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Kevin B Korb, 3 Feb 2023

Raina MacIntyre has been one of the voices of reason amongst epidemiologists during the Covid pandemic. These voices were given a hearing in the first year or so by both media and politicians, followed, however, by a now longer period of waning immunity to irrational and foolish misinformation, leading to widespread encouragement and support for whatever SARS-Cov-2 variants are floating around.

Dr MacIntyre’s book Dark Winter reviews the Covid pandemic and, in particular, makes a case that it originated from a lab leak at the Wuhan Institute of Virology (WIV). That case is not exactly airtight, however it does seem to support a preponderance of evidence kind of verdict. (However, I won’t commit to that: on my part it is a mere seeming; I have not investigated it myself.) She points out that the leak hypothesis received a dismissive response in the beginning, for three reasons: it was conflated with the entirely different hypothesis that the pandemic was intentionally caused by China in a bioterror attack (upon themselves, apparently); it was early on put forward by Donald Trump, in the conflated form, and many media commentators therefore immediately turned against it; the community of virologists, not acting as a unity but acting independently in defence of their own interests, loudly and publicly denounced it as an impossibility, boosted by many science journalists. Virologists, despite having a clear conflict of interest (their research careers depend, in part, on lower levels of regulation of their labs), were repeatedly turned to as expert commentators on the issue and even called upon by the WHO to participate in their investigation of Covid’s origins in Wuhan, an investigation that was denied access to much of the most important information by China (e.g., the WIV’s genomic database) and nevertheless reported no credibility to the hypothesis of a lab leak at WIV as the source for the pandemic. According to their report, ignorance of evidence supporting a lab leak works just as well as evidence against it.

The conflicts of interest and credibility of the virology community in dealing with Covid certainly deserve a much more critical examination by both media and politicians. Anthony Fauci, for example, has mostly gotten a free pass from the media on “gain-of-function” research (GOF) funding by the NIH, which research attempts to make viruses more dangerous, with a view to better understanding the threats they pose. NIH funding for it, during a declared moratorium on this kind of research, was apparently approved by Dr Fauci in the form of grants to EcoHealth Alliance, which in turn funded GOF research at WIV. This may have been unwitting by Dr Fauci, since there is at least one level of indirection, however his flat claim to have not funded gain-of-function research during the moratorium on such funding appears to be false. 

Dr MacIntyre goes on to review the long history of lab leaks in virological and bioweapons research. That history is far more alarming than most scientists have been willing to acknowledge, let alone communicate, and is a valuable contribution of the book. She quite rightly observes that much of the lab research of interest here is “dual-use” research, that is, research which has, perhaps, a primary civilian purpose, as in protecting public health, but potential military or terrorist uses as well. Whenever multiple different uses, or also accidental outcomes, are possible, there is a decision problem: do the likely benefits of the civil purpose outweigh the potential disvalue of accidental pandemics or intentional misuse?

Rather than MacIntyre’s question about Covid’s origin, I suggest the more important question put by her Dark Winter is:

Should we support lab virology in its gain-of-function or chimeric (recombinant) research into dangerous viruses or not? And, if so, with what controls?

This question has been raised before and argued around, without any clear resolution. Virologists, and before them bioengineers working on GMO products, have pointed to potential benefits of this kind of research. For a recent example, chimeric research on the Omicron variant has determined that the coding for the spike protein cannot fully explain the lessened virulence of Omicron strains, and then the researchers went on to identify a distinct protein that is involved. Whatever the ramifications of this research, we can probably agree that knowing more about the mechanisms of transmission and virulence of SARS-Cov-2 is a good thing. A more generic defence of this kind of research is very commonly put, for example in this statement from the Washington Post: “The creation of recombinant or chimeric viruses in the laboratory is merely mimicking what happens naturally as viruses circulate, researchers say.” Or, as some have said, whatever is produced in the laboratory will be eventually produced by evolution anyway. Having done quite a lot of work with evolutionary algorithms, I can testify that that is just false. As Stephen Jay Gould liked to say, if you replay the tape of evolution, it’ll play back differently. Some evolutionary pathways are more accessible than others, and the less likely may never be traversed. In any case, even if we agreed that evolution would eventually find any GOF product, it makes a good deal of difference when that eventuality arises. If it’s too soon, we may be woefully unready.

There are many ways of framing MacIntyre’s question, but putting it as a formal decision problem can help stop endless, spinning arguments. Dr MacIntyre certainly has the right general idea here, suggesting it be analysed using epidemiological risk analysis. However, she fails to complete this thought in her book, saying only “I use this risk analysis as an exercise in the course Bioterrorism and Health Intelligence” at UNSW (p. 60) and giving only vague and under-supported indications of some of the needed probabilities.

I will below set up the problem as a choice between alternative public policies, which can help make the most important issues clear and help focus debate on them. It is really a question for the entire world, the international community, and perhaps that’s the very reason it has been neglected: there is no natural seat of responsibility for dealing with such problems. 

MacIntyre’s problem can be presented in either greater or lesser detail as a formal decision problem, but to provide a bound on discussion, let’s consider this a decision between three actions: let the research proceed without oversight or regulation; stop it by international agreement worldwide (at least amongst countries and labs that obey international law); adopt some international regulatory regime which, for example, requires regular independent inspections of labs to ensure they meet agreed standards. Currently, without debate, or even much acknowledgement, we are pursuing something like the first path, for, although there are WHO recommendations, they are entirely voluntary (and not even maintained on their website). To be sure, the US’s NIH does have its own regulatory mechanism for GOF US-funded research (currently under review; see, e.g., this Science article), and no doubt so too do some other national governments. But pandemics, by definition, are a worldwide problem, not national problems, and so require an international response. 

To solve the decision problem properly, we need some hard-to-come by numbers. For example, we would need to know the probabilities that over some period, say a year, that a virology lab, conducting research according to some given standard of safety, would accidentally release viruses capable of causing a pandemic. Many other like questions would also need to be answered, for example, what is the disvalue of an average pandemic under different circumstances, as measured perhaps in Quality-adjusted life years (or QALYs, a common measure of value which assesses not just life-years saved, but the quality of those years when diminished by disability or illness).

As I said, Dr MacIntyre doesn’t provide the ingredients needed to solve this decision problem, one of global significance and interest. She does, however, raise the problem explicitly, which is already exceptional. For what it’s worth, I shall put the question even more explicitly, in the form of this decision table:

ActionPandemic¬PandemicExpected Value
GOF-V x pV x (1-p)(-V x p) + (V x (1-p))
GOF-R-V x qV x (1-q)(-V x q) + (V x (1-q))
¬(GOF ∨ GOF-R)-V x rV x (1-r)(-V x r) + (V x (1-r))

Each row presents one mutually exclusive action. I use abbreviations for concision. GOF stands for allowing unregulated gain-of-function and chimeric research; GOF-R for allowing them only under an international regulatory regime, incorpoating biosecurity standards and independent inspections; ¬(GOF ∨ GOF-R) for not allowing them at all. “Pandemic” means a pandemic ensues during some time period, say a year, although not necessarily due to that research, as it could be natural or also someone deploying a virus as a bioweapon outside regulated laboratories. -V is the disvalue of an average pandemic; therefore, V is the value of avoiding it. p is the probability of such a pandemic arising given unregulated GOF research; q is the probability given regulated GOF research; r is the probability given a prohibition on research. These probabilities are unlikely to be the same, as argued by both proponents and detractors of GOF. The former claim GOF allows us to better understand, prevent and/or prepare for and respond to future pandemics, while the latter suggests the well-established human ability to make mistakes will lead to a higher probability of pandemics. Rather than engage in ungrounded disputation, as has occurred up to now, I propose that a serious effort be made to estimate those numbers based upon a review of the history of labs and their leaks, as well as the history of both natural and artificial epidemics. 

As in all real-world modeling, there are many different choices in both level of detail and the approach to modeling implied by the above decision table. For example, one could argue that the value/disvalue of a pandemic varies depending upon the action taken, since one of the goals of GOF is to find means to mitigate pandemics. For simplicity, for now at least, I would prefer to let such considerations impact the probability of an average pandemic arising (i.e., p, q, r). In any case, a serious research project would have to consider these things. Here, I’m only presenting the problem, and in a summary form.

In any case, if we can settle upon the numbers, whether well-justified or simply as working hypotheses, then we can find the maximum expected value in the last column above, and so choose an action.

My real point is that the public deserves, and should also demand, an answer to this decision problem from health experts, the World Health Organization and our politicians. Crickets is not an answer. The virologists’ nearly unanimous and unreflective defence of their own research is also not an answer.

Just recently, two of the leaders of the UNEP investigations into Covid origins have written in indirect support for this idea (Butler and Randolph, “There has been a suppression of the truth, secrecy and cover-ups on an Orwellian scale over the origin of Covid-19 in China”; note also the editorial at the bottom by Ian Birrell):

Irrespective of the origin of the pandemic, however, this debate has exposed that self-regulation of ‘gain of function’ research has been a dismal failure.

Self-regulation, indeed, is an indicator of the public, and especially of the media, failing to take a public interest stance on a topic.

The missing analysis of Dr MacIntyre would be of interest, if only because any and all informed analyses of the problem will aid public understanding of the problem. The more the better. Nevertheless, the most serious answer to the decision problem requires a properly funded, interdisciplinary research program, one that everyone should be demanding of the UN and WHO, in my opinion. It should be run by experts, but excluding those who have professional conflicts of interest, especially virologists; for example, it should include experts in epidemiology and its history, and in decision modeling and analysis.

Dr MacIntyre puts the case for a public debate over the decision problem as clearly as can be done (p. 230):

This is a threat that affects everyone, crosses national boundaries, and which cannot be effectively managed either in the traditional disciplinary silos or by individual nation states. Instead, it requires coordination, thought leadership and novel, cross-disciplinary, global solutions.