Scientific Advancement during Pandemic Times

Estimates of Mortality Rate

The COVID-19 pandemic, produced by the coronavirus SARS-CoV-2, is a watershed moment in science. Global collaboration and data sharing have fuelled extraordinary advances in epidemiology, clinical care, prevention, treatment, and the speed with which vaccines are developed. All of this would not have been possible without the relentless work, commitment, dedication, and insight of scientists and researchers around the world, from lab workers to clinical trial primary investigators and everyone in between. However, these scientific breakthroughs have highlighted flaws in the scientific research environment and provide crucial lessons for the future.

Uncertainties about the Nature of the Virus

Reality is objectively boundless, indefinite, and ever-changing, and it encompasses both non-human nature and human civilisation. It moves and is founded on objective laws that are independent of the human intellect, even if those laws contain uncertainty. SARS-CoV-2 is an example of how uncertainty is intrinsic to reality. The novel virus first surfaced at the tail end of 2019 and immediately began having a profound impact on human existence and society. The speed with which it expanded and the breadth of its reach were unprecedented. Its origin, evolution, and personality were unknown. In terms of scientific endeavour, these years have been extraordinary. Science has unearthed numerous unknowns concerning the pandemic while working at a breakneck pace. As a result of collaborative efforts, we now know a lot more about the virus and the sickness it produces, and with a considerable amount of certainty.

Research on subjects unrelated to COVID-19 has been hampered: According to Michael Lauer of the US National Institutes of Health, 80 percent of clinical trials have been halted or terminated. Many researchers were compelled to put their own research on hold to focus on patient care in overburdened hospital systems as resources were diverted to the pandemic. Long-planned HIV/AIDS and other infectious illness trials, for example, were suspended as researchers focused on COVID-19. We won’t know the entire cost of these quick shifts in research priorities for several years. It’s critical to ensure that research systems have the capacity and resilience to adapt to changing objectives while minimising disruption to ongoing research. Nonetheless, there is still a lot to learn. Uncertainties concerning the virus’s origin, nature, distribution, and impact on people’s lives and livelihoods continue. The fact that the virus mutates as it travels, introducing new unknowns, adds to the confusion. New research questions have arisen as a result of concerns regarding increasing infectivity, transmissibility, and severity of emerging variations.

Following “Variants of Concern,” according to evolutionary reasoning, are far more transmissible than the virus’s original version. The argument also supports the possibility of variants that elude the immune response of persons who have already been infected with the virus. Because of the logical conclusion indicated before, some of the newer types are spreading swiftly and impacting a huge number of people. However, because the population infected by the newer variants is qualitatively different (both socially and biologically) from that infected by the original variant, it’s challenging to capture concepts like virus transmissibility in a meaningful way. To put it another way, the virus isn’t the only one that’s evolving; the host population and the environment in which the virus interacts with the host are also evolving, adding to the complexity. What appears to be the nature or influence of a single virus variation is actually the result of a complicated interplay.

Surprisingly, any intervention that inhibits the virus’s distribution, such as vaccination, increases the virus’s evolutionary pressure and forces it to mutate into variants that can potentially resist the vaccine. However, in order for this to happen, the virus must spread swiftly and infect a significant number of human hosts. This occurrence can only be avoided by mass vaccination of the human population. Leaving a huge population unvaccinated puts everyone at risk, including those who have received vaccinations. However, the fact that the impact of vaccinations on the transmissibility of a specific variety (particularly the B.1.617.2, or Delta, form, which has been extensively reported as being more infectious and transmissible) is still unknown adds to the complication.

Existing vaccines appear to be moderately effective against the new variations, according to scientific research; but, real-world data on their efficiency is insufficient to draw clear judgments. Although it is becoming increasingly clear that vaccinated people have a lower rate of infection—in fact, they have a much lower rate of contracting a severe disease that may require hospitalisation—there is concern that current vaccine versions may not provide the same level of protection against future variants. As a result, booster vaccine dosages have been developed, generating additional scientific challenges. What is, for example, the ideal dose interval? Is it possible that a vaccine cocktail would be more effective? Will people who have previously been infected with SARS-CoV-2 need a second dose? These topics, as well as the disputes that surround them, are unmistakably the result of scientific progress in understanding and treating the coronavirus.

The disagreement within the scientific community (and the resulting uncertainty among health policy officials) about the optimal dosage interval between two Oxford/AstraZeneca doses to ensure optimum efficacy—ranging from four weeks to 45 weeks—is one example. Although there appears to be a growing consensus that a 12-week gap between treatments is ideal, scientific verification will take time to reach a definitive decision in this area. Longer gaps have been linked to more effective immunological responses in the past, but the decision will eventually have to consider other factors, such as the first dose’s real-world effectiveness, the dominant variant in a cluster, the population’s risk profile and vulnerabilities, and the social reality of actual vaccine availability. Indeed, some of these characteristics of social reality impose an impossible weight on research in the sense that science cannot be expected to fix some of these issues.

Another striking example of the phenomenon’s dynamic character is the increased occurrence of fungal infections such as mucormycosis in moderately severe COVID-19 patients treated with medications such as oxygen assistance and steroids. It’s even possible that the condition causes excessive blood sugar and, in certain cases, mucormycosis. In comparison to viral and bacterial diseases, the knowledge of pathology and therapies for fungal diseases in humans is still in its infancy. However, as a result of this side effect of the pandemic, medical scientists are paying closer attention to fungal illnesses.

The Limitations of Perception

The COVID-19 pandemic has also highlighted the scientific constraints raised by the question, “How do we know what we know?” Because of the phenomenon’s great intricacy, the foundation of our understanding is in flux. Consider the nature of COVID-19’s distribution. It is fluid and frequently devoid of a pattern. Furthermore, the majority of people sick are asymptomatic. Because of the disease’s peculiarities, obtaining and analysing information is particularly difficult. Any data-based model aimed at stimulating disease propagation must first account for disease dynamics and irregularities, which necessitates consistent high levels of testing and tracing.

Due to the virus’s proclivity for mutating as it spreads, such research must consider the characteristics of the variation circulating in a given area. This would necessitate regular genome sequencing data that could be supplied into the model on a regular basis. The demographic characteristics and profile of biological hazards and vulnerabilities of the population, as well as the fraction of the population who has already infected the virus, would undoubtedly be taken into account in such investigations (disaggregated by the demographic features and biological profiles).

Vaccination programmes will expand in scope as time goes on, introducing additional variables to consider. The effectiveness of administrative and community-level surveillance programmes, as well as social factors such as Info 1density of population and quality of living space, awareness and acceptance of COVID-19 appropriate protocol, and awareness and acceptance of COVID-19 appropriate protocol, all play a role in determining the disease’s spread. To put it another way, such studies will have to account for variables such as the virus’s internal epidemiological and evolutionary trajectory (which may or may not be consistent), the demographic and biological characteristics of the host population, and the social reality of the region where the virus and the host interact. All of these variables are dynamic, as stated previously. As the pandemic continues, more unknowns arise, such as the severity of the sickness and the efficiency of vaccines.

Speeding up such data models to predict disease transmission is an entirely different task, given the heterogeneities and specificities of all of these parameters. “The heterogeneities, the right degree of granularity of sampling, and the extent and scope of data gathering,” says Satyajit Rath, a well-known immunologist and specialist in infections and diseases at the Indian Institute of Science Education and Research (IISER). Any model would be a meaningless mathematical exercise without timely access to such comprehensive and detailed information that provides insight into the different types of clusters that are exposed to the virus. As a result, developing models to forecast the coronavirus’s path is a challenging and risky task.

Estimates of Mortality Rate

When the phenomena in issue occur unexpectedly and result in a massive influx of new feelings, the limitation in terms of the way of gathering information multiplies. The estimations of death have been one of the many apparent examples of this intricacy during the pandemic. The unexpected increase in deaths, along with the fact that COVID-19 fatalities occur in a variety of ways, has made tallying the number of deaths difficult all across the world. Existing Info 2death-counting approaches have shown to be ineffective. Furthermore, many governments’ pseudo-scientific behaviour has manifested itself in purposeful attempts to suppress or alter mortality data or to thwart efforts to improve data-gathering procedures despite scientific professionals’ advice, frequently in the name of “national prestige.” Other methods, such as calculating the number of “excess deaths” during the pandemic, are now being used by experts and media to obtain a better idea of the true scale of mortality. According to recent research by the Institute for Health Metrics and Evaluation (IHME), the number of deaths directly related to the disease is around seven million, far more than official sources suggest.

Estimates of “excess fatalities” in the media based on data from several Indian municipal corporations’ hint to severe under-counting in official statistics. In the face of an unprecedented circumstance, it is clear that traditional procedures for calculating casualties have failed.

Hypothesis around the Spread

These epistemological ambiguities frequently lead to rushed and distorted conclusions based on incomplete information, which are frequently influenced by ideological prejudices. Data and procedure limitations that lead to rash conclusions are undoubtedly a factor that widens the gap between a phenomenon and its understanding. In such cases, social attitudes and prejudices serve as arbiters for genuinely epistemological concerns. The ongoing controversy over the origins of SARS-CoV-2 is a good example of this. In circulation, there are two different theories. One theory claims that the virus began in the wild, most likely in bats, and then spread across species before reaching humans in a modified form. It’s not uncommon for infections to jump species, which is known as zoonosis. The phenomena have been linked to a number of pandemics and epidemics, which are referred known as zoonotic illnesses.

The alternative theory is that the pandemic was started by an unintentional discharge of a virus from a laboratory in Wuhan, China’s capital (some extreme versions of this hypothesis claim that the release was deliberate). Some contend that the virus was already in the laboratory’s inventory. Others claim it was an engineered or modified virus generated as a result of what are known as “gain of function” tests on coronaviruses undertaken by the laboratory. In these trials, different animals are inoculated with diverse bacteria, and purposeful alterations in microorganisms are introduced. While such scientific trials are not without controversy, they are widespread and are used to better evaluate the danger of developing zoonotic diseases and to create vaccines or other medicines in advance.

It’s important to recognise that the discussion isn’t evenly balanced. “However, while both possibilities [animal-human overflow and lab-leak] are plausible, they are not equally likely,” says Kristian G. Andersen, Professor, Department of Immunology and Microbiology (California campus), The Scripps Research Institute, California, U.S. Natural emergence is a highly likely scientific theory for the emergence of SARS-CoV-2, based on precedent, data, and other facts, whereas the lab leak remains a dubious incomplete hypothesis with no convincing proof.

SARS-CoV-2 is thought to be a zoonotic transmission, according to the scientific community. In December 2020, the World Health Organization (WHO) commissioned a team of scientists to investigate four possible pathways for the virus’s introduction: i. direct zoonotic transmission, ii. introduction via intermediate host followed by zoonotic transmission, iii. introduction via the cold/food chain, and iv. introduction via a laboratory incident. The team determined that the first approach was a “possible-to-likely pathway” based on available information, while the second was a “likely to very probable pathway” based on available evidence. A “possible channel” was identified for introduction through cold/food chain items. The virus’s introduction via a laboratory mishap was deemed “very implausible.”

However, a number of well-known scientists and scientific journalists have advocated for more research before drawing any conclusions. Many of them, like the group of 18 experts that wrote to the magazine Science, Info 3emphasising the need for further clarity on the pandemic’s origins, can be classified as objectively sceptical. They urge a thorough assessment of both hypotheses that is “transparent, objective, data-driven, inclusive of broad knowledge, subject to independent oversight, and responsibly managed to minimise the influence of conflicts of interest,” according to them. Some of these scientists, such as Ralph Baric, a renowned virologist and Professor at the University of North Carolina in the United States, agree with the natural spill over hypothesis but advocate for a thorough investigation into various aspects of the coronavirus’ evolution and transmission into humans, including the safety precautions implemented in laboratories that experiment with such microbes. Others, on the other hand, are more likely to believe in the lab-leak scenario.

This level of scepticism is beneficial to scientific progress. Indeed, the WHO team of scientists has emphasised the need for a phase II investigation to further analyse the findings. While the scientific community agrees that these follow-up studies should be launched right away, the geopolitics surrounding the issue threatens to become a major impediment to any objective investigation—yet another example of society interfering with the scientific method in a way that stifles progress. Cooperation among scientists and between nations is critical to the success of any such investigation. There is, without a doubt, evidence to support the natural origin concept, yet it is insufficient to be deemed conclusive. The progenitor of SARS-CoV-2, for example, is a topic of debate. There has also been no identification of the intermediate species via which the virus was transmitted from bats to humans (because it was not a case of direct zoonosis). Despite examining thousands of samples from hundreds of wildlife species, the lab-leak argument is supported by the inability to pinpoint these “smoking-guns.” The Middle East Respiratory Syndrome (MERS), a viral respiratory disease caused by another coronavirus (MERS-CoV) that was originally discovered in Saudi Arabia in 2012, required significantly less investigations to identify the human infection’s intermediate animal source—dromedary camels. In and of itself, this appears to be pretty unusual. The path of zoonotic illnesses is well-known to be complicated, with many concerns and uncertainties. Identifying the path of zoonotic transmission is a time-consuming and difficult task. Many other parts of zoonosis science, in general, are both unknown and changing. Evidence on the association between zoonotic illnesses and biodiversity, or between human activities and zoonotic transmissions, for example, is still emerging.

Regardless of the exact transmission route of SARS-CoV-2, which will be uncovered someday, preferably through scientific techniques (rather than geopolitics), the philosophical question that remains is one of data constraints and evidence gathering methodologies. It belongs to the category of epistemology. The method of sampling, the sample size, the geographical targeting of samples, the species to be collected, and the degree of seroprevalence among the intermediary hosts all have a role in determining the progenitor and intermediary host. A negative result does not always suggest the lack of an intermediary animal. It could just signal the necessity for a more thorough search, which the WHO phase II investigations should account for. Further research could, for example, look into examining blood samples maintained in blood banks across China since 2019 for coronavirus antibodies. These testing could reveal how long the virus has been circulating in humans.

Other, more technical questions include the “presence of a furin cleavage site” in SARS-CoV-2, which promotes the virus’s entrance into human cells by enhancing the receptor-binding process. This has been used to support the theory that the virus was created artificially. SARS-CoV-2 is not the only virus with similar properties; additional viruses, including coronaviruses, have been identified. The role of the furin cleavage site in SARS-CoV-2 infection in humans is a topic of debate among scientists. Even David Baltimore, a virologist and Nobel laureate, has withdrawn his assertion that this property of the virus was a “smoking-gun” that validated the lab-leak scenario. Other scientists argue that the evolutionary distance between SARS-CoV-2 and its closest known relative makes lab manipulation impossible.

To put it another way, there isn’t enough evidence to say where the virus came from. Is it, however, equivalent to dismissing a hypothesis that appears to be the most probable and best explains the existing evidence? Science, of course, continues its search for new evidence in the face of limited evidence, but it also frequently moves forward with “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. Of course, the truth, in this case, is imprecise, tentative and subject to further study. Regardless of the philosophical challenge of competing hypotheses’ explanatory capacity in the face of insufficient data, the discussion shows the problem’s complexity and epistemological limits. It is also obvious that a rigorous search for evidence will take a long time, leaving room for quick assumptions that may titillate preconceptions in the meanwhile.

Various perspectives on scientific progress

The ramifications of science’s advancement, which are usually reserved for academic arguments, are prominently on display (and will greatly enrich the academic debates for many years to come). However, a layperson’s understanding of the phenomenon—the actuality of the pandemic and its scientific research and discovery—is difficult. The fact that it is objective yet unpredictable, contingent, and changing in a way that can only be partially predicted cannot be expected to be understood, especially in the context of a pandemic that has irreversibly damaged material lives and world perspectives.

The pandemic has affected every part of society. Unsurprisingly, the phenomenon’s abrupt, severe, and widespread impact has created a strong felt need among all—be it a layperson, a topic specialist, or a scientific researcher—to comprehend and explain the phenomenon’s nature and discover answers to the dilemma. As a result, it’s only reasonable to see a variety of initiatives in this direction from various parts of society. In order to know and act in real time, there is a strong sense of urgency. We’re attempting to construct a plane while flying it at a high rate. Science is, understandably, held in high regard for its ability to deliver steadfastly and promptly.

Scientific research, on the other hand, is complicated and time-consuming. There isn’t much room for rapid fixes. Science advances as a result of fierce rivalry between many hypotheses. These theories are constantly put to the test, both in terms of logic and, more significantly, in terms of evidence. Modern science evolves through these discussions, which are either validated or refuted by evidence. This rigorous approach to scientific discovery gives it a self-correcting quality. However, it also suggests that scientific advancement takes time and that the results are frequently temporary and vulnerable to change. The intense desire to understand a phenomenon may push scientific study in a particular direction, resulting in higher financial and intellectual investments, but this does not ensure scientific success. Despite the fact that the practise of science, including the choice of research problems, is socially moulded, scientific progress is real in the sense that it has an objective and autonomous character.

Consider the disagreement over the virus’s route of transmission: is it airborne, or does it only spread via droplets? This question has been the subject of a year-long scientific debate. It all started with the nearly inescapable conclusion that the disease is spread via droplets. However, over the course of a year, the research community has come to the conclusion that aerosols travelling through the air are the predominant mode of virus transmission. The discussion has raised additional concerns regarding the criteria used to classify droplets and aerosols. The issue was not merely intellectual; it had significant ramifications for public health measures such as the sort of mask to wear, the significance of ventilation, and the appropriate distance standards needed to protect individuals from the infection. The argument has advanced our understanding of the mode of transmission of many contagious diseases and may reshape our understanding of what defines an “airborne disease.” It will generate new research issues in the fields of disease pathology and scientific history.

Similarly, testing the efficacy and effectiveness of therapies such as the antiviral medicine Remdesivir and plasma therapy, which were previously utilised in a trial-and-error approach, has taken time. There’s also the case of the medicine Hydroxychloroquine (HCQ), which was heralded as a COVID-19 panacea in the early days of the outbreak but was abandoned after only a few months. Breakthrough infections among those who have already been vaccinated or correlates of protection for SARS-CoV-2 vaccinations are two other examples of how research is still working to establish understanding, even as fresh varieties appear to add to the complexity of these challenges. Scientific discoveries are contingent, subject to verification and correction, which may appear to be a limitation of science, especially in the face of an extreme humanitarian situation that demands quick remedies. There is a distinct mismatch between different sectors of society’s expectations of science and the nature and pace of scientific development—a mismatch that puts social pressure on scientific practise, fosters scepticism, and permits various types of speculation to circulate throughout society.

Take, for example, the development of vaccinations against SARS-CoV-2. Despite the fact that the vaccinations were developed in record time, society as a whole expected them to be available even sooner. However, before the vaccines could be approved for widespread use, they had to undergo a series of tests to determine their immunogenicity, safety, efficacy, and effectiveness, as well as the monitoring of any potential adverse effects in real-world settings. Testing a vaccine is a lengthy procedure that necessitates thorough data collection in laboratories, clinical settings, and real-world scenarios.

However, due to a pressing need, numerous vaccinations were approved for emergency use before they were tested Info 4in real-world settings. In fact, Bharat Biotech International Limited’s COVAXIN was considered for accelerated approval even before the results of the Phase 3 trials demonstrating its efficacy in people were available for publishing and review. In this case, the clearance procedure appeared to be driven more by politics than by scientific logic. “Emergency Use Approvals” for treatments, medicines, and vaccinations have become the norm rather than the exception, given the urgency of the problem. No other vaccine, on the other hand, has been licenced without the public release of Phase 3 trial findings.

The merits of the exception made in this case (or any other), as well as its ethical and scientific ramifications, will undoubtedly be debated in the future by experts. Regardless of the nature of the exception, it is clear that the rigours of scientific practise were partially compromised, but this was justified by the severity of the crisis. While there is an expectation that science will provide an immediate and comprehensive explanation of the pandemic as well as a long-term solution, the reality is that science, despite its great and real success in understanding and controlling the pandemic, can only provide partial solutions that are rife with uncertainties for the time being.

References

  1. DOI: https://doi.org/10.1016/S0140-6736(20)32709-4, (2020, December 19) Science during COVID-19: where do we go from here? TheLancet
  2. https://doi.org/10.1787/75f79015-en (2021) COVID-19: A pivot point for science, technology and innovation? OECDiLibrary
  3. Haseltine A William U.S (2021, May 25). How COVID Changed Science. Scientific American
  4. Bakshi Sandipan. ( 2021, September 10), The trajectory of scientific progress in the time of pandemic. Frontline
  5. Krishnaswamy S, Govindarajan T.R, (2021 July 16) The controversy being created about the origins of the virus that causes COVID-19. Frontline
  6. Katakam Anupama (2021, August 27). Why counting the dead matters. Frontline

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