J Korean Med Sci.  2024 Jan;39(4):e40. 10.3346/jkms.2024.39.e40.

Application of the Time Derivative (TD) Method for Early Alert of Influenza Epidemics

• Kang SK
• Son WS
• Kim BI

• KMID: 2551970
• DOI: http://doi.org/10.3346/jkms.2024.39.e40

Abstract

Background
In order to minimize the spread of seasonal influenza epidemic to communities worldwide, the Korea Disease Control and Prevention Agency has issued an influenza epidemic alert using the influenza epidemic threshold formula based on the results of the influenza-like illness (ILI) rate. However, unusual changes have occurred in the pattern of respiratory infectious diseases, including seasonal influenza, after the coronavirus disease 2019 (COVID-19) pandemic. As a result, the importance of detecting the onset of an epidemic earlier than the existing epidemic alert system is increasing. Accordingly, in this study, the Time Derivative (TD) method was suggested as a supplementary approach to the existing influenza alert system for the early detection of seasonal influenza epidemics.
Methods
The usefulness of the TD method as an early epidemic alert system was evaluated by applying the ILI rate for each week during past seasons when seasonal influenza epidemics occurred, ranging from the 2013–2014 season to the 2022–2023 season to compare it with the issued time of the actual influenza epidemic alert.
Results
As a result of applying the TD method, except for the two seasons (2020–2021 season and 2021–2022 season) that had no influenza epidemic, an influenza early epidemic alert was suggested during the remaining seasons, excluding the 2017–2018 and 2022–2023 seasons.
Conclusion
The TD method is a time series analysis that enables early epidemic alert in real-time without relying on past epidemic information. It can be considered as an alternative approach when it is challenging to set an epidemic threshold based on past period information. This situation may arise when there has been a change in the typical seasonal epidemic pattern of various respiratory viruses, including influenza, following the COVID-19 pandemic.

Keyword

Seasonal Influenza; Early Epidemic Alert System; Time Derivative; Influenza-Like Illness (ILI); Influenza Epidemic Threshold

Figure

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  Fig. 1 The process of setting the adjusted parameter k.The analysis was conducted excluding the 2020–2021 and 2021–2022 seasons when there were no influenza epidemics.aResult: The suggested early alert times based on the Time Derivative method (week).bDiff (Difference): The difference between the actual week of issuance for the seasonal influenza epidemic alert and the suggested early alert time based on the Time Derivative method (week).

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  Fig. 2 Weekly ILI rate from 2013 to 2023, results of TD analysis, and influenza epidemic baseline by seasons.ILI = influenza-like illness, TD = Time Derivative.

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  Fig. 3 Results of TD analysis in the 2019–2020 and 2022–2023 seasons. Difference: The ILI rate difference between this week and last week indeed represents the time derivative (dt = yt - yt-1T). Threshold: This is composed of the cumulative average and cumulative standard deviation of the time derivative in each season. If the time derivative exceeds the threshold at the first moment, and early epidemic alerts is possible (dt > µt + k · σt. [adjusted parameter: k]).

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