Finally, the large amount of anomalies registered in Italian and international cities’ RSVs made these datasets unusable for any kind of statistical inference.Ĭonclusion: In the considered timespans, Google Trends has proved to be reliable only for surveys concerning RSVs of countries worldwide. Furthermore, only RSVs of countries worldwide did not exceed confidence threshold. However, the correlations between RSVs and COVID-19 cases underwent significant variations even in these two datasets ( M a x | Δ | = + 625 % for Italian regions, and M a x | Δ | = + 175 % for countries worldwide). Results: Google Trends has been subject to an acceptable quantity of anomalies only as regards the RSVs of Italian regions (0% in both periods 1 and 2) and countries worldwide (9.7% during period 1 and 10.9% during period 2). The percentage increase Δ was used to quantify the difference between two values. A dataset was deemed unreliable if the confident data exceeded 20% (confidence threshold). Two RSVs were considered statistical confident when t < 1.5. Welch’s t-test was used to assess the statistical significance of the differences between the average RSVs of the various countries, regions, or cities of a given dataset. Pearson and Spearman correlations between RSVs and the number of COVID-19 cases were calculated day by day thus to highlight any variations related to the day RSVs were collected. When the anomalies exceeded 20% of the sample size, the whole sample was excluded from the statistical analysis. When a missing value was revealed (anomaly), the affected country, region or city was excluded from the analysis. To do this, by calling i the country, region, or city under investigation and j the day its RSV was collected, a Gaussian distribution X i = X ( σ i, x ¯ i ) was used to represent the trend of daily variations of x i j = R S V s i j. Each dataset was analyzed to observe any dependencies of RSVs from the day they were gathered. The search category was set to all categories. The survey covered Italian regions and cities, and countries and cities worldwide. Methods: RSVs of the query coronavirus + covid during February 1-Decem(period 1), and February 20-(period 2), were collected daily by Google Trends from December 8 to 27, 2020. In particular, the paper focuses on the analysis of relative search volumes (RSVs) quantifying their dependence on the day they are collected. Objective: The aim of this study is to test the reliability of a widely used infoveillance tool which is Google Trends. In this context, the use of infoveillance tools has become a primary necessity. 2Technological and Scientific Research, Redeev srl, Napoli, Italyīackground: Alongside the COVID-19 pandemic, government authorities around the world have had to face a growing infodemic capable of causing serious damages to public health and economy.1Research and Disclosure Division, Mensana srls, Brescia, Italy.
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