Guess Who's Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance

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dc.contributor.authorNsoesie, Elaine O.en
dc.contributor.authorBuckeridge, David L.en
dc.contributor.authorBrownstein, John S.en
dc.date.accessioned2019-11-22T20:13:26Zen
dc.date.available2019-11-22T20:13:26Zen
dc.date.issued2014-01en
dc.description.abstractBackground: Alternative data sources are used increasingly to augment traditional public health surveillance systems. Examples include over-the-counter medication sales and school absenteeism. Objective: We sought to determine if an increase in restaurant table availabilities was associated with an increase in disease incidence, specifically influenza-like illness (ILI). Methods: Restaurant table availability was monitored using OpenTable, an online restaurant table reservation site. A daily search was performed for restaurants with available tables for 2 at the hour and at half past the hour for 22 distinct times: between 11:00 am-3:30 pm for lunch and between 6:00-11:30 PM for dinner. In the United States, we examined table availability for restaurants in Boston, Atlanta, Baltimore, and Miami. For Mexico, we studied table availabilities in Cancun, Mexico City, Puebla, Monterrey, and Guadalajara. Time series of restaurant use was compared with Google Flu Trends and ILI at the state and national levels for the United States and Mexico using the cross-correlation function. Results: Differences in restaurant use were observed across sampling times and regions. We also noted similarities in time series trends between data on influenza activity and restaurant use. In some settings, significant correlations greater than 70% were noted between data on restaurant use and ILI trends. Conclusions: This study introduces and demonstrates the potential value of restaurant use data for event surveillance.en
dc.description.notesWe thank Sumiko Mekaru for suggestions regarding data analysis. This work is partially supported by a research grant the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior National Business Center (DoI/NBC) contract number D12PC000337. The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/NBC, or the US Government.en
dc.description.sponsorshipIntelligence Advanced Research Projects Activity (IARPA) via Department of Interior National Business Center (DoI/NBC) [D12PC000337]en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.2196/jmir.2998en
dc.identifier.eissn1438-8871en
dc.identifier.issue1en
dc.identifier.othere22en
dc.identifier.pmid24451921en
dc.identifier.urihttp://hdl.handle.net/10919/95847en
dc.identifier.volume16en
dc.language.isoenen
dc.rightsCreative Commons Attribution 2.0 Genericen
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/en
dc.subjectpopulation surveillanceen
dc.subjectrestaurantsen
dc.subjectepidemicsen
dc.subjectoutbreaksen
dc.titleGuess Who's Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillanceen
dc.title.serialJournal of Medical Internet Researchen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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