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An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan
BACKGROUND: Early surveillance to prevent the spread of influenza is a major public health concern. If there is an association of influenza epidemics with mobile app data, it may be possible to forecast influenza earlier and more easily. OBJECTIVE: We aimed to assess the relationship between seasona...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874815/ https://www.ncbi.nlm.nih.gov/pubmed/35142628 http://dx.doi.org/10.2196/31131 |
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author | Katayama, Yusuke Kiyohara, Kosuke Hirose, Tomoya Ishida, Kenichiro Tachino, Jotaro Nakao, Shunichiro Noda, Tomohiro Ojima, Masahiro Kiguchi, Takeyuki Matsuyama, Tasuku Kitamura, Tetsuhisa |
author_facet | Katayama, Yusuke Kiyohara, Kosuke Hirose, Tomoya Ishida, Kenichiro Tachino, Jotaro Nakao, Shunichiro Noda, Tomohiro Ojima, Masahiro Kiguchi, Takeyuki Matsuyama, Tasuku Kitamura, Tetsuhisa |
author_sort | Katayama, Yusuke |
collection | PubMed |
description | BACKGROUND: Early surveillance to prevent the spread of influenza is a major public health concern. If there is an association of influenza epidemics with mobile app data, it may be possible to forecast influenza earlier and more easily. OBJECTIVE: We aimed to assess the relationship between seasonal influenza and the frequency of mobile app use among children in Osaka Prefecture, Japan. METHODS: This was a retrospective observational study that was performed over a three-year period from January 2017 to December 2019. Using a linear regression model, we calculated the R(2) value of the regression model to evaluate the relationship between the number of “fever” events selected in the mobile app and the number of influenza patients ≤14 years of age. We conducted three-fold cross-validation using data from two years as the training data set and the data of the remaining year as the test data set to evaluate the validity of the regression model. And we calculated Spearman correlation coefficients between the calculated number of influenza patients estimated using the regression model and the number of influenza patients, limited to the period from December to April when influenza is prevalent in Japan. RESULTS: We included 29,392 mobile app users. The R(2) value for the linear regression model was 0.944, and the adjusted R(2) value was 0.915. The mean Spearman correlation coefficient for the three regression models was 0.804. During the influenza season (December–April), the Spearman correlation coefficient between the number of influenza patients and the calculated number estimated using the linear regression model was 0.946 (P<.001). CONCLUSIONS: In this study, the number of times that mobile apps were used was positively associated with the number of influenza patients. In particular, there was a good association of the number of influenza patients with the number of “fever” events selected in the mobile app during the influenza epidemic season. |
format | Online Article Text |
id | pubmed-8874815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88748152022-03-10 An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan Katayama, Yusuke Kiyohara, Kosuke Hirose, Tomoya Ishida, Kenichiro Tachino, Jotaro Nakao, Shunichiro Noda, Tomohiro Ojima, Masahiro Kiguchi, Takeyuki Matsuyama, Tasuku Kitamura, Tetsuhisa JMIR Form Res Original Paper BACKGROUND: Early surveillance to prevent the spread of influenza is a major public health concern. If there is an association of influenza epidemics with mobile app data, it may be possible to forecast influenza earlier and more easily. OBJECTIVE: We aimed to assess the relationship between seasonal influenza and the frequency of mobile app use among children in Osaka Prefecture, Japan. METHODS: This was a retrospective observational study that was performed over a three-year period from January 2017 to December 2019. Using a linear regression model, we calculated the R(2) value of the regression model to evaluate the relationship between the number of “fever” events selected in the mobile app and the number of influenza patients ≤14 years of age. We conducted three-fold cross-validation using data from two years as the training data set and the data of the remaining year as the test data set to evaluate the validity of the regression model. And we calculated Spearman correlation coefficients between the calculated number of influenza patients estimated using the regression model and the number of influenza patients, limited to the period from December to April when influenza is prevalent in Japan. RESULTS: We included 29,392 mobile app users. The R(2) value for the linear regression model was 0.944, and the adjusted R(2) value was 0.915. The mean Spearman correlation coefficient for the three regression models was 0.804. During the influenza season (December–April), the Spearman correlation coefficient between the number of influenza patients and the calculated number estimated using the linear regression model was 0.946 (P<.001). CONCLUSIONS: In this study, the number of times that mobile apps were used was positively associated with the number of influenza patients. In particular, there was a good association of the number of influenza patients with the number of “fever” events selected in the mobile app during the influenza epidemic season. JMIR Publications 2022-02-10 /pmc/articles/PMC8874815/ /pubmed/35142628 http://dx.doi.org/10.2196/31131 Text en ©Yusuke Katayama, Kosuke Kiyohara, Tomoya Hirose, Kenichiro Ishida, Jotaro Tachino, Shunichiro Nakao, Tomohiro Noda, Masahiro Ojima, Takeyuki Kiguchi, Tasuku Matsuyama, Tetsuhisa Kitamura. Originally published in JMIR Formative Research (https://formative.jmir.org), 10.02.2022. https://creativecommons.org/licenses/by/4.0/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 JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Katayama, Yusuke Kiyohara, Kosuke Hirose, Tomoya Ishida, Kenichiro Tachino, Jotaro Nakao, Shunichiro Noda, Tomohiro Ojima, Masahiro Kiguchi, Takeyuki Matsuyama, Tasuku Kitamura, Tetsuhisa An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title | An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title_full | An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title_fullStr | An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title_full_unstemmed | An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title_short | An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan |
title_sort | association of influenza epidemics in children with mobile app data: population-based observational study in osaka, japan |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874815/ https://www.ncbi.nlm.nih.gov/pubmed/35142628 http://dx.doi.org/10.2196/31131 |
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