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A Study on Monitoring System for Infectious Diseases Using Temporal Model with Application to Seoul Metropolitan Area

  • Crisisonomy
  • Abbr : KRCEM
  • 2017, 13(11), pp.157-166
  • DOI : 10.14251/crisisonomy.2017.13.11.157
  • Publisher : Crisis and Emergency Management: Theory and Praxis
  • Research Area : Social Science > Public Policy > Public Policy in general
  • Received : September 22, 2017
  • Accepted : November 9, 2017
  • Published : November 30, 2017

Hye Inn Song 1 Heo, Tae Young 2 Ban, Yong-un 2

1제주연구원
2충북대학교

Accredited

ABSTRACT

In this study, we proposed a systematic algorithm to monitor and detect outbreak of infectious disease and applied it to mumps data. The Farrington algorithm used in this study is a model that reflects temporal trend, seasonality, and over-dispersion of the data. It provides a reference value to judge outbreak by comparing it with observation. If observation at some time point is bigger than reference value, that time point is then assigned to be outbreak time. The application of the Farrington algorithm to the mumps data of Seoul’s autonomous regions showed correct detection at increase points, and there are many outbreaks especially in the majority of autonomous districts from 2013 to the first half of 2014. The algorithm proposed in this study could provide more systematic and accurate information on disease surveillance and help the government to cope with outbreaks quickly and appropriately when applied to the monitoring system of various diseases.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.