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

• Main Authors: Nsoesie, Elaine O (Author), Buckeridge, David L (Author), Brownstein, John S (Author)
• Format: Book
• Published: JMIR Publications, 2014-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1438-8871; 10.2196/jmir.2998
• Keywords: Computer applications to medicine. Medical informatics; R858-859.7; Public aspects of medicine; RA1-1270
• Source: Journal of Medical Internet Research, Vol 16, Iss 1, p e22 (2014)

BackgroundAlternative data sources are used increasingly to augment traditional public health surveillance systems. Examples include over-the-counter medication sales and school absenteeism. ObjectiveWe sought to determine if an increase in restaurant table availabilities was associated with an increase in disease incidence, specifically influenza-like illness (ILI). MethodsRestaurant 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. ResultsDifferences 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. ConclusionsThis study introduces and demonstrates the potential value of restaurant use data for event surveillance.