Publishing Policies

Using infodemiology data for surveillance purposes has been called “infoveillance” [Eysenbach 2008, Eysenbach 2009]:

"Infoveillance is important for both the supply and demand sides. Public health professionals want to know, for example, if there is a surge of misinformation on the Internet on vaccination, so that public health campaigns and “health marketing” efforts can effectively counterbalance the misinformation. Public health professionals also need to know about surges in information demand, be it to address “epidemics of fear” by supplying the public with appropriate information, or to detect real disease outbreaks for which spikes in Internet searches or chatter in newsgroups and postings on microblogs (Twitter etc) may be an early predictor." [Eysenbach 2009]

The term "social listening" is sometimes used as a synonym for infoveillance, but has also been more narrowly defined as "the process of identifying and assessing what is being said about a company, product, brand, or individual, within forms of electronic interactive media" [Anderson et al, 2017]. The term "social listening" was first used in the public health context in 2015 by Heather Cole-Lewis when tracking sentiments on e-cigarettes on Twitter [Cole-Lewis et al, 2015].  

Infoveillance/social listening has been identified as one of the pillars to fight an infodemic [Tangcharoensathien et al, 2020; Eysenbach 2020].

See also related E-Collections: 

Infoveillance, Infodemiology and Digital Disease Surveillance  (JPHS)

Infodemiology and Infoveillance  (JMIR)

Information prevalence studies measure the absolute or relative number of occurrences of a certain keyword or concept (eg, misinformation or facts) in a pool of information [Eysenbach 2009]. These kinds of studies are particularly useful if we track them longitudinally (ie, track how the number of internet postings on a given health-specific topic changes over time), as we would, for example, to see changes in relation to certain external events, such as a media campaign or a disease outbreak.

With demand-based infodemiology indicators we usually refer to data generated from the search and “click” (ie, navigation) behavior of people. [Eysenbach 2009]

This section lists all substantive corrections, additions or changes made to articles and reviews subsequent to their first publication in the journal. Corrigenda are usually submitted by the corresponding author of the original article, or the section editor. Published papers are considered "final", thus JMIR makes corrections to published papers only in exceptional circumstances. Note that while we do not charge to correct errata that are the responsibility of the publisher, we charge a $190 fee for discretionary corrigenda and addenda (please submit a correction under that section, if it is the authors' responsibility/decision to correct or add information to a already published article).

For corrigenda that are discretionary and a result of author-oversight (e.g., corrections in the affiliation etc.) we charge a $190 processing fee to make changes in the original paper and publish an erratum. Please submit a correction statement (text similar to http://www.jmir.org/2015/3/e76/) at http://www.jmir.org/author/submit/1 under the section "Discretionary Corrigenda".

Research Letters present new, early, or preliminary research findings. The text should use standard research headings of Introduction, Methods, Results, and Discussion and should be no longer than 750 words, with a maximum of 10 references and 2 tables or figures. The APF for Research Letters accepted after peer review is lower than the standard APF.

A commentary is published alongside other articles published in JMIR Publications journals. Commentaries are typically invited. Unsolicited commentaries may be considered at the discretion of the editor. They may or may not be peer-reviewed. Articles submitted as a commentary should offer thoughtful criticism of published work, drawing from evidence, expertise, and/or additional perspectives. 

JMIR Infodemiology, a peer-reviewed, premier journal in the field of infodemiology, health information, data science, and misinformation is inviting submissions to a special issue on “Exploring the Intersection Between Health Information, Disinformation, and Generative AI Technologies.” 

For more details, please see: https://infodemiology.jmir.org/announcements/412

Find information about JMIR Infodemiology's Editorial Board here: https://infodemiology.jmir.org/about-journal/editorial-board