Summary

Fundamental structural features of risk maps influence how health risk and burden information is understood. The mapping of health data by medical geographers in the 1800s has evolved into the field of geovisualization and the use of online, geographic information system (GIS) interactive maps. Thematic (statistical) map types provide basic principles for mapping geographic health data. It is important to match the nature of statistical data with map type to minimize the potential for communicating misleading messages. Strategic use of structural map features can facilitate or hinder accurate comprehension of health risk messages in maps. A key challenge remains in designing maps to communicate a clear message given the complexity of modern health risk burdens. Various structural map features such as symbols, color, grouping of statistical data, scale, and legend must be considered for their impact on accurate comprehension and message clarity. Cognitive theory in relationship to map comprehension plays a role, as do insights from research on visualizing uncertainty, future trends in developing predictive mapping tools for public health planning, the use of geo-social and “big data,” as well as data ownership.