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

2Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Liu, J., & Suzuki, S. (2022). Real-Time Detection of Flu Season Onset: A Novel Approach to Flu Surveillance. International Journal of Environmental Research and Public Health, 19(6). https://doi.org/10.3390/ijerph19063681

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free