  While many dashboards for visualizing COVID-19 data exist, most separate
geospatial and temporal data into discrete visualizations or tables. Further,
the common use of choropleth maps or space-filling map overlays supports only a
single geospatial variable at once, making it difficult to compare the temporal
and geospatial trends of multiple, potentially interacting variables, such as
active cases, deaths, and vaccinations. We present CoronaViz, a COVID-19
visualization system that conveys multilayer, spatiotemporal data in a single,
interactive display. CoronaViz encodes variables with concentric, hollow
circles, termed geocircles, allowing multiple variables via color encoding and
avoiding occlusion problems. The radii of geocircles relate to the values of
the variables they represent via the psychophysically determined Flannery
formula. The time dimension of spatiotemporal variables is encoded with
sequential rendering. Animation controls allow the user to seek through time
manually or to view the pandemic unfolding in accelerated time. An adjustable
time window allows aggregation at any granularity, from single days to
cumulative values for the entire available range. In addition to describing the
CoronaViz system, we report findings from a user study comparing CoronaViz with
multi-view dashboards from the New York Times and Johns Hopkins University.
While participants preferred using the latter two dashboards to perform queries
with only a geospatial component or only a temporal component, participants
uniformly preferred CoronaViz for queries with both spatial and temporal
components, highlighting the utility of a unified spatiotemporal encoding.
CoronaViz is open-source and freely available at http://coronaviz.umiacs.io.
