In linear regression analysis, we found an extremely weak positive correlation between searches for “diarrea” ( R 2 0.122, p = 0.023) and increase in ICU admissions, no correlation for “mal di schiena” ( R 2 0.012, p = 0.496) and negative correlations for “prurito” ( R 2 0.119, p = 0.025) and tachycardia ( R 2 0.273, p < 0.001). For this analysis, we selected the same period of ICU admissions from February 24 to April 6 and we searched Google trends 1 week before using the Italian words “mal di schiena”, “tachicardia”, “prurito”, “diarrea”, corresponding to “back pain”, “tachycardia”, “itching” and “diarrhea” in English translation. To strengthen our results, we assessed whether a correlation between search volumes for commonly occurring symptoms not directly related to SARS-CoV-2 infection and ICU admissions existed or not. “fever” and “cough”-or even more specific such as “loss of smell” or “loss of taste” could be more explanatory of the viral outbreak’s evolution. Therefore, we postulated that simple terms referring to key early COVID-19 symptoms-e.g. However, at least in Italy, the search of keywords as “coronavirus” or “pneumonia” during the COVID-19 crisis was broadly unspecific and mostly attributable to informative purposes, showing a linear increase temporally corresponding to the interest toward the pandemic from mass media and public opinion. Recent research attempted to explore the relationship between Google Trends and COVID-19 and to evaluate the possibility of predicting new cases from internet searches. Indeed, Google searches for cough and fever preceded by 1 week, the need for critical care in Italy and by 2 weeks deaths from COVID-19.
Could we brace for impact? Could we predict the outbreak? Observing Google Trends, we noted a correlation between the dynamics of key searches for symptoms referable to SARS-CoV-2 infection, the increase in ICU admissions and new deaths.
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