COVID-19 pandemic – Page 2

The Government Project

Considering how much the Government of India has missed anticipating – the rise of a second wave of COVID-19 infections, the crippling medical oxygen shortage, the circulation of new variants of concern – I have been wondering about why we assemble giant institutions like governments: among other things, they are to weather uncertainty as best as our resources and constitutional moralities will allow. Does this mean bigger the institution, the farther into the future it will be able to see? (I’m assuming here a heuristic that we normally are able to see, say, a day into the future with 51% uncertainty – slightly better than chance – for each event in this period.)

Imagine behemoth structures like the revamped Central Vista in New Delhi and other stonier buildings in other cities and towns, the tentacles of state control dictating terms in every conceivable niche of daily life, and a prodigious bureaucracy manifested as tens of thousands of civil servants most of whom do nothing more than play musical chairs with The Paperwork.

Can such a super-institution see farther into the future? It should be able to, I’d expect, considering the future – in one telling – is mostly history filtered through our knowledge, imagination, priorities and memories in the present. A larger government should be able to achieve this feat by amassing the talents of more people in its employ, labouring in more and more fields of study and experiment, effectively shining millions of tiny torchlights into the great dark of what’s to come.

Imagine one day that the Super Government’s structures grow so big, so vast that all the ministers determine to float it off into space, to give it as much room as it needs to expand, so that it may perform its mysterious duties better – something like the City of a Thousand Planets.

The people of Earth watch as the extraterrestrial body grows bigger and bigger, heavier and heavier. It attracts the attention of aliens, who are bemused and write in their notebooks: “One could, in principle, imagine ‘creatures’ that are far larger. If we draw on Landauer’s principle describing the minimum energy for computation, and if we assume that the energy resources of an ultra-massive, ultra-slothful, multi-cellular organism are devoted only to slowly reproducing its cells, we find that problems of mechanical support outstrip heat transport as the ultimate limiting factor to growth. At these scales, though, it becomes unclear what such a creature would do, or how it might have evolved.”

One day, after many years of attaching thousands of additional rooms, corridors, cabinets and canteens to its corse, the government emits a gigantic creaking sound, and collapses into a black hole. On the outside, black holes are dull: they just pull things towards them. That the pulled things undergo mind-boggling distortions and eventual disintegration is a triviality. The fun part is what happens on the inside – where spacetime, instead of being an infinite fabric, is curved in on itself. Here, time moves sideways, perpendicular to the direction in which it flows on the outside, in a state of “perpetual freefall”. The torch-wielding scientists, managers, IAS officers, teachers, thinkers are all trapped on the inner surface of a relentless sphere, running round and round, shining their lights to look not into the actual future but to find their way within the government itself.

None of them can turn around to see who it is that’s chasing them, or whom they’re chasing. The future is lost to them. Their knowledge of history is only marginally better: they have books to tell them what happened, according to a few historians at one point of time; they can’t know what the future can teach us about history. And what they already know they constantly mix and remix until, someday, like the progeny of generations of incest, what emerges is a disgusting object of fascination.

The government project is complete: it is so big that it can no longer see past itself.

Exporting risk

I’m torn between admitting that our cynicism about scientists’ solutions for the pandemic is warranted and the palliative effects of reading this Reuters report about seemingly nothing more than the benevolence of richer nations not wasting their vaccine doses:

Apart from all the other transgressions – rather business as usual practices – that have transpired thus far, this is one more testimony to all those instances of insisting “we’re all in this together” being just platitudes uttered to move things along. And if it weren’t enough already that poorer nations must make do with the leftovers of their richer counterparts that ordered not as many doses as they needed but as many as would reassure their egos (a form of pseudoscience not new to the western world), the doses they’re going to give away have been rejected for fear of leading to rare but life-threatening blood clots. To end the pandemic, what kills you can be given away?

COVID-19, due process and an SNR problem

At a press conference streamed live on March 18, the head of the European Medicines Agency (EMA) announced that the body – which serves as the European Union’s drug and vaccine regulator – had concluded that the AstraZeneca COVID-19 vaccine was not associated with unusual blood clots that some vaccine recipients had reported in multiple countries. The pronouncement marked yet another twist in the roller-coaster ride the embattled shot has experienced over the past few months. But it has also left bioethicists debating how it is that governments should respond to a perceived crisis over vaccines during a pandemic.

Over the last two weeks or so, a fierce debate raged after a relatively small subset of people who had received doses complained of developing blood clots related to potentially life-threatening conditions. AstraZeneca, a British-Swedish company, didn’t respond to the concerns at first even though the EMA and the WHO continued to hold their ground: that the vaccine’s benefits outweighed its risks, so people should continue to take it. However, a string of national governments, including those of Germany, France and Spain, responded by pausing its rollout while scientists assessed the risks of receiving the vaccine.

Aside from allegations that AstraZeneca tried to dress up a significant mistake during its clinical trials of the vaccine as a ‘discovery’ and cherry-picked data from the trials to have the shot approved in different countries, the company has also been grappling with the fact that the shot was less efficacious than is ideal against infections by new, more contagious variants of the novel coronavirus.

But at the same time, the AstraZeneca vaccine is also one of the more affordable ones that scientists around the world have developed to quell the COVID-19 pandemic – more so than the Pfizer and Moderna mRNA vaccines. AstraZeneca’s candidate is also easier to store and transport, and is therefore in high demand in developing and under-developed nations around the world. Its doses are being manufactured by two companies, in India and South Korea, although geographically asymmetric demand has forced an accelerating vaccination drive in one country to come at the cost of deceleration in another.

Shot in the arm

Now that the EMA has reached its verdict, most of the 20 countries who had hit the pause button have announced that they will resume use of the vaccine. However, the incident has spotlighted a not-unlikely problem with the global vaccination campaign, and which could recur if scientists, ethicists, medical workers and government officials don’t get together to decide where they can draw the line between abundant precaution and harm.

In fact, there are two versions of this problem: one in countries that have a functional surveillance system that responds to adverse events following immunisation (AEFIs) and one in countries that don’t. An example of the former is Germany, which, according to the New York Times, decided to pause the rollout based on seven reports of rare blood clots from a pool of 1.6 million recipients – a naïve incidence rate of 0.0004375%. But as rare disorders go, this isn’t a negligible figure.

One component of the post-AEFI response protocol is causality assessment, and one part of this is for experts to check if certain purported side-effects are clustered in time and then to compare those to the illness’s time distribution for a long time before the pandemic. It’s possible that such clustering could have prompted health officials in Germany and other countries to suspend the rollout.

The Times quoted a German health ministry statement saying, “The state provides the vaccine and therefore has special duties of care”. These care considerations include what the ministry understands to be the purpose of the rollout (to reduce deaths? To keep as many people healthy as possible?) read together with the fact that vaccines are like drugs except in one important way: they’re given to healthy – and not to sick – people. To quote Stephan Lewandowsky, an expert of risk communication at the University of Bristol, from Science:

“You’ve got to keep the public on board. And if the public is risk-averse, as it is in Europe … it may have been the right decision to stop, examine this carefully and then say, ‘The evidence, when considered transnationally, clearly indicates it is safe to go forward.’”

On the other hand is the simpler and opposing calculus of how many people didn’t develop blood clots after taking the vaccine, how many more people the virus is likely to have infected in the time the state withheld the vaccine, how many of them were at greater risk of developing complications due to COVID-19 – topped off by the fact of the vaccines being voluntary. On this side of the argument, the state’s carefulness is smothering, considering it’s using a top-down policy without accounting for local realities or the state’s citizens’ freedom to access or refuse the vaccine during a pandemic.

Ultimately there appears to be no one right answer, at least in a country where there’s a baseline level of trust that the decision-making process included a post-vaccination surveillance system that’s doing its job. Experts have also said governments should consider ‘mixed responses’ – like continuing rollouts while also continuing to examine the vaccines, given the possibility that a short-term review may have missed something a longer term exercise could find. One group of exerts in India has even offered a potential explanation.

The background rate

In countries where such a system doesn’t exist, or does but is broken, like India, there is actually one clear answer: to be transparent and accountable instead of opaque and intractable. For example, N.K. Arora, a member of India’s National COVID-19 Task Force, told The Hindu recently that while the body would consider post-vaccination data of AstraZeneca’s vaccine, it also believed the fraction of worrying cases to be “very, very low”. Herein lies the rub: how does it know?

As of early March, according to Arora, the Union health ministry had recorded “50-60” cases of AEFIs that may or may not be related to receiving either of the two vaccines in India’s drive, Covaxin and Covishield. (The latter is the name of AstraZeneca’s shot in India.) Reading this with Arora’s statements and some other facts of the case, four issues become pertinent.

First is the deceptively simple problem of the background rate. Journalist Priyanka Pulla’s tweets prompt multiple immediate concerns on this front. If India had reported 10 cases of disease X in 20 years, but 10 more cases show up within two weeks after receiving one dose of a vaccine, should we assume the vaccine caused them? No – but it’s a signal that we should check for the existence of a causal link.

Experts will need to answer a variety of questions here: How many people have disease X in India? How many people of a certain age-group and gender have disease X? How many people of different religious and/or ethnic groups have disease X? How many cases of disease X are we likely to have missed (considering disease-underreporting is a hallmark of Indian healthcare)? How many cases of disease X should we expect to find in the population being vaccinated in the absence of a vaccine? Do the 10 new cases, or any subset of them, have a common but invisible cause unrelated to the vaccine? Do we have the data for all these considerations?

Cornelia Betsch, a psychologist at the University of Erfurt, told Science that “most of the cases of rare blood disorders were among young women, the group where vaccine hesitancy already runs highest”. Can India confirm or deny that this trend is reflected in its domestic data as well? This seems doubtful. Sarah Iqbal reported for The Wire Science in September 2020 that “unequal access to health”, unequal exposure to potentially disease-causing situations, unequal representation in healthcare data and unequal understanding of diseases in non-cis-male bodies together already render statements like ‘women have better resistance to COVID-19’ ignorant at best. Being able to reliably determine and tackle sex-wise vaccine hesitancy seems like a tall order.

The second issue is easy to capture in one question, which also makes it harder to ignore: why hasn’t the government released reports or data about AEFIs in India’s COVID-19 vaccination drive after February 26, 2021?

On March 16, a group of 29 experts from around the country – including virologist T. Jacob John, who has worked with the Indian Council of Medical Research on seroprevalence surveys and has said skeptics of the Indian drug regulator’s Covaxin approval were “prejudiced against Indian science/product” – wrote to government officials asking for AEFI data. They said in their letter:

We note with concern that critical updates to the fact sheets recommended by the CDSCO’s Subject Expert Committee have not been issued, even though they are meant to provide additional guidance and clarify use of the vaccines in persons such as those with allergies, who are immunocompromised or using immunosuppressants, or using blood thinners/anticoagulants. There are gaps in AEFI investigations at the local level, affecting the quality of evidence submitted to State and National AEFI Committees who depend on these findings for making causality assessments. The National AEFI Committee also has a critical role in assessing cases that present as a cluster and to explore potential common pathways. In our letter dated January 31, 2021, we asked for details of all investigations into deaths and other serious AEFIs, as well as the minutes of AEFI monitoring committees, and details of all AEFI committee members and other experts overseeing the vaccine rollout. We have not received any response.

City of Omelas

The third issue is India’s compliance with AEFI protocols – which, when read together with Pulla’s investigation of Bharat Biotech’s response to a severe adverse event in its phase 3 trials for Covaxin, doesn’t inspire much confidence. For example, media reports suggest that medical workers around the country aren’t treating all post-vaccination complaints of ill-health, but especially deaths, on equal footing. “Currently, we are observing gaps in how serious adverse events are being investigated at the district level,” New Delhi-based health activist Malini Aisola told IndiaSpend on March 9. “In many instances local authorities have been quick to make public statements that there is no link to the vaccine, even before investigations and post mortem have taken place. In some cases there is a post mortem, in some cases there isn’t.”

Some news reports of people having died of heart-related issues at a point of time after taking Covishield also include quotes from doctors saying the victims were known to have heart ailments – as if to say their deaths were not related to the vaccine.

But in the early days of India’s COVID-19 epidemic, experts told The Wire that even when people with comorbidities, like impaired kidney function, died due to renal failure and tested positive for COVID-19 at the time of death, their passing could be excluded from the official deaths tally only if experts had made sure the two conditions were unrelated – and this is difficult. Having a life-threatening illness doesn’t automatically make it the cause of death, especially since COVID-19 is also known to affect or exacerbate some existing ailments, and vice versa.

Similarly, today, is the National AEFI Committee for the COVID-19 vaccination drive writing off deaths as being unrelated to the vaccine or are they being considered to be potential AEFIs? And is the committee deliberating on these possibilities before making a decision? The body needs to be transparent on this front a.s.a.p. – especially since the government has been gifting AstraZeneca’s shots to other countries and there’s a real possibility of it suppressing information about potential problems with the vaccine to secure its “can do no wrong” position.

Finally, there’s the ‘trolley problem’, as the Times also reported – an ethical dilemma that applies in India as well as other countries: if you do nothing, three people will get hit by a train and die; if you pull a lever, the train will switch tracks and kill one person. What do you do?

But in India specifically, this dilemma is modified by the fact that due process is missing; this changes the problem to one that finds better, more evocative expression in Ursula K. Le Guin’s short story The Ones Who Walk Away from Omelas (1973). Omelas is a fictitious place, like paradise on Earth, where everyone is happy and content. But by some magic, this is only possible if the city can keep a child absolutely miserable, wretched, with no hope of a better life whatsoever. The story ends by contemplating the fate of those who discover the city’s gory secret and decide to leave.

The child in distress is someone – even just one person – who has reported an AEFI that could be related to the vaccine they took. When due process plays truant, when a twisted magic that promises bliss in return for ignorance takes shape, would you walk away from Omelas? And can you freely blame those who hesitate about staying back? Because this is how vaccine hesitancy takes root.

The Wire
March 20, 2021

Anti-softening science for the state

The group of ministers (GoM) report on “government communication” has recommended that the government promote “soft topics” in the media like “yoga” and “tigers”. We can only speculate what this means, and that shouldn’t be hard. The overall spirit of the document is insecurity and paranoia, manifested as fantasies of reining in the country’s independent media into doing the government’s bidding. The promotion of “soft” stories is in line with this aspiration – “soft” here can only mean stories that don’t criticise the government, its actions or policies, and be like ‘harmless entertainment’ for a politically inert audience. It’s also no coincidence that the two examples on offer of such stories skirt the edges of health and environmental journalism; other examples are sure to include reports of scientific discoveries.

Science is closely related to the Indian state in many ways. The current government in particular, in power since 2014, has been promoting application-oriented R&D (a bias especially visible in budgetary allocations); encouraging ill-prepared research facilities to self-finance; privileging certain private interests (esp. the Reliance and Adani groups) vis-à-vis natural resources like coal, coastal zones and spectrum allocations; pillaging India’s ecological commons for industrialisation; promoting pseudoscience (which further disempowers those closer to society’s margins); interfering at universities by appointing vice-chancellors friendly to the ruling party (and if that doesn’t work, jailing students on ridiculous charges that include dissent); curtailing academic freedom; and hounding after scientists and institutions that threaten its preferred narratives.

With this in mind, it’s important for science journalism outlets and science journalists to not become complicit – inadvertently or otherwise – in the state project to “soften” science, and start reporting, if they aren’t already, on issues with a closer eye on their repercussions on the wider society. The idea that science journalism can or should be objective the way science is is nonsensical because the idea that science is an objective enterprise is nonsensical. The scientific method is a technique to obtain information about the natural universe while steadily subtracting the influence of human biases and other limitations. However, what scientists choose to study, how they design their studies and what is ultimately construed to be knowledge are all deeply human enterprises.

On top of this, science journalism is driven by journalists’ sense of good and bad: We write favourably about the former and argue against the latter. We write about some telescope unravelling a long-standing cosmogonic problem and also publish an article calling out homeopathy’s bullshit. We write a scientific paper that uses ingenious methods to prove its point and also call out Indian academia as an unsafe space for queer-trans people.

Some have advanced a defence that simply focusing on “good science” can inculcate in the audience a sense of what is “worthy” and “desirable” while denying “bad science” the platform and publicity it seeks. This is objectionable on two counts.

First, who decides what is “worthy”? For example, some scientists, especially in the ‘senior’ cadre and the more influential and/or powerful for it, make this choice by deferring to the wisdom of scientific journals, chosen according to their impact factors, and what the journals have deemed worthy of publishing. But abiding by this heuristic only means we continue to participate in and extend the lifetime of the existing ways of knowledge production that privilege white scientists, male scientists and richer scientists – and sensational positive results on topics that the scientists staffing the journals’ editorial boards would like to focus on.

Second, being limited to goodness at a time when badness abounds is bad, at least severely tone-deaf (but I’m disinclined to be so charitable). Very broadly, that science is inherently amoral is a pithy factoid by this point. There have been far too many incidents in history for anyone to still be able to overlook, in good faith, the fact that science’s prescriptions unguided by human morals and values are quite likely to lead to humanitarian disasters. We may even be living through one such. Scientists’ rapid and successful development of new vaccines against a new pathogen was followed by a global rush to acquire enough doses. But the world’s industrial and economic powers have ensured that the strongest among them have enough to vaccine their entire populations more than once, have blocked petitions at global fora to loosen patents on these vaccines to expand manufacturing and distribution, have forced desperate countries to purchase doses at prices higher than those for developed blocs like the EU, and have allowed corporate behemoths to make monumental profits even as they force third-world nations to pledge sovereign assets to secure supplies. It’s fallacious to claim scientific labour makes the world a better place when the fruits of such labour must still be filtered, like so much else, through the capitalist sieve.

There are many questions for the science journalist to consider here: why have some communities in certain countries been affected more than others? Why is there so little data on the vaccines’ consequences for pregnant women? Do we know enough to discuss the pandemic’s effects on women? Why, at a time when so many scientists and engineers were working to design new ventilators, was there no unified standard to ensure usability? If the world has demonstrated that it’s possible to design, test, manufacture and administer vaccines against a new virus in such a short time, why have we been waiting so long for effective defences against neglected tropical diseases? How do the racial, gender and ethnic identifies of clinical trials affect trial outcomes? Is it ethical for countries that hosted vaccine clinical trials to get the first doses? Should we compulsorily prohibit patents on drugs, therapies and devices important to ending pandemics? If so, what might the consequences be for drug development? And what good is a vaccine if we can’t also ensure all the world’s 7.x billion people can be vaccinated simultaneously?

The pandemic isn’t a particularly ‘easy’ example either. For example, if the government promises to develop new supercomputers, who can use them and what problems will they be used to solve? How can we improve the quality and quantity of research conducted at institutes funded by state governments? Why do so many scientists at public universities plagiarise scientific papers? On what basis are the winners of the S.S. Bhatnagar Award chosen? Should we formally do away with subscription-funded scientific journals in favour of open-access publishing, overlay journals and post-publication peer-review? Is methane really a “clean fuel” even though its extraction and transportation will impose a considerable dirty cost? Why can’t we have more GM foods in the market even though the science is ‘good’? Is it worthwhile to invest Rs 10,000 crore in a human spaceflight programme that lacks long-term vision? And so forth.

Simply focusing on “good science” at our present time is not enough. I also reject the argument that it’s not for science journalists to protect or defend science simply because science, whatever it’s interpreted to mean, is not the preserve of scientists. As an enterprise rooted in its famous method, science is a tool of empowerment: it encourages discovery and deliberation; I’m not sure if it’s fair to say it encourages dissent as well but there is evidence that science can accommodate it without resorting to violence and subjugation.

It’s not for nothing that I’m more comfortable holding up an aspirin tablet for someone with a headache than a jar of leaves from the Patanjali Ayurved stable: being able to know how and why something works is power in the same way knowing how the pharmaceutical industry manipulates markets, how to file an RTI application, what makes an FIR valid or invalid, what the election commission’s model code of conduct stipulates or what kind of land a mall can be built on is power. All of it represents control, especially the ability to say ‘no’ and mean it.

This is ultimately what the GoM report fantasises about – and what the present government desires: the annulment of individual and institutional resistance, one subset of which is the neutralisation of science’s ability to provoke questions about atoms and black holes as much as about the circumstances in which scientists study them, about the nature, utility and purpose of knowledge, and the relationships between science, capital and the state.

Addendum

In January 2020, the Office of the Principal Scientific Adviser (PSA) to the Government of India organised a meeting with science journalists and communicators from around the country to discuss what the two parties could do for each other. Us journalists and communicators aired a lot of grievances during the meeting as well as suggestions on fixing long-standing and/or particularly thorny problems (some notes here).

In light of the government’s renewed attention on curbing press freedom and ludicrous suggestions in the report, such as one by S. Gurumurthy that the news should be a “mixture of truth and untruth”, I’m not sure where that leaves the PSA’s plans for future consultation nor – considering parts of the report seemingly manufactured consent – whether good-faith consultation will be possible going ahead. I can only hope that members of this community at least evoke and keep the faith.

Magic bridges

The last two episodes of the second season of House, the TV series starring Hugh Laurie as a misanthropic doctor at a facility in Princeton, have been playing on my mind off and on during the COVID-19 pandemic. One of its principal points (insofar as Dr Gregory House can admit points to the story of his life) is that it’s ridiculous to expect the families of patients to make informed decisions about whether to sign off on a life-threatening surgical procedure, say, within a few hours when in fact medical workers might struggle to make those choices even after many years of specific training.

The line struck me to be a chasm stretching between two points on the healthcare landscape – so wide as to be insurmountable by anything except magic, in the form of decisions that can never be grounded entirely in logic and reason. Families of very sick patients are frequently able to conjure a bridge out of thin with the power of hope alone, or – more often – desperation. As such, we all understand that these ‘free and informed consent’ forms exist to protect care-providers against litigation as well as, by the same token, to allow them to freely exercise their technical judgments – somewhat like how it’s impossible to physically denote an imaginary number (√-1) while still understanding why they must exist. For completeness.

Sometimes, it’s also interesting to ask if anything meaningful could get done without these bridges, especially since they’re fairly common in the real world and people often tend to overlook them.

I’ve had reason to think of these two House episodes because one of the dominant narratives of the COVID-19 pandemic has been one of uncertainty. The novel coronavirus is, as the name suggests, a new creature – something that evolved in the relatively recent past and assailed the human species before the latter had time to understand its features using techniques and theories honed over centuries. This in turn predicated a cascade of uncertainties as far as knowledge of the virus was concerned: scientists knew something, but not everything, about the virus; science journalists and policymakers knew a subset of that; and untrained people at large (“the masses”) knew a subset of that.

But even though more than a year has passed since the virus first infected humans, the forces of human geography, technology, politics, culture and society have together ensured not everyone knows what there is currently to know about the virus, even as the virus’s interactions with these forces in different contexts continues to birth even more information, more knowledge, by the day. As a result, when an arbitrary person in an arbitrary city in India has to decide whether they’d rather be inoculated with Covaxin or Covishield, they – and in fact the journalists tasked with informing them – are confronted by an unlikely, if also conceptual, problem: to make a rational choice where one is simply and technically impossible.

How then do they and we make these choices? We erect magic bridges. We think we know more than we really do, so even as the bridge we walk on is made of nothing, our belief in its existence holds it up and stiff beneath our feet. This isn’t as bad as I’m making it seem; it seems like the human thing to do. In fact, I think we should be clearer about the terms on which we make these decisions so that we can improve on them and make them better.

For example, all frontline workers who received Covaxin in the first phase of India’s vaccination drive had to read and sign off on an ‘informed consent’ form that included potential side effects of receiving a dose of the vaccine, its basic mechanism of action and how it was developed. These documents tread a fine line between being informative and being useful (in the specific sense of the risk of debilitating action by informing too much and of withholding important information in order to skip to seemingly useful ‘advice’): they don’t tell you everything they can about the vaccine, nor can they assert the decision you should make.

In this context, and assuming the potential recipient of the vaccine doesn’t have the education or training to understand how exactly vaccines work, a magic bridge is almost inevitable. So in this context, the recipient could be better served by a bridge erected on the right priorities and principles, instead of willy-nilly and sans thought for medium- or long-term consequences.

There’s perhaps an instructive analogy here with software programming, in the form of the concept of anti-patterns. An anti-pattern is a counterproductive solution to a recurrent problem. Say you’ve written some code that generates a webpage every time a user selects a number from a list of numbers. The algorithm is dynamic: the script takes the user-provided input, performs a series of calculations on it and based on the results produces the final output. However, you notice that your code has a mistake due to which one particular element on the final webpage is always 10 pixels to the left of where it should be. Being unable to identify the problem, you take the easy way out: you add a line right at the end of the script to shift that element 10 pixels to the right, once it has been rendered.

This is a primitive example of an anti-pattern, an action that can’t be determined by the principles governing the overall system and which exists nonetheless because you put it there. Andrew Koenig introduced the concept in 1995 to identify software programs that are unreliable in some way, and which could be made reliable by ensuring the program conforms to some known principles. Magic bridges are currently such objects, whose existence we deny often because we think they’re non-magical. However, they shouldn’t have to be anti-patterns so much as precursors of a hitherto unknown design en route to completeness.

Pandemic: Science > politics?

By Mukunth and Madhusudhan Raman

Former Union health secretary K. Sujatha Rao had a great piece in The Indian Express on January 14, whose takeaway she summarised in the following line:

Science, evidence and data analytics need to be the bedrock of the roll-out policy, not politics and scoring brownie points for electoral advantages.

However, we can’t help but be reminded of the difference between what should be and what will be. We all (at least those of us who have been on the same side since 2014) know what should be. But as we’ve seen with the National Registry of Citizens (NRC), the Citizenship (Amendment) Act (CAA) 2019 and most recently the farm laws, our present government doesn’t change its mind.

In the last example, the Supreme Court intervened to stay the laws’ implementation but the mediation committee it put together somehow wound up with most members being known to be sympathetic to the government’s position. So what will be, will be – and this is likely to be true vis-à-vis Covaxin as well.

Prime Minister Narendra Modi has already guaranteed as much by determining to foot the cost of 5.5 million doses of Covaxin using the PM CARES fund, which lies beyond public oversight. The Central Drug Standards Control Organisation also played its part by pushing through Covaxin’s approval on terms no one has heard of – and which no one can therefore falsify.

However, this isn’t a pitch for a nihilist position. When Sujatha Rao writes that the government should prize science, evidence and data more than politics and elections, she is right – but we must also ask why. The government has clear incentives to prioritise politics. By thrusting Bharat Biotech – Covaxin’s maker – to the forefront, Modi can claim his ‘Atma Nirbhar’ and ‘Make in India’ schemes have been successful. Also, two important state elections are around the corner: West Bengal and Tamil Nadu.

These are issues that people, but especially ‘Middle Indians’, have an eye on and according to which they vote. The government has also said it is approving Covaxin because it is concerned with the ‘UK variant’. While no reason can be good enough to justify the use of a vaccine candidate in the population sans data from phase 3 clinical trials, the government has effectively set up Covaxin to be failure-proof: if it works, it works; if it doesn’t, it becomes the fault of the variant.

Taken together, Modi’s biggest mistake here is criminal negligence – for pushing Covaxin in the absence of efficacy data (which leads to a cascade of ethical dilemmas) – especially since there are fewer questions over Covaxin’s safety. And negligence is a difficult case to stick to this party or in fact to many people.

Granted, public-spirited science teachers, communicators and journalists can take it upon themselves (ourselves) to persuade readers as to why Covaxin’s approval is really bad – that though everything may turn out okay, it sets a terrible precedent for what this government is allowed to do, how such unchecked power may wreak deadly havoc in future crises, and ultimately that we become a people okay with settling for less, increasingly blind to the banal incrementalism of evil.

In fact, if the mainstream press manages to forget concerns about vaccine apartheid within the country, the dominant narrative as the vaccine roll-out is a few months in is going to be: “India is doing just fine, thank you very much.”

But while the Modi government’s actions may only be negligent – albeit criminally so – in the domains of public healthcare and ‘scientific temper’, they amount to something more egregious if we include the political dimensions of our present moment as well.

None of this means words like those of Sujatha Rao are unnecessary. We need to never forget what should be, and we need to keep protesting for our own sakes. (“Protests sometimes look like failures in the short term, but much of the power of protests is in their long-term effects, on both the protesters themselves and the rest of society.” – Zeynep Tufekci) If we don’t, this government might pretend even less than it currently does that it is following some rules or guidelines from time to time.

However, limiting our exhortations to insist at every turn that “science is more important than politics during a pandemic” risks playing down the importance and influence of political motivations altogether – as well as assuming that the state machinery will automatically give way to scientific ones when lives are at stake.

A politician’s principal responsibility is not to govern but to win elections; good governance is a means to this electoral end. And the way people have voted for many decades attests to the reality of this incentive. While this claim may not be palatable from a theoretical point of view, consider it empirically: the Indian government has seldom responded to national crises to the detriment of potential electoral gains. Examples of such crises include the 1962, 1971 and 1999 conflicts, the nuclear tests and economic liberalisation. During the Emergency, the government itself embodied this crisis.

More recently, numerous ministers and diplomats urged the India and Pakistan governments to find diplomatic solutions after the Pulwama attack and also after the questionable Balakot airstrike, in early 2019. In previous years, they had been preceded by the disagreeable events of Aadhaar implementation, demonetisation and the Goods and Services Tax. But Modi and his fellows won by a bigger margin in 2019 than they had five years earlier.

This happened partly because his success in elections rests on his impression as the Strongman of India, so his resolutions of choice involve flashy displays of strength and machismo.

Against this background: we need to admit political factors into the conversations we – rather, experts like health policymakers, heads of institutions, epidemiologists, healthcare workers, etc. – have from the beginning, instead of ruing the inevitable influence of politics later, so that we may anticipate it and take advantage of it.

For example, consider the conversation surrounding academic publishing. Academics perform most of the work that goes into publishing an academic paper (research, writing and reviewing). Publishing houses add only marginal value to journals – yet publishers charge exorbitant fees to access the results of publicly funded research once it is published. This is unfair, and many academics have said so.

However, the fact that publishing conglomerates are publicly traded companies whose primary responsibility is to generate profits for their shareholders finds little mention in conversations. In this case, the publishers’ profit-seeking motives are fundamental to the problem at hand – but are often disregarded in the first analysis (what should be) and subsequently bemoaned (what will be). For this to happen once is tragic; for it to repeat itself every few months is wasteful.

Similarly, the nationwide lockdown from March to July 2020 served a political purpose: it was a grand gesture, decisive, appealing to ‘Middle Indians’, in addition to supplying the government a pretext to disband protests against the CAA and the NRC. Just before the lockdown, the public conversation had been centred on what the government should be doing. However, most scientists and economists didn’t engage with the political dimension of this decision.

If we had, we may not have been side-tracked into conversations about weekend curfew versus night curfew, or cash transfers versus vouchers, etc. We would perhaps have recognised that our responsibility is not to operate within the parameters set by the government (“How effective was the lockdown?”) but instead recognise that the government’s decisions are politically motivated – so we can ask “Why lock down in the first place?”

A future obscured by exponential growth

A couple months into the COVID-19 pandemic, I think most of us realised how hard it is to comprehend the phenomenon of exponential growth. Mathematically, it’s trivial – a geometric progression – but more physically, the difference between linear and exponential growth is very non-trivial, as a cause-effect chain where each effect leads to multiple new cases according to a fixed growth ratio. The effect is an inability to fully anticipate future outcomes – to prepare mentally for the ‘speed’ with which an exponential series can scale up – rendered remarkable by us not having planned for it.

For example, the rice and chessboard problem is a wonderful story to tell because it’s hard for most people to see the punchline coming. To quote from Wikipedia: “If a chessboard were to have wheat placed upon each square such that one grain were placed on the first square, two on the second, four on the third, and so on (doubling the number of grains on each subsequent square), how many grains of wheat would be on the chessboard at the finish?” The answer is 18,446,744,073,709,551,615 – a 100-million-times greater than the number of stars in the Milky Way. Many people I know have become benumbed by the scale of India’s COVID-19 epidemic, which zipped from 86k active cases on May 30 to 545k on July 31, and from 1M total cases on July 17 to 7.3M on October 15. On August 1, 1965, Vikram Sarabhai delivered the convocation address at IIT Madras, which included the following quip:

Everyone here is undoubtedly familiar with the expression ‘three raised to the power of eighteen’. It is a large number: 38,74,20,489, thirty-eight crore, seventy-four lakh, twenty thousand, four hundred and eighty-nine. What it means in dynamic terms is quite dramatic. If a person spreads gossip to just three others and the same is passed on by each of them to three others, and so on in succession, in just eighteen steps almost the entire population of India would share the spicy story.

Because of its mathematical triviality and physical non-triviality, I think we have a tendency to abstract away our impression of exponential growth – to banish it out of our imagination and lock it away into mathematical equations, such that we plug in some numbers and extract the answers without being able to immediately, intuitively, visualise or comprehend the magnitude of change, the delta as it were, in any other sense-based or emotional way. And by doing so, we are constantly surprised by the delta every time we’re confronted with it. Say the COVID-19 epidemic in India had a basic reproductive number of 1.4, and that everyone was familiar with this figure. But simply knowing this value, and the fundamental structure of a geometric progression, doesn’t prepare people for the answer. They know it’s not supposed to be N after N steps, but they’re typically not prepared for the magnitude of 1.4^N either.

I recently came across a physical manifestation of this phenomenon in a different arena – technology – through a Twitter account. The oldest Homo sapiens technologies include fire, tool-making, wheels and cropping. But while the recursive application of these technologies alone may have given rise, in a millennium (i.e. 1,000 steps), to, say, a subsistence agriculture economy with some trade, that’s not what happened. Instead, two other things did (extremely broadly speaking): the technologies cut down the time required for different processes, and which subsequently came to be occupied by the application of these technologies to solve other problems. The geometric-like progression that followed exponentiated not the technologies themselves but these two principles, of sorts, rapidly opening up new methods and opportunities to extract value from our surroundings, and eventually from ourselves, to add to the globalising value chain.

To get a quick sense of the rapidity of this progress, check out @MachinePix on Twitter. Their latest tweet (as of 11 am on October 17) describes a machine that provides a “motion-compensated” gangway for workers moving between a ship and an offshore wind turbine; many others depict ingenious contraptions ranging from joyously simple to elegantly complicated – from tape-dispensers and trains windows that auto-tint to automated food-packaging and super-scoopers. There’s even a face-mask gun that seems to deliver an amount of pain suitable for anti-maskers.

But closer to the point of this discussion: taken together, @MachinePix’s tweets demonstrate the extent to which we have simplified and/or automated different processes, and the amount of time humans have collectively saved as a result. This, again, can’t be a straightforward calculation: we don’t just apply the same technologies over and over to perform the same tasks. We also apply technologies to each other to compound or even modify their effects, effectively leading to new technologies and, thus, new applications – from the level of toothbrush plus toothpaste to liquefaction plus rocket engines. The tools we develop also alter the structure of society, which in turn changes aspirations and leads to the birth of yet more technologies, but ordered along different priorities.

In the last few months, I learnt many of these features in an intimate way through Factorio, a video-game that released earlier this year. The premise is that your spaceship has crashed on an alien planet, with many of the same natural resources as Earth. You now need to work your way through a variety of technologies and industrial systems and ultimately build a rocket, and launch yourself off to Earth. The ‘engine’ at the game’s centre, the thing that drives your progress, is a recipe-based manufacturing system. You mine resources, process them into different products, combine them to make components, and combine the components to make machines. The machines automate some or all of these processes to make more sophisticated machines and robots, and so forth. To move objects, you use different kinds of inserters and conveyor belts; for fluids – from water to lubricant – there are pipes, tanks, even fluid wagons attached to trains.

A zoomed-out scene from Factorio. This is ‘Main Station’, one of five bases I operate in this scenario.

I’m still finding my way around the extent of the game; the technology tree is very high and has scores of branches. The scenario I’m currently playing goes beyond a rocket to using satellites, but doesn’t include the planet’s alien creatures, who attack your base if you antagonise them or pollute too much. I often think it would’ve been much better to allow final-year students of mechanical engineering (which I studied) to play this game instead of making them sit through hours of boring lectures on logistics, quality control, operations research, supply-chain management, etc. Factorio doesn’t set out to teach you these things but that’s what you learn – and on the way, you also discover how easy it is for things to get out of control, become too complicated, too chaotic – sometimes just too big to fail.

Sometimes, you’ve invested so much in developing one technology that you’re unable to back out, and you start to disprivilege other ambitions in favour of this one. This happened to me recently: being hell-bent on building nuclear reactors to keep up with the demand for power, I had to give up on building a satellite.

Instead of a linear or even a tree-like model of technology development, imagine a circular one: at the centre is the origin, and the circumference is where you are, the present (it’s not a single point in space-time; it’s multiple points in space at one time). Technologies emerge from the origin and branch out towards the perimeter in increasingly intricate branches. By the time they’ve reached the outer limits, to where you are, you have nuclear power, rocketry, robotic construction networks and high-grade weapons. But in this exponentially interconnected world, what do you change and where to effect a difference somewhere else? And how can you hope to be sure there won’t be any other effects?

My new favourite example of this, from the few-score @MachinePix tweets I’ve scrolled through thus far, is the rotary screen printer. It shows, among many other things, that there’s a second way in which exponential growth disrupts our ability to predict its outcomes. Could a fantasy writer working all those millennia ago have predicted this device’s existence? They may have, they may have not, just as we contemplate what the future might look like from today, but sometimes presume to anticipate – even though we really can’t – the full breadth of what lies in store for humankind. Can we even say if the rotary screen printer will still be around?

Featured image: An artist’s rendering of spaceships hovering above a city. More importantly, this image belongs to a genre quite popular in the 2000s, perhaps the late 1990s too, when image-editing software wasn’t as versatile as it is today and when the internet was only just beginning to democratise access to literature and videos, among other things, so the most common idea of first contact looked a lot like this. Credit: Javier Rodriguez/pixabay.

India’s missing research papers

If you’re looking for a quantification (although you shouldn’t) of the extent to which science is being conducted by press releases in India at the moment, consider the following list of studies. The papers for none of them have been published – as preprints or ‘post-prints’ – even as the people behind them, including many government officials and corporate honchos, have issued press releases about the respective findings, which some sections of the media have publicised without question and which have quite likely gone on to inform government decisions about suitable control and mitigation strategies. The collective danger of this failure is only amplified by a deafening silence from many quarters, especially from the wider community of doctors and medical researchers – almost as if it’s normal to conduct studies and publish press releases in a hurry and take an inordinate amount of time upload a preprint manuscript or conduct peer review, instead of the other way around. By the way, did you know India has three science academies?

ICMR’s first seroprevalence survey (99% sure it isn’t out yet, but if I’m wrong, please let me know and link me to the paper?)
Mumbai’s TIFR-NITI seroprevalence survey (100% sure. I asked TIFR when they plan to upload the paper, they said: “We are bound by BMC rules with respect to sharing data and hence we cannot give the raw data to anyone at least [until] we publish the paper. We will upload the preprint version soon.”)
Biocon’s phase II Itolizumab trial (100% sure. More about irregularities here.)
Delhi’s first seroprevalence survey (95% sure. Vinod Paul of NITI Aayog discussed the results but no paper has pinged my radar.)
Delhi’s second seroprevalence survey (100% sure. Indian Express reported on August 8 that it has just wrapped up and the results will be available in 10 days. It didn’t mention a paper, however.)
Bharat Biotech’s COVAXIN preclinical trials (90% sure)
Papers of well-designed, well-powered studies establishing that HCQ, remdesivir, favipiravir and tocilizumab are efficacious against COVID-19 🙂

Aside from this, there have been many disease-transmission models whose results have been played up without discussing the specifics as well as numerous claims about transmission dynamics that have been largely inseparable from the steady stream of pseudoscience, obfuscation and carelessness. In one particularly egregious case, the Indian Council of Medical Research announced in a press release in May that Ahmedabad-based Zydus Cadila had manufactured an ELISA test kit for COVID-19 for ICMR’s use that was 100% specific and 98% sensitive. However, the paper describing the kit’s validation, published later, said it was 97.9% specific and 92.37% sensitive. If you know what these numbers mean, you’ll also know what a big difference this is, between the press release and the paper. After an investigation by Priyanka Pulla followed by multiple questions to different government officials, ICMR admitted it had made a booboo in the press release. I think this is a fair representation of how much the methods of science – which bridge first principles with the results – matter in India during the pandemic.

The number of deaths averted

What are epidemiological models for? You can use models to inform policy and other decision-making. But you can’t use them to manufacture a number that you can advertise in order to draw praise. That’s what the government’s excuse appears to be vis-à-vis the number of deaths averted by India’s nationwide lockdown.

When the government says 37,000 deaths were averted, how can we know if this figure was right or wrong? A bunch of scientists complained that the model wasn’t transparent, so its output had to be taken with a cupful of salt. But as an article published in The Wire yesterday noted, these scientists were asking the wrong questions – that the number of deaths averted is only a decoy.

So say the model had been completely transparent. I don’t see why we should still care about the number of deaths averted. First, such a model is trying to determine the consequences of an action that was not performed, i.e. the number of people who might have died had the lockdown not been imposed.

This scenario is reminiscent of a trope in many time-travel stories. If you went back in time and caused someone to do Y instead of X, would your reality change or stay the same considering it’s in the consequent future of Y instead of X? Or as Ronald Bailey wrote in Reason, “If people change their behaviour in response to new information unrelated to … anti-contagion policies, this could reduce infection growth rates as well, thus causing the researchers to overstate the effectiveness of anti-contagion policies.”

Second, a model to estimate the number of deaths averted by the lockdown will in effect attempt to isolate a vanishingly narrow strip of the lockdown’s consequences to cheer about. This would be nothing but extreme cherry-picking.

A lockdown has many effects, including movement restrictions, stay-at-home orders, disrupted supply of essential goods, closing of businesses, etc. Most, if not all, of them are bound to exact a toll on one’s health. So the number of deaths the lockdown averted should be ‘adjusted’ against, say, the number of people who couldn’t get life-saving surgeries, the number of migrant labourers who died of heat exhaustion, the number of TB patients who developed MDR-TB because they couldn’t get their medicines on time, even the number of daily-wage earners’ children who died of hunger because their parents had no income.

So the only models that can hope to estimate a meaningful number of deaths averted by the lockdown will also have simplified the context so much that the mathematical form of the lockdown will be shorn of all practical applicability or relevance – a quantitative catch-22.

Third, the virtue of the number of deaths averted is a foregone conclusion. That is, whatever its value is, it can only be a good thing. So as an indisputable – and therefore unfalsifiable – entity, there is nothing to be gained or lost by interrogating it, except perhaps to elicit a clearer view of the model’s innards (if possible, and only relative to the outputs of other models).

Finally, the lockdown will by design avert some deaths – i.e. D > 0 – but D being greater than zero wouldn’t mean the lockdown was a success as much D‘s value, whatever it is, being a self-fulfilling prophecy. And since no one knows what the value of D is or what it ought to be, even less what it could have been, a model can at best come up with a way to estimate D – but not claim a victory of any kind.

So it would seem the ‘number of deaths averted’ metric is a ploy disguised as a legitimate mathematical problem whose real purpose is to lure the ‘quants’ towards something they think challenges their abilities without realising they’re also being lured away from the more important question they should be asking: why solve this problem at all?