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

The study demonstrates the value of multiscale spatial analysis in understanding geographical disease patterns, revealing that dysentery incidence in China is governed by different factors across regions.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2025-10-23
DOI
https://doi.org/10.3389/fpubh.2025.1663473
Primary Topic
Spatial and Panel Data Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Shuo‐Ming Ou, Ke Hu, Chaojie Li, Mingyang Yu et al.
Frontiers in Public Health
Spatial and Panel Data Analysis
article

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

Shuo‐Ming Ou, Ke Hu, Chaojie Li, Mingyang Yu, Xingjin Yang, Xing Zhang, Di Xiao
article en

Abstract

The study demonstrates the value of multiscale spatial analysis in understanding geographical disease patterns, revealing that dysentery incidence in China is governed by different factors across regions.

Frontiers in Public HealthVol. 13
Nanjing Health and Health Commission (CN), Guizhou Aerospace Power Science & Tech (China) (CN), Zhengzhou Central Hospital (CN), Community Health Center (US), Xiamen Chang Gung Hospital (CN), Qiannan Normal College For Nationalities (CN)
National Health Commission of the People's Republic of China
Openalex Percentile: Top 61%
Spatial and Panel Data Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.