Clinical and Translational Research
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Methodol. May 20, 2022; 12(3): 99-106
Published online May 20, 2022. doi: 10.5662/wjm.v12.i3.99
COVID-19 and thyroid disease: An infodemiological pilot study
Ioannis Ilias, Charalampos Milionis, Eftychia Koukkou
Ioannis Ilias, Charalampos Milionis, Eftychia Koukkou, Department of Endocrinology, Diabetes & Metabolism, Elena Venizelou Hospital, Athens GR-11521, Greece
Author contributions: All authors conceived this work, searched the literature, analyzed the data, performed the analyses, and wrote this manuscript.
Institutional review board statement: The statement is not applicable since this is a web-based data study.
Clinical trial registration statement: The statement is not applicable since this is a web-based data study.
Informed consent statement: The statement is not applicable since this is a web-based data study.
Conflict-of-interest statement: The authors declare that they have no conflict of interest to disclose.
Data sharing statement: All the data for this study can be obtained from the publicly available sources https://coronavirus.jhu.edu/map.html&https://trends.google.com.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ioannis Ilias, MD, PhD, Consultant Physician-Scientist, Department of Endocrinology, Diabetes & Metabolism, Elena Venizelou Hospital, 2, Elena Venizelou Sq., Athens GR-11521, Greece. iiliasmd@yahoo.com
Received: November 23, 2021
Peer-review started: November 23, 2021
First decision: February 8, 2022
Revised: February 11, 2022
Accepted: March 26, 2022
Article in press: March 26, 2022
Published online: May 20, 2022
Processing time: 176 Days and 9.1 Hours
Abstract
BACKGROUND

Google Trends searches for symptoms and/or diseases may reflect actual disease epidemiology. Recently, Google Trends searches for coronavirus disease 2019 (COVID-19)-associated terms have been linked to the epidemiology of COVID-19. Some studies have linked COVID-19 with thyroid disease.

AIM

To assess COVID-19 cases per se vs COVID-19-associated Google Trends searches and thyroid-associated Google Trends searches.

METHODS

We collected data on worldwide weekly Google Trends searches regarding “COVID-19”, “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)”, “coronavirus”, “smell”, “taste”, “cough”, “thyroid”, “thyroiditis”, and “subacute thyroiditis” for 92 wk and worldwide weekly COVID-19 cases' statistics in the same time period. The study period was split in half (approximately corresponding to the preponderance of different SARS-COV-2 virus variants) and in each time period we performed cross-correlation analysis and mediation analysis.

RESULTS

Significant positive cross-correlation function values were noted in both time periods. More in detail, COVID-19 cases per se were found to be associated with no lag with Google Trends searches for COVID-19 symptoms in the first time period and in the second time period to lead searches for symptoms, COVID-19 terms, and thyroid terms. COVID-19 cases per se were associated with thyroid-related searches in both time periods. In the second time period, the effect of “COVID-19” searches on “thyroid’ searches was significantly mediated by COVID-19 cases (P = 0.048).

CONCLUSION

Searches for a non-specific symptom or COVID-19 search terms mostly lead Google Trends thyroid-related searches, in the second time period. This time frame/sequence particularly in the second time period (noted by the preponderance of the SARS-COV-2 delta variant) lends some credence to associations of COVID-19 cases per se with (apparent) thyroid disease (via searches for them).

Keywords: Data collection; Epidemiology; Thyroid; Medical informatics; Methods; Trends

Core Tip: Google Trends searches for coronavirus disease 2019 (COVID-19)-associated terms have been linked to the epidemiology of COVID-19. In this study we aimed to assess worldwide COVID-19 cases per se vs COVID-19-associated Google Trends searches and thyroid-associated Google Trends searches for 92 wk. The study period was split in half and in each time period we performed cross-correlation analysis and mediation analysis. Significant cross correlation function factors for “COVID-19” and “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)” were mostly found in the second time period, whereas COVID-19 cases per se were associated with “thyroid” searches in both time periods. In the second time period, which was characterized by the spread of SARS-CoV-2 delta variant, the effect of “COVID-19” searches on “thyroid” searches was significantly mediated by COVID-19 cases (P = 0.048). The observed time frame/sequence lends some credence to associations of COVID-19 cases per se with (apparent) thyroid disease.