Pandemic – emergence of uncertainty
Early January 2020. A feeling of uncertainty emerged with the initial news of the infection. SARS-CoV-2? A new Acute Respiratory Syndrome? The conference calls started quickly. In Australia, China is nearby. On several dimensions: geographic, economic, social. Prior to the pandemic, China accounted for one-third of all exports and more than 45,000 international students at Australian universities.
An outbreak of respiratory syndromes in Wuhan quickly became a major concern in the Southern hemisphere. On February 1, our borders were closed to China and by mid-March also to Iran, Italy, and South Korea. By March 21, the borders were completely closed for what would turn out to be the majority of 2020, and they remain closed at the beginning of 2021. There is still no travel abroad for Australians unless they obtain a travel permit, and those are rare.
On March 22, as a core measure in the implementation of pandemic response structures, I was given the mandate to set up a critical intelligence unit to support our public policies and services for managing the SARS-CoV-2 pandemic. This decision was based on the realization that the decisions to be made over the next several months would require critical appraisal, by a team with sophisticated capacities for knowledge synthesis, data analysis, and mobilization of clinical expertise. On March 26, the COVID-19 Critical Intelligence Unit launched its activities [https://aci.health.nsw.gov.au/covid-19/critical-intelligence-unit].
Big evidence – volume, velocity, variety, and veracity
As with the concept of big data, the pandemic has generated what might be called big evidence. In terms of volume, more than 100,000 scientific articles (about 4% of the global scientific output for 2020) have been published [Else 2020]. In terms of velocity, more than 30,000 articles were published in pre-publication, many of them first on the newswires, and the intervals between studies and publication have shrunk, especially for articles about the pandemic. In terms of variety, the nature of the articles published has changed over the course of the pandemic, with articles on modeling and diagnosing dominating early on and those on public health interventions and mental health prevailing more recently. Science (and pseudoscience) has permeated social networks. Finally, in terms of veracity, scientific retractions have also been in the news, and numerous polarized opinions and conspiracy theories have emerged, while studies providing contextualized insights remain scarce. More recently, such conclusions relating to vaccine studies have also been the subject of debate.
This pace, cadence, and complexity created significant challenges for decision-making at both the clinical and public policy levels. The role of the unit we established was to conduct, in an unbiased manner, various rapid knowledge syntheses and to mobilize tacit knowledge that could support decision-making. We established a rapid synthesis team (whose reports were produced in under 24 hours early in the pandemic), an empirical data team (which produced a digital dashboard that was updated daily and various weekly reports), a clinical intelligence group (that included various academic clinicians), and a research intelligence group (that coordinated research activities in care and services and public health) [Levesque et al. 2020].
Fundamentally, the unit’s guiding principles are: transparency of information sources, sufficiency in extraction and analysis, triangulation of types of evidence, and transposition to the real-world context. In such a context, the unit’s products had to be fast (often produced in less than 24 hours), fairly exhaustive without being overly so, brief and clear, and focused on the evidence and not on the detail. A continuing challenge is to produce advisories that differentiate between the absence of evidence, evidence of the absence of evidence, evidence of evidence, and the transposition of evidence to address the questions formulated by decision-makers.
Uncertainty as a platform for change – clinical decision-making and public policy
In essence, the pandemic created a paradoxical situation for evidence-based decision-making. First, the scientific evidence was sparse at the beginning of the pandemic and many decisions had to be made in a context of uncertainty. Then, another type of uncertainty was created by the sheer size of the scientific corpus and the fact that the science was emerging at a rapid pace and soon produced a situation in which evidence was contradictory. The evidence changed over time and varied greatly from one context to another.
Because the pandemic is a dynamic phenomenon, with different countries being at different epidemic stages, and with pandemic control measures also varying between contexts, a range of contradictory results have emerged. For example, mask use appears to be effective in some places but not in others, epidemic curves suggest that factors of infection transmission are highly variable, and the indirect effects of the pandemic have not been experienced to the same extent everywhere. This is not to mention the variability in approaches adopted for clinical management of confirmed cases and other patients.
Another emerging paradox has to do with uncertainty and the impact of research on clinical and policy decisions. Even if the quality of scientific output is still tenuous in many respects, it does not take much to influence decision making. While strong systematic reviews usually have difficulty penetrating the clinical sector and the public health planning and policy-making arena in normal times, in this time of pandemic the appetite for evidence, however weak, has increased. Combined with good mechanisms for communication with various clinical groups, ranging from primary care to emergency care, community services, and clinical specialties, the reviews and syntheses produced during the pandemic have been translated rapidly into clinical and organizational practice guidelines, within days to weeks (see Communities of Practice website: https://aci.health.nsw.gov.au/covid-19/communities-of-practice).
Research and scientific dissemination in real time
The pandemic has not only influenced how research has been used in planning the response at the population or system level. It has also created a natural experiment environment in which research has been integrated into clinical care delivery and management of the population response. Multiple cohort studies have emerged, real-time research has been funded, and innovative data collection methods have created a variety of real-time living research laboratories. Primary care electronic medical records have become accessible via rapid retrieval systems to monitor the situation in near real time, using primary care as a sentinel.
The health care system has undergone rapid transformation, particularly with respect to the halting of elective procedures, a drastic reduction in discretionary demand for care, the use of information technology for remote care, and the reorganization of care processes and patient trajectories. In such a turbulent context, capturing the transformation by collecting experiential data has served to complement the more formal mechanisms of care and services research.
In terms of individual clinical care delivery, various electronic instruments have been implemented to capture and circulate information related to COVID-19 cases, creating an opportunity to study this cohort beyond ongoing clinical trials. Many clinicians have also had questions from their patients about the pandemic and have drawn on the daily work of the Critical Intelligence Unit to answer them, despite the uncertainty. Discussions about science and evidence, uncertainty, and debates around thorny issues have thus become more prominent in the clinical space.
Regarding decision-makers, supporting a response that is proportional to the risk and to the emergence of evidence has meant putting in place tools for communicating and disseminating scientific evidence. The need to integrate different forms of knowledge and discuss the strength of scientific evidence has become part of public policy-makers’ daily routine.
A new research paradigm?
The pandemic has created a distinctive environment for research and knowledge transfer that would be difficult to generate under normal circumstances. The sense of urgency, the emotion, and the complexity of the situation are, in themselves, unique. Still, we need to learn from this experience and influence how we fund, plan, and conduct research for the later phases of the pandemic and whatever comes next. Several researchers crossed the threshold between research and activism during the pandemic. Many researchers became pan-experts or omni-experts, invited to provide insights into many subjects that extended well beyond the boundaries of their research expertise. It is essential that we put in place sustained and rigorous mechanisms for carrying out such roles. Structuring research and scientific dissemination activities within the time horizons of both the clinician and the decision-maker is possible—the pandemic has thrust us into it!
Perhaps the issue is no longer simply “how to disseminate”, but also “how to do research in a real-world context.” Translating the opportunities created by the pandemic, a common enemy that has captured everyone’s attention for months, will not be easy when suddenly everyone—researchers, clinicians and decision-makers—will be refocusing their attention on a myriad of areas of interest. The notion of debate and of integrating knowledge to respond to complex issues is an avenue that our Critical Intelligence Unit is exploring for transposing a structure erected during an emergency into a permanent structure incorporating the same ingredients and methods in a peri-pandemic context. The challenge is before us. One year later, uncertainty is still omnipresent on several fronts.
Jean-Frédéric Levesque, MD, PhD, FRCP
CEO, Agency for Clinical Innovation, New South Wales, Australia
Adjunct professor, Centre for Primary Health Care and Equity, University of New South Wales
Else, H. How a torrent of COVID science changed research publishing — in seven charts. Nature 588, 553 (2020). https://www.nature.com/articles/d41586-020-03564-y
Levesque, J-F., Sutherland, K., Watson, D.E., Currow, D.C., Bolevich, Z., Koff, E. Learning Systems in Times of Crisis: the Covid-19 Critical Intelligence Unit in New South Wales, Australia. November 23, 2020. https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0542