Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US.
Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US.
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DOI：
10.1080/19475683.2022.2133167
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发表时间：
2022
期刊：
影响因子：
5
通讯作者：
Pagan, Jose A.
中科院分区：
文献类型：
--
作者：
Zhang, Xuan;Mu, Lan;Zhang, Donglan;Mao, Yuping;Shi, Lu;Rajbhandari-Thapa, Janani;Chen, Zhuo;Li, Yan;Pagan, Jose A.
关键词：
自2021年12月以来，COVID-19大流行已导致全球确诊病例超过6亿例。心血管疾病（CVD）既是COVID-19死亡率的风险因素，也是许多COVID-19患者出现的并发症。这项研究使用Twitter数据来识别相关推文的时空模式以及与国家、地区和州一级每日COVID-19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）期间提及COVID-19和CVD相关词汇的推文，并使用GIScience技术将推文地理编码到州一级。我们进一步提出并验证了Twitter用户注册状态可以作为地理标记的可行代理。我们应用地理和时间分析来调查人们何时何地谈论COVID-19和CVD。我们的研究结果表明，COVID-19和CVD相关推文的趋势与COVID-19的趋势相关，特别是每日死亡人数。这些社交媒体信息表明，即使在医学界开始就COVID-19的心血管疾病方面达成共识和理论支持之前，心血管疾病在COVID-19大流行中的重要作用已得到广泛认可。第二波疫情导致相关推文再次上升，但没有第一波那么多，因为推文频率从2月到4月增加，到6月下降，并在7月反弹。在地区层面，与全国整体相比，四个地区（东北部、中西部、北部和西部）的相关推文趋势相同。然而，只有东北地区的推文数量、新病例和新死亡病例之间具有高度相关性（0.8-0.9）。对于第二波确诊的新病例，主要贡献地区南部和西部并没有像第一波那样涟漪那么多相关推文。我们的理解是，早期的消息在第一波中引起了美国各地更多的关注和讨论，尽管当时有些地区受到的影响不如东北部。这项研究可以扩大到更多的地理和时间尺度，并与更多的物理和社会经济变量，在未来更好的数据采集。
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.
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影响因子：
1.5
作者：
Liu S;Young SD
通讯作者：
Young SD
影响因子：
12.7
作者：
Mackey, Tim K.;Kalyanam, Janani;Lanckriet, Gert
通讯作者：
Lanckriet, Gert
影响因子：
3.9
作者：
Francis, Diane B.
通讯作者：
Francis, Diane B.
影响因子：
7.4
作者：
Nagel AC;Tsou MH;Spitzberg BH;An L;Gawron JM;Gupta DK;Yang JA;Han S;Peddecord KM;Lindsay S;Sawyer MH
通讯作者：
Sawyer MH
DOI：
10.15585/mmwr.mm6912e2
发表时间：
2020-03-27
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
--
作者：
CDC COVID-19 Response Team
通讯作者：
CDC COVID-19 Response Team