An Online Tool for Understanding and Monitoring COVID-19 Trends and Spread Based on Self-Reporting Tweets

Jiacheng Xie, Ziyang Zhang, Joel Hilliard,Guanghui An, Xiaoting Tang,Yang Yu,Xiu-Feng Wan,Dong Xu

2023 IEEE International Conference on Medical Artificial Intelligence (MedAI)(2023)

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摘要
After three years of multiple waves, COVID-19 has become epidemic, causing recurrent outbreaks. Many of COVID-19 cases have mild symptoms self-assessed at home, making it difficult to acquire formal laboratory data. This makes it challenging to correctly track the daily total of confirmed cases and comprehend the disease pattern. To solve this problem, we developed a COVID-19 analytic platform https://covlab.tech/ based on self-reported tweets to track the pandemic's progression and trends. This study extends traditional infectious disease monitoring and holds crucial practical significance for understanding and controlling COVID-19.
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关键词
COVID-19,Twitter,machine learning,epidemic,self-reported tweets,data mining,symptoms,reinfection
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