An Online Risk Index for the Cross-Sectional Prediction of New HIV Chlamydia, and Gonorrhea Diagnoses Across U.S. Counties and Across Years.
AIDS Behav
; 22(7): 2322-2333, 2018 Jul.
Article
em En
| MEDLINE
| ID: mdl-29427233
The present study evaluated the potential use of Twitter data for providing risk indices of STIs. We developed online risk indices (ORIs) based on tweets to predict new HIV, gonorrhea, and chlamydia diagnoses, across U.S. counties and across 5 years. We analyzed over one hundred million tweets from 2009 to 2013 using open-vocabulary techniques and estimated the ORIs for a particular year by entering tweets from the same year into multiple semantic models (one for each year). The ORIs were moderately to strongly associated with the actual rates (.35 < rs < .68 for 93% of models), both nationwide and when applied to single states (California, Florida, and New York). Later models were slightly better than older ones at predicting gonorrhea and chlamydia, but not at predicting HIV. The proposed technique using free social media data provides signals of community health at a high temporal and spatial resolution.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Infecções por Chlamydia
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Gonorreia
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Infecções por HIV
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Mídias Sociais
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Big Data
Tipo de estudo:
Diagnostic_studies
/
Etiology_studies
/
Observational_studies
/
Prevalence_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
País/Região como assunto:
America do norte
Idioma:
En
Revista:
AIDS Behav
Assunto da revista:
CIENCIAS DO COMPORTAMENTO
/
SINDROME DA IMUNODEFICIENCIA ADQUIRIDA (AIDS)
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Estados Unidos