ArticleInternational journal of public health2014
Demand-based web surveillance of sexually transmitted infections in Russia.
Article in International journal of public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Digital Epidemiological Approaches in HIV Research: a Scoping Methodological Review.Current HIV/AIDS reports · 2023Article
- Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020Article
- Harnessing digital data and data science to achieve 90-90-90 goals to end the HIV epidemic.Current opinion in HIV and AIDS · 2019Review
- Age-related differences in the accuracy of web query-based predictions of influenza-like illness.PloS one · 2015Article
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Authors and funding
6 authors.
Funding
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Abstract
objectivesTo investigate the possibility of using HIV- and syphilis-related web queries to predict incident diagnosis rates of sexually transmitted infections in Russia.
methodsThe regional volume of HIV/syphilis queries, normalized to the total number of queries submitted to the most popular search engine, was used to predict the notification rates of HIV/syphilis in each region by applying both global non-spatial and spatial statistics.
resultsNationwide, both search volumes and regional HIV/syphilis diagnosis rates were positively spatially auto-correlated, indicating a clustered pattern of spatial distribution. A high positive correlation between notification rates and search volume was observed. Compared with linear models, spatially explicit geographically weighted models adjusted for broadband Internet diffusion proved superior in predicting the regional level of the HIV/syphilis epidemic on the basis of their search volume.
conclusionsTimeliness, easy availability, low cost, and transparency make HIV- and syphilis-related web queries a promising addition to traditional methods of disease surveillance in Russia. Geographically weighted regression provides useful insights, as it is able to capture the spatial heterogeneity of the relationship between search volume and disease incidence.
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