No description available.

No description available.

No description available.

Recently mosquito-borne illnesses (MBI) such as Chikungunya (CHIKV) and Zika virus (ZV) proved to be of major public health importance in the Western Hemisphere. The purpose of this study was to determine the prevalence of selfreported MBI by geographic region in Nueva Vida, Nicaragua and gain insight into the number of community members seeking medical attention for MBI. This study involved a door-to-door survey of 1015 households (N=5778) in Nueva Vida, a community within Ciudad Sandino, Nicaragua and capture of spatial video of the community to determine areas of potential high risk for MBI outbreaks. The community is divided into sections, or etapas, and surveys were completed for each of the five etapas. The head of the household completed the survey and a response rate of approximately 82% was achieved for Nueva Vida. The number of selfreported MBI totaled 1,730 individuals or 29.9% of the surveyed population. Of the self-reported illnesses, 2.4 % were malaria (N=42), 5.0% were dengue (N=87), 91.9 % were chikungunya (N= 1589), and 0.7% were Zika (N =12). For all MBI 21.25 % of the population visited a doctor (N=1228) and 2.71 % visited a hospital (N= 157). Environmental risk factors such as standing water and trash were documented through spatial video. MBI and environmental risk factors were mapped using geospatial analysis. MBI varied by location with etapas 2 and 3 having the highest prevalence MBI (30% and 26%, respectively). Maps provided a visualization of MBI prevalence and environmental risk factors, illustrating sections of etapas 2, 3, and 4 as the highest risk zones in the community for potential MBI outbreaks, such as ZV or CHIKV. The data demonstrates that MBI have a great potential to impact the Nueva Vida community. Results suggest a need for educational programs onMBI transmission and targeted prevention activities in high-risk areas, specifically with the potential spread of ZV in a community where CHIKV prevalence was previously high.

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Background: Childhood Sexual Abuse (CSA) has been linked to a range of adult health problems. This study investigates the association between CSA and sexual risk behaviors of college students in Appalachia. Methodology: Students enrolled in introductory psychology courses at a four-year university in the Appalachian region participated in this survey in 2015. All analyses were completed in SAS. Among 995 participants, the average age was 20 and 69% were female. Simple and multivariate logistic regressions were completed for CSA to predict alcohol use before sex, self-reported diagnosis of Sexually Transmitted Diseases (STD), and unintended pregnancy. Age, gender, and other Adverse Childhood Experiences (ACEs) (physical, emotional, verbal abuse, substance abuse in family, family mental illness, and family incarceration) were considered as covariates. Only significant covariates were included in the final model. Results: In the unadjusted models, CSA was significantly associated with alcohol use before sex (OR=2.66, CI=1.62-4.38), risk of STD (OR=2.42, CI=1.12-5.21), and unintended pregnancy (OR=5.72, CI=3.12-10.50). Association between CSA and unintended pregnancy (OR=3.12, CI=1.60-6.08) was significant in the final model. CSA increased the odds of drinking alcohol before sex by 1.83 among females compared to males (CI=1.31-2.54). In the final model, verbal abuse was significantly associated with alcohol use before sex (OR=1.56, CI=1.1-2.22) and STD (OR=4.05, CI=2.11-7.75) while physical abuse was a significant predictor of unintended pregnancy (OR=2.14, CI=1.07-4.30). Conclusion: CSA increased the odds of some risky sexual behaviors among this college aged sample. However, the importance of other forms of ACEs also deserve further exploration.

Southern adolescents are among the most affected groups in the United States (US) for human immunodeficiency virus (HIV) infections. The prevalence of unprotected sex is higher in white adolescents compared to minority adolescents despite racial disparities of HIV infection in the US. In addition, females are at an increased risk for unprotected sex compared to males. The objective of this study was to evaluate condom use is US high school (HS) students in southern states. Weighted data were obtained from the 2011 and 2013 National Youth Risk Behavior Survey (N=28,793). Condom use was defined as respondents using a condom at last sexual intercourse. Descriptive statistics, chi-squared analyses, simple, and multiple logistic regression were used to examine the influence of race and gender on condom use among southern HS students using SAS software. Bivariate analyses illustrates that compared to white females, minority males were more likely to use condoms (OR-1.79; CI-1.66-1.92). Multivariate analyses show that compared to white females, minority males and white males were more likely to use condoms (OR-2.04; CI-1.87-2.23, OR-1.74; CI-1.61-1.87, respectively). In addition, students who had a body weight perception of “overweight” (OR-2.23; CI-2.08-2.38) increased the odds of condom use compared to body weight perception of "about the right weight". Gender and race along with psychosocial factors were associated with condom use in HS students in the southern states. These results can be utilized to target HIV prevention activities to key affected populations.

ETSU Elevates Housing placed third and is represented by Appalachia Service Project (ASP), ETSU College of Public Health and Ballad Health Department of Population Health. The groups will work together to launch “Healthy Homes: Tri-Cities” to provide critical home repairs for families in the Tri-Cities region in need of warmer, safer and drier housing. The majority of these repairs will be made by volunteers from the region to elevate one family at a time out of substandard housing. In an effort to select the projects with the greatest potential return on investment for the patient and stakeholders, projects may be referred by Ballad Health or ASP will select applicants with stated health concerns.

Housing and health care are more closely related than ever before. To address this issue head-on, Ballad Health, Appalachia Service Project, and East Tennessee State University's College of Public Health created a regional partnership to research and provide a more holistic and effective approach to healthcare by meeting the housing needs of families in northeast Tennessee and southwest Virginia. Presenters will be Nicole Intagliata, Director of Programs at ASP, and Megan Quinn, Associate Professor at East Tennessee State University. (Megan is replacing Paula Masters from Ballad Health who was originally scheduled to speak.) The session will conclude with a short presentation by Nick Oliver of Hinton Rural Life Center, winner of the Best Practices Award for Home Repair Practices. He'll share about their Healthy Homes Checklist, work with their local Red Cross chapter to check for proper smoke detector installation, and partnership with health care providers to help improve conditions at homes that are linked to health concerns.

The current Zika virus epidemic in the Western hemisphere is representative of the confluence of global climate change and infectious disease expansion, and vector modeling represents a pertinent and timely method to analyze the environment associated with Zika-carrying mosquitoes. Among many mosquito species distribution models, there are varying opinions on which variables are most predictive and, consequently, should be included in modeling efforts. While climate variables (e.g.,mean temperature, mean precipitation) are routinely included, some argue that human population dynamics, in the form of population density and socioeconomic status, should also be included. This project aimed to test the importance of including human population characteristics by modelling the Zika virus vector Aedes aegypti in the Southeastern United States with climate variables, population density, and poverty characteristics. A. aegypti occurrences, global climate data, and population characteristics were obtained from publicly available sources and sampled at a resolution of 2.5 arc-minutes. Data pre and post-processing was completed in ArcMap 10.3 and models were created in Maxent v.3.3.3k. Four models were developed for this project: a climate-only model, a climate and population density model, a climate and poverty model, and a combined model with climate, population density, and poverty. Models were evaluated by comparing test and training area under the curve metrics, omission and commission errors, and variable jackknifing results. The climate-only model performed poorly compared to models with human population characteristics. The combined model was the best fit, though the model with climate and population density had a lower commission rate (21.0% and 20.6%, respectively). Jackknife results for the full model showed that population density was the most significant contributor to the model. This research indicates that more consideration should be given to human population characteristics when modelling mosquito habitats.