Conceptualising population health: from mechanistic thinking to complexity science

Abstract

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

Re-imagining decision making: addressing a discrete social driver of HIV/AIDS through the lens of complexity science

“…Despite the opportunities that complexity science provides to the healthcare sector at theoretical levels (Snowden 2005, Leach et al 2010, Jayasinghe 2011, Paina and Peters 2012 the implementation of complexity based HIV prevention remains marginal, especially at grassroots levels. Moving from theory to practice requires a paradigm shift from controllable variables towards a naturalistic focus on the complexity of transient networks, relationships, interdependencies and feedback.…”

The process of developing distributed-efficacy and social practice in the context of ‘ending AIDS’

“…Increasingly, direct and indirect links are being made between health care and complexity science (Burman, Moerschell, Mamabolo, Aphane, & Delobelle, 2015b;Jayasinghe, 2011;Plsek, 2003). In 2008, it was argued that the HIV epidemic is an example of a complex health-related phenomenon which requires capacities to be developed that are "able to deal with complexity .…”

Complexity Science to Conceptualize Health and Disease: Is It Relevant to Clinical Medicine?

“…This idea of open systems with feedback loops has been extended to describe the earth's ecosystem (eg, the Gaia hypothesis) and population health. 9 Complexity science emerged in the 20th century, postulating a new paradigm that integrates systems theory and cybernetics. Complexity science has several key concepts that distinguish it from the mechanistic approach: adaptation, lack of hierarchies, self-organization, and emergence.…”