Driving role of climatic and socioenvironmental factors on human brucellosis in China: machine-learning-based predictive analyses.

ABSTRACT:

Background

Brucellosis is a common zoonotic infectious disease in China. This study aimed to investigate the incidence trends of brucellosis in China, construct an optimal prediction model, and analyze the driving role of climatic factors for human brucellosis.

Methods

Using brucellosis incidence, and the socioeconomic and climatic data for 2014-2020 in China, we performed spatiotemporal analyses and calculated correlations with brucellosis incidence in China, developed and compared a series of regression and Seasonal Autoregressive Integrated Moving Average X (SARIMAX) models for brucellosis prediction based on socioeconomic and climatic data, and analyzed the relationship between extreme weather conditions and brucellosis incidence using copula models.

Results

In to

SUBMITTER: Chen H 

PROVIDER: S-EPMC10091610 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature