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

TitleUsing internet search data to predict new HIV diagnoses in China: a modelling study
Authors
Keywordshealth informatics
internet
predictive model
search query
surveillance
Issue Date2018
PublisherBMJ Publishing Group: BMJ Open. The Journal's web site is located at http://bmjopen.bmj.com
Citation
BMJ Open, 2018, v. 8 n. 10, p. article no. e018335 How to Cite?
AbstractObjectives Internet data are important sources of abundant information regarding HIV epidemics and risk factors. A number of case studies found an association between internet searches and outbreaks of infectious diseases, including HIV. In this research, we examined the feasibility of using search query data to predict the number of new HIV diagnoses in China. Design We identified a set of search queries that are associated with new HIV diagnoses in China. We developed statistical models (negative binomial generalised linear model and its Bayesian variants) to estimate the number of new HIV diagnoses by using data of search queries (Baidu) and official statistics (for the entire country and for Guangdong province) for 7 years (2010 to 2016). Results Search query data were positively associated with the number of new HIV diagnoses in China and in Guangdong province. Experiments demonstrated that incorporating search query data could improve the prediction performance in nowcasting and forecasting tasks. Conclusions Baidu data can be used to predict the number of new HIV diagnoses in China up to the province level. This study demonstrates the feasibility of using search query data to predict new HIV diagnoses. Results could potentially facilitate timely evidence-based decision making and complement conventional programmes for HIV prevention.
Persistent Identifierhttp://hdl.handle.net/10722/278629
ISSN
2017 Impact Factor: 2.413
2015 SCImago Journal Rankings: 1.448
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Q-
dc.contributor.authorCHAI, Y-
dc.contributor.authorLi, X-
dc.contributor.authorYoung, SD-
dc.contributor.authorZhou, J-
dc.date.accessioned2019-10-21T02:11:08Z-
dc.date.available2019-10-21T02:11:08Z-
dc.date.issued2018-
dc.identifier.citationBMJ Open, 2018, v. 8 n. 10, p. article no. e018335-
dc.identifier.issn2044-6055-
dc.identifier.urihttp://hdl.handle.net/10722/278629-
dc.description.abstractObjectives Internet data are important sources of abundant information regarding HIV epidemics and risk factors. A number of case studies found an association between internet searches and outbreaks of infectious diseases, including HIV. In this research, we examined the feasibility of using search query data to predict the number of new HIV diagnoses in China. Design We identified a set of search queries that are associated with new HIV diagnoses in China. We developed statistical models (negative binomial generalised linear model and its Bayesian variants) to estimate the number of new HIV diagnoses by using data of search queries (Baidu) and official statistics (for the entire country and for Guangdong province) for 7 years (2010 to 2016). Results Search query data were positively associated with the number of new HIV diagnoses in China and in Guangdong province. Experiments demonstrated that incorporating search query data could improve the prediction performance in nowcasting and forecasting tasks. Conclusions Baidu data can be used to predict the number of new HIV diagnoses in China up to the province level. This study demonstrates the feasibility of using search query data to predict new HIV diagnoses. Results could potentially facilitate timely evidence-based decision making and complement conventional programmes for HIV prevention.-
dc.languageeng-
dc.publisherBMJ Publishing Group: BMJ Open. The Journal's web site is located at http://bmjopen.bmj.com-
dc.relation.ispartofBMJ Open-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjecthealth informatics-
dc.subjectinternet-
dc.subjectpredictive model-
dc.subjectsearch query-
dc.subjectsurveillance-
dc.titleUsing internet search data to predict new HIV diagnoses in China: a modelling study-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1136/bmjopen-2017-018335-
dc.identifier.pmid30337302-
dc.identifier.pmcidPMC6196849-
dc.identifier.scopuseid_2-s2.0-85055079245-
dc.identifier.hkuros307934-
dc.identifier.volume8-
dc.identifier.issue10-
dc.identifier.spagearticle no. e018335-
dc.identifier.epagearticle no. e018335-
dc.publisher.placeUnited Kingdom-

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