Visualization techniques have proven to be useful tools to support decision making and to cope with increasing amount of data. In order to help analyzing the progressionof number of COVID-19 cases, we propose a new visual analytic tool . We use k-nearest neighbors of cities to mimic regions and allow analysis of COVID-19 dissemination based on the comparison of a city under consideration and its neighborhood , moreover, such analysis is performed based on periods of time , which facilitates  assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in regions of S\~ao Paulo state, Brazil.
Visual analytics techniques are useful tools to support decision-making and cope with increasing data, which is particularly important when monitoring natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers choose to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination . We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on the comparison of a city under consideration and its neighborhood . Moreover, such analysis is performed based on periods , which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of S\~ao Paulo state, Brazil.
R
Visualization techniques have proven to be
Visual analytics techniques are
R
decision making and to
decision-making and
R
amount of data. In order to help analyzing the progressionof number of COVID-19 cases,
data, which is particularly important when monitoring natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers choose to understand or even prevent dissemination paths. In this paper,
R
analytic tool
analytics tool for monitoring COVID-19 dissemination
R
regions and allow analysis of
neighboring cities and analyze
R
, moreover,
. Moreover,
D
of time
A
the
R
regions
neighboring cities