Public reaction to Chikungunya outbreaks in Italy—Insights from an extensive novel data streams-based structural equation modeling analysis

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

Computational socioeconomics

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies

Eliciting Disease Data from Wikipedia Articles

Traditional disease surveillance systems suffer from several disadvantages, including reporting lags and antiquated technology, that have caused a movement towards internet-based disease surveillance systems. This study presents the use of Wikipedia article content in this sphere.  We demonstrate how a named-entity recognizer can be trained to tag case, death, and hospitalization counts in the article text. We also show that there are detailed time series data that are consistently updated that closely align with ground truth data.  We argue that Wikipedia can be used to create the first community-driven open-source emerging disease detection, monitoring, and repository system