  Maps have played an important role in epidemiology and public health since
the beginnings of these disciplines. With the advent of geographical
information systems and advanced information visualization techniques,
interactive maps have become essential tools for the analysis of geographical
patterns of disease incidence and prevalence, as well as communication of
public health knowledge, as dramatically illustrated by the proliferation of
web-based maps and disease surveillance ``dashboards'' during the COVID-19
pandemic. While such interactive maps are usually effective in supporting
static spatial analysis, support for spatial epidemiological visualization and
modelling involving distributed and dynamic data sources, and support for
analysis of temporal aspects of disease spread have proved more challenging.
Combining these two aspects can be crucial in applications of interactive maps
in epidemiology and public health work. In this paper, we discuss these issues
in the context of support for disease surveillance in remote regions, including
tools for distributed data collection, simulation and analysis, and enabling
multidisciplinary collaboration.
