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. 2022 Mar 19;19(6):3681.
doi: 10.3390/ijerph19063681.

Real-Time Detection of Flu Season Onset: A Novel Approach to Flu Surveillance

Jialiang Liu  1 , Sumihiro Suzuki  2
Affiliations

Real-Time Detection of Flu Season Onset: A Novel Approach to Flu Surveillance

Jialiang Liu et al. Int J Environ Res Public Health. .

Abstract

The current gold standard for detection of flu season onset in the USA is done retrospectively, where flu season is detected after it has already started. We aimed to create a new surveillance strategy capable of detecting flu season onset prior to its starting. We used an established data generation method that combines Google search volume and historical flu activity data to simulate real-time estimates of flu activity. We then applied a method known as change-point detection to the generated data to determine the point in time that identifies the initial uptick in flu activity which indicates the imminent onset of flu season. Our strategy exhibits a high level of accuracy in predicting the onset of flu season at 86%. Additionally, on average, we detected the onset three weeks prior to the official start of flu season. The results provide evidence to support both the feasibility and efficacy of our strategy to improve the current standard of flu surveillance. The improvement may provide valuable support and lead time for public health officials to take appropriate actions to prevent and control the spread of the flu.

Keywords: change point detection; influenza; public health; surveillance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Illustration of using change point detection method for flu season onset detection.
Figure 2
Figure 2
Early signal of flu season onset, 2007–2015 seasons.
See this image and copyright information in PMC

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