The Southern Nevada Health District (SNHD) has the opportunity to expand upon a recent pilot study conducted in conjunction with team members from University of Rochester and their subcontractors at Google[X] and Answer Informatics working with a social media monitoring software (SoMMS) entitled nEmesis. The software nEmesis identifies tweets suggestive of foodborne illness by following a user for up to two weeks after the user posts from a food establishment. The nEmesis software then assigns a score to the food establishment based on the quantity and severity of sick tweets. In the pilot program, researchers are observing whether restaurants with high scores also tended to have worse health inspection outcomes as compared to blind assigned controls. In the proposed research, SNHD plans to expand the software by incorporating existing foodborne illness data, including foodborne illness complaints and customer's sanitation complaints, into the software and allowing it to influence the score. The score will then be used as a tool to determine when and where a regulatory response is needed such as a routine inspection, or an epidemiological investigation, depending on the severity. By using this novel technology, SNHD will potentially be able to identify cases of unreported foodborne illness faster and investigate cases and potential outbreaks quickly resulting in the reduced spread of disease in the community. Furthermore, if the intervention of unifying the nEmesis software with other foodborne illness predictors is able to identify foodborne illness outbreaks more quickly, less valuable time will need to be spent in the field investigating foodborne illness concerns. In the proposed research study, SNHD will evaluate whether the intervention has an effect on foodborne illness in the community by monitoring rates of lab?confirmed salmonellosis and E. coli O157:H7, quantity of foodborne illness reports, and quantity of customer complaints on restaurant sanitation. Secondly, SNHD will evaluate whether the intervention has an effect on time spent investigating verified foodborne illness complaints and verified customer sanitation complaints. This data will be collected over the life of the research and then compared to baseline data and analyzed for differences.
