GIS method and the Social Vulnerability Index in Climate Change Vulnerability Assessment

A major barrier in climate change studies is the analysis and interpretation of various climate related data.  To address this problem, we developed a technique within ArcGIS that utilizes a raster overlay.  In a typical raster overlay, each cell of each layer references the same geographic location which makes it well suited to combining characteristics for numerous layers into a single layer. Numeric values are then assigned to each characteristic, allowing you to mathematically combine the layers and assign a new value to each cell in the output layer. Using the raster overlay approach at a county level for the state of Illinois we took multiple sets of data, in particular the Center for Diseases Control and Prevention (CDC) Social Vulnerability Index and various climate (e.g. flood, etc.) and health related data (e.g. asthma hospitalizations, etc.) to evaluate their application to various climate-sensitive diseases.  The results of the analysis allowed us to visualize climate change impacts to individual counties throughout Illinois and determine which of those counties have the highest risk based on historical trend analysis.  This will eventually help decision makers with future adaption planning that will impact health and address gaps in critical public health functions and service.