Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains

Daniel Doerr, Kun Hu, Sondra Renly, Stefan Edlund, Matthew Davis, James H. Kaufman, Justin T Lessler, Matthias Filter, Annemarie Käsbohrer, Bernd Appel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Over the last decades the globalization of trade has significantly altered the topology of food supply chains. Even though food-borne illness has been consistently on the decline, the hazardous impact of contamination events is larger [1-3]. Possible contaminants include pathogenic bacteria, viruses, parasites, toxins or chemicals. Contamination can occur accidentally, e.g. due to improper handling, preparation, or storage, or intentionally as the melamine milk crisis proved. To identify the source of a food-borne disease it is often necessary to reconstruct the food distribution networks spanning different distribution channels or product groups. The time needed to trace back the contamination source ranges from days to weeks and significantly influences the economic and public health impact of a disease outbreak. In this paper we describe a model-based approach designed to speed up the identification of a food-borne disease outbreak source. Further, we exploit the geospatial information of wholesaler-retailer food distribution networks limited to a given food type and apply a gravity model for food distribution from retailer to consumer. We present a likelihood framework that allows determining the likelihood of wholesale source(s) distributing contaminated food based on geo-coded case reports. The developed method is independent of the underlying food distribution kernel and thus particularly applicable to empirical distributions of food acquisition.

Original languageEnglish (US)
Title of host publicationGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
Pages44-47
Number of pages4
DOIs
StatePublished - 2012
Event1st ACM SIGSPATIAL International Workshop on the Use of GIS in Public Health, HealthGIS 2012 - In Conjunction with the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - Redondo Beach, CA, United States
Duration: Nov 6 2012Nov 6 2012

Other

Other1st ACM SIGSPATIAL International Workshop on the Use of GIS in Public Health, HealthGIS 2012 - In Conjunction with the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
CountryUnited States
CityRedondo Beach, CA
Period11/6/1211/6/12

Fingerprint

Food supply
Food Chain
food supply
Supply Chain
Supply chains
Contamination
food
Distribution Network
Modeling
modeling
Likelihood
Gravity Model
Globalization
Empirical Distribution
Public Health
Bacteria
Virus
Preparation
Speedup
Electric power distribution

Keywords

  • food distribution
  • food-borne disease
  • geospatial data
  • geospatial modeling
  • maximum likelihood estimation

ASJC Scopus subject areas

  • Earth-Surface Processes
  • Computer Science Applications
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Information Systems

Cite this

Doerr, D., Hu, K., Renly, S., Edlund, S., Davis, M., Kaufman, J. H., ... Appel, B. (2012). Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems (pp. 44-47) https://doi.org/10.1145/2452516.2452525

Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains. / Doerr, Daniel; Hu, Kun; Renly, Sondra; Edlund, Stefan; Davis, Matthew; Kaufman, James H.; Lessler, Justin T; Filter, Matthias; Käsbohrer, Annemarie; Appel, Bernd.

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. p. 44-47.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Doerr, D, Hu, K, Renly, S, Edlund, S, Davis, M, Kaufman, JH, Lessler, JT, Filter, M, Käsbohrer, A & Appel, B 2012, Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains. in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. pp. 44-47, 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Public Health, HealthGIS 2012 - In Conjunction with the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, United States, 11/6/12. https://doi.org/10.1145/2452516.2452525
Doerr D, Hu K, Renly S, Edlund S, Davis M, Kaufman JH et al. Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. p. 44-47 https://doi.org/10.1145/2452516.2452525
Doerr, Daniel ; Hu, Kun ; Renly, Sondra ; Edlund, Stefan ; Davis, Matthew ; Kaufman, James H. ; Lessler, Justin T ; Filter, Matthias ; Käsbohrer, Annemarie ; Appel, Bernd. / Accelerating investigation of food-borne disease outbreaks using pro-active geospatial modeling of food supply chains. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. pp. 44-47
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