  Public health officials dealing with pandemics like COVID-19 have to evaluate
and prepare response plans. This planning phase requires not only looking into
the spatiotemporal dynamics and impact of the pandemic using simulation models,
but they also need to plan and ensure the availability of resources under
different spread scenarios. To this end, we have developed a visual analytics
environment that enables public health officials to model, simulate, and
explore the spread of COVID-19 by supplying county-level information such as
population, demographics, and hospital beds. This environment facilitates users
to explore spatiotemporal model simulation data relevant to COVID-19 through a
geospatial map with linked statistical views, apply different decision measures
at different points in time, and understand their potential impact. Users can
drill-down to county-level details such as the number of sicknesses, deaths,
needs for hospitalization, and variations in these statistics over time. We
demonstrate the usefulness of this environment through a use case study and
also provide feedback from domain experts. We also provide details about future
extensions and potential applications of this work.
