Background: The outbreak of the new coronavirus disease (COVID-19) has affected human life to a great extent on a worldwide scale. During the coronavirus pandemic, public health professionals at the early outbreak faced an extraordinary challenge to track and quantify the spread of disease. Objective: To investigate whether a digital surveillance model using google trends (GT) is feasible to monitor the outbreak of coronavirus in the Kingdom of Saudi Arabia. Methods: We retrieve GT data using ten common COVID-19 symptoms related keywords from March 2, 2020, to October 31, 2020. Spearman correlation were performed to determine the correlation between COVID-19 cases and the Google search terms. Results: GT data related to Cough and Sore Throat were the most searched symptoms by the Internet users in Saudi Arabia. The highest daily correlation found with the Loss of Smell followed by Loss of Taste and Diarrhea. Strong correlation as well was found between the weekly confirmed cases and the same symptoms: Loss of Smell, Loss of Taste and Diarrhea. Conclusions: We conducted an investigation study utilizing Internet searches related to COVID-19 symptoms for surveillance of the pandemic spread. This study documents that google searches can be used as a supplementary surveillance tool in COVID-19 monitoring in Saudi Arabia.
翻译:目标:调查使用谷歌趋势的数字监测模型(GT)是否可行,以监测在沙特阿拉伯王国爆发的冠状病毒(COVID-19),方法:从2020年3月2日到2020年10月31日,我们利用10个共同COVID-19症状相关关键词检索GT数据。Spearman进行了相关调查,以确定COVID-19案例与谷歌搜索术语之间的相互关系。结果:沙特阿拉伯互联网用户搜索最多的症状是与Cough和Sore Throat有关的GT数据。在Taste和Diarrhea之后,每天发现的最高关联与Taste和Diarrhea的气味损失有关。在每周确认的案例与同样的症状之间也发现了强烈的关联:气味损失、Taste和Diarhea。结论:我们进行了一项调查研究,利用互联网搜索与COVI-19的病例相关数据进行COVI-19监测,以监测沙特阿拉伯的这一工具可以传播。