Category Archives: Philosophy of Epidemiology – general

African Centre for Epistemology and Philosophy of Science (ACEPS): launch announced

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The African Centre for Epistemology and Philosophy of Science (ACEPS) is housed in the Department of Philosophy at the University of Johannesburg. ACEPS fosters intra-African and global conversation in the areas of Epistemology and Philosophy of Science by bringing African insights, questions and values into meaningful conversation with other philosophical traditions. ACEPS was founded in 2016 by co-directors Professor Alex Broadbent and Professor Veli Mitova, and Dr Mongane Wally Serote, Dr Ben Smart, Chad Harris and Zinhle Mncube. ACEPS’s groundbreaking philosophical work is organised around three umbrella projects:

• Indigenous Knowledge Systems;
• Health and Medicine in Africa; and
• Rationality and Power.

Kindly diarise the following date for the Centre’s launch:
• Date: Friday, 19 May 2017
• Time: 15:00-17:30
• Venue: Humanities Common Room, C-Ring 319, Auckland Park Campus, University of Johannesburg

The launch will take the format of a public forum where panelists will exchange their opinion and ideas on the following topic: “Why an African Centre for Epistemology and Philosophy of Science?” A formal invitation will be sent out soon with all the details.

Anyone interested in attending from further afield is welcome to contact me. There will be a larger conference event organised in due course, with more lead time.

Website: https://www.uj.ac.za/faculties/humanities/aceps/Pages/default.aspx

Paper: Causality and Causal Inference in Epidemiology: the Need for a Pluralistic Approach

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Delighted to announce the online publication of this paper in International Journal of Epidemiology, with Jan Vandenbroucke and Neil Pearce: ‘Causality and Causal Inference in Epidemiology: the Need for a Pluralistic Approach‘

This paper has already generated some controversy and I’m really looking forward to talking about it with my co-authors at the London School of Hygiene and Tropical Medicine on 7 March. (I’ll also be giving some solo talks while in the UK, at Cambridge, UCL, and Oxford, as well as one in Bergen, Norway.)

The paper is on the same topic as a single-authored paper of mine published late 2015, ‘Causation and Prediction in Epidemiology: a Guide to the Methodological Revolution.‘ But it is much shorter, and nonetheless manages to add a lot that was not present in my sole-authored paper – notably a methodological dimension that, as a philosopher by training, I was ignorant. The co-authoring process was thus really rich and interesting for me.

It also makes me think that philosophy papers should be shorter… Do we really need the first 2500 words summarising the current debate etc? I wonder if a more compressed style might actually stimulate more thinking, even if the resulting papers are less argumentatively airtight. One might wonder how often the airtight ideal is achieved even with traditional length paper… Who was it who said that in philosophy, it’s all over by the end of the first page?

Paper – Tobacco in Korea

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Alex Broadbent and Seung-sik Hwang, 2016. ‘Tobacco and epidemiology in Korea: old tricks, new answers?’ Journal of Epidemiology and Community Health doi:10.1136/jech-2015-206567.

Now available online first, open access.

http://jech.bmj.com/content/early/2016/01/14/jech-2015-206567.full

For those at the recent CauseHealth workshop N=1, this relates to the same key topic (viz. the application of population evidence to an individual), but in the legal rather than clinical context.

 

Workshop, Helsinki: What do diseases and financial crises have in common?

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AID Forum: “Epidemiology: an approach with multidisciplinary applicability”

(Unfamiliar with AID forum? For the very idea and the programme of Agora for Interdisciplinary Debate, see www.helsinki.fi/tint/aid.htm)

DISCUSSED BY:

Mervi Toivanen (economics, Bank of Finland)

Jaakko Kaprio (genetic epidemiology, U of Helsinki)

Alex Broadbent (philosophy of science, U of Johannesburg)

Moderated by Academy professor Uskali Mäki

Session jointly organised by TINT (www.helsinki.fi/tint) and the Finnish Epidemiological Society (www.finepi.org)

TIME AND PLACE:

Monday 9 February, 16:15-18

University Main Building, 3rd Floor, Room 5

http://www.helsinki.fi/teknos/opetustilat/keskusta/f33/ls5.htm

TOPIC: What do diseases and financial crises have in common?

Epidemiology has traditionally been used to model the spreading of diseases in populations at risk. By applying parameters related to agents’ responses to infection and network of contacts it helps to study how diseases occur, why they spread and how one could prevent epidemic outbreaks. For decades, epidemiology has studied also non-communicable diseases, such as cancer, cardiovascular disease, addictions and accidents. Descriptive epidemiology focuses on providing accurate information on the occurrence (incidence, prevalence and survival) of the condition. Etiological epidemiology seeks to identify the determinants be they infectious agents, environmental or social exposures, or genetic variants. A central goal is to identify determinants amenable to intervention, and hence prevention of disease.

There is thus a need to consider both reverse causation and confounding as possible alternative explanations to a causal one. Novel designs are providing new tools to address these issues. But epidemiology also provides an approach that has broad applicability to a number of domains covered by multiple disciplines. For example, it is widely and successfully used to explain the propagation of computer viruses, macroeconomic expectations and rumours in a population over time.

As a consequence, epidemiological concepts such as “super-spreader” have found their way also to economic literature that deals with financial stability issues. There is an obvious analogy between the prevention of diseases and the design of economic policies against the threat of financial crises. The purpose of this session is to discuss the applicability of epidemiology across various domains and the possibilities to mutually benefit from common concepts and methods.

QUESTIONS:

1. Why is epidemiology so broadly applicable?

2. What similarities and differences prevail between these various disciplinary applications?

3. What can they learn from one another, and could the cooperation within disciplines be enhanced?

4. How could the endorsement of concepts and ideas across disciplines be improved?

5. Can epidemiology help to resolve causality?

READINGS:

Alex Broadent, Philosophy of Epidemiology (Palgrave Macmillan 2013)

http://www.palgrave.com/page/detail/?sf1=id_product&st1=535877

Alex Broadbent’s blog on the philosophy of epidemiology:

https://philosepi.wordpress.com/

Rothman KJ, Greenland S, Lash TL. Modern Epidemiology 3rd edition.

Lippincott, Philadelphia 2008

D’Onofrio BM, Lahey BB, Turkheimer E, Lichtenstein P. Critical need for family-based, quasi-experimental designs in integrating genetic and social science research. Am J Public Health. 2013 Oct;103 Suppl 1:S46-55. doi:10.2105/AJPH.2013.301252.

Taylor, AE, Davies, NM, Ware, JJ, Vanderweele, T, Smith, GD & Munafò, MR 2014, ‘Mendelian randomization in health research: Using appropriate genetic variants and avoiding biased estimates’. Economics and Human Biology, vol 13., pp. 99-106

Engholm G, Ferlay J, Christensen N, Kejs AMT, Johannesen TB, Khan S, Milter MC, Ólafsdóttir E, Petersen T, Pukkala E, Stenz F, Storm HH. NORDCAN: Cancer Incidence, Mortality, Prevalence and Survival in the Nordic Countries, Version 7.0 (17.12.2014). Association of the Nordic Cancer Registries. Danish Cancer Society. Available from http://www.ancr.nu.

Andrew G. Haldane, Rethinking of financial networks; Speech by Mr Haldane, Executive Director, Financial Stability, Bank of England, at the Financial Student Association, Amsterdam, 28 April 2009: http://www.bis.org/review/r090505e.pdf

Antonios Garas et al., Worldwide spreading of economic crisis: http://iopscience.iop.org/1367-2630/12/11/113043/pdf/1367-2630_12_11_113043.pdf

Christopher D. Carroll, The epidemiology of macroeconomic expectations: http://www.econ2.jhu.edu/people/ccarroll/epidemiologySFI.pdf

Two recent papers

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I’ve had two papers come out this month (/year!):

‘Risk Relativism and Physical Law’ in Journal of Epidemiology and Community Health – http://jech.bmj.com/content/69/1/92?etoc

‘Disease as a theoretical concept: The case of HPV-itis’ in Studies in History and Philosophy of Biological and Biomedical Sciences – http://www.sciencedirect.com/science/article/pii/S1369848614000910

Is the Methodological Axiom of the Potential Outcomes Approach Circular?

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Hernan, VanderWeele, and others argue that causation (or a causal question) is well-defined when interventions are well-specified. I take this to be a sort of methodological axiom of the approach.

But what is a well-specified intervention?

Consider an example from Hernan & Taubman’s influential 2008 paper on obesity. In that paper, BMI is shown up as failing to correspond to a well-specified intervention; better-specifed interventions include one hour of strenuous physical exercise per day (among others).

But what kind of exercise? One hour of running? Powerlifting? Yoga? Boxing?

It might matter – it might turn out that, say, boxing and running for an hour a day reduce BMI by similar amounts but that one of them is associated with longer life. Or it might turn out not to matter. Either way, it would be a matter of empirical inquiry.

This has two consequences for the mantra that well-defined causal questions require well-specified interventions.

First, as I’ve pointed out before on this blog, it means that experimental studies don’t necessarily guarantee well-specified interventions. Just because you can do it doesn’t mean you know what you are doing. The differences you might think don’t matter might matter: different strains of broccoli might have totally different effects on mortality, etc.

Second, more fundamentally, it means that the whole approach is circular. You need a well-specified intervention for a good empirical inquiry into causes and you need good empirical inquiry into causes to know whether your intervention is well-specified.

To me this seems to be a potentially fatal consequence for the claim that well-defined causal questions require well-specified interventions. For if that were true, we would be trapped in a circle, and could never have any well-specified interventions, and thus no well-defined causal questions either. Therefore either we really are trapped in that circle; or we can have well-defined causal questions, in which case, it is false that these always require well-specified interventions.

This is a line of argument I’m developing at present, inspired in part by Vandebroucke and Pearce’s critique of the “methodological revolution” at the recent WCE 2014 in Anchorage. I would welcome comments.

Causation, prediction, epidemiology – talks coming up

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Perhaps an odd thing to do, but I’m posting the abstracts of my two next talks, which will also become papers. Any offers to discuss/read welcome!

The talks will be at Rhodes on 1 and 3 October. I’ll probably deliver a descendant of one of them at the Cambridge Philosophy of Science Seminar on 3 December, and may also give a very short version of 1 at the World Health Summit in Berlin on 22 Oct.

1. Causation and Prediction in Epidemiology

There is an ongoing “methodological revolution” in epidemiology, according to some commentators. The revolution is prompted by the development of a conceptual framework for thinking about causation called the “potential outcomes approach”, and the mathematical apparatus of directed acyclic graphs that accompanies it. But once the mathematics are stripped away, a number of striking assumptions about causation become evident: that a cause is something that makes a difference; that a cause is something that humans can intervene on; and that epidemiologists need nothing more from a notion of causation than picking out events satisfying those two criteria. This is especially remarkable in a discipline that has variously identified factors such as race and sex as determinants of health. In this talk I seek to explain the significance of this movement in epidemiology, separate its insights from its errors, and draw a general philosophical lesson about confusing causal knowledge with predictive knowledge.

2. Causal Selection, Prediction, and Natural Kinds

Causal judgements are typically – invariably – selective. We say that striking the match caused it to light, but we do not mention the presence of oxygen, the ancestry of the striker, the chain of events that led to that particular match being in her hand at that time, and so forth. Philosophers have typically but not universally put this down to the pragmatic difficulty of listing the entire history of the universe every time one wants to make a causal judgement. The selective aspect of causal judgements is typically thought of as picking out causes that are salient for explanatory or moral purposes. A minority, including me, think that selection is more integral than that to the notion of causation. The difficulty with this view is that it seems to make causal facts non-objective, since selective judgements clearly vary with our interests. In this paper I seek to make a case for the inherently selective nature of causal judgements by appealing to two contexts where interest-relativity is clearly inadequate to fully account for selection. Those are the use of causal judgements in formulating predictions, and the relation between causation and natural kinds.

Stability: an epidemiological ingredient in the realism debate?

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I’m preparing a talk on stability for the New Thinking in Scientific Realism Conference that opens in Cape Town tomorrow. I introduced the notion of stability in my book, defined like this:

“A result, claim, theory, inference, or other scientific output is stable if and only if

(a) in fact, it is not soon contradicted by good scientific evidence; and

(b) given best current scientific knowledge, it would probably not be soon contradicted by good scientific evidence, if good research were done on the topic.” (Broadbent 2013, 63)

The introduction of this notion was a response to the perceived difficulties around “translating” epidemiological (or more generally biomedical) findings into good health policy. At Euroepi in Porto, 2012, I argued that translation was not the main or only difficulty for using epidemiological results, and that stability – or rather, the lack of it – was important. After all, one cannot comfortably rely on a result if one cannot be confident that the next study won’t completely contradict it, and that seems to happen pretty often in at least some areas of epidemiological investigation.

Thus the reasons for introducing the notion were thoroughly practical. More recently, though, I have been trying to tighten up the philosophical credentials of the notion, and that’s what I’m going to be talking about in Cape Town. Is stability epistemically significant? Can it be shown to be epistemically significant without collapsing into approximate truth? Can it be distinguished from approximate truth without collapsing into empirical adequacy? These are the questions I will seek to answer.

What’s interesting for me is that, as far as I can see, it’s pretty easy to answer these questions affirmatively. If I’m right about that, then this will be a nice case where studying actual science gives rise to new philosophical insights. The desire to make public health policy that will not have to be revised six months down the line is eminently practical; yet the proposal of a status that scientific hypotheses might have, distinct from truth and empirical adequacy and all the rest, is eminently abstract. If stability really is both defensible and novel, then it will illustrate the oft-repeated mantra that philosophers of science would benefit from looking more closely at science. I am personally put on guard when I hear that said, not because I disagree in principle, but because experience has taught me to suspect either lip service, or an excuse for poor philosophy. Perhaps I’m also guilty of one or both of these; I will be interested to see what Cape Town says.

“Risk Relativism” paper accepted – thanks to those who commented

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Just a note to thank those who offered comments on the revisions of “Risk relativism and physical law”. This has now been accepted by Journal of Epidemiology and Community Health, where it will feature as part of a “Debate” with invited comments from couple of epidemiologists. Not entirely sure when, since they will presumably have to write their comments now. Anyway I really appreciate the feedback I got on this one – definitely improved the final result. Thanks.

Comments sought: Risk relativism and physical law

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The attached is a revise and resubmit, and will form part of a Debate in Journal of Epidemiology and Community Health. I have until 25 July to submit. Comments are very welcome. Text is 2100 words. Feel free to comment/track changes in the doc if so inclined.

2014-07-19 Risk relativism and physical law – version for comment