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Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study

BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic affects common diseases, but its impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial for approximate real-time statistics and because of ease in access, is expected to be used for infection explanation f...

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Autores principales: Niu, Qian, Liu, Junyu, Zhao, Zixi, Onishi, Miyu, Kawaguchi, Asuka, Bandara, Anuradhi, Harada, Keiko, Aoyama, Tomoki, Nagai-Tanima, Momoko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617033/
https://www.ncbi.nlm.nih.gov/pubmed/36309663
http://dx.doi.org/10.1186/s12879-022-07790-9
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author Niu, Qian
Liu, Junyu
Zhao, Zixi
Onishi, Miyu
Kawaguchi, Asuka
Bandara, Anuradhi
Harada, Keiko
Aoyama, Tomoki
Nagai-Tanima, Momoko
author_facet Niu, Qian
Liu, Junyu
Zhao, Zixi
Onishi, Miyu
Kawaguchi, Asuka
Bandara, Anuradhi
Harada, Keiko
Aoyama, Tomoki
Nagai-Tanima, Momoko
author_sort Niu, Qian
collection PubMed
description BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic affects common diseases, but its impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial for approximate real-time statistics and because of ease in access, is expected to be used for infection explanation from an information-seeking behavior perspective. We aimed to explain HFMD cases before and during COVID-19 using Google Trends. METHODS: HFMD cases were obtained from the National Institute of Infectious Diseases, and Google search data from 2009 to 2021 in Japan were downloaded from Google Trends. Pearson correlation coefficients were calculated between HFMD cases and the search topic “HFMD” from 2009 to 2021. Japanese tweets containing “HFMD” were retrieved to select search terms for further analysis. Search terms with counts larger than 1000 and belonging to ranges of infection sources, susceptible sites, susceptible populations, symptoms, treatment, preventive measures, and identified diseases were retained. Cross-correlation analyses were conducted to detect lag changes between HFMD cases and search terms before and during the COVID-19 pandemic. Multiple linear regressions with backward elimination processing were used to identify the most significant terms for HFMD explanation. RESULTS: HFMD cases and Google search volume peaked around July in most years, excluding 2020 and 2021. The search topic “HFMD” presented strong correlations with HFMD cases, except in 2020 when the COVID-19 outbreak occurred. In addition, the differences in lags for 73 (72.3%) search terms were negative, which might indicate increasing public awareness of HFMD infections during the COVID-19 pandemic. The results of multiple linear regression demonstrated that significant search terms contained the same meanings but expanded informative search content during the COVID-19 pandemic. CONCLUSIONS: The significant terms for the explanation of HFMD cases before and during COVID-19 were different. Awareness of HFMD infections in Japan may have improved during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. The public interest reflected in information-seeking behavior can be helpful for public health surveillance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07790-9.
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spelling pubmed-96170332022-10-30 Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study Niu, Qian Liu, Junyu Zhao, Zixi Onishi, Miyu Kawaguchi, Asuka Bandara, Anuradhi Harada, Keiko Aoyama, Tomoki Nagai-Tanima, Momoko BMC Infect Dis Research BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic affects common diseases, but its impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial for approximate real-time statistics and because of ease in access, is expected to be used for infection explanation from an information-seeking behavior perspective. We aimed to explain HFMD cases before and during COVID-19 using Google Trends. METHODS: HFMD cases were obtained from the National Institute of Infectious Diseases, and Google search data from 2009 to 2021 in Japan were downloaded from Google Trends. Pearson correlation coefficients were calculated between HFMD cases and the search topic “HFMD” from 2009 to 2021. Japanese tweets containing “HFMD” were retrieved to select search terms for further analysis. Search terms with counts larger than 1000 and belonging to ranges of infection sources, susceptible sites, susceptible populations, symptoms, treatment, preventive measures, and identified diseases were retained. Cross-correlation analyses were conducted to detect lag changes between HFMD cases and search terms before and during the COVID-19 pandemic. Multiple linear regressions with backward elimination processing were used to identify the most significant terms for HFMD explanation. RESULTS: HFMD cases and Google search volume peaked around July in most years, excluding 2020 and 2021. The search topic “HFMD” presented strong correlations with HFMD cases, except in 2020 when the COVID-19 outbreak occurred. In addition, the differences in lags for 73 (72.3%) search terms were negative, which might indicate increasing public awareness of HFMD infections during the COVID-19 pandemic. The results of multiple linear regression demonstrated that significant search terms contained the same meanings but expanded informative search content during the COVID-19 pandemic. CONCLUSIONS: The significant terms for the explanation of HFMD cases before and during COVID-19 were different. Awareness of HFMD infections in Japan may have improved during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. The public interest reflected in information-seeking behavior can be helpful for public health surveillance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07790-9. BioMed Central 2022-10-29 /pmc/articles/PMC9617033/ /pubmed/36309663 http://dx.doi.org/10.1186/s12879-022-07790-9 Text en © The Author(s) 2022 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
Niu, Qian
Liu, Junyu
Zhao, Zixi
Onishi, Miyu
Kawaguchi, Asuka
Bandara, Anuradhi
Harada, Keiko
Aoyama, Tomoki
Nagai-Tanima, Momoko
Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title_full Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title_fullStr Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title_full_unstemmed Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title_short Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study
title_sort explanation of hand, foot, and mouth disease cases in japan using google trends before and during the covid-19: infodemiology study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617033/
https://www.ncbi.nlm.nih.gov/pubmed/36309663
http://dx.doi.org/10.1186/s12879-022-07790-9
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