| Summary: | Humans live in societies full of rich, complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems contributing to disease processes including the mechanisms underlying the influence of social contexts on these biological systems. Approaches that empirically recognize the inherent complexity of social life are therefore critical, and should be applied over the life span. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health.
|
|---|