@文章{信息:doi/10.2196/23518，作者=“Jimenez, Alberto Jimenez和Estevez-Reboredo, Rosa M和Santed, Miguel A和Ramos, Victoria”，标题=“与COVID-19症状相关的谷歌搜索和西班牙本地COVID-19发病率:相关性研究”，期刊=“J Med Internet Res”，年=“2020”，月=“12月”，日=“18”，卷=“22”，数=“12”，页=“e23518”，关键词=“行为流行病学;大数据;智能数据;跟踪;重点学科;预测;预测;infosurveillance;infodemiology;背景:COVID-19与甲型H1N1流感、黑死病和天花等其他疾病一样，是人类历史上最大的流行病之一。 This study is a small contribution that tries to find contrasted formulas to alleviate global suffering and guarantee a more manageable future. Objective: In this study, a statistical approach was proposed to study the correlation between the incidence of COVID-19 in Spain and search data provided by Google Trends. Methods: We assessed the linear correlation between Google Trends search data and the data provided by the National Center of Epidemiology in Spain---which is dependent on the Instituto de Salud Carlos III---regarding the number of COVID-19 cases reported with a certain time lag. These data enabled the identification of anticipatory patterns. Results: In response to the ongoing outbreak, our results demonstrate that by using our correlation test, the evolution of the COVID-19 pandemic can be predicted in Spain up to 11 days in advance. Conclusions: During the epidemic, Google Trends offers the possibility to preempt health care decisions in real time by tracking people's concerns through their search patterns. This can be of great help given the critical, if not dramatic need for complementary monitoring approaches that work on a population level and inform public health decisions in real time. This study of Google search patterns, which was motivated by the fears of individuals in the face of a pandemic, can be useful in anticipating the development of the pandemic. ", issn="1438-8871", doi="10.2196/23518", url="//www.mybigtv.com/2020/12/e23518/", url="https://doi.org/10.2196/23518", url="http://www.ncbi.nlm.nih.gov/pubmed/33156803" }