A modeling framework to accelerate food-borne outbreak investigations

作者：Hu Kun^*; Renly Sondra; Edlund Stefan; Davis Matthew; Kaufman James

来源：Food Control, 2016, 59: 53-58.

DOI：10.1016/j.foodcont.2015.05.017

• Food safety
• Food-borne infections
• Geospatial data
• Geospatial modeling
• Likelihood-based method
• Epidemiology
• Outbreaks
• Public health informatics

Food safety procedures are critical to reducing pathogen caused food-borne disease (FBD). However there is no way to completely eliminate the risk of consuming contaminated products. When prevention efforts fail, rapid identification of the contaminated product is essential. The medical and economic losses incurred grow with the duration of the outbreak. In this paper we show that before an outbreak occurs, analysis of food sales data, as a proactive intervention, can provide useful product intelligence that we can exploit during an outbreak investigation to accelerate the identification process. Using real grocery retail sales data from Germany, we have implemented a likelihood-based approach to study how such data can be used to accelerate the investigation during the early stages of an outbreak.

• 出版日期2016-1
• 单位IBM