The aim of this research project, funded by the German Research Foundation (DFG), is to efficiently identify the source of large-scale outbreaks of foodborne disease while contamination-caused illnesses are still occurring, in order to resolve investigations earlier and avert potential illnesses. It proposes a holistic system for real-time source detection, which combines a dynamic commodity flow model with a spatio-temporal method for source localization on networks.
The concept of this project is to bring data and modern analytical techniques to the problem of identifying the source of largescale outbreaks of foodborne illness. Determining the spatial origin of a contaminated food is a challenging problem due to the complexity of the food supply and the absence of data. Current investigative methods are time and resource intensive, and often unsuccessful. The planned collaboration connects the areas of public health and system engineering to propose a solution to this problem, using network theory and computational statistical epidemiology. Methodologies from these areas supplement each other, e.g. tracing back outbreaks of foodborne disease to their location and time of origin requires knowledge of the underlying distribution network. Research on transport demand modeling of food logistics has helped create a methodology for modeling aggregate commodity flows needed for the traceback studies. The project aims to combine these two methods to create a holistic system for real-time source detection, the Traceback Tool. It will serve as a planning tool to facilitate a probabilistic analysis of the source of product contamination events, and to make strategic recommendations regarding allocation of investigative resources. Extensive testing of the Traceback Tool across historical outbreak cases, quantifying benefits in comparison to current methods in outbreak identification followed by real-time application during outbreak emergencies, will be necessary to determine the utility of the proposed methodology to public health. It is believed that the Traceback Tool will benefit different communities, such as food-safety regulatory bodies, by offering improved methods for rapidly identifying the source of foodborne diseases. Researchers in the field of systems engineering and computational epidemiology will also benefit from the suggested theoretical advances on this important problem.
Food Logistics, Sustainability, Transport Logistics
Massachusetts Institute of Technology (MIT), Kühne Logistics University