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J Public Health Manag Pract. 2017 Nov/Dec;23(6):577-580. doi: 10.1097/PHH.0000000000000516.

Using Twitter to Identify and Respond to Food Poisoning: The Food Safety STL Project.

Author information

1
Brown School, Washington University in St Louis, St Louis, Missouri (Dr Harris); Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts (Drs Hawkins, Tuli, and Brownstein); Department of Pediatrics, Harvard Medical School, Boston, Massachusetts (Drs Hawkins and Brownstein); City of St Louis Department of Health, St Louis, Missouri (Ms Nguyen); Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington (Dr Nsoesie); and Chicago Department of Public Health, Chicago, Illinois (Mr Mansour).

Abstract

CONTEXT:

Foodborne illness affects 1 in 4 US residents each year. Few of those sickened seek medical care or report the illness to public health authorities, complicating prevention efforts. Citizens who report illness identify food establishments with more serious and critical violations than found by regular inspections. New media sources, including online restaurant reviews and social media postings, have the potential to improve reporting.

OBJECTIVE:

We implemented a Web-based Dashboard (HealthMap Foodborne Dashboard) to identify and respond to tweets about food poisoning from St Louis City residents.

DESIGN AND SETTING:

This report examines the performance of the Dashboard in its first 7 months after implementation in the City of St Louis Department of Health.

MAIN OUTCOME MEASURES:

We examined the number of relevant tweets captured and replied to, the number of foodborne illness reports received as a result of the new process, and the results of restaurant inspections following each report.

RESULTS:

In its first 7 months (October 2015-May 2016), the Dashboard captured 193 relevant tweets. Our replies to relevant tweets resulted in more filed reports than several previously existing foodborne illness reporting mechanisms in St Louis during the same time frame. The proportion of restaurants with food safety violations was not statistically different (P = .60) in restaurants inspected after reports from the Dashboard compared with those inspected following reports through other mechanisms.

CONCLUSION:

The Dashboard differs from other citizen engagement mechanisms in its use of current data, allowing direct interaction with constituents on issues when relevant to the constituent to provide time-sensitive education and mobilizing information. In doing so, the Dashboard technology has potential for improving foodborne illness reporting and can be implemented in other areas to improve response to public health issues such as suicidality, spread of Zika virus infection, and hospital quality.

PMID:
28166175
PMCID:
PMC5540821
DOI:
10.1097/PHH.0000000000000516
[Indexed for MEDLINE]
Free PMC Article

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