The objective of this thesis is to analyze how existing data can address Chagas disease transmission risk in South America given data availability. A literature review was conducted to determine prominent variables that models use to assist with Chagas disease mitigation efforts, followed by a Web search to collect publicly available spatial data pertaining to these variables. The data were then used to create maps of data availability and in an agent-based model to identify which variables are most associated with disease transmission risk. Data availability varied widely across South America, and model results indicate that datasets related to household size and spatial housing arrangement are most important to Chagas disease infection in urban areas. Governments can use this information to better direct their resources to collect data and control the spread of triatomine vectors and Chagas disease more effectively, and potentially identify more cost-effective strategies for vector elimination.