We also identified and investigated restaurants with more than two foodborne illness reports in the same year, since most restaurants appeared to have one or two reports, and because the CDC defines a foodborne disease outbreak as more than one case of a similar illness due to consumption of a common food (Daniels et al., 2002 and Jones et al., 2013). We extracted food

vehicles mentioned in the FOOD outbreak reports and the Yelp data according to the CDC convention of categorizing and grouping implicated find more foods (Painter et al., 2009 and Painter et al., 2013). Broadly, the taxonomy consisted of three major categories: aquatic animals, land animals and plants. These categories were hierarchically distributed into subcategories as shown in Fig. 2. Initially, we grouped the data into five major categories: aquatic, dairy–eggs, fruits–nuts, meat–poultry, and vegetables. Based on observations from this grouping, we further analyzed nineteen more specific categories,

capturing all the major food groups. The nineteen categories consisted of fish, crustaceans, mollusks, dairy, eggs, beef, game, pork, poultry, grains–beans, fruits–nuts, fungi, leafy, root, sprout, vine-stalk, shellfish, vegetables, and meat. The aquatic, shellfish, vegetables and meat categories consisted of all foods that belonged selleck chemical to these categories but could not be assigned to the more specific categories such as leafy, crustaceans, poultry, etc. We excluded the oils–sugars category since most meals include natural or processed oils and/or sugars. Foods implicated in foodborne illness were either categorized as simple or complex. Simple foods consisted of a single ingredient (e.g., lettuce) or could be classified into a single category

(e.g., fruit salad). Complex foods consisted of multiple ingredients that could be classified into more than one commodity (e.g., pizza). For example, if pizza were implicated in an alleged foodborne illness report, we documented three food categories: grains–beans (crust), vine-stalk (tomato sauce), and dairy (cheese). If a report included a food item not easily identifiable (such as a traditional dish), we used Google search heptaminol engine to locate the main ingredients in a typical recipe (e.g., meat, vegetable, aquatic, etc.) and categorized the food accordingly. To compare foods implicated by Yelp and the CDC, we focused on reports from 2006 to 2011, because the 2012 Yelp data were incomplete. We ranked the nineteen food categories separately for Yelp and FOOD, according to the frequency with which each food category was implicated per year. Food categories with the same frequency were assigned the average of their rankings. Correlations of the ranked food categories were assessed using Spearman’s rank correlation coefficient, ρ. Analyses were performed in SAS 9.1.3 (SAS Institute, Inc., Cary, NC). De-identified reviews of 13,262 businesses closest to 29 U.S. colleges in fifteen states (Table A.