The vast majority of theses in this collection are open access and freely available. There are a small number of theses that have access restricted to the WWU campus. For off-campus access to a thesis labeled "Campus Only Access," please log in here with your WWU universal ID, or talk to your librarian about requesting the restricted thesis through interlibrary loan.

Date Permissions Signed

8-10-2020

Date of Award

Summer 2020

Document Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Environmental Sciences

First Advisor

Landis, Wayne G.

Second Advisor

McLaughlin, John F., 1962-

Third Advisor

Stackelberg, Katherine von

Abstract

This study proposes the use of the Bayesian network relative risk model (BN-RRM) to estimate the risk associated with the release of gene drives as vectors to control disease, using Ponce, Puerto Rico as a case study. Bayesian networks are an appropriate risk assessment tool for quantitatively and probabilistically examining complex systems involving multiple stressors acting on multiple endpoints in a wide variety of situations. The emerging field of synthetic biology has the capacity to drastically alter ecological systems with the use of gene drive engineered organisms as a method to alter population dynamics. The purpose of the release of a gene drive organism is for the introduced genetic material to propagate within the wild type population and persist within the environment. There are many proposed gene drive designs and no regulatory framework that quantitatively assess the risk associated with the use of gene drive engineered organisms released to the environment. The risk assessment describes how the gene drive may spread through the populations of wild type mosquitoes and decrease rates of disease. The Bayesian network relative risk model can perform the risk assessment of gene drive engineered Ae. aegypti for vector control and as part of an adaptive management strategy to reduce dengue and Zika transmission. This study illustrates how the BN-RRM can integrate gene drive related information within a risk assessment framework suitable for adaptive management of these novel stressors.

Type

Text

Keywords

Ecological risk assessment, Bayesian network, gene drive

Publisher

Western Washington University

OCLC Number

1183855520

Subject – LCSH

Genetic engineering--Government policy--Puerto Rico--Ponce; Bayesian statistical decision theory; Mosquitoes as carriers of disease--Puerto Rico--Ponce; Ecological risk assessment--Puerto Rico--Ponce; Gene drives; Synthetic biology--Puerto Rico--Ponce

Geographic Coverage

Ponce (P.R.)

Format

application/pdf

Genre/Form

masters theses

Language

English

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.

Download

Share

COinS