PeerJ (May 2020)

Evaluation of a novel syndromic surveillance system for the detection of the 2007 melamine-related nephrotoxicosis foodborne outbreak in dogs and cats in the United States

  • Hsin-Yi Weng,
  • Mark A.L. Gaona,
  • Philip H. Kass

DOI
https://doi.org/10.7717/peerj.9093
Journal volume & issue
Vol. 8
p. e9093

Abstract

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The 2007 nephrotoxicosis outbreak associated with melamine and cyanuric acid adulteration of pet foods in the United States sparked an urgent need for a nationwide companion animal surveillance program. In 2016, we introduced a syndromic surveillance system based on a novel epidemiological algorithm, the proportionate diagnostic outcome ratio (PDOR). The PDOR procedure was validated using simulated outbreaks of foodborne illness (i.e., aflatoxicosis and gastrointestinal illness) in dogs and cats. In this study, we further evaluated the PDOR procedure using the 2007 melamine-related outbreak of nephrotoxicosis. The performance of the PDOR procedure was assessed by the time to alert and positive predictive value (PPV). Electronic medical records of dogs and cats seen at networked primary care veterinary hospitals across the United States were retrieved from a centralized database. The data of four relevant syndromic components: elevated serum creatinine concentration, vomiting, anorexia, and lethargy from July 28, 2006 to May 31, 2007 were prospectively analyzed using the PDOR algorithm. The results showed that the alerts generated from the analysis of elevated serum creatinine concentration could have led to an early detection of this nephrotoxicosis foodborne outbreak and were well matched to the reported timeline of the outbreak. Additionally, we also observed variations in the performance of the PDOR procedure across age of animals and syndromic components, with the PPVs ranged from 0.61 to 1.0. Combined with the findings from previous evaluations using simulated outbreak scenarios, this study provided additional evidence that the PDOR procedure can be applied in syndromic surveillance to effectively and accurately detect various types of foodborne illness outbreaks in companion animals. However, the interpretations of and responses to alerts require an understanding of clinical veterinary medicine and relevant syndromic knowledge, and should not be based solely on quantitative measures.

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