The Internet and the Anti-Vaccine Movement: Tracking the 2017 EU Measles Outbreak

Mavragani, Amaryllis; Ochoa, Gabriela

doi:10.3390/bdcc2010002

Cited by 40 publications

(37 citation statements)

References 25 publications

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“…Finally, forecasting models for AIDS prevalence in the US are estimated, at both national and State level, so as to elaborate on the usefulness of the tool in health assessment in the US. The top related queries for ' AIDS (Search Term)' include 'aids hiv' (100), 'hearing aids' (99), 'hiv' (97), 'aids symptoms' (33), 'aids and hiv' (25), 'aids day' (24), 'africa aids' (22), 'aids cure' (16), 'aids test' (11), 'aids statistics' (11), and 'aids virus' (10). For ' AIDS (Illness)' , the top related queries include 'aids' (100), 'hiv' (26), 'aids hiv' (14), 'hiv/aids' (6), 'aids symptoms' (5), 'africa' (4), 'aids day' (4), 'hiv symptoms' (3), 'aids cure' (2), 'hiv infection' (2), 'hiv transmission' (2), and 'aids statistics' (2).…”

Section: Resultsmentioning

confidence: 99%

Forecasting AIDS prevalence in the United States using online search traffic data

Mavragani

Ochoa

2018

J Big Data

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Big Data, characterized by large volumes, high processing speed, and wide variety of datasets [1-3], have been shown to be very valuable in health care research, with Health Informatics being the field in which big data analytics have been extensively applied [4]. A popular way of addressing the challenge of Big Data is the analysis of online search traffic data [5, 6], mainly with data from Google Trends [7]. Over the past decade, this field of research, i.e., analyzing online search traffic data, has been widely used and is growing in popularity for assessing various topics, though it has mostly focused on the fields of Health and Medicine [8]. Many studies on the subject have empirically shown that Google Trends' data are related to public health data. Topics that have been explored up to this point include the analysis, assessment, and prediction of epidemics and outbreaks, as, for example, Ebola [9, 10], Measles [11], the Bed-Bug epidemic [12], and Tuberculosis [13]. A much studied

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Section: Resultsmentioning

confidence: 99%

Forecasting AIDS prevalence in the United States using online search traffic data

Mavragani

Ochoa

2018

J Big Data

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“…The online vaccine debate is an example of one of these debates and is an important issue ripe for investigation. As a result of the recent increase in the outbreaks of diseases, such as measles and whooping cough, the anti-vaccination movement is considered by some experts to be an emerging public health problem [17,18]. For example, the World Health Organization listed the rise of the anti-vaccination campaign as a top ten health emergency of 2019 [19].…”

Section: Online Public Health Debatesmentioning

confidence: 99%

The Online Vaccine Debate: Study of a Visual Analytics System

Ninkov

Sedig

2020

Informatics

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Online debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the efficacy and morality of vaccines. When people examine such online debates, they encounter numerous and conflicting sources of information. This information forms the basis upon which people take a position on such debates. This has profound implications for public health. It necessitates a need for public health stakeholders to be able to examine online debates quickly and effectively. They should be able to easily perform sense-making tasks on the vast amount of online information, such as sentiments, online presence, focus, or geographic locations. In this paper, we report the results of a user study of a visual analytic system (VAS), and whether and how this VAS can help with such sense-making tasks. Specifically, we report a usability evaluation of VINCENT (VIsual aNalytiCs systEm for investigating the online vacciNe debaTe), a VAS previously described. To help the reader, we briefly discuss VINCENT’s design in this paper as well. VINCENT integrates webometrics, natural language processing, data visualization, and human-data interaction. In the reported study, we gave users tasks requiring them to make sense of the online vaccine debate. Thirty-four participants were asked to perform these tasks by investigating data from 37 vaccine-focused websites. Half the participants were given access to the system, while the other half were not. Selected study participants from both groups were subsequently asked to be interviewed by the study administrator. Examples of questions and issues discussed with interviewees were: how they went about completing specific tasks, what they meant by some of the feedback they provided, and how they would have performed on the tasks if they had been placed in the other group. Overall, we found that VINCENT was a highly valuable resource for users, helping them make sense of the online vaccine debate much more effectively and faster than those without the system (e.g., users were able to compare websites similarities, identify emotional tone of websites, and locate websites with a specific focus). In this paper, we also identify a few issues that should be taken into consideration when developing VASes for online public health debates.

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“…Infodemiology, i.e., information epidemiology, is a concept introduced by Gunther Eysenbach [10][11]. In the field of infodemiology, internet sources and data are employed in order to inform public health and policy [12][13], and are valuable for the monitoring and forecasting of outbreaks and epidemics [14], as for example Ebola [15], Zika [16], MERS [17], influenza [18], and measles [19][20].…”

Section: Introductionmentioning

confidence: 99%

On the predictability of COVID-19 in USA: A Google Trends analysis

Mavragani¹,

Gillas²

2020

Preprint

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During the difficult times that the world is facing due to the COVID-19 pandemic that has already had severe consequences in all aspects of our lives, it is imperative to explore novel approaches of monitoring and forecasting the regional outbreaks as they happen or even before they do. In this paper, the first approach of exploring the role of Google query data in the predictability of COVID-19 in the US at both national and state level is presented. The results indicate that Google Trends correlate with COVID-19 data, while the estimated models exhibit strong predictability of COVID-19. In line with previous work that has argued on the value of online real-time data in the monitoring and forecasting epidemics and outbreaks, it is evident that such infodemiology approaches can assist public health policy makers, in order to address the most crucial issue; that of flattening the curve, allocating health resources, and increasing the effectiveness and preparedness of the respective health care systems.

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The Internet and the Anti-Vaccine Movement: Tracking the 2017 EU Measles Outbreak

Cited by 40 publications

References 25 publications

Forecasting AIDS prevalence in the United States using online search traffic data

Forecasting AIDS prevalence in the United States using online search traffic data

The Online Vaccine Debate: Study of a Visual Analytics System

On the predictability of COVID-19 in USA: A Google Trends analysis

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