On: Embracing Complexity for Systemic Interventions

Transmission Series Ep. 5

Episode: 31

Date: May 5, 2020

Evolutionary biologist.

Review of 5 Transmission Essays.

• John Krakauer and Michelle Carlson on COVID and Spiraling Frailty Syndrome
• Stefani Crabtree on What History Can Teach Us About Resilience
• Van Savage on The Informational Pitfalls of Selective Testing
• David Tuckett, Lenny Smith, Gerd Gigerenzer, and Jürgen Jost on Making Good Decisions Under Uncertainty
• Cristopher Moore on The Heavy Tail of Outbreaks

Key Takeaways

• Complex problems.
  • Broad averages are misleading.
  • Outcomes can be much more volatile than expected.
  • Need to understand local variation.
  • Need to present all possible outcomes.
• Complex problems require complex interventions.
  • We tend to collapse causality into single causes.
  • Important problems tend to be complex and rarely have simple causes.
  • We poorly understand how to resolve complex problems.
  • We typically don’t look for complex solutions as we prefer simple ones.

Key Concepts

Cristopher Moore on The Heavy Tail of Outbreaks

• Danger of averages.
  • Consider the variance, as well as the mean.
  • System averages are especially misleading if there is large local variance.
    • Example in COVID-19: impact of super-spreaders on R0.
  • Averages can hide heavy tails.
    • Probability of outliers can be much higher than you anticipate.
  • See “The End of Average“.

Van Savage on The Informational Pitfalls of Selective Testing

• Constraints: testing capacity.
  • Reporting the number of tests instead of incidence of cases.
    • Can happen when true cases outnumber the testing capacity.
  • Reporting the growth in testing instead of the growth in cases.
    • Can happen when both testing and incidence of cases expands rapidly.
• Solution: massively expand testing and/or test randomly.

David Tuckett, Lenny Smith, Gerd Gigerenzer, and Jürgen Jost on Making Good Decisions Under Uncertainty

• Decision making under high uncertainty.
  • Data is not sufficient to support probabilities.
• Solution: present all possible outcomes: understand potential variance.
  • Counter-factuals, simulations, null models.
• Recognize the limitation of narratives (subject to cognitive biases).

John Krakauer and Michelle Carlson on COVID and Spiraling Frailty Syndrome

• Complex problems require complex solutions
  • Example: frailty:
    • Complex syndrome that increases after age 65.
    • Physical activity provides complex solution.
    • Less costly than drugs and other mono-therapies.
    • See “Interventions for Human Frailty: Physical Activity as a Model“.
• Difficult to implement, convince people.
  • We are energy-minimizing cognitive systems.
  • If we can find dominant mono-causal explanations, we prefer them.
• Medicine needs to evolve to allow for more complex interventions.
  • Examples: physical activity, sleep.

Stefani Crabtree on What History Can Teach Us About Resilience

• All civilizations have experienced and learnt how to cope with pandemics.
  • Often, pandemics have contributed to the downfall of empires.
• Rarely the case that interesting or dramatic phenomena have simple causes.
  • Always tempting to collapse causality into a single cause.
  • Example COVID-19:
    • Outcomes are not only driven by virus.
    • Pre-existing inequalities hugely affect severity in pathology.
• Complex causality requires complex control or complex intervention.
  • Things are connected in subtle ways.
  • There are non-linearities.
  • There are different phases and critical transitions.
• We have a poor understanding on how to intervene into complex systems.
  • Last thing we want to do is pretend that they are simple systems.