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Peer Reviews (226)

Published on in Vol 3, No 2 (2022): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38724, first published .
Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Authors of this article:

Zubair Shah1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

    Peer-Review Report


    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.”


    General Comments

    The paper [1] uses Google Trends (GT) to identify correlations between search queries and vaccinations. GT has been used previously by others for similar and other problems. The paper is well written. The Methods section can be improved. The Results section has a good explanation.

    Specific Comments

    Major Comments
    1. The novelty of the paper is limited.
    2. The Introduction is short and can be extended to include more relevant studies.
    3. The Methods section needs more details. For instance, how GT works, especially when keywords are two words “vaccine reservation.” Does it search for all queries that include both words vaccine and reservation or vaccine OR reservation, or does it search for an exact match (“vaccine reservation”)? More search terms can be included, such as synonyms of reservation like an appointment or booking. Additionally, how was data normalized? What is lag week?

    Conflicts of Interest

    None declared.

    1. Rovetta A. Google Trends as a predictive tool for COVID-19 vaccinations in Italy: a retrospective infodemiological analysis. JMIRx Med 2022;3(2):e35356 [https://med.jmirx.org/2022/2/e35356/]

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    GT: Google Trends

    Edited by E Meinert; This is a non–peer-reviewed article. submitted 13.04.22; accepted 13.04.22; published 19.04.22

    Copyright

    ©Zubair Shah. 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.