods, our surroundings, our shared cosmologies even and infused the fabrics of our every day with a cynical dye that we know won’t come off easily. Many of our lived experiences carried an awful symmetry like the circular one of a bangle, or a CD. How do you orient it? How do you say which way is up, or left, just by looking at it? You can’t. In the parlance of Euclidean geometry, 2020 was just as non-orientable. There was no before and after. Even our universe isn’t as bad: despite the maddening nature of the flatness problem, and the even more maddening fact of Earth’s asymptotically infinite loneliness, the universe is nearly flat. You’d have to travel trillions upon trillions of light-years in any direction before you have any chance of venturing into your past, and even then only because our instruments and our sciences aren’t accurate enough to assert, with complete certainty, that the universe is entirely flat and that your past will always lie in the causal history of your future. 2020 was, however, a singularity – an entrapment of reality within a glass bubble in which time flowed in an orbit around the centre, in perpetual free-fall and at the same time managing to get nowhere really. You can forget teasing out individual noodles from the hot lump on your plate because it’s really a black hole, probably something worse for shunning any of the mysteries that surround the microscopic structure of black holes in favour of maida, that great agent of constipation. As you stare at it, you could wait for its effects to evaporate; you could throw more crap into it in the hopes of destabilising it, like pushing yourself to the brink of nihilism that Thucydides noticed among the epidemic-stricken people of Athens more than two millennia ago; or you could figure out ingenious ways à la Penrose to get something good out of it. If you figure this out, please let the rest of us know. And until then, good luck with your Maggi.
pandemic
In conversation with Sree Srinivasan
On May 1, I was hosted on a webinar by the American journalist Sree Srinivasan, along with Anna Isaac of The News Minute and Arunabh Saikia of Scroll.in. As part of his daily show on the COVID-19 crisis, hosted by Scroll.in, Srinivasan hosts a few people working in different areas, and they all chat about what they’re doing and how they’re dealing with everything that’s going on for about an hour. However, our episode, the 50th of the series, was a double feature: the first 60 minutes was a conversation among us journalists, and for the next 50 minutes or so, Srinivasan had on Aseem Chhabra to discuss the lives and work of Irrfan Khan and Rishi Kapoor, who had passed away a few days earlier. The full video is available to view here as well as is embedded below.
I also transcribed the portion of the video where I spoke for two reasons. First, because I’d like to remember what I said, and writing helps me do that. Second, I’m a lousy speaker because I constantly lose my train of thought, and often swallow words that I really should have spoken out loud, often rendering what I’m saying difficult to piece together. So by preparing a transcript, pasted below, I can both clarify what I meant in the video as well as remember what I thought, not just what I said.
How would you grade Indian journalism at the moment, in these last two months, in terms of coverage of the COVID-19 pandemic?
The mainstream English press has been doing okay, I guess, but even then to paint it all with the same brush is very difficult because there are also very different stories to cover at a time like this. For example, many social and political issues are being covered well by specific publications. Some others are addressing different aspects of this.
In fact, if I had to pick out one aspect that I could say we’re not doing enough about is in terms of the science itself. The coronavirus outbreak is a crisis, and a large part of it is rooted in health issues, in scientific issues – much like climate change, antimicrobial resistance, etc. A lot of journalists are doing a good job of covering how this outbreak has impacted our society, our economy, etc. but there’s actually very little going into understanding how the virus really works or how epidemiologists or virologists do what they do.
One easy example is this business of testing kits. There’s a lot of controversy now about the serological tests that ICMR procured, probably at inflated prices, are not very accurate. The thing is, whenever you’re in a crisis like this and somebody’s rapidly developing kits – testing kits or ventilators or anything like that – there is always going to be a higher error rate.
Also, no test is 100% perfect. Every test is error-prone, including false positives and false negatives. But in this rush to make sure everything is covered, most of what is being elided – at least among organisations that are taking the trouble – is the science itself [of how tests are developed, why the errors are unavoidable, etc.]. That’s a significant blindspot.
But on the positive side of it, there is also a heightened awareness now of the need to understand how science works. We’ve been seeing this at The Wire, I don’t know if it applies to other organisations: there is a sort of demand… the engagement with science stories has increased. We’re using this opportunity to push out these stories, but the thing is we’re also hoping that once this pandemic ends and the crisis passes, this appreciation for science will continue, especially among journalists.
Apart from this, I don’t want to attempt any grading.
What is your reaction to the value of data journalism at this time?
The value of charts has been great, and there are lots of charts out there right now, projecting or contrasting different data-points. Just a few days ago we published a piece with something like 60 charts discussing the different rates of testing and positivity in all of India’s states.
But the problem with these charts – and there is a problem, that needs to be acknowledged – is that they tend to focus the conversation on the data itself. The issue with that is that they miss ground realities. [I’m not accusing the charts of stealing the attention so much as giving the impression, or supporting the takeaway, that the numbers being shown are all that matter.]
While data journalism is very important, especially in terms of bringing sense to the lots of numbers floating about, [it also feeds problematic narratives about how numbers are all that matter.] I recently watched this short clip on Twitter in which a bunch of people were crowded at a quarantine centre in Allahabad fighting for food. There was very little food available and I think they were daily-wage labourers. I think there is a lot being said about the value and virtues of data journalism and visualisations but I don’t think there is much being said at all – but definitely needs to be – about how data can’t ever describe the full picture.
Especially in India, and we’ve seen this recently with the implementation of the Aadhaar programme as well: even if your success rate with something is as high as 99%, 1% of India’s population is still millions of people [and it’s no coincidence that they already belong to the margins of society.] And this is something I’ve thus far not seen data stories capture. Numbers are good to address the big picture but they’ve been effectively counterproductive during this crisis in terms of distracting from the ground stories. [So even the best charts can only become the best stories if they’re complemented with some reporting.]
The Wire compiled a list of books to read during the lockdown, with recommendations by its staff. You recommended Dune by Frank Herbert. Why?
Dune to me was an obvious choice for [three] reasons. One is that Dune is set on a planet where you already see life in extremes, especially with the tribe of the Fremen, who play an important role in the plot. What really stayed with me about that book was its sort of mystic environmentalism, about how humans and nature are connected. The book explores this in a long-winded way, but that’s something we’ve seen a lot of these days in terms of zoonoses – [pathogens] that jump from animals to humans.
There’s also a lot of chatter these days about killing bats because they host coronaviruses. But all of that is rubbish. Humans are very deeply responsible for this crisis we’ve brought on ourselves in many ways.
This also alludes to what Anna Isaac mentioned earlier: what do you mean by normal? Yes, life probably will return to normal in India’s green zones next week, but the thing is, once this crisis ends, there’s still climate change, antimicrobial resistance and environmental degradation awaiting us that will bring on more epidemics and pandemics. Ecologists who have written for us have discussed this concept called ‘One Health’, where you don’t just discuss your health in terms of your body or your immediate environment but also in terms of your wider environment – at the ecosystem level.
Dune I think is a really good example of sci-fi that captures such an idea. And Dune is also special because it’s sci-fi, which helps us escape from our reality better, because sci-fi is both like and unlike.
The third reason it’s special is because the movie adaptation is coming out later this year, so it’s good to be ready. 😀
[When asked for closing remarks…]
When I started out being a journalist, I was quite pissed off that there wasn’t much going on in terms of the science coverage in India. So my favourite stories to write in the last eight years I’ve been a journalist have been about making a strong point about a lot of knowledge being out there in the world that seems like it’s not of immediate benefit or use [but is knowledge – and therefore worth knowing – nonetheless]. That’s how I started off being a science journalist.
My forte is writing about high-energy physics and astrophysics. Those are the stories I’ve really enjoyed covering and that’s the sort of thing that’s also lacking at the moment in the Indian journalism landscape – and that’s also the sort of coverage of science news we wanted to bring into the pandemic.
Here, I should mention that The Wire is trying to build what we hope will be the country’s first fully reader-funded, independent science news website. We launched it in February. We really want to put something together like the Scientific American of India. You can support that by donating at thewire.in/support. This is really a plea to support us to go after stories that we haven’t seen many others cover in India at the moment.
Right now, most stories are about the coronavirus outbreak but as we go ahead, we’d like to focus more and more on two areas: science/society and pure research, stuff that we’re finding out but not talking about probably because we think it’s of no use to us [but really that’s true only because we haven’t zoomed out enough].
On India’s path to community transmission
There’s a virus out there among many, many viruses that’s caught the world’s attention. This virus came into existence somewhere else, it doesn’t matter where, and developed a mutation at some point that allowed it to do what it needs to do inside the body of one specific kind of animal: Homo sapiens. And once it enters one Homo sapiens, it takes advantage of its new surroundings to produce more copies of itself. Then, its offspring wait for the animal to cough or sneeze – acts originally designed to expel irritating substances – to exit their current home and hopefully enter a new one. There, these viruses go through the same cycle of reproduction and expulsion, and so forth.
This way, the virus has infected over 210,000 people in the last hundred days or so. Some people’s bodies have been so invaded by the virus that their immune systems weren’t able to fight it off, and they – nearly 9,000 of them – succumbed to it.
Thus far, the virus has reportedly invaded the bodies of at least 282 people in India. There’s no telling how the virus will dissipate through the rest of the population – if it needs to – except by catching people who have the virus early, separating them from the rest of the population for long enough to ensure they don’t have and/or transmit the virus or, if they do, providing additional treatment, and finally reintegrating them with the general population.
But as the virus spreads among more and more people, it’s going to become harder and harder to tell how every single new patient got their particular infection. Ultimately, a situation is going to arise wherein too many people have the virus for public-health officials to be able to say how exactly the virus got to them. The WHO calls this phase ‘community transmission’.
India is a country of over 1.3 billion people, and is currently on the cusp of what the Indian Council of Medical Research (ICMR) has called ‘stage 3’ – the advent of community transmission. It’s impossible to expect a developing country as big and as densely populated as India to begin testing all 1.3 billion Indians for the virus as soon as there is news of the virus having entered the national border because the resource cost required to undertake such an exercise is extremely high, well beyond what India can generally afford. However, this doesn’t mean Indians are screwed.
Instead of testing every Indian, ICMR took a different route. Consider the following example: there’s a population of red flecks randomly interspersed with yellow flecks. You need to choose a small subset of flecks from this grid (shown below) such that checking for the number of yellow flecks in the subset gives you a reliable idea of the number of yellow flecks overall.
The ideal subset would be the whole set, of course, so there is one more catch: you have a fixed amount of money to figure out the correct answer (as well as for a bunch of other activities), so it’s in your best interests to keep the subset as small as possible. In effect, you need to balance the tension between two important demands: getting to a more accurate answer while spending less.
Similarly, ICMR assumed that the virus is randomly distributed in the Indian population, and decided to divide the population into different groups, for example by their relative proximity to a testing centre. That is, each testing centre would correspond to the group of all people who live closer to that testing centre than any other. Then, ICMR would pick a certain number of people from each group, collect their nasal and throat samples and send it to the corresponding labs for tests.
Say group size equals 100. For a Bernoulli random variable with unknown probability p, if no events occur in n independent trials, the maximum value of p (at 95% confidence) is approximately 3/n. In our case, n = 100 and p at 95% confidence is 3/100, which is 3%. Since this is the upper bound, it means less than 3% of the population has the ‘event’ which didn’t occur in n trials – which in our case is the event of ‘testing positive’. Do note, this is what is safe to say; it’s not what may actually be happening on the ground. So by increasing the sample size n as much as possible, ICMR can ascertain with higher and higher confidence as to whether the corresponding group has community transmission or not.
Thus far, ICMR has said there is no community transmission in India based on these calculations. Independent experts have been reluctant to take its word, however, because while ICMR has publicised what the sample size and the number of positives are, there is very little information about two other things.
First: we don’t know how ICMR selected the samples that it did for testing. While the virus’s distribution in the population can be considered to be random, especially if community transmission is said to have commenced, the selection of samples needs to have an underlying logic. What is that logic?
Second: we don’t know the group sizes. It’s important for the sample size to be proportionate to the group size. So without knowing what the group size underlying each sample is, it becomes impossible to tell if ICMR is doing its job right.
On March 17, one ICMR scientist said that some testing centres had admitted fewer people with COVID-19-like symptoms and the source of whose infections was unknown (i.e. community transmission) than the size of the sample chosen from their corresponding group. She was suggesting that ICMR’s choice of samples from each group was large enough to not overlook community transmission. To translate in terms of the example above: she was saying ICMR’s subset size was big enough to catch at least one yellow fleck – and didn’t.
As it happens, on March 20, ICMR announced that it would begin testing for a potential type of community-transmission cases even though its sampling exercise had produced 1,020 negative results in 1,020 samples (distributed across 51 testing centres).
The reasons for this are yet unclear but suggests that ICMR suspects there is community transmission of the virus in the country even though its methods – which ICMR has always stood by – haven’t found evidence of such transmission. This in turn prompts the following question: why not test for all types of community transmission? The answer is the same as before: ICMR has limited resources but at the same time has been tasked with discovering how many yellow flecks are there in the total population.
The virus is not an intelligent creature. In fact, it’s extremely primitive. Each virus is in its essence a packet of chemical reactions, and when each reaction happens depends on a combination of internal and external conditions. Other than this, the virus does not harbour any intentions or aspirations. It simply responds to stimuli that it cannot manipulate or affect in any way.
The overarching implication is that beyond how good the virus is at spreading from person to person, a pandemic is what it is because of human interactions, and because of human adaptation and mitigation systems. And as more and more people get infected, and their groups verge towards the WHO’s definition of ‘community transmission’, the virus’s path through the population becomes less and less obvious, but at the same time a greater depth of transmission opens the path to better epidemiological modelling.
When such transmission happens in a country like India, the body responsible for keeping the people safe – whether the Union health ministry, ICMR or any other entity – faces the same challenge that ICMR did. This is also why direct comparisons of India’s and South Korea’s testing strategies are difficult to justify, especially of the number of people tested per million: India has nearly 26-times as many people but spends 11.5-times less on healthcare per capita.
At the same time, ICMR isn’t making it easy for anyone – least of all itself – when it doesn’t communicate properly, and leaves itself open to criticism, which in turn chips away at its authority and trustworthiness in a time as testing as this. Demonetisation taught us very well that a strategy is only as good as its implementation.
But on the flip side, it wouldn’t be amiss to make a distinction here: between testing enough to get a sense of the virus’s prevalence in the population – in order to guide further action and policy – and the fact that the low expenditure on public healthcare is always going to incentivise India to skew towards a sampling strategy instead of an alternative that requires mass-testing. ICMR and the Union health ministry haven’t inspired confidence on the first count but it’s important to ensure criticism of the former doesn’t spillover into criticism of the latter as well.
Anyway, the corresponding sampling strategy is going to have to be based on a logic. Why? Because while the resources for the virus to spread exist abundantly in nature (in the form of humans), the human response to containing the spread requires resources that humans find hard to get. Against the background of this disparity, sampling, testing and treatment logics – such as Italy’s brutal triaging policy – help us choose better sampling strategies; predict approximately how many people will need to be quarantined in the near future; prepare our medical supplies; recruit the requisite number of health workers; stockpile important drugs; prepare for economic losses; issue rules of social conduct for the people; and so forth.
A logic could even help anticipate (or perpetuate, depending on your appetite for cynicism) ‘leakages’ arising due to, say, caste or class issues. Think of it like trying to draw a circle with only straight lines of a fixed length: with 200 strokes, you could technically draw a polygon with 200 sides that looks approximately like a circle – but it will still have some discernible edges and vertices that won’t exactly map on a circle, leaving a small part of the latter out. Similarly, using a properly designed technique that can predict which person might get infected and who might not can still catch a large number of people – but the technique won’t catch all of them.
One obvious way to significantly improve the technique’s efficacy as it stands is to account for the fact that more than half of all Indians are treated at private hospitals whereas you can be tested for COVID-19 only at a government facility, and not all VRDLs receive samples from all private hospitals in their respective areas.
Ultimately, the officials who devise the logics must be expected to justify how the combination of all logics can – even if only on paper – uncover most, if not all, cases of the virus’s infection in India.
When deGrasse Tyson pulled a Pinker
Since this post was published, an upward-edited version has been republished on The Wire.
Twitter is, among other things, that place on the internet where people fight over the tips of icebergs. There is often the presumption that what ends up on Twitter has been thought through and carefully condensed to fit into the arbitrary 280-character limit, but then again, there is also ample evidence to the contrary: many of its users get caught up in the tips that they think that’s all there is. These possibilities cast a dark shadow on Twitter’s claim to represent reality. More often than not, it is its own world, and has nothing to do with the world around it except that it collects the worst opinions from there unto itself. Last night Neil deGrasse Tyson joined in:
deGrasse Tyson has been one of those people calling attention to how what we’re reading about science on the web is often just a pinhole-sized snapshot of a more glorious thing lying hidden from view – just like an iceberg. Reading him, you’d think that when he says stuff about astronomy and cosmology, he’s not losing any context and that he’s simply presenting what he can in 280 characters on the microblogging platform. Then again, the tweet above appears to be evidence to the contrary: a tweet that seems to presume to contain all the arguments and histories of the five issues it mentions in (exactly) 280 characters and which, in one fell swoop, dismisses all the outrage of the political left.
It certainly gets my goat that the left has been painted as anti-fact and that the right is guided by righteous logic when in fact this is the result of the deeper dismissal of the validity of the social sciences and humanities, which have served throughout history to make facts right and workable in their various contexts. The right has appropriated the importance of quantitative measures – and that alone – and brandishes it like a torch even as the world burns below.
For example, As Alex Gladstein, chief strategy officer at the Human Rights Foundation and VP of strategy of the Oslo Freedom Forum, recently wrote in the New Republic, “dictators love development statistics” because “they’re an easily faked way to score international points”. Excerpt:
From the development initiatives of Jeffrey Sachs and Bill Gates, to Tony Blair’s despotic partnerships or Tom Friedman championing Chinese autocracy in The New York Times, the last two decades have seen political concerns repeatedly sidelined by development statistics. The classic defence of dictatorship is that without the messy constraints of free elections, free press, and free protests, autocrats can quickly tear down old cities to build efficient new ones, dam rivers to provide electricity, and lift millions out of poverty. The problem with using statistics to sing the praises of autocracy is that collecting verifiable data inside closed societies is nearly impossible. From Ethiopia to Kazakhstan, the data that “proves” that an authoritarian regime is doing good is often produced by that very same regime.
And by attacking the validity of the social sciences and humanities, the left has effectively had the rug pulled out from under its feet, and the intellectual purpose of its existence delegitimised. We’re still talking about deGrasse Tyson’s tweet because, in his view, it seems facts are all there is, that data alone should settle the debate but that emotions are unnecessarily stretching it out. Thousands of other tweets swirl around it in response, telling him that he’s right even though the left will eat him alive for it.
You see, the right is the data and the left is the “soft science”, which – Quillette would have you believe – might as well be a synonym for ‘non-data’ and nonsense. And the only challenge the right is prepared to brook, or pretends to be prepared to brook, is numbers: those symbols that work one digit at a time, one character at a time, but which putatively contain everything you need to know about something, no further explanation required. This exaltation of mathematical logic, and Boolean algebra and lambda calculus, we’ve already seen before in the revanchist politics of the ‘New Atheist’ movement, and perhaps more recently when a Silicon Valley dude announced he had rediscovered history.
Anyway, right now, I, nor anyone else, don’t have – shouldn’t have – just numbers to rebut deGrasse Tyson’s argument because that’s not all there is. But I personally feel compelled to try to come up with something concise if only to see what I come up with, and it’s this: deGrasse Tyson is pulling a Steven Pinker*. The first three numbers on the list in his tweet have been on a downward trend for quite some time thanks to a) pharmaceutical innovation, b) increasing awareness of and sensitivity about what those issues actually stand for, and c) policies that open new avenues of treatment and legislation that deters casualties. (However, trends in disease mortality are currently being ‘disrupted’ by the rise of antimicrobial resistance, climate change and – lest we forget – the lopsided effects of these stressors on already-stressed economies.) The fourth number, despite being about accidents and not wilful acts of malice actuated by the availability of guns, has also been on the decline (except for a relatively small spike in absolute numbers in 2016):
Pinker is relevant here because of his disingenuous conclusion that the world is becoming a better place, and that cognitive biases are to blame for the left’s unwillingness to acknowledge that. His analyses are problematic because, especially in the domain of environmental action, they provide snapshots of the full picture – as if he’s content to work with the tips of icebergs. For example, consider the following excerpt from a rebuttal by George Monbiot to Pinker’s claim that countries become cleaner as they get richer, in the latter’s 2018 book Enlightenment Now:
Pinker suggests that the environmental impact of nations follows the same trajectory, claiming that the “environmental Kuznets Curve” shows they become cleaner as they get richer. To support this point, he compares Nordic countries with Afghanistan and Bangladesh. It is true that they do better on indicators such as air and water quality, as long as you disregard their impacts overseas. But when you look at the whole picture, including carbon emissions, you discover the opposite. The ecological footprints of Afghanistan and Bangladesh (namely the area required to provide the resources they use) are, respectively, 0.9 and 0.7 hectares per person. Norway’s is 5.8, Sweden’s is 6.5 and Finland, that paragon of environmental virtue, comes in at 6.7.
David Bell, a historian of science, took aim at a different portion of the book, in which Pinker appeared to be blind to the efforts of people who had fought, struggled and bent the arc of justice to serve them, instead labouring with the presumption that people should stop complaining because life has just automatically become better:
Did Enlightenment forms of reasoning and scientific inquiry lie behind modern biological racism and eugenics? … Not at all, Pinker assures us. That was just a matter of bad science. … But Pinker largely fails to deal with the inconvenient fact that, at the time, it was not so obviously bad science. The defenders of these repellent theories, used to justify manifold forms of oppression, were published in scientific journals and appealed to the same standards of reason and utility upheld by Pinker. “Science” did not by itself inevitably beget these theories … The later disproving of these theories did not just come about because better science prevailed over worse science. It came about as well because of the moral and political activism that forced scientists to question data and conclusions they had largely taken for granted.
deGrasse Tyson, it would seem, has fallen prey to a similar bout of snapshotism: he has cherry-picked one moment in history where the number of gun-deaths (per 48 hours) is lower than the number of deaths due to medical errors, flu, suicide and car accidents, all shorn of the now-denounced context that humankind and all its broken systems are trying to improve them.
What his tweet, which presumes to be the entire iceberg in some people’s worldview when in fact it is only the tip, fails to say is that America is doing little to nothing to prevent more gun deaths from happening, and in fact whose political establishment has often condoned the deleterious cultures of white nationalism and “involuntary celibacy” that powers it. If deGrasse Tyson had compared the effects of gun deaths on the conscience of a nation with the global failure to make polluters pay, with rising income inequality, with the decreasing resilience to pandemics in the developing world or with nationalism+xenophobia, he’d have been closer to the truth of it: We don’t have to be ashamed of deaths due to medical errors, fly, suicide and car accidents, but we do have to be ashamed of mass murders.
*deGrasseTyson also falls prey to a bit of the “poverty first, Moon/Mars next” fallacy in assuming that if there are multiple problems, they must be solved one after another even if the resources exist for us to tackle some or all of them in parallel.