Automated detection for probable homologous foodborne disease outbreaks

Xiao Xiao, Yong Ge, Yunchang Guo, Danhuai Guo, Yi Shen, Yuanchun Zhou, Jianhui Li

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

4 Scopus citations


Foodborne disease, a rapid-growing public health problem, has become the highest-priority topic for food safety. The threat of foodborne disease has stimulated interest in enhancing public health surveillance to detect outbreaks rapidly. To advance research on food risk assessment in China, China National Center for Food Safety Risk Assessment (CFSA) sponsored a project to construct an online correlation analysis system for foodborne disease surveillance beginning in October 2012. They collect foodborne disease clinical data from sentinel hospitals across the country. They want to analyze the foodborne disease outbreaks existed in the collected data and finally find the link between pathogen, incriminated food sources and infected persons. Rapid detection of outbreaks is a critical first step for the analysis. The purpose of this paper is to provide approaches that can be applied to an online system to rapidly find local and sporadic foodborne disease outbreaks out of the collected data. Specifically, we employ DBSCAN for local outbreaks detection and solve the parameter self-adaptive problem in DBSCAN. We also propose a new approach named K-CPS (K-Means Clustering with Pattern Similarity) to detect sporadic outbreaks. The experimental results show that our methods are effective for rapidly mining local and sporadic outbreaks from the dataset.

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference, PAKDD 2015, Proceedings
EditorsTu-Bao Ho, Hiroshi Motoda, Hiroshi Motoda, Ee-Peng Lim, Tru Cao, David Cheung, Zhi-Hua Zhou
Number of pages13
ISBN (Print)9783319180373
StatePublished - 2015
Externally publishedYes
Event19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015 - Ho Chi Minh City, Viet Nam
Duration: May 19 2015May 22 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015
Country/TerritoryViet Nam
CityHo Chi Minh City


  • Clustering
  • Foodborne disease outbreak detection
  • Frequent patterns
  • Parameters self-adaptive

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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