Study on the influence of meteorological factors on influenza in different regions and predictions based on an LSTM algorithm.

ABSTRACT:

Background

Influenza epidemics pose a threat to human health. It has been reported that meteorological factors (MFs) are associated with influenza. This study aimed to explore the similarities and differences between the influences of more comprehensive MFs on influenza in cities with different economic, geographical and climatic characteristics in Fujian Province. Then, the information was used to predict the daily number of cases of influenza in various cities based on MFs to provide bases for early warning systems and outbreak prevention.

Method

Distributed lag nonlinear models (DLNMs) were used to analyse the influence of MFs on influenza in different regions of Fujian Province from 2010 to 2021. Long short-term memory (LSTM) was used to train and model daily cases of in

SUBMITTER: Zhu H 

PROVIDER: S-EPMC9745690 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature