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For more information about PLOS Subject Areas, click here. A social media work group, consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, conducted a systematic primary literature review using the PRISMA framework to identify research, published through Februaryanswering either of the following questions:, dj white operational research paper.
Examples of social media included are Facebook, MySpace, microblogs e. The literature on the use of social media to support public health practice has identified many gaps and biases in current knowledge.
Despite the potential for success identified in exploratory studies, there are limited studies on interventions and little use of social media in practice. However, information gleaned from the articles demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention.
A primary recommendation resulting from the review is to identify opportunities that enable public health professionals to integrate social media analytics into disease surveillance and outbreak management practice. Citation: Charles-Smith LE, Reynolds TL, Cameron MA, Conway M, Lau EHY, Olsen JM, et al. PLoS ONE 10 10 : e Received: May 18, ; Accepted: September 15, ; Published: October 5, This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
The work is made available under the Creative Commons CC0 public domain dedication. Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: Project management support for this effort was provided by the International Society for Disease Surveillance. Participation of CDC and LECS was supported in part by Pacific Northwest National Laboratory's Laboratory Directed Research and Development Program, dj white operational research paper.
Competing interests: The authors have declared that no competing interests exist. Social media communication is an increasingly utilized outlet for people to freely create and post information that is disseminated and consumed worldwide through the Internet, dj white operational research paper. News media, traditional scientific outlets, and social media create a platform for minority viewpoints and personal information, which is not being captured by other sources.
Social media can create a sense of anonymity, allowing for unadulterated personal expression when compared to traditional face-to-face meetings, especially among young people and about intimate matters [ 1 ].
In this respect, social media provide an additional informal source of data dj white operational research paper can be used to identify health information not reported to medical officials or health departments and to reveal viewpoints on health-related topics, especially of a sensitive nature. In the past 10 years, research articles connecting disease surveillance with Internet use have increased in number, most likely due to the increase in availability of health-related information from various Internet sites.
For example, Wikipedia article hits [ 2 ], Google search terms Google Flu Trends [ 3 ], dj white operational research paper, and online restaurant reservation availability OpenTable [ 4 ] were modeled against the number of patients with influenza-like illness ILI reported by the Centers for Disease Control and Prevention CDC.
Several literature reviews have looked at the potential of this type of research to benefit human health. Moorhead et al. conducted a review dj white operational research paper research studies to identify potential uses, benefits, and limitations of social media to engage the general public, patients, and health professionals in health communication [ 5 ].
Although articles identified benefit from using social media in health communications, the authors note a lack of research focused on the evaluation of short- and long-term impacts on health communication practices. Bernardo et al. provided a scoping review of the use of search queries and social media in disease surveillance [ 6 ]. First reported inthe reviewed literature highlighted accuracy, speed, and cost performance that was comparable to existing disease surveillance systems and recommended the use of social media programs to support those systems.
Velasco et al. defined their literature review to contain only peer-reviewed articles on event-based disease surveillance [ 7 ] in which they identified and described 12 existing systems. Walters et al. The paper points out that including emerging media, such as blogs and Short Message Service SMSinto these systems along with standardized metrics to evaluate the performance of different surveillance systems is crucial to the advancement of these early warning systems.
As members of the International Society for Disease Surveillance ISDSwe established a social media working group henceforth called the workgroup to develop research, technology, and operational innovations in electronic public health surveillance. We proposed to evaluate the use of social media to enable public health professionals to realize positive, valuable, and timely community health outcomes at the local, state, regional, national, and global levels.
To address these goals, we followed the PRISMA process [ 9 ] by systematically compiling and analyzing literature that demonstrates innovation in electronic public health surveillance through the use of social media. By focusing on how research on social media data further defined below can be used for actionable disease surveillance, we are able to bring to light the best ways of using these tools to target vulnerable populations and improve public health in the broad spectrum from identifying and monitoring disease outbreaks to addressing traditionally intractable health concerns, such as adolescent drug and alcohol use.
This systematic review builds upon the preferred reporting items outlined in the PRISMA Statement in effort to properly assess the quality and quantity of health-related research using social media analytics for active surveillance, S1 Checklist. Articles using data sources, such as Internet searches, ProMed-mail, and citizen-generated data were not included.
In Marcha query of scientific literature databases PubMed, Embase, Scopus, and Ichushi-Web was conducted for all literature published through February to determine potential publications for review by the workgroup Table 1. Searches were further refined to include dj white operational research paper human subjects and to exclude review i.
Articles published in Italian, German, Dutch, English, Spanish, and Japanese were included in the search check box because of multilingualism within the workgroup. The workgroup was formed from members of the ISDS with diverse background specialties, e. Within the group, a pair of members evaluated dj white operational research paper collected abstract in detail for possible inclusion in the systematic review.
Each member recorded the following information from each potential publication: author sdate of publication, publication type e. Requirements were that each study must be published as original researchand must analyze social media. The initial review was done for all documents containing an abstract, including peer-reviewed conference proceedings or white papers. An article was excluded if the full text was not available, if only methods were described i.
Any differences of opinion about whether to include a paper were resolved through discussion until the workgroup achieved a consensus on inclusion or exclusion. For each article fitting the review inclusion criteria, one workgroup member was assigned to extract and record specific details from the full-text article.
This information included background e, dj white operational research paper. To assess involvement of a public health jurisdiction in the study or intervention, a reviewer searched the acknowledgements for funding agency and methods for direct public health involvement.
In addition, the reviewers included any information they believed might have introduced bias into the study. Note that to date, this study protocol has not been registered.
After removing duplicates, 1, studies remained for the abstract screening step. We excluded 1, of these studies because they were reviews, letters, commentaries, or did not address either of the research questions. An additional 8 studies were excluded because the full-text publications were not available. These excluded study abstracts or presentations reported promising preliminary research addressing active disease surveillance.
Topics ranged from targeting sexually transmitted diseases in traditionally hard-to-reach populations [ 10 — 13 ] to detecting unusual events, anomalies, and social disruption for early warning systems [ 14 ]. The abstract screening process resulted in studies identified for detailed review of full-text articles.
After this review, we further excluded studies that did not meet our definition of social media e. We identified a total of 60 studies that met our eligibility criteria and addressed at least one of the two research questions, dj white operational research paper.
This process took dj white operational research paper a dj white operational research paper to complete because the authors donated their free time to review and analyze the literature. The studies examined data from January [ 46 ] to January [ 38 ] with the majority focused on Comparison to CDC reports were most commonly used dj white operational research paper evaluate the effectiveness of the various surveillance techniques presented.
Most Twitter-based studies identified study populations through automatic means, i. The articles reported that study sizes were measured either by the number of tweets, ranging from thousand [ 38 ] to 2 billion [ 22 ], or the number of unique social media users, ranging from users [ 28 ] to Most studies were published in English dj white operational research paper in Japaneseand all were exploratory in nature.
Thirty-two studies were identified as targeting a vulnerable population to improve health outcomes. These studies emphasized dj white operational research paper with users rather than automatic algorithms and therefore typically contained focused populations and smaller datasets. The study sizes ranged from 19 post-partum women [ 48 ] toTwitter users from 9 distinct areas [ 26 ], dj white operational research paper.
Populations studied were generally more focused than Question 1 studies, e. The study populations dated from January [ 1 ] to February [ 66 ], although many do not disclose study periods. Interestingly, the studies addressing Question 2 first appeared inbut published literature on Question 1 does not appear until Also, there is a spike in addressing both questions during Fig 2.
The spectrum of studies selected for review were subject to publication bias because only primary literature was included and, therefore, other non-published information collected by state or federal health agencies was not incorporated. Dj white operational research paper choice of data search engines may have excluded valid studies that may not have been published in journals exposed through this process. In addition, there may be more recent articles published since our collection end date of March The types of bias can be broken down into six different categories.
There were 14 articles displaying a faulty study design due to the choice of time period [ 1617dj white operational research paper, 27333740dj white operational research paper, 4247 ], data source [ 184260 ], study scope [ 3742 ], reporting of results [ 3754 ], or lack of result measure [ 5051 ].
Temporal relationship and directionality bias within 8 studies caused issues in the ability to extrapolate data [ 166567 ] or infer directionality or causality [ 28325569 ]. A few studies had sample sizes that were too small to draw conclusions, i. Other biases present in the reviewed articles were reliability bias [ 22285468 ] and selective interpretation bias [ 32dj white operational research paper, 40 ].
These supportive agencies reside in England London and the United States of America USA California, Louisiana, Michigan, and Washington State. One research paper, funded by the University of Maryland, USA, described the implementation of social media communication by a local Taiwan government for disaster management, which showed promise over current national awareness and response protocols [ 69 ].
Other universities showing interest in support of social media research were located in Australia, Germany, Italy, Japan, United Kingdom UKand USA. The private funding agencies that supported reviewed literature are found in the UK and USA. Only 3 papers contained a co-author who was affiliated with a public health agency, i.
Note that some articles contained more than one funding agency. The key to our systematic literature review of Question 1 was to identify if, when, and how social media have been applied for disease surveillance and outbreak management to support and improve public health. All of these studies were exploratory research and did not contain any type of intervention analysis. Influenza-like illness ILI was the first disease to be modeled using social media data in our review Table 3.
We identified 15 original, exploratory studies on ILI targeting social media users e. From simple text searches, e. A study by Sadilek, Kautz, and Silenzioapplied their technique to identify the health of any person through geo-tagged Twitter microblogs in an effort to predict disease transmission [ 15 ].
In general, correlation between social media data and national health statistics, e. We identified 6 studies that used different social media programs to determine if the timeliness and sensitivity of detection for other infectious disease outbreaks e. In a study by Chunara, Andrews, and Brownsteindj white operational research paper, the volume of cholera-related Twitter posts and HealthMap news media reports were compared to official Haiti cholera case reports during the first days of the outbreak [ 23 ].
The changes in social media and news data trends were detected dj white operational research paper to 2 weeks earlier than official case data, which they believe could have had direct implications on the disease outbreak and control measures taken [ 23 ].
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