An Environmental Data Collection for COVID-19 Pandemic Research
An Environmental Data Collection for COVID-19 Pandemic Research
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DOI：
10.3390/data5030068
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发表时间：
2020-09-01
期刊：
影响因子：
2.6
通讯作者：
Yang, Chaowei
中科院分区：
文献类型：
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作者：
Liu, Qian;Liu, Wei;Yang, Chaowei
COVID-19病毒性疾病于二零一九年底浮出水面，并迅速蔓延至地球仪各地。为了快速应对这一流行病，并为各种社区提供数据支持（例如，国家科学基金会（NSF）时空创新中心与包括国际研究人员和实施战略在内的各种任务组一起构建了一个时空平台。与仅提供病毒和健康数据的类似平台相比，该平台将病毒相关环境数据收集（EDC）视为大流行地理空间分析的重要组成部分。EDC包含已证实或可能影响COVID-19传播和毒力或影响大流行对人类健康影响的环境因素（例如，温度、湿度、降水量、空气质量指数和污染物、夜间光照（NTL））。在该平台/框架中，跨多个时空尺度处理和组织环境数据以用于各种应用（例如，每日温度、湿度、降水量的全球绘图，大流行病与各城市气候和天气因素平均值的相关性）。本文介绍COVID-19相关环境数据收集的原始输入数据、再处理数据的结构和元数据、数据存储以及共享和质量控制方法。
The COVID-19 viral disease surfaced at the end of 2019 and quickly spread across the globe. To rapidly respond to this pandemic and offer data support for various communities (e.g., decision-makers in health departments and governments, researchers in academia, public citizens), the National Science Foundation (NSF) spatiotemporal innovation center constructed a spatiotemporal platform with various task forces including international researchers and implementation strategies. Compared to similar platforms that only offer viral and health data, this platform views virus-related environmental data collection (EDC) an important component for the geospatial analysis of the pandemic. The EDC contains environmental factors either proven or with potential to influence the spread of COVID-19 and virulence or influence the impact of the pandemic on human health (e.g., temperature, humidity, precipitation, air quality index and pollutants, nighttime light (NTL)). In this platform/framework, environmental data are processed and organized across multiple spatiotemporal scales for a variety of applications (e.g., global mapping of daily temperature, humidity, precipitation, correlation of the pandemic to the mean values of climate and weather factors by city). This paper introduces the raw input data, construction and metadata of reprocessed data, and data storage, as well as the sharing and quality control methodologies of the COVID-19 related environmental data collection.