Layout 1


ISDS Annual Conference Proceedings 2012. This is an Open Access article distributed under the terms of the Creative Commons Attribution-
Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and
reproduction in any medium, provided the original work is properly cited.

ISDS 2012 Conference Abstracts

Who’s Not Coming to Dinner? Evaluating Trends in
Online Restaurant Reservations for Outbreak
Surveillance
Elaine O. Nsoesie*1, 2, 4, David L. Buckeridge3 and John S. Brownstein1, 2, 3

1Children’s Hospital Informatics Program, Boston Children’s Hospital, Boston, MA, USA; 2Department of Pediatrics, Harvard Medical
School, Boston, MA, USA; 3Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC,
Canada; 4Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA

Objective
The objective of this study is to evaluate whether trends in online

restaurant table reservations can be used as an early indicator for a
disease outbreak.

Introduction
Epidemiologists, public health agencies and scientists increasingly

augment traditional surveillance systems with alternative data sources
such as, digital surveillance systems utilizing news reports and so-
cial media, over-the-counter medication sales, and school absen-
teeism. Similar to school absenteeism, an increase in reservation
cancellations could serve as an early indicator of social disruption in-
cluding a major public health event. In this study, we evaluated
whether a rise in restaurant table availabilities could be associated
with an increase in disease incidence.

Methods
We monitored table availability using OpenTable; an online restau-

rant table reservation site for cities in the USA and Mexico. Our
analysis can be summarized as follows. First, using the OpenTable
site, we searched for the number of restaurants with available tables
for two persons at lunch and dinner. Since different regions and in-
dividuals have different eating habits, we defined the lunch period
between 12-3:30pm and dinner between 6-10:30pm. We searched for
available tables every hour and half past the hour for every day of
the week. Next, we investigated any occurrences of social unrest and
natural disasters, which might have affected the trend in the time se-
ries. Lastly, using moving averages, cross-correlations and regression
models, we elucidated and compared the time-trend in the data of

table availabilities to data collected for various disease outbreaks. In
the USA, we examined table availability for restaurants in Boston,
Atlanta, Baltimore and Miami. For Mexico, we studied table avail-
abilities in Cancun, Mexico City, Puebla, Monterrey, and Guadala-
jara.

Results
Preliminary results indicated differences in mean table availabili-

ties observed during weekdays and weekends. However, these dif-
ferences were statistically significant only for Boston and Miami (p
< 0.01). Statistical significant differences were also observed for
mean table availabilities at lunch and dinner for all the cities (p <
0.001).

Conclusions
The unavailability of reasons for cancellations introduces limita-

tions to this data source. However, monitoring increases in cancella-
tion of restaurant table reservations may be moderately useful for
detecting epidemics especially in developing countries with limited
public health infrastructures and resources. We therefore present a
framework for future surveillance efforts.

Keywords
developing countries; infectious diseases; alternative data sources;
reservation sites

*Elaine O. Nsoesie
E-mail: elaine.nsoesie@childrens.harvard.edu

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e170, 2013