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APHA Scientific Session and Event Listing

Recorded presentation

Isaac Triebold, BA¹, Margaret Khaitsa, PhD², William Nganje, PhD³, Julie Goplin, MS⁴, Penelope Gibbs, PhD², and Neil Dyer, DVM⁵. (1) Great Plains Institute of Food Safety, North Dakota State University, 1301 12th Avenue N, Fargo, ND 58105, 701-231-8250, Isaac.Triebold@ndsu.edu, (2) Department of Veterinary and Microbiological Sciences, North Dakota State University, 1301 12th Ave N, Fargo, ND 58105, (3) Department of Agribusiness and Applied Economics, North Dakota State University, 1301 12th Ave N, Fargo, ND 58105, (4) North Dakota Department of Health, 600 E Boulevard Ave., Dept. 301, Bismarck, ND 58505, (5) Department of Veterinary Diagnostic Services, North Dakota State University, 1301 12th Ave N, Fargo, ND 58105

Syndromic surveillance is an automated, non-traditional form of surveillance that relies on patient data that precedes diagnosis for the purpose of early outbreak detection. North Dakota uses a system of syndromic surveillance known as RedBat® (ICPA, Austin, TX). This system is relatively new to the state and there is need to evaluate its technical effectiveness and long-run economic viability. One way of evaluating this system is using data from historical outbreaks. The objective of the study is to evaluate the effectiveness of RedBat® in detecting a gastrointestinal disease outbreak using historical data and project its economic viability for the state of North Dakota. Data from an outbreak of Escherichia coli 0157:H7 at a large restaurant chain provided by the North Dakota department of health (NDDoH) was used for the analysis. Economic data on cost of the RedBat® system and potential health improvement benefits were obtained from the NDDoH budget, the CDC, and the Economic Research Service of the USDA. Binomial distributions were used to estimate the probability of RedBat® successfully detecting an outbreak earlier than conventional disease surveillance methods. These probabilities were incorporated in a real options (cost-benefit analysis) model to determine the economic viability of the system. Preliminary results indicate that with proper configuration RedBat® could be cost-effective in detecting the outbreak, in this particular case 8 days earlier than the traditional passive surveillance system. The RedBat® system could serve as a viable tool to help minimize cost associated with foodborne outbreaks.

Learning Objectives:

• Evaluate the economic effectiveness of syndromic surveillance systems using a novel real options approach.

Keywords: Food Safety, Surveillance

Presenting author's disclosure statement:

Any relevant financial relationships? No

Recorded presentation