A multi-method spatial analysis of dysentery incidence determinants across Chinese provinces.

ABSTRACT:

Introduction

Dysentery remains a significant notifiable Class B infectious disease in China, exhibiting distinct spatial variations in incidence patterns. This persistent geographical heterogeneity necessitates a systematic investigation into the underlying influencing factors to inform targeted prevention and control strategies.

Methods

Our analytical approach incorporated Moran's I index for spatial autocorrelation analysis, multiple linear regression (MLR) for preliminary assessment, and advanced spatial regression models including spatial error model (SEM), geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR). The analysis incorporated socioeconomic, educational, healthcare, and demographic factors within a unified spatial fr

SUBMITTER: Hu K 

PROVIDER: S-EPMC12588939 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature