Presenting Complexity Theory

Despite significant biomedical breakthroughs and the opportunities it has afforded us, UNAIDS has reiterated the need to devote more effort in communities to “ensure that the AIDS response is people-centered and take it to new levels” [1]. There is a growing consensus that this would require us moving beyond biomedical responses and towards innovative biosocial responses that make sense to local communities and contribute to ending AIDS by 2030 (UNAIDS 2014 as cited in Burman, 2018). UNAIDS also express the need for emerging biosocial responses to be able to confront the ‘complex life challenges’ experienced by people at risk of HIV and AIDS [1].

If effective progress towards ’ending AIDS by 2030’ is to be realised in the evidently complex and dynamic South African HIV landscape, then we should step outside “the ‘ordered’ epistemological parameters of the existing prevention ‘messaging’ mind set towards a more systemic approach that emphasises agency, structure and social practices.” [2]. It is vital that we shift towards an approach that is able to identify and respond to both linear and nonlinear dynamics that impact on the HIV epidemic [3].

The Inadequacy of Reductionist Science

In a summary of four dominant biosocial HIV management strategies, (Campbell & Cornish 2010) argued that the reason ‘first and second-generation’ interventions failed to achieve the goals they had set out was because they were often developed by external experts and imposed on communities in a ‘top-down’ fashion [1]. South African prevention and development initiatives have often presumed that citizens will act as neat and tidy variables in a linear equation responding to external inputs in expected ways, with no consideration of the context that the initiative is implemented in [4]. The attitudes of decisionmakers suggest that communities will remain static while experts scrutinize, diagnose, assess, plan and attempt to implement strategies designed to fundamentally change people’s behaviours in complex landscapes [4]. This stance taken up by public health and its practitioners reflects their need to uphold a Newtonian/reductionist paradigm with a reasoning process as follows: by reducing an entity to smaller parts and understanding the properties and characteristics of these smaller parts the whole can be understood more comprehensively [5]. From this perspective, HIV prevention is seen as a problem with an observable cause and effect and a solution that is definable and within reach [2].

The reality is that the landscape of HIV transmission is complex (complex only refers to the nature of the problem not the difficulty). We are faced with “wicked problems” that exhibit non-linear interactions and feedback between components in social systems. This imbues social systems with a great degree of uncertainty when looking forward, yet gives an observable (and solvable) cause and effect when looking retrospectively [2].

Prevention programmes informed by reductionist paradigms are inadequate to account for the challenges and complexities of the South African HIV epidemic [5] They are unable to mediate the local sentiments, perspectives and the perceived needs and interests of the target communities, nor are they sufficiently concerned about the complex social relations in which these programmes operate in. Programmes that use reductionist methods can be appropriate for systems that have a finite amount of independent, homogenous elements interacting in an orderly manner with a comparably low degree of interconnectivity.

But there is realization that this reductionist, ‘one-size-fits-all’ mode of operation may be ill-suited when dealing with nonlinear cause-effect relationships at various levels such as the HIV/AIDS epidemic. [6]. Traditional scientific approaches under these circumstances are extremely limited and ultimately collapse leaving the social sciences divided. Complexity science can perhaps provide us with an alternative pathway.

The Rationale for a paradigm shift - Complexity Theory

For Durkheim, social reality is an amalgamation of invisible relations and Bourdieu (1989; 1968) identifies the “real not with substances but with relations” [7]. Experiments done by social scientist show that the process of human decision making is far more complicated than presumed by the “rational choice between alternatives” line of thought (Klein, 2008 and Kahneman, 2011 as cited in [4]). Complexity thinking has emerged in social sciences over the last few years as a robust conceptual framework to help us understand and work with unpredictable behaviours in complex systems without resorting to reductionist methods [4].

Complexity theory is a set of tools for modelling complex systems. Complex systems are made up of many constituents that are highly interconnected, interdependent and distributed without centralized control. Organisation is established from the interaction of the parts through a process of self-organisation that in turn gives rise to the emergence of new levels of organisation. It is not possible to fully isolate one component or reduce the whole entity to one component. The whole is different from the sum of its parts and their relations. The focus of analysis shifts away from understanding the properties of individual elements towards understanding how the elements with other elements in the system and emerges into a new entity [5]. The whole is “qualitatively different from their parts” [5, p. 10].

The high interdependence of the parts creates nonlinearity. Linearity is a continuingly recurring and prevalent theme in complex systems. It arises from the evidence that when we put two things together the result may not necessarily be a simple addition of each elements properties in isolation. It is possible to get a combined effect that is greater or less than the simple sum of each part because of their interdependent nature. For this reason, prior identification of discrete ‘solutions’ to ‘problems’ in complex situations is unrealistic [2].

Towards the application of Complexity Theory

The current institutional logic of development plans and policies are biased towards technical, linear forms of social theorising. This is institutionally enmeshed into the South African development apparatus and is unlikely to achieve our developmental goals as it is structurally inappropriate to deal with the complexities of the current HIV/AIDS landscape. There is a contrast between the developmental apparatus and the realities on the ground which could cause a glass ceiling of developmental impact to be reached if alternative paradigms are not explored and utilized.

The next article will explore possible uses of complexity theory through complex adaptive systems. These conceptual tools show us that there is much potential in tackling the discrete, underlying properties of the dynamic system rather than focusing solely on surface level characteristics/descriptors.

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Work Cited

[1] Burman, C. J. (2018). The Taming Wicked Problems Framework: A plausible biosocial contribution to ‘ending AIDS by 2030’. TD: The Journal for Transdisciplinary Research in Southern Africa, 14(1), 1-12.

[2] Burman, C. J., Aphane, M., Mtapuri, O., & Delobelle, P. (2015). Expanding the prevention armamentarium portfolio: A framework for promoting HIV-Conversant Communities within a complex, adaptive epidemiological landscape. SAHARA: Journal of Social Aspects of HIV/AIDS Research Alliance, 12(1), 18-29.

[3] Burman, C. J., & Aphane, M. A. (2016). Leadership emergence: the application of the Cynefin framework during a bio-social HIV/AIDS risk-reduction pilot. African Journal of AIDS Research, 15(3), 249-260.

[4] Burman, C. J., Mamabolo, R., Aphane, M., Lebese, P., & Delobelle, P. (2013). The South African developmental landscape: restricted potentials or expansive, complex adaptive opportunities?. TD: The Journal for Transdisciplinary Research in Southern Africa, 9(1), 17-37.

[5] Turner, J. R., & Baker, R. M. (2019). Complexity theory: An overview with potential applications for the social sciences. Systems, 7(1), 4.

[6] Van Beurden, E. K., Kia, A. M., Zask, A., Dietrich, U., & Rose, L. (2013). Making sense in a complex landscape: how the Cynefin Framework from Complex Adaptive Systems Theory can inform health promotion practice. Health promotion international, 28(1), 73-83.

[7] D. Byrne and G. Callaghan, Complexity theory and the social sciences: The state of the art, Routledge, 2013.