Causal Loop Diagram - the Department of Computer Science!

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Common Phenomena In Complex Systems• Counter-intuitive behaviour(Often fb interactions)• Snowballing: When things go bad, they often go verybad very quickly– “Vicious cycles” lead to “cascading” of problems(Due to positive feedback)– “Path dependence”: Different starting points canlead to divergence in project progress(Due to positive feedback interacting w/ mult.negative fb)• Policy resistance: Situation can be unexpectedlydifficult to change(Typically due to negative feedbacks that resistchange)
Examples of Policy Resistance– Cutting cigarette tar levels reduces cessation– Cutting cigarette nicotine levels leads to compensatorysmoking– Targeted anti-tobacco interventions lead to equallytargeted coupon programs by tobacco industry– Charging for supplies for diabetics as cost-cuttingmeasure leads to higher overall costs due to reduced selfmanagement,faster disease progression, higher demandfor dialysis & transplants– ARVs prolong lives of HIV carriers, but lead to resurgentHIV epidemic due to lower risk perception– “Saving money” by understaffing STI clinics, leads to longtreatment wait, greater risk of transmission by infectives&bigger epidemics– Antibiotic overuse worsens pathogen resistance– Antilock breaks lead to more risky driving– Natural feedback: Intergenerational “Vicious Cycles”
Page 5 and 6: Consider A → B• We are reasonin
Page 7 and 8: Tips• Variables will often be nou
Page 9 and 10: Example 2• Ambiguous Link: Someti
Page 11 and 12: Feedback Loops• Loops in a causal
Page 13 and 14: Example “Balancing Loops”• Ba
Page 15 and 16: Best Practice:Indicating (Pronounce
Page 17 and 18: Classic FeedbacksSusceptibles -+Con
Page 19 and 20: Example Vicious/Virtuous Cycles•
Page 21 and 22: More Elaborate DiagramsKaranfil, 20
Page 23 and 24: Causal Loop Structure :Dynamic Impl
Page 25 and 26: CL Dynamics: Goal Seeking(Balancing
Page 27 and 28: Growth and Plateau• Loop structur
Page 29 and 30: Measles & Mumps in SKDepartment of
Page 31 and 32: Three STIs: Test Volume vs CaseCoun
Page 33 and 34: Cases and Contact Tracing6000500040
Page 35: Broadening the Model Boundaries:End
Page 39 and 40: Slides Adapted from External Source
Page 41 and 42: Unclear VariablesVariables Lacking
Page 43 and 44: Refining a Diagram• It takes time
Page 45 and 46: Polarity• A → + B Does not mean
Page 47 and 48: Critical: Notion of “Increase”
Page 49 and 50: Artifactual Loop 2
Page 51 and 52: State of the System: Stocks(Levels,
Page 53 and 54: Changes to State: Flows (“Fluxes
Page 55 and 56: Flows 2• May be measured by total
Page 57 and 58: 109.5Flow Impact on StockFlow2,0001
Page 59 and 60: Delayed Impact
Page 61: Slides Adapted from External Source

Causal Loop Diagram - the Department of Computer Science!

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