GEOSPATIAL MODELING OF ASTHMA POPULATION IN RELATION TO AIR POLLUTION– A DECISION SUPPORT FOR HEALTH ADMINISTRATION

Current observations indicate that asthma is growing every year in the United States, specific reasons for this are not well understood. This study stems from an ongoing research effort to investigate the spatio-temporal behavior of asthma and its relatedness to air pollution. The association between environmental variables such as air quality and asthma related health issues over Mississippi State are investigated using Geographic Information Systems (GIS) tools and applications. Health data concerning asthma obtained from Mississippi State Department of Health (MSDH) for a 9-year period 2003-2011, and data of air pollutant concentrations (PM2.5) collected from United States Environmental Protection Agency (USEPA) web resources, are analyzed geospatially to establish the impacts of air quality on human health specifically related to asthma. Disease mapping using geospatial techniques provides valuable insights into the spatial nature, variability, and association of asthma to air pollution. Asthma patient hospitalization data from Mississippi has been analyzed and mapped using quantitative Choropleth techniques in ArcGIS. Patients have been geocoded to their respective zip codes. Potential air pollutant sources of interstate highways, industries, and other land use data have been integrated into a common geospatial platform to understand their adverse contribution on human health. Addresses of existing hospitals and emergency clinics are being injected into analysis to further understand their proximity and easy access to patient locations. At the current level of analysis and understanding, the spatial distribution of Asthma is observed in the populations of zip code regions along the gulf coast, interstate highways, and in counties of Northeast Mississippi. It is also found that asthma is prevalent in most of the urban population. This GIS based project is useful for health risk assessment and provides information decision makers can potentially use to determine placement of future satellite clinics.