Date of Award
Open Access Dissertation
Doctor of Philosophy (PhD)
Marine Sciences and Technology
The coastal watersheds around Massachusetts Bay are home to millions of people, many of whom recreate in coastal waters and consume locally harvested shellfish. Epidemiological data on food-borne illness and illnesses associated with recreational water exposure are known to be incomplete. Of major food categories, seafood has the highest recorded rate of associated foodborne illness. In total, the health impacts from these marine-sourced risks are estimated to cost millions of dollars each year in medical expenses or lost productivity. When recorded epidemiological data is incomplete it may be possible to estimate abundance or prevalence of specific pathogens or toxins in the source environment, but such environmental health challenges require an interdisciplinary approach.
This dissertation is divided into four sections: (1) a presentation of two frameworks for organizing research and responses to environmental health issues; (2) an exploration of human population dynamics in Massachusetts Bay coastal watersheds from 2000 to 2010 followed by a review of, and identification of potential indicators for, five marine-sourced risks: Enterococcus bacteria, Vibrio parahaemolyticus bacteria, Hepatitis A Virus, potentially toxigenic Pseudo-nitzschia genus diatoms, and anthropogenic antibiotics; (3) an introduction to environmental health research in the context of a changing data landscape, presentation of a generalized workflow for such research with a description of data sources relevant to marine environmental health for Massachusetts Bay; and (4) generation of models for the presence/absence of Enterococcus bacteria and Pseudo-nitzschia delicatissima complex diatoms and model selection using an information-theoretic approach.
This dissertation produced estimates of coastal watershed demographics and usage levels for anthropogenic antibiotics, it also demonstrated that Pseudo-nitzschia delicatissima complex diatoms may be present in any season of the year. Of the modeling generation and selection, the Enterococcus model performed poorly overall, but the Pseudo-nitzschia delicatissima complex model performed adequately, demonstrating high sensitivity with a low rate of false negatives. This dissertation concludes that monitoring data collected for other purposes can be used to estimate marine-sourced risks in Massachusetts Bay, and such work would be improved by data from purpose-designed studies.
Kress, Marin M., "Identification and Use of Indicator Data to Develop Models for Marine-Sourced Risks in Massachusetts Bay" (2016). Graduate Doctoral Dissertations. 249.