Mahroum, N, Adawi, M, Sharif, K et al. (8 more authors) (2018) Public reaction to Chikungunya outbreaks in Italy—Insights from an extensive novel data streams-based structural equation modeling analysis. PLoS ONE, 13 (5). e0197337. ISSN 1932-6203
Abstract
The recent outbreak of Chikungunya virus in Italy represents a serious public health concern, which is attracting media coverage and generating public interest in terms of Internet searches and social media interactions. Here, we sought to assess the Chikungunya-related digital behavior and the interplay between epidemiological figures and novel data streams traffic.
Reaction to the recent outbreak was analyzed in terms of Google Trends, Google News and Twitter traffic, Wikipedia visits and edits, and PubMed articles, exploiting structural modelling equations.
A total of 233,678 page-views and 150 edits on the Italian Wikipedia page, 3,702 tweets, 149 scholarly articles, and 3,073 news articles were retrieved. The relationship between overall Chikungunya cases, as well as autochthonous cases, and tweets production was found to be fully mediated by Chikungunya-related web searches. However, in the allochthonous/imported cases model, tweet production was not found to be significantly mediated by epidemiological figures, with web searches still significantly mediating tweet production. Inconsistent relationships were detected in mediation models involving Wikipedia usage as a mediator variable. Similarly, the effect between news consumption and tweets production was suppressed by the Wikipedia usage. A further inconsistent mediation was found in the case of the effect between Wikipedia usage and tweets production, with web searches as a mediator variable. When adjusting for the Internet penetration index, similar findings could be obtained, with the important exception that in the adjusted model the relationship between GN and Twitter was found to be partially mediated by Wikipedia usage. Furthermore, the link between Wikipedia usage and PubMed/MEDLINE was fully mediated by GN, differently from what was found in the unadjusted model.
In conclusion—a significant public reaction to the current Chikungunya outbreak was documented. Health authorities should be aware of this, recognizing the role of new technologies for collecting public concerns and replying to them, disseminating awareness and avoid misleading information.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Mahroum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Institute of Rheumatology & Musculoskeletal Medicine (LIRMM) (Leeds) > Experimental Musculoskeletal Medicine (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Jan 2019 14:42 |
Last Modified: | 21 Jan 2019 14:42 |
Status: | Published |
Publisher: | Public Library of Science |
Identification Number: | 10.1371/journal.pone.0197337 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141281 |