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Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity

BACKGROUND: Google Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies...

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Autores principales: Sato, Kenichiro, Mano, Tatsuo, Iwata, Atsushi, Toda, Tatsushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286439/
https://www.ncbi.nlm.nih.gov/pubmed/34275447
http://dx.doi.org/10.1186/s12874-021-01338-2
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author Sato, Kenichiro
Mano, Tatsuo
Iwata, Atsushi
Toda, Tatsushi
author_facet Sato, Kenichiro
Mano, Tatsuo
Iwata, Atsushi
Toda, Tatsushi
author_sort Sato, Kenichiro
collection PubMed
description BACKGROUND: Google Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results. METHODS: We extracted the relative GT search volume for keywords associated with COVID-19 symptoms, and evaluated their Granger-causality to weekly COVID-19 positivity in eight English-speaking countries and Japan. In addition, the impact of media coverage on keywords with significant Granger-causality was further evaluated using Japanese regional data. RESULTS: Our Granger causality-based approach largely decreased (by up to approximately one-third) the number of keywords identified as having a significant temporal relationship with the COVID-19 trend when compared to those identified by Pearson or Spearman’s rank correlation-based approach. “Sense of smell” and “loss of smell” were the most reliable GT keywords across all the evaluated countries; however, when adjusted with their media coverage, these keyword trends did not Granger-cause the COVID-19 positivity trends (in Japan). CONCLUSIONS: Our results suggest that some of the search keywords reported as candidate predictive measures in earlier GT-based COVID-19 studies may potentially be unreliable; therefore, caution is necessary when interpreting published GT-based study results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01338-2.
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spelling pubmed-82864392021-07-19 Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity Sato, Kenichiro Mano, Tatsuo Iwata, Atsushi Toda, Tatsushi BMC Med Res Methodol Research BACKGROUND: Google Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results. METHODS: We extracted the relative GT search volume for keywords associated with COVID-19 symptoms, and evaluated their Granger-causality to weekly COVID-19 positivity in eight English-speaking countries and Japan. In addition, the impact of media coverage on keywords with significant Granger-causality was further evaluated using Japanese regional data. RESULTS: Our Granger causality-based approach largely decreased (by up to approximately one-third) the number of keywords identified as having a significant temporal relationship with the COVID-19 trend when compared to those identified by Pearson or Spearman’s rank correlation-based approach. “Sense of smell” and “loss of smell” were the most reliable GT keywords across all the evaluated countries; however, when adjusted with their media coverage, these keyword trends did not Granger-cause the COVID-19 positivity trends (in Japan). CONCLUSIONS: Our results suggest that some of the search keywords reported as candidate predictive measures in earlier GT-based COVID-19 studies may potentially be unreliable; therefore, caution is necessary when interpreting published GT-based study results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01338-2. BioMed Central 2021-07-18 /pmc/articles/PMC8286439/ /pubmed/34275447 http://dx.doi.org/10.1186/s12874-021-01338-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sato, Kenichiro
Mano, Tatsuo
Iwata, Atsushi
Toda, Tatsushi
Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title_full Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title_fullStr Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title_full_unstemmed Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title_short Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity
title_sort need of care in interpreting google trends-based covid-19 infodemiological study results: potential risk of false-positivity
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286439/
https://www.ncbi.nlm.nih.gov/pubmed/34275447
http://dx.doi.org/10.1186/s12874-021-01338-2
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