Literature DB >> 29278678

Using social media as a tool to predict syphilis.

Sean D Young1, Neil Mercer2, Robert E Weiss3, Elizabeth A Torrone4, Sevgi O Aral5.   

Abstract

Syphilis rates have been rapidly rising in the United States. New technologies, such as social media, might be used to anticipate and prevent the spread of disease. Because social media data collection is easy and inexpensive, integration of social media data into syphilis surveillance may be a cost-effective surveillance strategy, especially in low-resource regions. People are increasingly using social media to discuss health-related issues, such as sexual risk behaviors, allowing social media to be a potential tool for public health and medical research. This study mined Twitter data to assess whether social media could be used to predict syphilis cases in 2013 based on 2012 data. We collected 2012 and 2013 county-level primary and secondary (P&S) and early latent syphilis cases reported to the Center for Disease Control and Prevention, along with >8500 geolocated tweets in the United States that were filtered to include sexual risk-related keywords, including colloquial terms for intercourse. We assessed the relationship between syphilis-related tweets and actual case reports by county, controlling for socioeconomic indicators and prior year syphilis cases. We found a significant positive relationship between tweets and cases of P&S and early latent syphilis. This study shows that social media may be an additional tool to enhance syphilis prediction and surveillance.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Social media; Syphilis; Twitter

Mesh:

Year:  2017        PMID: 29278678      PMCID: PMC5843531          DOI: 10.1016/j.ypmed.2017.12.016

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  3 in total

1.  Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.

Authors:  Cynthia Chew; Gunther Eysenbach
Journal:  PLoS One       Date:  2010-11-29       Impact factor: 3.240

Review 2.  Sexually transmitted infections among US women and men: prevalence and incidence estimates, 2008.

Authors:  Catherine Lindsey Satterwhite; Elizabeth Torrone; Elissa Meites; Eileen F Dunne; Reena Mahajan; M Cheryl Bañez Ocfemia; John Su; Fujie Xu; Hillard Weinstock
Journal:  Sex Transm Dis       Date:  2013-03       Impact factor: 2.830

3.  Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes.

Authors:  Sean D Young; Caitlin Rivers; Bryan Lewis
Journal:  Prev Med       Date:  2014-02-08       Impact factor: 4.018

  3 in total
  13 in total

Review 1.  A scoping review of the use of Twitter for public health research.

Authors:  Oduwa Edo-Osagie; Beatriz De La Iglesia; Iain Lake; Obaghe Edeghere
Journal:  Comput Biol Med       Date:  2020-05-16       Impact factor: 4.589

2.  Ethical Perspectives in Sharing Digital Data for Public Health Surveillance Before and Shortly After the Onset of the COVID-19 Pandemic.

Authors:  Romina A Romero; Sean D Young
Journal:  Ethics Behav       Date:  2021-03-04

3.  The Adaptive Behavioral Components (ABC) Model for Planning Longitudinal Behavioral Technology-Based Health Interventions: A Theoretical Framework.

Authors:  Sean D Young
Journal:  J Med Internet Res       Date:  2020-06-26       Impact factor: 5.428

Review 4.  A scoping review of the use of Twitter for public health research.

Authors:  Oduwa Edo-Osagie; Beatriz De La Iglesia; Iain Lake; Obaghe Edeghere
Journal:  Comput Biol Med       Date:  2020-05-16       Impact factor: 4.589

Review 5.  Social media based surveillance systems for healthcare using machine learning: A systematic review.

Authors:  Aakansha Gupta; Rahul Katarya
Journal:  J Biomed Inform       Date:  2020-07-02       Impact factor: 6.317

6.  The More the Merrier? Should Antibiotics be Used for Rhinoplasty and Septorhinoplasty?-A Review.

Authors:  Ravina Kullar; Julia Frisenda; Paul S Nassif
Journal:  Plast Reconstr Surg Glob Open       Date:  2018-10-16

7.  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

8.  Social Big Data as a Tool for Understanding and Predicting the Impact of Cannabis Legalization.

Authors:  Sean D Young; Howard Padwa; Erin E Bonar
Journal:  Front Public Health       Date:  2019-10-04

9.  Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data.

Authors:  Mike Conway; Mengke Hu; Wendy W Chapman
Journal:  Yearb Med Inform       Date:  2019-08-16

10.  Using internet search data to predict new HIV diagnoses in China: a modelling study.

Authors:  Qingpeng Zhang; Yi Chai; Xiaoming Li; Sean D Young; Jiaqi Zhou
Journal:  BMJ Open       Date:  2018-10-17       Impact factor: 2.692

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