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Maps have played an important role in epidemiology and public health sincethe beginnings of these disciplines. With the advent of geographicalinformation systems and advanced information visualization techniques,interactive maps have become essential tools for the analysis of geographicalpatterns of disease incidence and prevalence, as well as communication ofpublic health knowledge, as dramatically illustrated by the proliferation ofweb-based maps and disease surveillance ``dashboards'' during the COVID-19pandemic. While such interactive maps are usually effective in supportingstatic spatial analysis, support for spatial epidemiological visualization andmodelling involving distributed and dynamic data sources, and support foranalysis of temporal aspects of disease spread have proved more challenging.Combining these two aspects can be crucial in applications of interactive mapsin epidemiology and public health work. In this paper, we discuss these issuesin the context of support for disease surveillance in remote regions, includingtools for distributed data collection, simulation and analysis, and enablingmultidisciplinary collaboration.

Temporal and Spatial Elements in Interactive Epidemiological Maps