Health department use of social media to identify foodborne illness — Chicago, Illinois, 2013–2014

Morbidity and Mortality Weekly Report

Volumn 63, Issue 32, 2014, Pages 681-685

  Harris, Jenine K ^a   Mansour, Raed ^b   Choucair, Bechara ^b   Bhatt, Jay ^b   Olson, Joe ^c   Nissen, Cory ^c  

^a WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

^b CHICAGO DEPARTMENT OF PUBLIC HEALTH   (United States)

^c FoodBorne Chicago   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; EPIDEMIC; FOOD POISONING; HEALTH SURVEY; HUMAN; METHODOLOGY; PUBLIC HEALTH SERVICE; SOCIAL MEDIA; UNITED STATES; UTILIZATION REVIEW;

CHICAGO; DISEASE OUTBREAKS; FOODBORNE DISEASES; HUMANS; POPULATION SURVEILLANCE; PUBLIC HEALTH ADMINISTRATION; SOCIAL MEDIA;

EID: 84906718736     PISSN: 01492195     EISSN: 1545861X     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. McCabe-Sellers BJ, Beattie SE. Food safety: emerging trends in foodborne illness surveillance and prevention. J Am Diet Assoc 2004;104:1708-17.
2. Mead PS, Slutsker L, Dietz V, et al. Food-related illness and death in the United States. Emerg Infect Dis 1999;5:607-25.
3. Campbell ME, Gardner CE, Dwyer JJ, Isaacs SM, Krueger PD, Ying JY. Effectiveness of public health interventions in food safety: a systematic review. Can J Public Health 1998;89:197-202.
4. Ordun C, Blake JW, Rosidi N, et al. Open source health intelligence (OSHINT) for foodborne illness event characterization. Online J Public Health Inform 2013;5.
5. Harrison C, Jorder M, Stern H, et al. Using online reviews by restaurant patrons to identify unreported cases of foodborne illness—New York City, 2012-2013. MMWR 2014;63:441-5.
6. Kuehn BM. Agencies use social media to track foodborne illness. JAMA 2014;312:117-8.
7. Feinerer I, Buchta C, Geiger W, Rauch J, Mair P, Hornik K. The textcat package for n-gram based text categorization in R. J Stat Softw 2013;52:1-17.
8. Sadilek A, Brennan S, Kautz H, Silenzio V. nEmesis: Which restaurants should you avoid today? Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing. Palm Springs, CA, November 7-9, 2013.
9. Kang JS, Kuznetsova P, Luca M, Choi Y. Where not to eat? improving public policy by predicting hygiene inspections using online reviews. Proceedings of the Conference on Empirical Methods in Natural Language Processing, Seattle, WA, October 18-21, 2013;22:58-77.