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Early detection of influenza outbreak using time derivative of incidence

Authors
  • Son, Woo-Sik1
  • Park, Ji-Eun2
  • Kwon, Okyu1
  • 1 National Institute for Mathematical Sciences, Daejeon, 34047, South Korea , Daejeon (South Korea)
  • 2 Korea Institute of Oriental Medicine, Daejeon, 30675, South Korea , Daejeon (South Korea)
Type
Published Article
Journal
EPJ Data Science
Publisher
Springer Berlin Heidelberg
Publication Date
Sep 11, 2020
Volume
9
Issue
1
Identifiers
DOI: 10.1140/epjds/s13688-020-00246-7
Source
Springer Nature
Keywords
License
Green

Abstract

For mitigation strategies of an influenza outbreak, it can be helpful to understand the characteristics of regional and age-group-specific spread. In South Korea, however, there has been no official statistic related to it. In this study, we extract the time series of influenza incidence from National Health Insurance Service claims database, which consists of all medical and prescription drug-claim records for all South Korean population. The extracted time series contains the number of new patients by region (250 city-county-districts) and age-group (0–4, 5–19, 20–64, 65+) within a week. The number of cases of influenza (2009–2017) is 12,282,356. For computing an onset of influenza outbreak by region and age-group, we propose a novel method for early outbreak detection, in which the onset of outbreak is detected as a sudden change in the time derivative of incidence. The advantage of it over the cumulative sum and the exponentially weighted moving average control charts, which have been widely used for the early outbreak detection of infectious diseases, is that information on the previous non-epidemic periods are not necessary. Then, we show that the metro area and 5–19 age-group are earlier than the rural area and other age-groups for the start of the influenza outbreak. Also, the metro area and 5–19 age-group peak earlier than the rural area and other age-groups. These results would be helpful to design a surveillance system for timely early warning of an influenza outbreak in South Korea.

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