Early warning of influenza epidemics using meteorological factors and machine learning

Corresponding author: gehui, gehui@chinacdc.cn

DOI: 10.12201/bmr.202012.00008

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  Abstract: Influenza is a highly infectious disease, and meteorological factors are the key factors which can cause an outbreak and epidemic among people. This study mainly discusses how to integrate the meteorological factors of multi-source big data with the incidences on influenza in a certain area. To explore the influence of meteorological factors on the incidence of influenza by the methods of machine learning, and construct the early warning and prediction models. The results showed that average temperature, average wind speed, maximum temperature, daily cumulative radiation, maximum wind speed and average air pressure were associated with the outbreak of influenza. Since influenza activity is the result of a variety of influencing factors, further research can be considered to evaluate and monitor the epidemic situation of influenza through multi factor and multi prediction methods, so as to achieve better warning effect and minimize the social impact and economic losses caused by influenza.

  Key words: Meteorological factors; Influenza; Big data; Machine learning; Early warning

  Submit time: 5 January 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2020-12-23	bmr.202012.00008V1	Download

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