Microsimulation Models for Disaster Policy Making
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Two executable simulation models for answering policy questions were designed and implemented. The first for a flood management case, and the second for a disease transmission case that is currently underway. The flood simulation model differs from earlier natural disaster simulation models in several respects. It represents explicitly the geographical location and the economic strength of each household. It is also equipped with a graphical user interface, making it possible to design policies interactively, and to test their outcomes. If policy options are compared, the simulation results can automatically be transformed into decision trees. The flood simulation model shows that a micro-level representation makes it possible to investigate the distributional effects of policy changes. Novel features of the disease transmission model include the use of (anonymized) data representing nine million individuals, the inclusion of important parts of the contact patterns, and the explicit representation of places. The disease transmission model shows that the incorporation of social structure allows for a more realistic representation of disease spread than do models that assume homogenous mixing. Using this model, it is possible to conduct experiments of significant policy relevance, such as investigating the initial growth of an epidemic on a real-world network. Together, the two cases demonstrate the usefulness of a spatially explicit micro-level representation for policy simulation models in the area of disaster management.
Place, publisher, year, edition, pages
Kista: Institutionen för data- och systemvetenskap (tills m KTH) , 2005.
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526
Microsimulation, Policy Making, Disaster Management
IdentifiersURN: urn:nbn:se:su:diva-525ISBN: 91-7155-076-3OAI: oai:DiVA.org:su-525DiVA: diva2:195024
2005-05-31, sal B, Forum, Isafjordsgatan 39, Kista, 10:00
Gotts, Nick, PhD
Boman, Magnus, Prof
List of papers