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First day: I learned about modeling strategies that can be used to better understand potentially universal properties of damage and repair of the dynamic system. Some were compared to empirical data. Hormesis was introduced (in the context of bone health) as an important consideration in modeling resilience. Open questions included that some patterns/observations obtained from simulations remain to be explored further (e.g., three 'trajectories': die, recover/die, & recover). Still open for me is how to actually apply some of the great ideas discussed today. For example, I had already considered the life-course in outcomes in (older) adults, but still don't have a good handle on how to actually incorporate or study this in an already aged population, or if it's possible. I have some of the same questions regarding the most useful (pre-)processing of time-series data. However, the 'middle out' approach seems to be a useful way to reduce the dimensions of complexity associated with modeling.
Second day: The extended discussion on the differences in the definition of resilience (e.g., engineering vs. ecological) and the addition of the concept of reserve further highlighted the need for standardization of definitions to make sure researchers are all on the same page. Mechanistic models and mice models show promise of better understanding the dynamics of the (aging) human, but caution is advised in trying to translate these interpretations. A case study brilliantly demonstrated that apply these concepts to 'real life' situations (e.g., patient care) requires much more thought. This was reinforced by another case that was interesting, not only from a network interaction standpoint, but also because the patient often knows their state/potential outcomes better than typical 'objective' tests.
Particularly impactful for me was the example of resilience on a community level in the Pueblo people. I find it a wonderful model to follow for understanding what factors contribute to the resilience in other contexts.