Lyme disease poses an uncertain dynamic threat to many people and public health systems. However, rather different perspectives related to the societal impact of Lyme Disease exist. Thousands of plausible evolutions of lyme disease are generated using different System Dynamics models of Lyme Disease and are studied in this exploratory study with new data analysis techniques in order to assess the risk posed by Lyme disease, in this case to the Dutch population and the Dutch health care system. The risk is scored in the Dutch National Risk Assessment framework adapted to deeply uncertain dynamically complex risks, and mapped in a new type of risk diagram developed for uncertain complex risks in order to compare the risk posed by Lyme disease to many other plausible risks. Scenario discovery techniques are used to identify a small set of representative scenarios that could be used for subsequent capability analysis.

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Date created

• 2012 July 22-2012 July 26

Type

• Document

Processing Activity

• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

License

• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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ITEM CONTEXT

Part of

ab062956a014e30aaf02b44e9d33088e

Scope and Contents

Part of

23d738ba88f8333bc39725f9cb5bd0b8

Scope and Contents

Part of

b90fd81032b7dbf0c9f90f3dc3a33f1c

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Collection

System Dynamic Society Records

Scope and Contents

Collecting area

• This collection is part of the University Archives