Department of Anesthesiology, San Diego School of Medicine, University of California, San Diego, California, United States of America.
Global Health Policy Institute, San Diego, California, United States of America.
PLoS One. 2020 Oct 28;15(10):e0241330. doi: 10.1371/journal.pone.0241330. eCollection 2020.
According to current reporting, the number of active coronavirus disease 2019 (COVID-19) infections is not evenly distributed, both spatially and temporally. Reported COVID-19 infections may not have properly conveyed the full extent of attention to the pandemic. Furthermore, infection metrics are unlikely to illustrate the full scope of negative consequences of the pandemic and its associated risk to communities.
In an effort to better understand the impacts of COVID-19, we concurrently assessed the geospatial and longitudinal distributions of Twitter messages about COVID-19 which were posted between March 3rd and April 13th and compared these results with the number of confirmed cases reported for sub-national levels of the United States. Geospatial hot spot analysis was also conducted to detect geographic areas that might be at elevated risk of spread based on both volume of tweets and number of reported cases.
Statistically significant aberrations of high numbers of tweets were detected in approximately one-third of US states, most of which had relatively high proportions of rural inhabitants. Geospatial trends toward becoming hotspots for tweets related to COVID-19 were observed for specific rural states in the United States.
Population-adjusted results indicate that rural areas in the U.S. may not have engaged with the COVID-19 topic until later stages of an outbreak. Future studies should explore how this dynamic can inform future outbreak communication and health promotion.
根据目前的报告，2019 年冠状病毒病（COVID-19）活跃感染的数量在空间和时间上分布不均。报告的 COVID-19 感染可能没有恰当地传达出对大流行的充分关注。此外，感染指标不太可能说明大流行及其对社区相关风险的全部负面影响的范围。
为了更好地了解 COVID-19 的影响，我们同时评估了 3 月 3 日至 4 月 13 日期间发布的有关 COVID-19 的 Twitter 消息的地理空间和纵向分布，并将这些结果与美国次国家级别的确诊病例数进行了比较。还进行了地理空间热点分析，以根据推文数量和报告病例数检测出可能处于传播高风险的地理区域。
在美国大约三分之一的州中，检测到与 COVID-19 相关的大量推文出现了统计学上显著的异常，其中大多数州的农村居民比例相对较高。与 COVID-19 相关的推文在特定农村州中呈现出成为热点的地理趋势。
人口调整后的结果表明，美国农村地区可能直到疫情爆发的后期才开始关注 COVID-19 话题。未来的研究应探讨这种动态如何为未来的疫情传播和健康促进提供信息。
