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About Alex Broadbent

Director of the Institute for the Future of Knowledge and Professor of Philosophy, University of Johannesburg

15 fatalities on the 15th in a taxi/minibus crash – maybe South Africans have a reason to fear COVID-19 less than Europeans

On 15 April, 15 occupants of a taxi-minibus (i.e. all of them) died in a head-on collision. Lockdown has reduced road fatalities to a record low, ironically; these people were particularly unlucky. But the event illustrates the kind of hazard that South Africans face daily. Life expectancy here is 59 for men, 65 for women. COVID-19 mortality rises sharply in the 60s, and, while this may not “transport” to African populations, we’re apparently happy to “transport” the exact same measures used elsewhere. Not enough cost-benefit analysis being done. Lockdown might save some from road traffic accidents but it will kill more from malnutrition and diseases endemic in the region, as malnutrition reduces resistance and medical supplies are diverted.

COVID on the Breadline

The Institute for the Future of Knowledge at the University of Johannesburg has partnered with Picturing Health to make a short documentary depicting the impact of severe lockdown measures on those living in poverty in the developing world.

COVID on the Breadline from PICTURING HEALTH on Vimeo.

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Predicting Pandemics: Lessons from (and for) COVID-19

This is a live online discussion between Jonathan Fuller and Alex Broadbent, hosted by the Institute for the Future of Knowledge in partnership with the Library of the University of Johannesburg. Comments and discussion are hosted on this page, and you can watch the broadcast here:

We know considerably more about COVID-19 than anyone has previously known about a pandemic of a new disease. Yet we are uncertain about what to do. Even where it appears obvious that strategies have worked or failed, it will take some time to establish that the observed trends are fully or even partly explained by anything we did or didn’t do. And when we take a lesson from one place and try to apply it in another, we have to contend with the huge differences between different places in the world, especially age and wealth. This conversation explores these difficulties, in the hope of improving our response to the uncertainty that always accompanies pandemics, our ability to tell what works, our sensitivity to context, and thus our collective ability to arrive at considered decisions with clearly identified goals and a based on a comprehensive assessment of the relevant costs, benefits, risks, and other factors.

Further reading:

Professor Alex Broadbent (PhD) is Director of the Institute for the Future of Knowledge at the University of Johannesburg and Professor of Philosophy at the University of Johannesburg. He specialises in prediction, causal inference, and explanation, especially in epidemiology and medicine. He publishes in major journals in philosophy, epidemiology, medicine and law, and his books include the path-breaking Philosophy of Epidemiology (Palgrave 2013) and Philosophy of Medicine (Oxford University Press 2019).

Dr Jonathan Fuller (PhD, MD) is a philosopher working in philosophy of science, especially philosophy of medicine. He is an Assistant Professor in the Department of History and Philosophy of Science (HPS) at the University of Pittsburgh, and a Research Associate with the University of Johannesburg. He is also on the International Philosophy of Medicine Roundtable Scientific Committee. He was previously a postdoctoral research fellow in the Institute for the History and Philosophy of Science at the University of Toronto.

The role of philosophers in the coronavirus pandemic

What is the point of philosophy? That’s a question many philosophers struggle with, not just because it is difficult to answer. That goes for many academic disciplines, including “hard” sciences and applied disciplines like economics. However, unlike physicists and economists, philosophers ought to be able to answer this question, in the perception of many. And many of us can’t, at least to our own satisfaction.

I’ve written some opinion pieces (1,2) and given some interviews during this period, and I know of a handful of other philosophers who have done so (like Benjamin Smart, Arthur Caplan, and Stefano Canali). However, I also know of philosophers who have expressed frustration at the “uselessness” of philosophy in times like these. At the same time, I’ve seen an opinion piece by a computer scientist, whose expert contribution is confined to the nature of exponential growth: something that all of us with a basic mathematical education have studied, and which anyone subject to a compound interest rate, for example through a mortgage, will have directly experienced.

Yet computer science hasn’t covered itself in glory in this epidemic. Machine learning publications claiming to be able to arrive at predictive models in a matter of weeks have been notably lacking in this episode, confirming, for me, the view that machine learning and epidemiology have yet to interact meaningfully. Why do computer scientists (only one, admittedly; most of them are surely more sensible) and philosophers have such different levels of confidence at pronouncing on matters beyond their expertise?

There are no experts on the COVID-19 pandemic

This pandemic is subject to nobody’s expertise. It’s a novel situation, and expertise is remarkably useless when things change, as economists discovered in 2008 and pollsters in 2016.

Of course, parts of the current situation fall within the domains of various experts. Infectious disease epidemiologists can predict its spread. But there is considerably more to this pandemic than predicting its spread. In particular, the prediction of the difference that interventions make requires a grasp of causal inference that is a distinct skill set from that of the prediction of a trend, as proponents of the potential outcomes approach have correctly pointed out. Likewise, the attribution, after the fact, of a certain outcome to an intervention only makes good sense when we know what course of action we are comparing that intervention with; and this may be underspecified, because the “would have died otherwise” trend is so hard to establish.

Non-infectious-disease epidemiologists may understand the conceptual framework, methodology, terminology and pitfalls of the current research on the pandemic, but they do not necessarily have better subject-specific expertise than many in public health, the medical field, or others with a grasp on epidemiological principles. Scientists from other disciplines may be worse than the layperson because, like the computer scientist just mentioned, they wrongly assume that their expertise is relevant, and in doing so either simplify the issue to a childish extent, or make pronouncements that are plain wrong. (Epidemiology is, in my view, widely under-respected by other scientists.)

Turning to economics and politics, economists can predict the outcome of a pandemic or of measures to control it only if they have input from infectious disease epidemiologists on the predictive claims whose impacts they are seeking to assess.

Moreover, the health impact of economic policies are well-studied by epidemiologists, and to some extent by health economists; but these are not typically knowledgeable about the epidemiology of infectious disease outbreaks of this nature.

Jobs for philosophers

In this situation, my opinion is that philosophers can contribute substantially. My own thinking has been around cost-benefit analysis of public health interventions, and especially the neglect of the health impact – especially in very different global locations – of boilerplate measures being recommended to combat the health impact of the virus. This is obviously a lacuna, and especially pressing for me as I sit writing this in my nice study in Johannesburg, where most people do not have a nice study. Africa is always flirting with famine (there are people who will regard this as an insult; it is not). Goldman Sachs is predicting a 24% decline in US GDP next quarter.

If this does not cost lives in Africa, that would be remarkable. It might even cost more lives than the virus would, in a region where only 3% are over 65 (and there’s no evidence that HIV status makes a difference to outcomes of COVID-19). South Africa is weeks into the epidemic and saw its first two deaths just today.

Yet the epidemiological community (at least on my Twitter feed) has entirely ignored either the consequences of interventions on health, merely pointing out that the virus will have its own economic impact even without interventions, which is like justifying the Bay of Pigs by pointing out that Castro would have killed people even without the attempted invasion. And context is nearly totally ignored. The discipline appears mostly to have fallen behind the view that the stronger the measure, the more laudable. Weirdly, those who usually press for more consideration of social angles seem no less in favour, despite the fact that they spend most of the rest of their time arguing that poverty is wrongly neglected as a cause of ill-health.

Do I sound disappointed in the science that I’m usually so enthusiastic about, and that shares with philosophy the critical study of the unknown? Here we have a virus that may well claim a larger death toll in richer countries with older populations, and a set of measures that are designed by and for those countries, and a total lack of consideration of local context. Isn’t this remarkable?

There is more to say, and many objections; I’ll write this up in an academically rigorous way as soon as I can. Meanwhile, I’ll continue to publish opinion pieces, where I think it’s useful. Right now, my point is that there’s a lot for philosophers to dissect here. I don’t mean in this particular problem, but in the pandemic as a whole. And the points don’t have to be rocket science. They can be as simple as recommending that a ban on sale of cigarettes be lifted.

What is required for us to be useful, however, is that we apply our critical thinking skills to the issue at hand. Falling in with common political groupings adds nothing unique and requires the suspension of the same critical faculties that we philosophers pride ourselves on in other contexts. This is a situation where nearly all the information on which decisions are being made is publicly available, where none of it is the exclusive preserve of a single discipline, and where fear clouds rational thought. Expert analyses of specific technical problems are also readily available. These are ideal conditions for someone trained to apply analytic skills in a relatively domain-free manner to contribute usefully.

Off the top of my head, here are a handful topic ideas:

  • How to circumscribe the consequences of COVID-19 that we are interested in when devising our measures of intervention (this is an ethical spin on the issue I’m interested in above)
  • The nature of good prediction (which I’ve worked on in the public health context – but there is so much more to say)
  • The epistemology of testimony, especially concerning expertise, in a context of minimal information (to get us past the “trust the scientists FFS” dogma – that’s an actual quote from Twitter)
  • The weighing of the rights of different groups, given the trade off between young and old deaths (COVID-19 kills almost no children, while they will die in droves in a famine)

One’s own expertise will suggest other topics, provided that the effort is to think critically rather than simply identify people with whom one agrees. I very much hope that we will not see a straightforward application of existing topics: inductive risk and coronavirus; definition of health and coronavirus; rights and coronavirus; etc. To be clear, I’m not saying that no treatment of coronavirus can mention inductive risk, definition of health, or rights; just that the treatment must start with Coronavirus. My motto in working on the philosophy of epidemiology is that my work is philosophical in character but epidemiological in subject: it is philosophical work about epidemiology. Where it suggests modifications to existing debates in philosophy, as does happen, that is great, but it’s not the purpose. The idea is to identify new problems, not to cast old ones in a new light. Perhaps there are no such things as new philosophical problems; but then again, perhaps it’s only by trying to identify new problems that we can cast new light on old ones.

Call to arms

The skill of philosophers, and the value in philosophy, does not lie in our knowledge of debates that we have had with each other. It lies in our ability to think fruitfully about the unfamiliar, the disturbing, the challenging, and even the abhorrent. The coronavirus pandemic is all these things. Let’s get stuck in.

Thinking rationally about Coronavirus

I have written an op ed which can be found here:

https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/country-readiness

There is also a very good (in my opinion) peace in the Lancet which emphasizes the importance of rate of spread and anticipates public health measures as an inevitability, better embraced sooner than later.

https://doi.org/10.1016/ S0140-6736(20)30567-5

Events like this really make me feel that epidemiology must be much more widely understood in the contemporary world. Debates about red meat do the same, but less dramatically. This is such a stark case. Epidemiological expertise must guide us and basic comprehension of epidemiology – even as basic as just knowing that there is such a thing and that there are Experts in it, and that they are not necessarily doctors – would help so much. Politicians aren’t better educated than the rest of the educated public. I’m not critiquing any particular decision – so far, things have mostly been sensible, I think – but the sense of not knowing could be greatly alleviated. How about just a short module on epidemiology as part of high school biology?…

Potential Outcomes Approach as “epidemiometrics”

In a review of Jan Tinbergen’s work, Maynard Keynes wrote:

At any rate, Prof. Tinbergen agrees that the main purpose of his method is to discover, in cases where the economist has correctly analysed beforehand the qualitative character of the causal relations, with what strength each of them operates… [1]

Nancy Cartwright cites this passage in the context of describing the business of econometrics, in the introduction to her Hunting Causes and Using Them [2]. Her idea is that econometrics assumes that economics can be an exact science, that economic phenomena are governed by causal laws, and sets out to quantify them, making econometrics a fruitful domain for a study of the connection between laws and causes.

This helped me with an idea that first occurred to me at the 9th Nordic Conference of Epidemiology and Register-Based Health Research, that the potential outcomes approach to causal inference in epidemiology might be understood as the foundational work of a sub-discipline within epidemiology, related to epidemiology as econometrics is to economics. We might call it epidemiometrics.

This suggestion appears to resonate with Tyler Vanderweele’s contention that:

A distinction should be drawn between under what circumstances it is reasonable to refer to something as a cause and under what circumstances it is reasonable to speak of an estimate of a causal effect… The potential outcomes framework provides a way to quantify causal effects… [3]

The distinction between causal identification and estimation of causal effects does not resolve the various debates around the POA in epidemiology, since the charge against the POA is that as an approach (the A part in POA) it is guilty of overreach. For example, the term “causal inference” is used prominently where “quantitative causal estimation” might be more accurate [4]. 

Maybe there is a lesson here from the history of economics. While the discipline of epidemiology does not pretend to uncover causal laws, as does economics, it nevertheless does seek to uncover causal relationships, at least sometime. The Bradford Hill viewpoints are for answering a yes/no question: “is there any other way of explaining the facts before us, is there any other answer equally, or more, likely than cause and effect?” [5]. Econometrics answers a quantitative question: what is the magnitude of the causal effect, assuming that there is one? This question deserves its own disciplines because, like any quantitative question, it admits of many more precise and non-equivalent formulations, and of the development of mathematical tools. Recognising the POA not as an approach to epidemiology research, but as a discipline within epidemiology is deserved.

Many involved in discussions of the POA (including myself and co-authors) have made the point that the POA is part of a larger toolkit and that this is not always recognised [6,7], while others have argued that causal identification is a separate goal of epidemiology from causal estimation and that is at risk of neglect [8]. The italicised components of these contentions do not in fact concern the business of discovering or estimating causality. They are points about the way epidemiology is taught, and how it is understood by those who practice it. They are points, not about causality, but about epidemiology itself.

A disciplinary distinction between epidemiology and a sub-discipline of epidemiometrics might assist in realising this distinction that many are sensitive to, but that does not seem to have poured oil on the water of discussions of causality. By “realising”, I mean enabling institutional recognition at departmental or research unit level, enabling people to list their research interests on CVs and websites, assisting students in understanding the significance of the methods they are learning, and, most important of all, softening the dynamics between those who “advocate” and those who “oppose” the POA. To advocate econometrics over economics, or vice versa, would be nonsensical, like arguing liner algebra is more or less important than mathematics. Likewise, to advocate or oppose epidemiometrics would be recognisably wrong-headed. There would remain questions about emphasis, completeness, relative distribution of time and resources–but not about which is the right way to achieve the larger goals.

Few people admit to “advocating” or “opposing” the methods themselves, because in any detailed discussion it immediately becomes clear that the methods are neither universally, nor never, applicable. A disciplinary distinction–or, more exactly, a distinction of a sub-discipline of study that contributes in a special way to the larger goals of epidemiology–might go a long way to alleviating the tensions that sometimes flare up, occasionally in ways that are unpleasant and to the detriment of the scientific and public health goals of epidemiology as a whole.

[1] J.M. Keynes, ‘Professor Tinbergen’s Method’, Economic Journal, 49 (1939), 558-68 n. 195.

[2] N. Cartwright, Hunting Causes and Using Them (New York: Cambridge University Press, 2007), 15.

[3] T. Vanderweele, ‘On causes, causal inference, and potential outcomes’, International Journal of Epidemiology, 45 (2016), 1809.

[4] M.A. Hernán and J.M. Robins, Causal Inference: What If (Boca Raton: Chapman & Hall/CRC, 2020).

[5] A. Bradford Hill, ‘The Environment and Disease: Association or Causation?’, Proceedings of the Royal Society of Medicine, 58 (1965), 299.

[6] J. Vandenbroucke, A. Broadbent, and N. Pearce, ‘Causality and causal inference in epidemiology: the need for a pluralistic approach’, International Journal of Epidemiology, 45 (2016), 1776-86.

[7] A. Broadbent, J. Vandenbroucke, and N. Pearce, ‘Response: Formalism or pluralism? A reply to commentaries on ‘Causality and causal inference in epidemiology”, International Journal of Epidemiology, 45 (2016), 1841-51.

[8] Schwartz et al., ‘Causal identification: a charge of epidemiology in danger of marginalization’, Annals of Epidemiology, 26 (2016), 669-673.

M, PhD and PostDoc opportunities at UJ

The University of Johannesburg has released a special call offering masters, doctoral and postdoctoral fellowships, for start asap, deadline 8th Feb 2020.

These are in any area, but I would like to specifically invite anyone wishing to work with myself (or colleagues at UJ) on any of the areas listed below. From May 2020, I will be Director of the Institute for the Future of Knowledge at UJ (a new institute – no website yet – but watch this space!), and being part of this enterprise will, I think, be very exciting for potential students/post-docs. I would be delighted to receive inquiries in any of the following areas:

  • Philosophy of medicine
  • Philosophy of epidemiology
  • Causation
  • Counterfactuals
  • Causal inference
  • Prediction
  • Explanation (not just causal)
  • Machine learning (in relation to any of the above)
  • Cognitive science
  • Other things potentially relevant to the Institute, my interests, your interests… please suggest!

If you’re interested please get in touch: abbroadbent@uj.ac.za

The call is here, along with instructions for applicants:

2020 Call for URC Scholarships for Master’s_Doctoral_Postdoctoral Fellowships_Senior Postdoctoral fellowships

DOCTORAL OPPORTUNITY – Biological complexity – still open

Despite receiving some good applications, I’ve been unable to find the right match for this position yet, originally advertised in August. If you are interested please follow instructions in the original ad here:

DOCTORAL OPPORTUNITY: Increasing Complexity – the First Rule of Evolution?

The opportunity will expire at end of January.