Can Aggregated Restaurant Inspection Data Help Us Understand Why Individual Foodborne Illness Outbreaks Occur?

Abstract: Restaurant inspections seek to identify and correct risk factors for foodborne illness, but restaurant inspection data are not typically used more broadly as a food safety surveillance tool. In 2015, there was an outbreak of Salmonella serotype Newport infections associated with multiple restaurants in a chain (chain A), primarily in Minnesota. The outbreak was associated with tomatoes that were likely contaminated at the point of production. The objective of this study was to demonstrate the potential usefulness of aggregated restaurant inspection data in aiding individual outbreak investigations. Reports of the last inspection for all chain A restaurants that preceded the first reported case meal date in the outbreak were obtained from local health departments and the Minnesota Department of Health. Ordinal logistic regression was used to assess differences in risk factor and good retail practice violation categories and specific violations in restaurants with zero cases (nonoutbreak restaurants) (n = 25), one to two cases (n = 16), and at least three cases (n = 13). For restaurants with a "protection from contamination" violation in the routine inspection that preceded the outbreak, the proportional odds ratio for outbreak level was 4.92 (95% confidence interval: 1.57, 15.39; P = 0.01). These findings suggest that food handling practices in the outbreak restaurants may have increased contamination of foods through cross-contamination, which in turn increased transmission at outbreak restaurants. These data suggest that aggregated data from routine inspection reports can provide useful information to aid in outbreak investigations and other foodborne illness surveillance and prevention activities.