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美国与新冠病毒疾病和心血管疾病相关推文的地理与时间分析

Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US.

作者信息

Zhang Xuan, Mu Lan, Zhang Donglan, Mao Yuping, Shi Lu, Rajbhandari-Thapa Janani, Chen Zhuo, Li Yan, Pagán José A

机构信息

Department of Geography, University of Georgia, Athens, GA, USA.

Division of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA.

出版信息

Ann GIS. 2022;28(4):491-500. doi: 10.1080/19475683.2022.2133167. Epub 2022 Oct 21.

Abstract

The COVID-19 pandemic has resulted in more than 600 million confirmed cases worldwide since December 2021. Cardiovascular disease (CVD) is both a risk factor for COVID-19 mortality and a complication that many COVID-19 patients develop. This study uses Twitter data to identify the spatiotemporal patterns and correlation of related tweets with daily COVID-19 cases and deaths at the national, regional, and state levels. We collected tweets mentioning both COVID-19 and CVD-related words from February to July 2020 (Eastern Time) and geocoded the tweets to the state level using GIScience techniques. We further proposed and validated that the Twitter user registration state can be a feasible proxy of geotags. We applied geographical and temporal analysis to investigate where and when people talked about COVID-19 and CVD. Our results indicated that the trend of COVID-19 and CVD-related tweets is correlated to the trend of COVID-19, especially the daily deaths. These social media messages revealed widespread recognition of CVD's important role in the COVID-19 pandemic, even before the medical community started to develop consensus and theory supports about CVD aspects of COVID-19. The second wave of the pandemic caused another rise in the related tweets but not as much as the first one, as tweet frequency increased from February to April, decreased till June, and bounced back in July. At the regional level, four regions (Northeast, Midwest, North, and West) had the same trend of related tweets compared to the country as a whole. However, only the Northeast region had a high correlation (0.8-0.9) between the tweet count, new cases, and new deaths. For the second wave of confirmed new cases, the major contributing regions, South and West, did not ripple as many related tweets as the first wave. Our understanding is that the early news attracted more attention and discussion all over the U.S. in the first wave, even though some regions were not impacted as much as the Northeast at that time. The study can be expanded to more geographic and temporal scales, and with more physical and socioeconomic variables, with better data acquisition in the future.

摘要

自2021年12月以来,新冠疫情已导致全球超过6亿例确诊病例。心血管疾病既是新冠死亡的一个风险因素,也是许多新冠患者会出现的一种并发症。本研究利用推特数据来识别国家、地区和州层面相关推文的时空模式以及与每日新冠病例和死亡人数的相关性。我们收集了2020年2月至7月(东部时间)提及新冠和心血管疾病相关词汇的推文,并使用地理信息科学技术将推文地理编码到州层面。我们进一步提出并验证了推特用户注册州可以作为地理标签的一个可行替代。我们应用地理和时间分析来调查人们谈论新冠和心血管疾病的地点和时间。我们的结果表明,与新冠和心血管疾病相关的推文趋势与新冠趋势相关,尤其是每日死亡人数。这些社交媒体信息揭示了即使在医学界开始就新冠疫情中心血管疾病方面形成共识并获得理论支持之前,人们就广泛认识到心血管疾病在新冠疫情中的重要作用。疫情的第二波导致相关推文再次增加,但幅度不如第一波,因为推文频率从2月到4月增加,到6月下降,7月又反弹。在地区层面,四个地区(东北部、中西部、北部和西部)与全国整体情况相比,相关推文趋势相同。然而,只有东北地区在推文数量、新增病例和新增死亡人数之间具有高度相关性(0.8 - 0.9)。对于第二波确诊的新增病例,主要贡献地区南部和西部产生的相关推文不如第一波多。我们的理解是,第一波疫情中的早期新闻在美国各地吸引了更多关注和讨论,尽管当时一些地区受到的影响不如东北部那么大。未来该研究可以扩展到更大的地理和时间尺度,并纳入更多物理和社会经济变量,同时获取更好的数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea42/9997116/6299021ee075/nihms-1857306-f0001.jpg

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