The trajectory of scientific progress in the time of pandemic

The scale and spread of the pandemic have imposed unprecedented demands on modern science. But science being bound by the complex nature of reality and its own method, humanity has no choice but to wait for the scientific method to provide the answers it so desperately seeks.

At a vaccination centre in Mumbai.

T he COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, represents a remarkable conjuncture in the history of science. It has led to an unprecedented pace of scientific progress and an unparalleled level of cooperation in its practice. In the process it has highlighted the complexity and uncertainty inherent in the nature of reality and associated with the scientific discovery of reality. Many critical aspects of the scientific development process are on display like never before in the history of science. At the same time, the phenomenon uncovers many false perceptions about reality and science that persist in various segments of society. It exemplifies a tension, if not a clash, between the real nature of scientific progress and the general understanding of it.

Philosophers of science, particularly those of the realist schools, have always commented on these aspects of the development of science, but the manner in which the whole process is playing itself out in front of us is perhaps unprecedented. This essay attempts to underline some of these aspects of science’s trajectory in the pandemic.

The complexity of the phenomenon

Reality, which encompasses both non-human nature and human society, is, in essence, objectively infinite, indeterminate and ever-changing. It exists in motion and is based on objective laws that are independent of the human mind, even if those laws themselves have uncertainty embedded in them. Uncertainty, therefore, is fundamental to reality, and SARS-CoV-2 is a case in point.

The novel virus appeared at the fag end of 2019 and began directly impacting human life and society in shocking ways. The pace of its spread and the scale of its reach were without parallel. Little was known about its origin, evolution and character. The past 18 months have been remarkable in terms of scientific endeavour. Working at breakneck speed, science has uncovered many unknowns about the pandemic. As a result of coordinated efforts, today we know much more and with a fair degree of certainty about the nature of the virus and the disease it causes.

Nonetheless, much remains to be known. Uncertainties still remain about the virus’ origin, nature, spread and impact on lives and livelihoods. The fact that the virus mutates as it spreads and throws up newer unknowns complicates things further. Concerns about increased infectivity, transmissibility, and the severity of newer variants have raised new research questions.

Evolutionary logic suggests that subsequent “Variants of Concern” are much more transmissible than the original version of the virus. The logic also supports the possibility of variants that can evade the immune response of people who have had the infection. Some of the newer variants are indeed spreading quickly and affecting a large number of people; this may be because of the logical inference mentioned above. But because the population that is infected by the newer variants is qualitatively different (both socially and biologically) from the population that was exposed to the original variant, it is difficult to meaningfully capture ideas such as transmissibility of the virus. In other words, it is not just the virus that is mutating; the host population and the environment in which the virus interacts with the host are also changing, adding layers of complexity. What appears to be the nature or the impact of a particular variant of the virus is, in reality, an outcome of a complex interaction.

Strikingly, any intervention such as a vaccine, which limits the virus spread, adds to the evolutionary pressure on the virus and forces it to mutate into variants that can potentially evade the vaccine. However, for this to happen, the virus needs to transmit quickly and infect many more human hosts, an eventuality that can only be avoided by the rapid vaccination of a large proportion of the human population. Leaving a large population unvaccinated poses a danger to all, including those who have been vaccinated. But again, the fact that the impact of vaccines on the transmissibility of a particular variant (especially the B.1.617.2, or Delta, variant, which has been widely reported as being more infectious and transmissible) is yet to be known with a fair degree of certainty adds another layer of complexity.

Scientific evidence appears to confirm that existing vaccines are reasonably effective against the new variants, but real-world data on their effectiveness are still insufficient to draw strong conclusions. Although it is becoming increasingly clear that the rate of infection is lower among the vaccinated—in fact, the rate of contracting a severe disease that may need hospitalisation is much lower—there is a concern that the current vaccine versions may not guarantee the same level of protection against future variants. This has spurred the development of booster doses of vaccines, raising new questions for science. For instance, what is the ideal interval between doses? Would a combination of vaccines provide greater efficacy? Will those infected with SARS-CoV-2 in the past require a second dose at all? These questions and the debates around them are clearly the outcome of the progress of science in understanding and dealing with the coronavirus.

The debate within the scientific community (and the ensuing confusion among health policy administrators) over the appropriate dosage interval—ranging from four weeks to 45 weeks—between two Oxford/AstraZeneca doses to achieve optimum efficacy is a case at hand. Although there seems to be a growing consensus that a 12-week gap between doses is optimum, arriving at any definite conclusion in this regard through the process of scientific verification will take time. Longer gaps have in the past been associated with more effective immunological responses, but the decision eventually will have to take into account other factors, including real-life effectiveness of the first dose, the dominant variant in a cluster, the risk-profile and vulnerabilities of the population, and the social reality of actual vaccine availability. In fact, some of these aspects of social reality place an impossible burden on science in the sense that science cannot be expected to resolve some of these problems.

Another striking instance of the phenomenon’s dynamic nature, leading to newer unknowns as part of its evolution, is the rising incidence of fungal infections, such as mucormycosis, in the course of treating relatively severe COVID-19 patients with therapeutics such as oxygen support and steroids. In fact, it is suspected that the disease itself may be leading to high sugar levels and eventually, in some cases, mucormycosis. The science of pathology and therapeutics of fungal diseases in humans is comparatively less developed than that of viral and bacterial diseases. This side-effect of the pandemic, however, has led to renewed attention on fungal diseases among the medical science fraternity. The different treatments and therapies to deal with COVID-19 appear to be revealing new layers of reality, engendering new questions to explore.

Epistemological limitations

The COVID-19 pandemic has also brought to the fore the limitations of science posed by the question, “How do we know what we know?” Given the extreme complexity of the phenomenon, the basis of our knowledge is itself uncertain and evolving.

For instance, consider the nature of the spread of COVID-19. It is dynamic and often lacks a pattern. Also, a large proportion of those infected are asymptomatic. These characteristics of the disease render information-gathering and analysis extremely complicated. Any data-based model that aims to mirror the spread of the disease has to at first incorporate the disease dynamics and its irregularity, which, in turn, requires consistently high levels of testing and tracing. The tendency of the virus to mutate as it spreads implies that such studies will have to take into account the nature of the variant that is spreading in a particular region. This would require regular data on genome sequencing that could be fed into the model. Such studies will certainly need to factor in the demographic features and profile of biological risks and vulnerabilities of the population, along with the proportion of the population that has already contracted the virus (disaggregated by the demographic features and biological profiles).

As vaccination programmes progress, they will add newer dimensions to reckon with. Social factors such as population density and quality of living space, awareness and acceptance of COVID-19 appropriate protocol, and the effectiveness of administrative and community level surveillance programmes also play a significant role in determining the spread of the disease. In other words, such studies will have to take into account the variables that are internal to the epidemiological and evolutionary trajectory of the virus (which itself may not be predictable), the demographic and biological characteristics of the host population, and the social reality of the region where the host and the virus interact. As already mentioned, all these factors are dynamic. The severity of the disease and the effectiveness of vaccines are additional imponderables that would emerge as the pandemic progresses.

Given the heterogeneities in and specificities of all these factors, scaling up such data models to predict the disease spread is another challenge altogether. Any such attempt must take into account, in the words of Satyajit Rath, renowned immunologist and specialist in infections and diseases with the Indian Institute of Science Education and Research (IISER), “the heterogeneities, the appropriate degree of granularity of sampling, and the extent and scale of data collection”. Without timely access to such detailed and granular information that provides insight into the different types of clusters that are exposed to the virus, any model would remain a mere mathematical exercise, which often leads to skewed results. Developing models to predict the trajectory of the coronavirus, therefore, is an extremely difficult exercise, fraught with uncertainties. A recent commentary titled “Predicting an Epidemic Trajectory is Difficult”, published in the Proceedings ofthe National Academy of Sciences , captures this limitation metaphorically:

“Predicting the trajectory of a novel emerging pathogen is like waking in the middle of the night and finding yourself in motion—but not knowing where you are headed, how fast you are travelling, how far you have come, or even what manner of vehicle conveys you into the darkness.”

Estimates of mortality

The limitation with regard to the method of seeking information escalates multifold when the phenomenon in question is shockingly sudden and results in a huge mass of new sensations. One of the many glaring instances of this complexity during the pandemic has been the estimates of mortality. The sudden spike in deaths, coupled with the fact that COVID-19 fatalities occur in different ways, has made compiling the fatality count difficult all over the world. The existing methods of counting deaths have proven to be inadequate. Further, the pseudo-scientific conduct of many governments, often in the name of “national prestige”, has manifested itself in deliberate attempts to hide or distort mortality data or to thwart efforts to improve information-gathering methods despite advice from scientific experts. Bharmar Mukherjee, a biostatistician and Professor of Epidemiology at the School of Public Health, University of Michigan, United States, who has been involved in tracking the trajectory of the pandemic in India, explains this complexity in the following words:

“The all-cause-mortality data from India has always been imperfect even before the pandemic, with a large proportion of deaths not medically reported, particularly deaths that happen outside health-care facilities and in rural areas. During the pandemic, the under-reporting of COVID cases and deaths became a more acute problem. A part of the reason is of course the pressure on the system, natural problems related to misclassification of cause of deaths, limited testing, but there appears to be an effect of the desire to maintain public image. It is hard to tease apart the confluence of factors that leads to the under-reporting.”

To get a better sense of the actual scale of fatalities, researchers and journalists are now using other methods, such as by calculating the number of “excess deaths” during the pandemic. A recent report by the Institute for Health Metrics and Evaluation (IHME) has used an updated methodology that accounts for “excess deaths” to conclude that the number of deaths that can be directly attributed to the disease is about seven million, a much higher figure than what the official sources indicate (“Counting the dead”, Frontline , June 4, 2021). Estimates in the media of “excess deaths” using data from different municipal corporations in India also point to significant under-counting in official records. It is evident that the usual methods of accounting for casualties have failed in the face of an unprecedented situation.

Searching for the “best” explanation

These epistemological uncertainties often allow for hurried and skewed judgments based on partial information, and often informed by ideological biases. The limitations of data and method leading to hasty conclusions are certainly a factor that enhances the gap between a phenomenon and its knowledge. In such instances, social beliefs and prejudices act as arbiters to questions that are essentially epistemological.

A striking example of this is the ongoing debate about the origins of SARS-CoV-2. There are two distinct theories in circulation. One argues that the virus originated in the wild, most probably in some species of bats, and then jumped species before reaching humans in a mutated form. Such jumping of species by pathogens, or zoonosis, is not uncommon. Many pandemics and epidemics have been attributed to the phenomenon, and they are therefore called zoonotic diseases.

The other hypothesis is that the pandemic was caused by an accidental release of a virus from a laboratory in Wuhan, the capital of Hubei province in China (some extreme versions of this hypothesis claim that the release was deliberate). The virus, some argue, was already available in the laboratory’s inventory. Others state that it was, in fact, an engineered or manipulated virus created as a result of what are broadly termed as “gain of function” experiments conducted by the laboratory on coronaviruses. These experiments include inoculation of different animals with various microbes and the introduction of deliberate mutations in microorganisms. While controversies surround such scientific experiments, they are not uncommon and are generally done to understand the risk of new zoonotic diseases and to develop vaccines or other therapeutics in advance.

The debate, one must appreciate, is not evenly poised. In the words of Kristian G. Andersen, Professor, Department of Immunology and Microbiology (California campus), The Scripps Research Institute, California, U.S.,

“However, while both scenarios [animal-human spillover and lab-leak] are possible, they are not equally likely.... Precedence, data and other evidence strongly favour natural emergence as a highly likely scientific theory for the emergence of SARS-CoV-2, while the lab leak remains a speculative incomplete hypothesis with no credible evidence.”

The general consensus in the scientific community has been that SARS-CoV-2 is an example of a zoonotic transmission. A team of scientists commissioned by the World Health Organisation (WHO) in December 2020 considered four possible pathways for the introduction of the virus: i. direct zoonotic transmission, ii. introduction through intermediate host followed by zoonotic transmission, iii. introduction through the cold/food chain, and iv. introduction through a laboratory incident. On the basis of available evidence, the team concluded that the first pathway was a “possible-to-likely pathway”, while the second was regarded to be a “likely to very likely pathway”. The introduction through cold/food chain products was considered a “possible pathway”. The introduction of the virus through a laboratory incident was regarded to be an “extremely unlikely pathway”.

However, several scientists and science journalists of repute have called for more studies before arriving at any definite conclusion. Many of them can be termed objectively sceptical, like the group of 18 scientists who wrote to the magazine Science , expressing the need for greater clarity about the pandemic’s origins. They demand a proper investigation of both hypotheses, one that is “transparent, objective, data-driven, inclusive of broad expertise, subject to independent oversight, and responsibly managed to minimise the impact of conflicts of interest”. Some of these scientists, such as Ralph Baric, a renowned virologist and a Professor at the University of North Carolina, U.S., agree with the natural spillover hypothesis but advocate a thorough investigation into different aspects of the evolution of the coronavirus and its transmission into humans, including the safety precautions put in place in laboratories that experiment with such microbes. There are, however, others who are more inclined to believe the lab-leak theory.

Such scepticism is healthy for the development of science. In fact, the WHO team of scientists themselves has stressed the need for a phase II study to further investigate the leads that have been arrived at. While there is consensus in the scientific community that these follow-up studies should be initiated immediately, the geopolitics surrounding the issue is threatening to become a major impediment to any objective inquiry—yet another example of society impinging upon the method of science in a manner that slows its progress. Cooperation within the scientific community and between nations is indispensable to the progress of any such inquiry.

Undoubtedly, there is evidence to support the natural origin hypothesis, but, it cannot be considered conclusive. For instance, there are questions regarding the progenitor of SARS-CoV-2. Neither has the intermediary species through which the virus was transmitted from bats to humans (considering that it was not a case of direct zoonosis) been identified. The inability to pinpoint these “smoking-guns”, despite testing thousands of samples from hundreds of wildlife species, lends credence to the lab-leak theory. The Middle East Respiratory Syndrome (MERS), a viral respiratory disease caused by another coronavirus (MERS-CoV) that was first identified in Saudi Arabia in 2012, required far fewer investigations to identify the intermediary animal source—dromedary camels—of infection in humans. This certainly strikes as very strange in itself. But when one studies the history of other zoonotic diseases such as Severe Acute Respiratory Syndrome (SARS), Human Immunodeficiency Virus (HIV) and Ebola, the picture begins to change (“ An engineered controversy ”, Frontline , July 16, 2021). The trajectory of zoonotic diseases is known to be complex, with doubts and uncertainties in the story. Identifying the trajectory of zoonotic transmissions is painstaking and time-consuming research. As a matter of fact, many other aspects of the science around zoonosis, in general, are itself uncertain and evolving. For instance, the evidence pertaining to the relationship between zoonotic diseases and biodiversity, or between human activities and zoonotic transmissions, is still emerging. Unsurprisingly, there is a vigorous scientific debate among competing hypotheses on these questions as well (“ Pseudoscience amid pandemic ”, Frontline , November 6, 2020).

Notwithstanding the actual transmission route of SARS-CoV-2, which will eventually be revealed, hopefully through scientific methods (and not geopolitics), the philosophical question that remains pertains to limitations of data and the methods of gathering evidence. It falls in the realm of epistemology. Identifying the progenitor and intermediary host is a challenging problem that has to account for the way of sampling, the sample size, the geographical targeting of samples, the species to be sampled, and the degree of seroprevalence among the intermediary hosts. A negative result may not necessarily imply the absence of an intermediary animal. It may just indicate the need for a better search, something that the WHO phase II studies should plan for. For instance, it has been suggested that further studies should aim at testing blood samples stored since 2019 in blood banks across China for antibodies for the coronavirus. Such tests may provide evidence of how far back in time the virus had been present among humans.

There are other more technical questions, such as the “occurrence of a furin cleavage site” in SARS-CoV-2 that enhances the receptor-binding process which aids the entry of the virus into human cells. This has been cited to prove that the virus was an engineered one (“ An engineered controversy ”, Frontline , July 16, 2021). However, here again, SARS-CoV-2 is not unique; there are other viruses, including other coronaviruses, known to be having similar characteristics. There is no consensus in the scientific community on the role played by the furin cleavage site in SARS-CoV-2 in infecting humans. Even David Baltimore, a distinguished virologist and Nobel laureate, who was initially reported to have regarded this feature of the virus as a “smoking-gun” validating the lab-leak theory, has retracted his statement. There are other scientists who claim that the evolutionary distance between SARS-CoV-2 and its closest known relative negates the possibility of lab manipulation.

To put it succinctly, the evidence on the origin of the virus is not yet conclusive. But is it tantamount to negating a hypothesis that appears to be the most plausible and explains the available evidence better than another competing hypothesis? In the face of limited evidence, science, of course, continues its search for new evidence, but at the same time it often moves ahead with what is philosophically termed as “abduction”, or “inference to the best explanation”, a form of reasoning that allows a jump from the premise that a given hypothesis provides a better explanation for the evidence than any other competing hypothesis to the conclusion that the given hypothesis is true. The truth in this case is, of course, approximate, tentative and open to scrutiny against further evidence. Notwithstanding the philosophical question of the explanatory power of competing hypothesis in the face of limited evidence, the debate reflects the problem’s complex nature and the epistemological limitations about it. It is also evident that a meticulous search for evidence will be a long-drawn affair, leaving, in the meanwhile, scope for easy inferences that often may titillate prejudices.

Varying perceptions about scientific development

The implications of the trajectory of progress of science that are otherwise confined to academic debates are vividly at play (and will greatly enrich the academic debates for many years to come). However, the complexity of the phenomena—the reality of the pandemic and its study and discovery through science—is difficult for a layperson to appreciate. The fact that it is objective yet uncertain, contingent, and evolving in a fashion that can only be partially predicted, cannot be expected to be grasped, especially in the context of a pandemic that has irrevocably impacted material lives and world views.

There is not a section of society that has been left untouched by the pandemic. Unsurprisingly, its sudden, severe and widespread impact has resulted in a strong felt-need among all—be it a layperson, a subject expert or a scientific researcher—to understand and explain the phenomenon’s nature and find solutions to the crisis. It is, therefore, natural to witness many efforts in this direction by different sections of society, from their respective standpoints. There is a sense of extreme urgency in order to know and to act in real time. We are trying to build a plane as we fly it and at great speed. Naturally, there is great expectation from science to deliver resolutely and immediately.

The progress of scientific inquiry, however, is complex and time-consuming. There is limited scope for quick fixes. Science progresses through severe competition among several hypotheses. These theories are continuously weighed against a rigorous scrutiny of logic and, most importantly, against the grain of evidence. It is through these debates, validated or negated by evidence, that modern science advances. This stringent method of scientific discovery renders it a self-correcting character. But it also implies that the process of scientific progress takes time and its results are often interim and subject to change. The urgent felt-need to make sense of a phenomenon may drive the trajectory of scientific inquiry in a specific direction, through increased financial and intellectual investments, but this does not guarantee progress in science. Scientific progress is real, in the sense that it has an objective and autonomous character, notwithstanding the fact that the practice of science, including the choice of research problems, is socially shaped.

Take the example of the debate on the virus’ mode of transmission: is it airborne or does it travel only through droplets? The scientific debate on this question has raged on for a year. It began with the almost foregone conclusion that the disease spreads through droplets. But in the course of a year the consensus among the research community is that aerosols travelling through air provide the main medium for transmission of the virus. The debate has opened up new questions about the criterion used to define droplets and aerosols. Noticeably, the debate was not just academic; it had vital implications for public health measures, such as the type of mask to wear, the importance of ventilation and the appropriate distancing norms required to protect people from the virus. The debate has contributed to the knowledge about the medium of spread of many contagious diseases and may redefine the idea of what constitutes an “air-borne disease”. It will throw up new research questions in the field of disease pathology and the history of the sciences.

Similarly, it has taken time to test the efficacy and effectiveness of treatments such as the anti-viral drug Remdesivir and plasma therapy which, until recently, were used in a trial-and-error mode. There is also the case of the drug Hydroxychloroquine (HCQ), which was celebrated as the panacea for COVID-19 in the early days of the pandemic but was discarded after a few months. Breakthrough infections among the already vaccinated or correlates of protection for SARS-CoV-2 vaccines are yet other examples of how science is still trying to establish knowledge, even as newer variants appear to add to the complexity of these issues.

The time-consuming and stringent method of science and the fact that scientific results are contingent, subject to verification and correction, may appear to be a limitation of science, especially in the face of an acute humanitarian crisis that demands immediate solutions. There is a clear mismatch between the expectations of science from different sections of society and the nature and pace of scientific development—a mismatch that puts a social pressure on the practice of science, lays the basis for scepticism and allows different kinds of speculation to circulate in society.

For instance, take the process of the development of vaccines for SARS-CoV-2. Even though the vaccines were developed in record time, society in general wanted them to be available at an even faster pace. However, before the vaccines could be deemed fit for mass use, they had to go through various phases of testing for evidence pertaining to immunogenicity, safety, efficacy and effectiveness and the monitoring of their potential adverse impacts in real-life conditions. Testing a vaccine is a long–drawn-out process that requires meticulous collection of data in laboratories, in clinical and real-world conditions. However, dire need resulted in emergency-use authorisation of several vaccines before testing them in real-life conditions. In fact, Covaxin, developed in India by Bharat Biotech International Limited, was considered for accelerated approval even before the results from the Phase 3 trials for its efficacy in humans were available for publication and review. The process of approvals in this case gave the impression that it was being driven by politics rather than scientific rationale. Given the gravity of the crisis, “Emergency Use Approvals” for treatments, medicines and vaccines have been the norm rather than the exception. No other vaccine, however, has been approved without the results of Phase 3 trials being made public.

The merits of the exception made in this particular case (or in any other), including its ethical and scientific repercussions, will certainly be up for debate among experts in the future. However, notwithstanding the nature of the exception, it is evident that the rigours of scientific practice were compromised partially, but that was warranted by the acuteness of the crisis.

Highlighting a dialectical contradiction

Reality, as the object of scientific inquiry, and its understanding engendered by science are bound in a dialectical contradiction. Each progressive step made by science uncovers a new aspect of reality, but it is also a step that leads to new layers of the unknown and begets newer questions to explore. This contradiction allows for a perpetual gap between reality and its comprehension through the accumulation of scientific knowledge.

The contradiction stems from the fact that while reality is infinite, the pursuit of science is an endless human endeavour to gain an increasingly accurate understanding of that objectively indeterminate and ever-changing reality. Science is a conscious effort, driven by wonder, and, most importantly, by material needs, to make sense of reality, including the laws that govern it, and act on it based on the knowledge gained. It is a never-ending process that uncovers new layers of unknowns at every turn, kindling “a light in Nature”, to use the words of Francis Bacon, “a light which in its very rising touch and illuminate all the border regions that confine upon the circle of our present knowledge”.

This gap between reality and its scientific comprehension poses a peculiar challenge for science, at times leading to extreme demands on it. Science is expected to make complete sense of reality and with absolute certainty. It is supposed to invest humans with the capacity to intervene and shape reality at every turn. Uncertainty, however, is inherent in reality and the method of science. A real phenomenon is extremely complex, has a plethora of dimensions, and is affected by a multitude of other phenomena. To complicate matters even more, these dimensions and phenomena themselves are dynamic as well. The scientific understanding of any real phenomenon and the ensuing capacity to intervene in and transform it in any effective manner are limited by the make-up of reality and the limitations in the current state of knowledge. Of course, the development of science and technology leads to an expansion of these capabilities. We now know better the laws that govern a natural phenomenon and are at times able to use that knowledge to effectively intervene in nature. But at other times, science may end up discovering only a few dimensions of the phenomenon. And, despite the increasing scientific knowledge, efforts to transform an aspect of reality may not yield the desired results.

The complication becomes manifold when the phenomenon in question is one that has put our material world in a deep and unprecedented crisis. The pandemic caused by the SARS-CoV-2 coronavirus is one such remarkable instance, a peculiar conundrum in the history of science. The novelty and complexity of the phenomenon imply the persistence of significant levels of uncertainty despite the rapid and unprecedented developments in science made possible by the great commitment and unprecedented cooperation on a truly global scale among the scientific community. While there is an expectation from science to provide an immediate and comprehensive explanation of, as well as thoroughgoing resolution to, the pandemic, the reality is that science, despite its great and real success in understanding the pandemic and providing the means to control it, can, for now, only deliver partial solutions that are laden with uncertainties.

Sandipan Baksi is a historian of science. His primary research interest is history of science in India under colonialism, with a particular focus on agricultural science. He is Director, Foundation for Agrarian Studies, Bengaluru.