World Health Organization

The WHA coronavirus resolution is not great for science

On May 19, member states of the WHO moved a vote in the World Health Assembly (WHA), asking for an independent investigation into the sources of the novel coronavirus.

Their exact demands were spelled out in a draft resolution that asked the WHO to, among other things, “identify the zoonotic source of the virus and the route of introduction to the human population, including the possible role of intermediate hosts, including through efforts such as scientific and collaborative field missions”.

The resolution was backed by 62 countries, including India, and the decision to adopt it was passed with 116 votes in favour, out of 194. This fraction essentially indicates that the overwhelming majority of WHO’s member states want to ‘reform’ the organisation towards a better response to the pandemic, especially in terms of obtaining information that they believe China has been reluctant to share.

The resolution follows from Australia’s demand in April 2020 for a public inquiry against China, suggesting that the Asian superpower was responsible for the virus and the global outbreak (not surprisingly, US President Donald Trump expressed his support). Together with the fact that the document doesn’t once mention China, the resolution is likely an expression of concern that seeks to improve international access to biological samples, specific locations and research data necessary to find out how the novel coronavirus came to infect humans, and which animal or avian species were intermediate hosts.

As it happens, this arguably legitimate demand doesn’t preclude the possibility that the resolution is motivated, at least in part, by the need to explore what is in many political leaders’ view the ‘alternative’ that the virus originated in a Chinese lab.

The WHA vote passed and the independent investigation will happen – but by who or how is unclear. Let’s assume for now that some team or other comes together and conducts the requisite studies.

What if the team does find that the virus is not lab-made? Will those WHO member states, and/or their politicians back home, that were in favour of the resolution to explore the ‘lab hypothesis’ let the matter rest? Or will they point fingers at the WHO and claim it is too favourable to China, as President Trump has already done and to which the resolution’s reformatory language alludes?

In fact, the investigation is unlikely to zero in on the virus’s origins if they were natural because too much time has passed since the first zoonotic spillover event. The bread crumbs could have long faded by the time the investigation team sets out on its task. It won’t be impossible, mind, but it will be very difficult and likely require many months to conclude.

But what if the investigation somehow finds that the virus was engineered in a lab and then leaked, either deliberately or accidentally? Will the scientists and those who believed them (including myself) stand corrected?

They will not. There’s a simple reason why: they – we – have thus far not been given enough evidence to reach this conclusion.

Indeed, there is already sufficient explanation these days to claim that the novel coronavirus is of natural origin and insufficient explanation that it was engineered. A study published on March 17, 2020, collected evidence for the former (and many others continue to do so). An excerpt from the conclusion:

The genomic features described here may explain in part the infectiousness and transmissibility of SARS-CoV-2 in humans. Although the evidence shows that SARS-CoV-2 is not a purposefully manipulated virus, it is currently impossible to prove or disprove the other theories of its origin described here. However, since we observed all notable SARS-CoV-2 features, including the optimised RBD and polybasic cleavage site, in related coronaviruses in nature, we do not believe that any type of laboratory-based scenario is plausible.

If there is any animosity at all directed at China for supposedly engineering the virus, the countries that backed the resolution could only have done so by actively ignoring the evidence that already exists to the contrary.

In this particular case, it becomes extremely important for the representatives of these countries to explain why they think the evidence that scientists have not been able to find actually exists, and that they are simply yet to discover it. That is, why do they think some pieces are missing from the puzzle?

There is of course room for a deeper counter-argument here, but it isn’t entirely tenable either. One could still argue that there might be a larger ‘super-theory’ that encompasses the present one even as it elucidates a non-natural origin for the virus. This is akin to the principle of correspondence in the philosophy of science. The advent of the theories of relativity did not invalidate the Newtonian theory of gravity. Instead, the former resemble the latter in the specific domain in which the latter is applicable. Similarly, a ‘super-theory’ of the virus’s origins could point to evidence of bioengineering even as its conclusions resemble the evidence I’m pointing to to ascertain that the virus is natural.

But even then, the question remains: Why do you think such a theory exists?

Without this information, we are at risk of wasting our time in each pandemic looking for alternate causes that may or may not exist, many of which are quite politically convenient as well.

Perhaps we can assimilate a sign of things to come based on Harsh Vardhan’s performance as the chairman of the WHA’s executive board. Vardhan was elected into this position at the same WHA that adopted the draft resolution, and his highest priority is likely to be the independent investigation that the resolution calls for. As it happens, according to OP8 of the resolution, the resolution:

… calls on international organisations and other relevant stakeholders to … address, and where relevant in coordination with Member States, the proliferation of disinformation and misinformation particularly in the digital sphere, as well as the proliferation of malicious cyber-activities that undermine the public health response, and support the timely provision of clear, objective and science-based data and information to the public.

India as a member state is certainly a stakeholder, and Nitin Gadkari, one of the country’s senior ministers, recently said in an interview that the novel coronavirus was made in a lab. This is misinformation plain and simple, and goes against the call for the “timely provision of clear, objective and science-based information to the public”. Will the chair address this, please – or even future instances of such imprudence?

Ultimately, unless the investigation ends with the conspiracists changing their minds, the only outcome that seems to be guaranteed is that scientists will know their leaders no longer trust their work.

Featured image: The assembly hall of the Palace of Nations, Geneva, where the World Health Assembly usually meets. Photo: Tom Page/Wikimedia Commons, CC BY-SA 2.0.

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.

Tuberculosis’s invisible millions – in cases and money

Tuberculosis (TB) has killed more than a billion people in the last 200 years. That’s more than any other infectious disease in that period. And, what’s worse is that, according to the World Health Organisation (WHO), less than half the cases worldwide are ever diagnosed.

India suffers the most. It has the highest burden of TB in the world: More than 2 million suffer from the disease, and this is despite years of work to control the disease.

TB was declared a global health emergency by the WHO in 1993. Then, in 2001, the first global “Stop TB Plan” came into effect, with an international network of donors and private and public sector organisations tackling TB-related issues around the world together.

The disease is prevalent among both rich and poor countries, but has more disastrous consequences in the latter because of limited access to healthcare, poor sanitation and undernutrition. The matter is worsened because of co-morbidity, where those with weakened immune systems—having suffered from diabetes or AIDS—fall prey to TB and die.

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And even between developing economies, there is significant variation in treatment levels because of difficulties in identifying new infections. In 2012, while China and India together accounted for 40% of the world’s burden of TB, the prevalence among 100,000 people was at least 167 in India and less than half that in China (about 68).

Technology can help

In an article in the journal PLOS Medicine, Puneet Dewan from the Bill & Melinda Gates Foundation and Madhukar Pai of McGill University have called for global efforts to identify, treat and cure the 3 million “missed” TB infections every year.

“Reaching all these individuals and ensuring accountable, effective TB treatment will require TB control programs to adopt innovative tools and modernize program service delivery,” they write.

In January 2015, the WHO representative to India, Nata Menabde, said the decline of TB incidence in the country was occurring at 2% per year, instead of the desired 19-20%. She added that it could be pulled up to 10% per year by 2025 if the country was ready to leverage better the available technology. The WHO’s goal is to eradicate TB by 2050. But for India that may prove to be too soon.

This is also what Dewan and Pai are calling for. The tech interventions could be in the form of e-health services, the use of mobile phones by doctors to notify centers of new cases, and disbursing e-vouchers for subsidized treatment.

And their demands are not unreasonable, given India’s progress so far. First, India has met one of the United Nations’ ambitious Millennium Development Goals by cutting TB prevalence to half in 2015 compared to prevalence in 1990. Second, according to Menabde, India is also on track to halve TB mortality by the end of this year compared to that in 1990. The accomplishment testifies to commitment from public and private sector initiatives and places the country in a good position from which to springboard toward stiffer targets. Continued support can sustain the momentum.

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In 2012, the previous government made TB a notifiable disease—mandating medical practitioners to report every TB case detected—going some way in reducing the number of “missing” cases. It also banned blood tests to diagnose TB for the lack of a clinical basis. While the delay in implementing these measures contributed to the rise of multidrug-resistant strains of the disease, they also revitalised efforts to meet targets set by the WHO at an important time. Then bad news struck.

Causing self-harm

India’s health budget for 2015-16 has not even managed to keep up with inflation. It is a mere 2% more than the previous year. For TB, this budgetary belt-tightening has meant taking a few steps back in the pace of developing cures against multi-drug resistant strains and in efforts to improve the quality of treatment at frontline private-sector agencies, which already provide more than 60% of patient care.

Dewan and Pai think TV programs, such as Aamir Khan’s Satyamev Jayate, and Amitabh Bachchan’s admission that he is a TB survivor will promote enough awareness to force changes in healthcare spending—but this seems far too beamish an outlook when the funding cuts and regulatory failures are factored in.

A new draft of the National Health Policy (NHP) was published in December. Besides providing a lopsided insight into the government’s thoughts on public healthcare, it made evident that ministers’ apathetic attitude, and not a paucity of public support, was to blame for poor policies.

Nidhi Khurana, a health systems researcher at the Johns Hopkins Bloomberg School of Public Health, summed up the NHP deftly in The Hindu:

The NHP refutes itself while describing the main reason for the National Rural Health Mission’s failure to achieve stronger health systems: “Strengthening health systems for providing comprehensive care required higher levels of investment and human resources than were made available. The budget received and the expenditure thereunder was only about 40 per cent of what was envisaged for a full revitalisation in the NRHM framework.” If this is not the case against diminished public funding for health, what is?