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.
翻译:视觉分析技术是支持决策和应对不断增加的数据的有用工具,这在监测自然或人为现象时尤其重要。在监测疾病进展时,视觉分析方法帮助决策者选择理解甚至防止传播途径。在本文中,我们提出一个新的视觉分析工具,用于监测COVID-19的传播。我们利用城市最近的邻里城市模仿相邻城市,并根据对所考虑的城市及其周边城市的比较分析COVID-19的传播情况。此外,这种分析是按时间进行的,有利于评估孤立政策。我们通过分析巴西圣保罗州相邻城市COVID-19的进展来验证我们的工具。