Literature DB >> 31449089

Harnessing digital data and data science to achieve 90-90-90 goals to end the HIV epidemic.

Steffanie A Strathdee1, Alicia L Nobles, John W Ayers.   

Abstract

PURPOSE OF REVIEW: Effective public health interventions depend on timely, accurate surveillance. Harnessing digital data (including internet searches, social media, and online media) and data science is an emerging approach to complement traditional surveillance in public health but has been underutilized in HIV prevention and treatment. RECENT
FINDINGS: We highlight recent examples that illustrate how social media data can be applied to HIV surveillance and prevention interventions.
SUMMARY: To achieve 90-90-90 goals to end the HIV epidemic, we encourage traditional public health researchers to partner with data scientists to supplement HIV surveillance programs with social media analytics to refine estimates of HIV infections and key populations at risk and to identify subgroups and regions where prevention and treatment efforts need to be bolstered. We also encourage interdisciplinary teams to design interventions to promote HIV prevention and linkage to care by leveraging digital media, such as search engines and social media, that have the potential to reach millions of people instantaneously.

Entities:  

Mesh:

Year:  2019        PMID: 31449089      PMCID: PMC6956609          DOI: 10.1097/COH.0000000000000584

Source DB:  PubMed          Journal:  Curr Opin HIV AIDS        ISSN: 1746-630X            Impact factor:   4.283


  31 in total

1.  "Is this a STD? Please help!": Online Information Seeking for Sexually Transmitted Diseases on Reddit.

Authors:  Alicia L Nobles; Caitlin N Dreisbach; Jessica Keim-Malpass; Laura E Barnes
Journal:  Proc Int AAAI Conf Weblogs Soc Media       Date:  2018-06

2.  Demand-based web surveillance of sexually transmitted infections in Russia.

Authors:  Alexander Domnich; Eva K Arbuzova; Alessio Signori; Daniela Amicizia; Donatella Panatto; Roberto Gasparini
Journal:  Int J Public Health       Date:  2014-07-11       Impact factor: 3.380

3.  Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.

Authors:  Michael Chary; Nicholas Genes; Christophe Giraud-Carrier; Carl Hanson; Lewis S Nelson; Alex F Manini
Journal:  J Med Toxicol       Date:  2017-08-22

4.  County-Level Vulnerability Assessment for Rapid Dissemination of HIV or HCV Infections Among Persons Who Inject Drugs, United States.

Authors:  Michelle M Van Handel; Charles E Rose; Elaine J Hallisey; Jessica L Kolling; Jon E Zibbell; Brian Lewis; Michele K Bohm; Christopher M Jones; Barry E Flanagan; Azfar-E-Alam Siddiqi; Kashif Iqbal; Andrew L Dent; Jonathan H Mermin; Eugene McCray; John W Ward; John T Brooks
Journal:  J Acquir Immune Defic Syndr       Date:  2016-11-01       Impact factor: 3.731

5.  Could behavioral medicine lead the web data revolution?

Authors:  John W Ayers; Benjamin M Althouse; Mark Dredze
Journal:  JAMA       Date:  2014-04-09       Impact factor: 56.272

6.  Digital disease detection--harnessing the Web for public health surveillance.

Authors:  John S Brownstein; Clark C Freifeld; Lawrence C Madoff
Journal:  N Engl J Med       Date:  2009-05-07       Impact factor: 91.245

7.  HIV testing among social media-using Peruvian men who have sex with men: correlates and social context.

Authors:  Evan A Krueger; ChingChe J Chiu; Luis A Menacho; Sean D Young
Journal:  AIDS Care       Date:  2016-05-03

Review 8.  Social Media Interventions to Promote HIV Testing, Linkage, Adherence, and Retention: Systematic Review and Meta-Analysis.

Authors:  Bolin Cao; Somya Gupta; Jiangtao Wang; Lisa B Hightow-Weidman; Kathryn E Muessig; Weiming Tang; Stephen Pan; Razia Pendse; Joseph D Tucker
Journal:  J Med Internet Res       Date:  2017-11-24       Impact factor: 5.428

9.  HIV-related posts from a Chinese internet discussion forum: An exploratory study.

Authors:  Yuan Dong; Xin Zhou; Yi Lin; Qichao Pan; Ying Wang
Journal:  PLoS One       Date:  2019-02-28       Impact factor: 3.240

10.  Leading by Example: Web-Based Sexual Health Influencers Among Men Who Have Sex With Men Have Higher HIV and Syphilis Testing Rates in China.

Authors:  Dan Wu; Weiming Tang; Haidong Lu; Tiange P Zhang; Bolin Cao; Jason J Ong; Amy Lee; Chuncheng Liu; Wenting Huang; Rong Fu; Katherine Li; Stephen W Pan; Ye Zhang; Hongyun Fu; Chongyi Wei; Joseph D Tucker
Journal:  J Med Internet Res       Date:  2019-01-21       Impact factor: 5.428

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  3 in total

Review 1.  Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review.

Authors:  Ihoghosa Iyamu; Oralia Gómez-Ramírez; Alice Xt Xu; Hsiu-Ju Chang; Sarah Watt; Geoff Mckee; Mark Gilbert
Journal:  Digit Health       Date:  2022-05-26

2.  Automated image analysis of instagram posts: Implications for risk perception and communication in public health using a case study of #HIV.

Authors:  Alicia L Nobles; Eric C Leas; Seth Noar; Mark Dredze; Carl A Latkin; Steffanie A Strathdee; John W Ayers
Journal:  PLoS One       Date:  2020-05-04       Impact factor: 3.240

3.  Three dimensions of COVID-19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis.

Authors:  Shan Qiao; Zhenlong Li; Chen Liang; Xiaoming Li; Caroline Rudisill
Journal:  Risk Anal       Date:  2022-07-13       Impact factor: 4.302

  3 in total

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