Health risk assessment

Vibrio bacteria are emerging pathogens responsible for 80,000 illnesses and 100
deaths in the United States each year. Infections are directly linked to the marine
environment and are acquired by consuming contaminated seafood or exposing wounds
during aquatic activities. Florida has the highest national incidence of vibriosis, with 20%
of its cases reported from the Indian River Lagoon region, a popular recreation destination.
This study utilized a combination of cultivation and molecular techniques to investigate
the local distribution of V. vulnificus, V. parahaemolyticus and V. cholerae in this local
waterway. The targeted species were found in an array of samples which may facilitate their
transmission to humans. Overall, these bacteria were abundant in estuarine sediments (Vp:
2,439 CFU/g, Vv: 303 CFU/g, Vc: 176 CFU/g), on the sharp edges of oyster shells (Vp: 82
CFU/cm, Vv: 102 CFU/cm, Vc: 41 CFU/cm), and in the water column (Vp: 3.78 CFU/ml,
Vv: 5.51 CFU/ml, Vc: 2.46 CFU/ml). Vibrio also pose a hazard to recreational anglers as
they were recovered from fish (Vp: 61%, Vv: 55%, Vc: 30%), live bait shrimp (Vp: 80%,
Vv: 37%, Vc: 0%) and hooks (Vp: 32%, Vv: 18%, Vc: 0%). Additionally, a molecular
analysis of the V. vulnificus virulence revealed that the local population was dominated by
disease-causing (vcgC) strains, which may explain why wound-related infections are
common in this region.
Vibrio occurrence varied both spatially and temporally due to their relationship with
salinity and temperature. These bacteria exhibited a strong negative correlation with
salinity, being particularly abundant near freshwater discharge locations. Due to Florida’s
year-round warm climate, these species were found to be permanent members of the local
microbial community. Seasonal peaks in abundance occurred between August and
October, a period which corresponds with the warmest water temperatures as well as
frequent rainfall. Predictive models were constructed based on these parameters to provide
a better understanding of how, when and where Vibrio spp. may be encountered by humans.
This information is important for both water management and healthcare initiatives, with
an overall goal of improving local recreational safety.

Groundwater aquifers are precious resources that has been serving human
consumption for many centuries. This resource is pristine in comparison with surface
waters such as lakes and canals, however, as population grows exponentially so does the
demand for groundwater and the need to study the potential of groundwater replenishment
programs. The injection of treated water or wastewater into an aquifer is a method to protect
this resource for current and future generations. Health concerns would be expected since
migration of water of “impaired quality” can affect the drinking water by contamination.
Regulatory barriers resulting from the perceived risks of adverse health effects from
pathogens such as viruses have limited the concept of this impaired water resources from
being used for groundwater replenishment programs. The objective of this study is to
examine the risk assessment using computational modeling with MODFLOW and MT3D groundwater transport simulation. The results from the simulation showed that after two years, the risk of contamination based on concentration contours from the injection well to the production wellfields for the City of Hollywood stabilized below 10- 6. The risk assessment provided important aspect to demonstrate the concept of using injection of treated water as an option for groundwater replenishment.

Wellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial neural network) to predict the wellness outcome. An approach to calculate wellness score is also addressed. All these classifiers are trained on real data, hence giving more accurate results. With this solution, there is a better way of keeping track of an individuals’ health. In this thesis, we present the design and development of such a system and evaluate the performance of the classifiers and design considerations to maximize the end user experience with the application. A user experience model capable of predicting the wellness score for a given set of risk factors is developed.

The purpose of this study was to determine whether an educational tobacco intervention impacted college students' perceptions relative to tobacco, self-efficacy, and perceived stress levels. The Health Belief Model (HBM) provided a theoretical framework to distinguish differences relative to tobacco between groups. Both the control (N=155) and intervention (N=184) group consisted of a convenience sample of students from a 2000-level health course. A pre- and post-test questionnaire was administered to both groups which included questions regarding demographics, tobacco use, HBM, self-efficacy, and perceived stress. Data analysis included frequency counts, confirmatory factor analysis, Cronbach's alpha, and two-way ANOVA. Two-way ANOVA results indicated statistically significant differences for the Health Belief Model questions (p=0.002) and self-efficacy items (p=0.03). No statistical significance was found regarding perceived stress. These findings provide evidence an educational tobacco intervention administered at the college level can have a significant impact on students.