Ling Bian - US grants

Geographic information systems (GIS) is an area of study causing increased excitement among students. This project, therefore, strives to enhance this area of geography by accomplishing specific objectives to improve the curriculum. New undergraduate courses, internships, and programs are being added, and a specific plan has been developed for enhancing four analytical geography courses. This plan also involves redesigning courses, updating laboratory computing and digital data analysis equipment, and redesigning laboratory exercises to incorporate the use of new analytical capabilities. It is also expected that the physical geography curriculum will be improved by incorporating modern image display and geographic information analysis capabilities into existing laboratory and field exercises.

DESCRIPTION (provided by applicant): Communicable diseases, such as influenza, are transmitted from individual to individual following a network of contacts in a population. Reports on recent outbreaks, such as SARS, the Bird flu, and the H1N1 flu, have repeatedly stressed the critical role of contact networks. We propose an innovative Three-population and Three-scale Social Network (3p3sNet) model to simulating the spatial and temporal dispersion of influenza in a metropolitan population in Buffalo, NY. The 3p3sNet aims to construct a realistic contact network by representing interacting and mobile behaviors of individuals at three scales and three types of places. These involve individual (microscopic) -> local network (mesoscopic) -> population (macroscopic) as nighttime population at homes, daytime population at workplaces, and pastime population at service places. Through this network, diseases disperse from infectious individuals to their local networks then to the population-wide network in a complex dynamic fashion. Modeling the disease dispersion through this network provides invaluable insights in who might be at risk, where and when this risk might occur, and with whom these at-risk individuals might be in contact. These insights lay the foundation of developing spatially and temporally sensitive intervention strategies targeted towards the most vulnerable individuals and social groups. Furthermore, the 3p3sNet can be applied in modeling the epidemiology of any disease where human contacts play a critical role. In implementing 3p3sNet, we propose to use mobile phone data to extract the individual interaction and travel behaviors. We embrace recent developments in economics, geostatistics, econometrics, and machine learning to construct the network. We develop an innovative co-kriging approach to expanding local households to population-wide households and a novel distance-based GEV discrete choice model to link homes to workplaces and service places. It is anticipated that the assemblage of these advanced methods will enable new capabilities and bring transformative improvements in health-related studies in metropolitan areas. We will conduct a data-rich validation process for the three constructed populations, the links between them, and the simulated disease dispersion through the population. A comprehensive range of independent datasets will be used to support the proposed validation. These involve high-resolution population, workplace, and service place data, surveys of individual interaction and travel behavior, and reports on influenza infections. The multidisciplinary team comprises world-renown leaders and scholars in epidemiology, agent-based and social network modeling, human mobility analysis, geographical information science, and machine learning. The proposed project represents emerging frontiers in the modeling of communicable diseases and will redefine the capabilities of epidemiological models.

This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase students' motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) by its focus on geotechnology (also called GIS or geospatial information systems) careers. The programmatic goal of this project is to prepare teachers to engage middle and high schools students in high-needs and high-potential school districts with cutting-edge web GIS knowledge and skills in order to motivate students to pursue formal school-based and informal out-of-school educational experiences. Project research, guided by social-cognitive career development theory and other work, will investigate what programmatic experiences contribute to student motivation and cognitive gains and what factors contribute to teacher integration of GIS content into the school curriculum.

During three years of the project, the project will offer a summer teacher workshop and a student GIS summer camp each year, The camp will include field trips to GIS-related industry and government agencies, supported by mentors from these organizations. The workshop and camp will support teachers and students in learning GIS concepts and skills. Teachers will also learn approaches to integrate GIS- and career-related in STEM and social studies classes. Students who attended the summer camp will be supported in organizing a GIS after-school club. This project will research one of the guiding questions of the ITEST program: What coherent sets of experiences effectively and efficiently support student competency, motivation and persistence for productive participation in the STEM-related workforce of today and the future? The project will use mixed methods research design including a quasi-experimental study. Research findings from this project will help educators better understand and address the context and factors that influence integration of GIS in middle and high school curricula.