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. 2014 Jan 22;16(1):e22.
doi: 10.2196/jmir.2998.

Guess who's not coming to dinner? Evaluating online restaurant reservations for disease surveillance

Elaine O Nsoesie  1 , David L Buckeridge, John S Brownstein
Affiliations

Guess who's not coming to dinner? Evaluating online restaurant reservations for disease surveillance

Elaine O Nsoesie et al. J Med Internet Res. .

Abstract

Background: 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.

Keywords: epidemics; outbreaks; population surveillance; restaurants.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The trend in the proportion of restaurants with table availability at 10:00 PM for Miami compared to Google Flu Trend data for Miami. (A) Restaurant table availability and Google Flu Trend curve; (B) curve with LOESS smoothing to capture the overall trend in availabilities.
Figure 2
Figure 2
The trend in the proportion of restaurants with table availability compared to trend in various estimates of influenza activity for different regions. (A) Google Flu Trend and restaurant table availability for Baltimore at 7:30 PM; (B, C) estimated % influenza-like illness (ILI) for Maryland and restaurant table availability for Baltimore at 7:00 PM and 3:30 PM, respectively; (D, E) Google Flu Trend and restaurant table availability for Atlanta at 3:00 PM and 6:30 PM, respectively; (F) estimated % ILI for Georgia and restaurant table availability for Atlanta at 12:30 PM; (G-I) Pan American Health Organization (PAHO) % positive for influenza and restaurant table availability for Mexico at 10:00 PM,10:30 PM, and 11:00 PM, respectively.
See this image and copyright information in PMC

References

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