A CyberGIS Approach to Exploring Neighborhood-level Vulnerability

Keywords: Social Vulnerability, cyberGIS, web-based GIS, COVID-19, Health Disparity, Disaster
Abstract Type: Paper Abstract

Abstract

Timely identification of disaster-prone neighborhoods and examination of disparity in disaster exposure are critical for policymakers to plan efficient disaster management strategies. These are also important for first responders and professionals in health and social care services to alleviate human suffering from disasters. Many studies have investigated racial, ethnic, and geographic disparities and populations most vulnerable to adverse events. However, not much attention has been paid to the development of easily accessible and reusable tools to enable (1) the prompt identification of vulnerable neighborhoods to disasters and (2) the examination of the social disparity in disaster impact. In this research, we have developed a cyberGIS-based visual analytics tool called vulnerable neighborhood explorer (VNE) that allows users to (1) delineate neighborhoods based on their selection of variables describing socioeconomic and demographic profiles and (2) explore which neighborhoods are susceptible to the impacts of disasters based on specific socioeconomic and demographic characteristics. As a case study, we used VNE and explored the disparities in COVID-19 cases, tests, and fatality rates among various neighborhood types in Chicago. Through this exploration process, we revealed that VNE can provide new insights into the identification of vulnerable neighborhoods that need immediate attention for disaster control, management, and relief.