ArticleEmerging infectious diseases2015
Use of Internet Search Queries to Enhance Surveillance of Foodborne Illness.
Article in Emerging infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Temporal Association Between ChatGPT-Generated Diarrhea Synonyms in Internet Search Queries and Emergency Department Visits for Diarrhea-Related Symptoms in South Korea: Exploratory Study.Journal of medical Internet research · 2025Article
- Seasonal Variation for Plantar Fasciitis: Evidence from Google Trends Search Query Data.Healthcare (Basel, Switzerland) · 2022Article
- SARFIMA model prediction for infectious diseases: application to hemorrhagic fever with renal syndrome and comparing with SARIMA.BMC medical research methodology · 2020Article
- Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering.JMIR public health and surveillance · 2020Article
- Correlation Between UpToDate Searches and Reported Cases of Middle East Respiratory Syndrome During Outbreaks in Saudi Arabia.Open forum infectious diseases · 2016Article
- Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda.CSCW : proceedings of the Conference on Computer-Supported Cooperative Work. Conference on Computer-Supported Cooperative WorkArticle
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a supplement to or extension of methods used to determine trends in foodborne illness over time, we propose the use of Internet search metrics. We compared Internet query data for foodborne illness syndrome-related search terms from the most popular 5 Korean search engines using Health Insurance Review and Assessment Service inpatient stay data for 26 International Classification of Diseases, Tenth Revision, codes for foodborne illness in South Korea during 2010-2012. We used time-series analysis with Seasonal Autoregressive Integrated Moving Average (SARIMA) models. Internet search queries for "food poisoning" correlated most strongly with foodborne illness data (r=0.70, p<0.001); furthermore, "food poisoning" queries correlated most strongly with the total number of inpatient stays related to foodborne illness during the next month (β=0.069, SE 0.017, p<0.001). This approach, using the SARIMA model, could be used to effectively measure trends over time to enhance surveillance of foodborne illness in South Korea.
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