In this dissertation I explore the application of two novel modeling
techniques for improving risk analysis of vector-borne disease and discuss their
potential use in integrating environmental risk assessment that guides
environmental and public health decisions. Techniques for analyzing risk have
been considered inadequate due to a lack of understanding of the problem and an
appropriate analytic-deliberative process clarifying the meaning of analytic
findings and uncertainty (National Research Council (NRC), 1996; Peterman and
Anderson, 1999). Thus, new integrative risk analysis tools are needed that are
responsive to more complex environmental problems. In this work, I develop a
qualitative community model that combines a conventional biomathematical
model of vector-borne disease transmission with recent developments in
community modeling. My procedure predicts the change in risk of vector-borne
disease from press perturbations, a disturbance that results in a permanent change
in a growth parameter. I also use a Relational Bayesian Modeling technique to
exploit existing data to determine plausible mechanisms and geospatial and
temporal patterns of disease spread. I apply these tools to Lyme disease and West
Nile Encephalitis as examples of two different vector-borne diseases associated
with complex ecological communities. Both the qualitative modeling and Bayesian
methods provide an integrated risk analysis framework that identifies relationships
important in the system and thus, guide the application of quantitative models or
provide sufficient information for management decisions. / Graduation date: 2003
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/32101 |
| Date | 06 March 2003 |
| Creators | Orme Zavaleta, Jennifer |
| Contributors | Edge, W. Daniel |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
Page generated in 0.0021 seconds