Browsing by Author "Stanforth, Austin"

Now showing 1 - 4 of 4
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    Exploratory Analysis of Dengue Fever Niche Variables within the Río Magdalena Watershed
    (MDPI, 2016-09-19) Stanforth, Austin; Moreno-Madriñán, Max J.; Ashby, Jeffrey; Department of Environmental Health Sciences, FSPH
    Previous research on Dengue Fever have involved laboratory tests or study areas with less diverse temperature and elevation ranges than is found in Colombia; therefore, preliminary research was needed to identify location specific attributes of Dengue Fever transmission. Environmental variables derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) satellites were combined with population variables to be statistically compared against reported cases of Dengue Fever in the Río Magdalena watershed, Colombia. Three-factor analysis models were investigated to analyze variable patterns, including a population, population density, and empirical Bayesian estimation model. Results identified varying levels of Dengue Fever transmission risk, and environmental characteristics which support, and advance, the research literature. Multiple temperature metrics, elevation, and vegetation composition were among the more contributory variables found to identify future potential outbreak locations.
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    Niche Modeling of Dengue Fever Using Remotely Sensed Environmental Factors and Boosted Regression Trees
    (MDPI, 2017-04) Ashby, Jeffrey; Moreno-Madriñán, Max J.; Yiannoutsos, Constantin T.; Stanforth, Austin; Environmental Health Science, School of Public Health
    Dengue fever (DF), a vector-borne flavivirus, is endemic to the tropical countries of the world with nearly 400 million people becoming infected each year and roughly one-third of the world’s population living in areas of risk. The main vector for DF is the Aedes aegypti mosquito, which is also the same vector of yellow fever, chikungunya, and Zika viruses. To gain an understanding of the spatial aspects that can affect the epidemiological processes across the disease’s geographical range, and the spatial interactions involved, we created and compared Bernoulli and Poisson family Boosted Regression Tree (BRT) models to quantify the overall annual risk of DF incidence by municipality, using the Magdalena River watershed of Colombia as a study site during the time period between 2012 and 2014. A wide range of environmental conditions make this site ideal to develop models that, with minor adjustments, could be applied in many other geographical areas. Our results show that these BRT methods can be successfully used to identify areas at risk and presents great potential for implementation in surveillance programs.
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    Solar Panel Efficacy vs. Altitude in an Urban City Environment
    (American Society for Engineering Education, 2015-06) Elkhatib, Wiaam; Schubert, Peter J.; Zusack, Steven; Rosales, Emily; Stanforth, Austin; Department of Engineering Technology, Purdue School of Engineering and Technology, IUPUI
    In light of current issues of global warming, pollution, and fossil fuel depletion, alternative and renewable energy sources are increasing in desirability. Among these, solar energy is a popular option. However, it is hypothesized that particulate pollution in urban atmospheres limits photovoltaic (PV) efficacy both in accumulated grime and also in altitude via sunlight attenuation. The objective of this study is to measure photovoltaic power output near solar noon at multiple heights within a city environment to determine the influence of altitude on power output. Building rooftops between 200 and 800 feet were sampled simultaneously with a ground level control within a broad university courtyard. Days having no cloud cover were preferentially chosen. Other factors to consider include the “urban heat island” effect and water vapor in the air, so meteorological parameters were measured simultaneously to reduce confounding errors. Multiple repeated tests were conducted to increase confidence, especially since the effect was anticipated to be small in magnitude. Additionally, students affiliated with the project completed surveys to assess how their involvement impacted their learning of experimental design and procedures. Students who chose not to participate were also surveyed to provide a control group. Comparisons in the data are drawn on a power to ambient light ratio to minimize bias between the PV panels used for testing. Preliminary analysis indicates the effect of altitude is minimal within the parameters of this study. Analysis of our data did not significantly demonstrate an improvement in solar productivity at increased altitudes. However, the rigorous test methodology developed provides a means for quantitative analysis in cities with greater levels of pollution relative to the city tested. The survey of students indicated a positive correlation between participation in the project and the amount students felt they learned during the process.
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    Spatiotemporal Variations in Heat-Related Health Risk in Three Midwestern U.S. Cities Between 1990 and 2010
    (Taylor & Francis Group in Geocarto International, 2013-04-15) Johnson, Daniel P.; Webber, Jeremy; Urs Beerval Ravichandra, Kavya; Lulla, Vijay; Stanforth, Austin
    Mortality from extreme heat is a leading cause of weather-related fatality, which is expected to increase in frequency with future climate scenarios. This study examines the spatiotemporal variations in heat-related health risk in three Midwestern cities in the United States between the years 1990 to 2010; cities include Chicago, Illinois, Indianapolis, IN, and Dayton, OH. In order to examine these variations we utilize the recently developed Extreme Heat Vulnerability Index (EHVI) that uses a principal components solution to vulnerability. The EHVI incorporates data from the U.S. Decadal Census and remotely sensed variables to determine heat-related vulnerability at an intra-urban level (census block group). The results demonstrate significant spatiotemporal variations in heat-health risk within the cities involved.