Predicting the incidence of common intestinal infectious diseases in Changzhou, China based on environmental factors and deep learning.

ABSTRACT:

Background

Intestinal infectious disease is a common infectious disease that is closely related to meteorological conditions and air pollution factors. We aim to construct a short-term prediction model for the daily incidence of common intestinal infectious diseases in Changzhou city.

Methods

The daily incidence data of hand, foot, and mouth disease and other infectious diarrhea in Changzhou and the daily meteorological data and air pollutant data in the same period were collected from May 13, 2014 to December 31, 2024. The meteorological data consisted of temperature, humidity, wind speed, air pressure, etc. Air pollutant data included PM_2.5, PM₁₀, SO₂, NO₂, O_3, and AQI indicators. Three models, Long Short-Term Memory (

SUBMITTER: Zheng X 

PROVIDER: S-EPMC12837124 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature