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?:abstract
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BACKGROUND: COVID 19 is one of the biggest pandemics in human history along with other diseases such as Spanish flu, plaque and smallpox This study is a small contribution that tries to find contrasted formulas to alleviate this global suffering and guarantee a more manageable future OBJECTIVE: In this study, a statistical approach has been proposed to study the correlation between the incidence of the COVID 19 epidemic in Spain and search data provided by Google Trends METHODS: Our method consists of the linear correlation between the Google Trends search data and the data provided by the National Center of Epidemiology in Spain -dependent on the Instituto de Salud Carlos III- of cases of COVID 19 reported with a certain time lag, enabling the identification of anticipatory patterns RESULTS: In response to the ongoing outbreak, our results demonstrate that using this 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, which can work on a population level, and inform public health decisions in real time
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