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A personalized activity-based spatiotemporal risk mapping approach to the COVID-19 pandemic

机译:基于个性的活动的时空风险绘图方法,用于Covid-19流行病

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The outbreak of the unprecedented Coronavirus Disease 2019 (COVID-19) pandemic calls for innovative risk assessment and mapping approaches to prompt public messaging. Most of the existing approaches aim to present population risks associated with geographic areas (e.g., county), thus providing limited values to guide individuals to take proactive measures against COVID-19. To better facilitate the general public to make informed decisions on daily activity plans, we propose an activity-based spatiotemporal risk mapping approach to capture and represent exposure risk at a personal level. This approach leverages the classical space-time representations to capture personal activity space and measures exposure risk in such activity space. This approach further implements geovisualization designs to communicate measured exposure information. To illustrate the usability of the approach, we have conducted a case study in Denver, Colorado with COVID-19 data from October 2020 and four representative travel profiles.
机译:爆发前所未有的冠状病毒疾病2019(Covid-19)大流行调用创新风险评估和绘图方法,以提示公开消息传递。大多数现有方法旨在呈现与地理区域(例如,县)相关的人口风险,从而提供有限的价值,以指导个人对Covid-19采取积极措施。为了更好地促进公众对日常活动计划做出明智的决定,我们提出了一种基于活动的时空风险映射方法来捕获和代表个人层面的暴露风险。这种方法利用经典时空表示来捕获个人活动空间并测量这种活动空间中的曝光风险。该方法进一步实现了地理化设计以传达测量的曝光信息。为了说明该方法的可用性,我们在科罗拉多州的丹佛举行了一个案例研究,来自10月2020年10月和四个代表性旅行简介的Covid-19数据。

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