and may be either beneficial or detrimental for the TB bacteria, depending on events at other scales of reality. These include, for example, the life conditions of the host and his or her interaction with family and healthcare providers; the constitution of the healthcare system providing treatment; and decisions of global actors like the Bill and Melinda Gates Foundation to fund technological solutions to be rolled out in contexts that favour budget cuts in government-funded healthcare in low-income countries where TB is rampant. In theory, the combination therapy that has been used for decades should make the development of drug resistance impossible. However, the configuration of actors at very different scales seems to create a situation where M. TB is able to engage with anti-TB drugs in ways similar to its engagements with mycobacteriophages.
The many glitches in drug delivery and global policy priorities create ample opportunity for TB bacteria to make use of their stochastic intelligence. Indeed, even if the intention is to kill them, drug-resistant bacteria may de facto be considered to be domesticated versions of treatable TB, created as they are by human intervention. Hence, one could apply Napier’s phrase: ‘… human selection for tameness is not “natural selection”; it is “human selection” – a social process about creating social environments in which certain genetic traits emerge. As such, it has quite a bit to do with evolution, but as much, or more, with the effects of social environments – including experimental settings – on genetics’ (Napier, this volume). Only, Napier is talking about multi-species interaction at a different scale, namely of domestication through selective breeding of foxes that become dog-like after only a few generations, and subsequently remain ‘dogs’. Napier shows here that social exposure is the key variable that allows genes to function or be shut off. He goes on to discuss another ‘social disease’, namely that of diabetes, where such biosocial dynamics have been largely ignored, globally leading to an over-reliance on biomedical and technical explanations and interventions that are too expensive to access for most people in most countries, while largely ignoring the social dynamics that drive diabetes in individual bodies on a global scale.
The critique of neo-Darwinian evolution that informs many of the contributions in this volume points to the centrality of the discussion of temporal scales with its embedded issues of ontogenesis and phylogenesis. Even if nature–nurture can now be de-separated, and bacteria and brain inform each other’s decisions through biosocial processes, scales of time become further complicated by the attempts to bridge such different scales of sociality. The return of epigenetics may imply an ‘evolution on speed’ in the sense that genetic changes may take effect much faster than previously assumed. If a conducive health environment exists, such change happens at the speed of generational turnover for a given kind of organism. In humans, it seems to happen at a pace (accentuated by the size of the population) that increasingly translates so-called non-communicable conditions and ‘lifestyle diseases’ into epidemics (Seeberg and Meinert 2015).
At the level of bacteria, change in the form of mutation happens at the speed of cell division, and decision making as described by Young may take place in the course of hours. Temporality is complicated by the interaction of organisms with different timescales, as in the case of M. TB. TB cases with drug-resistant strains constituted a negligible population a few decades ago, whereas the impact of the current failure to control TB may result in children and grandchildren of today’s TB patients attracting incurable strains of TB in coming decades. The temporal scales of different organisms are out of sync, so to speak, and the natural limitations of humans to act outside the scope of their own temporal horizon poses challenges to interdisciplinary ambitions.
Petryna (this volume) addresses this issue in her discussion of the human capacity, including that of scientists, to understand ecosystemic transformation in the context of global climate change. Here, both spatial and temporal scales are maximised, and yet the human capacity to predict – with whatever degree of uncertainty – the future impact of current man-made emissions into the global ecosystem is, by and large subject to arbitrary timeframes – and is furthermore characterised by the inability to understand sudden non-linear changes that may be either catastrophic tipping points or trigger points for remedial action. While such sudden changes may be observed relatively easily (thanks to technological intermediaries) at the microscopic level (because they happen rapidly when perceived through a human scale of time), the reverse is true for the perceived slow development of global change.
Behind folds of the changing horizon loom landscapes hidden by ‘blindsidedness’, Petryna points out, as she invokes Fabian’s classic work on coevalness. However, where Fabian criticised evolutionism in the social sciences for placing contemporary populations at different temporal levels (Fabian 1983), Petryna points us to a parallel temporal-teleological displacement in the relationship between science and nature, most clearly exemplified by Darwinism with its teleological assumption that adaptation necessarily prevails.
Synergies
How do conventional ways of classifying disease establish barriers to understanding the biosocial complexities that frame the workings of both disease and treatment? In her chapter on co-morbidity in Botswana, Livingston points out that biology is often assumed to be a main determinant of singular illnesses, but in situations of multiple sickness biology often points in many directions simultaneously: co-morbidities may be clearly intertwined with social, political and health systemic factors, which themselves interact at biological levels. The complex co-morbidity of TB, HIV/AIDS, and cancer can be seen as a biosocial synergy that plays itself out not only at the levels of social distribution and epidemiology of disease. It also shapes processes at the clinical level, when patients seek diagnosis and treatment in health systems whose institutional infrastructure is designed to separate disease categories into, for example, TB, HIV, or cancer. Yet, in the bodies and lives of patients these disease categories are intertwined, and this kind of synergy challenges our analytical categories and calls for reconceptualisation. Ontological certainties that distinguish one disease from the other are questioned, and how the diseases interact with each other and with social and other factors is foregrounded. Livingston gives the example of one form of cancer, Kaposi’s sarcoma, which practically does not exist in women unless they are HIV positive. So, are Kaposi’s sarcoma and HIV two diseases or one? Such matters of definition continue to be highly impacted by political, economic, moral and institutional projects that arise around specific diseases.
Whether diseases and epidemics are defined as single or multiple entities may be quite significant in cases where such definition comes to determine how health problems are addressed. If cancer is seen as intimately intertwined with and part of the HIV epidemic, this may have consequences for how funding is spent, how prevention and treatment is organised, and how patients are met in clinical contexts.
Co-morbidity, at the scale of epidemics, has been conceptualised as syndemic in response to the dominant biomedical conception of diseases as distinct entities in nature, located in specific organs, separate from other diseases and independent of the social and cultural contexts in which they are found (Singer 2009, 25). The syndemic perspective allows us to think about disease in relational rather than categorical terms, and to consider the importance of interacting social (and environmental) conditions that promote the spread of disease. In syndemics, the health effects of co-morbid conditions are not additive, but multiplicative (Singer 2009, 26).
Synergies are further explored in Meinert and Whyte’s description of the rapid spread of trauma and spirits in Northern Uganda after the civil war. The number of local healers dealing with spirit possessions grew significantly alongside an influx of NGOs and humanitarian organisations treating PTSD. The authors suggest analysing the spread as related syndemic processes of situated and concerned responses to violence, which involve local biosocial worlds, as well as humanitarian psychology. Pointing out that the behavioural symptoms of both spirits and trauma often co-exist with other problems such as alcoholism, HIV and diverse health conditions, the authors discuss how these problems are intimately intertwined, making the separation of the biological and the social untenable.
In
