Adolescent Pregnancy Prevention in San Jose, Costa Rica : Assessment of an Educational Intervention

This thesis explores adolescent pregnancy in San Jose, Costa Rica and examines a school-based pregnancy prevention intervention. The relationships between school, gender and risk of adolescent pregnancy are also analyzed, and recommendations are made for effective pregnancy prevention programming. The Purral region of Guadalupe on the outskirts of San Jose, Costa Rica, suffers a higher rate of adolescent pregnancy compared to the rest of the country. In response to this problem, the International Health Central American Institute (IHCAI) implemented a sexual health education program in two local secondary schools in 2006. Very little information about the program is available. It is known that the program was initially evaluated through assessments of the participants’ knowledge before and after the educational sessions. There was no evaluation of the youth attitudes or behaviors, adolescent pregnancies, or long-term impact. The author worked with IHCAI in San Jose, Costa Rica to perform an assessment of the longer term effects of this sexual health education program. They developed a questionnaire to evaluate the knowledge, attitudes, and behaviors surrounding sexual health of youth in the Purral community. Researchers at IHCAI later used this survey to collect data from adolescents who had participated in the educational intervention and those who had not. This thesis analyzes the data collected by IHCAI to assess the effectiveness of the - 2 - educational intervention and the influence of other factors on the knowledge, attitudes, and behaviors of adolescents in the Purral region. The thesis begins with an overview of adolescent pregnancy, Costa Rica and the Purral region, and a description of the education intervention implemented by IHCAI. The research goal, logic model, and methods are then described. The results are reported, and the thesis then concludes with discussion of the results as well as study limitations and recommendations for future research and intervention. This thesis will be used to guide IHCAI’s continuation and expansion of adolescent pregnancy prevention programming.

Validation of a Spatially Continuous EDEN Water-Surface Model for the Everglades, Florida

The Everglades Depth Estimation Network (EDEN) is an integrated network of realtime water-level monitoring, ground-elevation modeling, and water-surface modeling that provides scientists and managers with current (2000-present), online water-stage and water-depth information for the entire freshwater portion of the Greater Everglades. Continuous daily spatial interpolations of the EDEN network stage data are presented on grid with 400-square-meter spacing. EDEN offers a consistent and documented dataset that can be used by scientists and managers to: (1) guide large-scale field operations, (2) integrate hydrologic and ecological responses, and (3) support biological and ecological assessments that measure ecosystem responses to the implementation of the Comprehensive Everglades Restoration Plan (CERP) (U.S. Army Corps of Engineers, 1999). The target users are biologists and ecologists examining trophic level responses to hydrodynamic changes in the Everglades. The first objective of this report is to validate the spatially continuous EDEN water-surface model for the Everglades, Florida developed by Pearlstine et al. (2007) by using an independent field-measured data-set. The second objective is to demonstrate two applications of the EDEN water-surface model: to estimate site-specific ground elevation by using the validated EDEN water-surface model and observed water depth data; and to create water-depth hydrographs for tree islands. We found that there are no statistically significant differences between model-predicted and field-observed water-stage data in both southern Water Conservation Area (WCA) 3A and WCA 3B. Tree island elevations were derived by subtracting field water-depth measurements from the predicted EDEN water-surface. Water-depth hydrographs were then computed by subtracting tree island elevations from the EDEN water stage. Overall, the model is reliable by a root mean square error (RMSE) of 3.31 cm. By region, the RMSE is 2.49 cm and 7.77 cm in WCA 3A and 3B, respectively. This new landscape-scale hydrological model has wide applications for ongoing research and management efforts that are vital to restoration of the Florida Everglades. The accurate, high-resolution hydrological data, generated over broad spatial and temporal scales by the EDEN model, provides a previously missing key to understanding the habitat requirements and linkages among native and invasive populations, including fish, wildlife, wading birds, and plants. The EDEN model is a powerful tool that could be adapted for other ecosystem-scale restoration and management programs worldwide.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.