Authors' Response to Peer-Review Reports: https://med.jmirx.org/2022/2/e38695/
Published Article: https://med.jmirx.org/2022/2/e35356/
This is a peer-review report submitted for the paper “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.”
Round 1 Review
The subject of the brief paper  “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: a Retrospective Infodemiological Analysis” is timely and valuable to the audience of JMIRx Med. Overall, the paper is well structured, reads exceptionally well, and covers the existing literature quite well. The analysis of the data is interesting and well documented.
The author of the paper has selected keywords used in the Google Search engine, which could reveal an intention to take a vaccine against COVID-19 in Italy and compared this interest with headlines in the second most read newspaper in Italy. The paper has a transparent and replicable procedure to collect data and do statistical tests.
The results show a marked and significant cross-correlation between web queries on vaccine reservations and actual vaccinations against COVID-19 in Italy. On the other hand, the cross-correlation between vaccine-related news and vaccine web searches is low.
- I think that the limitations of this study are much broader than those listed in the work. There is a strong vaccine hesitation movement across different European countries, which could at least be mentioned in the work. The authors only noticed news in a newspaper on rare side effects of vaccination. This is what strongly influences, on the one hand, queries entered into a search engine and, on the other hand, a decrease in the number of vaccinations.
Conflicts of Interest
- Rovetta A. Google Trends as a predictive tool for COVID-19 vaccinations in Italy: a retrospective infodemiological analysis. JMIRx Med 2022;3(2):e35356 [FREE Full text]
Edited by E Meinert; This is a non–peer-reviewed article. submitted 11.04.22; accepted 11.04.22; published 19.04.22Copyright
©Artur Strzelecki. Originally published in JMIRx Med (https://med.jmirx.org), 19.04.2022.
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