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Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906695/ https://www.ncbi.nlm.nih.gov/pubmed/24451921 http://dx.doi.org/10.2196/jmir.2998 |
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author | Nsoesie, Elaine O Buckeridge, David L Brownstein, John S |
author_facet | Nsoesie, Elaine O Buckeridge, David L Brownstein, John S |
author_sort | Nsoesie, Elaine O |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3906695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-39066952014-01-30 Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance Nsoesie, Elaine O Buckeridge, David L Brownstein, John S J Med Internet Res Original Paper 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. JMIR Publications Inc. 2014-01-22 /pmc/articles/PMC3906695/ /pubmed/24451921 http://dx.doi.org/10.2196/jmir.2998 Text en ©Elaine O Nsoesie, David L Buckeridge, John S Brownstein. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.01.2014. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Nsoesie, Elaine O Buckeridge, David L Brownstein, John S Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title | Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title_full | Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title_fullStr | Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title_full_unstemmed | Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title_short | Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance |
title_sort | guess who’s not coming to dinner? evaluating online restaurant reservations for disease surveillance |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906695/ https://www.ncbi.nlm.nih.gov/pubmed/24451921 http://dx.doi.org/10.2196/jmir.2998 |
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