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      Authors’ Response to Peer Reviews of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

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          Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis

          Background Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature. Objective This paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends. Methods Through the cross-correlational analysis of well-targeted hypotheses, we investigate the predictive capacity of web searches related to COVID-19 toward vaccinations in Italy from November 2020 to November 2021. The keyword “vaccine reservation” query (VRQ) was chosen as it reflects a real intention of being vaccinated (V). Furthermore, the impact of the second most read Italian newspaper (vaccine-related headlines [VRH]) on vaccine-related web searches was investigated to evaluate the role of the mass media as a confounding factor. Fisher r-to-z transformation (z) and percentage difference (δ) were used to compare Spearman coefficients. A regression model V=f(VRH, VRQ) was built to validate the results found. The Holm-Bonferroni correction was adopted (P*). SEs are reported. Results Simple and generic keywords are more likely to identify the actual web interest in COVID-19 vaccines than specific and elaborated keywords. Cross-correlations between VRQ and V were very strong and significant (min r²=0.460, P* 55.8%; z>5.8; P*<.001). The regression model confirmed the greater significance of VRQ versus VRH (P*<.001 vs P=.03, P*=.29). Conclusions This research provides preliminary evidence in favor of using Google Trends as a surveillance and prediction tool for vaccine adherence against COVID-19 in Italy. Further research is needed to establish the appropriate use and limits of Google Trends for vaccination tracking. However, these findings prove that the search for suitable keywords is a fundamental step to reduce confounding factors. Additionally, targeting hypotheses helps diminish the likelihood of spurious correlations. It is recommended that Google Trends be leveraged as a complementary infoveillance tool by government agencies to monitor and predict vaccine adherence in this and future crises by following the methods proposed in this paper.
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            prenotazione vaccino, prenotazione vaccino + prenotare vaccino + fissare vaccino + appuntamento vaccino

            (2025)
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              prenotazione vaccino, appuntamento vaccino, prenotare vaccino, fissare vaccino

              (2025)

                Author and article information

                Contributors
                Journal
                JMIRx Med
                JMIRx Med
                JMIRxMed
                JMIRx Med
                JMIR Publications (Toronto, Canada )
                2563-6316
                Apr-Jun 2022
                19 April 2022
                19 April 2022
                : 3
                : 2
                : e38695
                Affiliations
                [1 ] R&C Research Bovezzo Italy
                Author notes
                Corresponding Author: Alessandro Rovetta rovetta.mresearch@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-4634-279X
                Article
                v3i2e38695
                10.2196/38695
                10414253
                a04241b1-b795-492d-bbe6-046953dc4303
                ©Alessandro Rovetta. Originally published in JMIRx Med (https://med.jmirx.org), 19.04.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIRx Med, is properly cited. The complete bibliographic information, a link to the original publication on https://med.jmirx.org/, as well as this copyright and license information must be included.

                History
                : 12 April 2022
                : 12 April 2022
                Categories
                Authors’ Response to Peer Reviews
                Authors’ Response to Peer Reviews

                covid-19,epidemiology,google trends,infodemiology,infoveillance,italy,public health,sars-cov-2,vaccinations,vaccines,social media analysis,social media

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