Evidence map›Paper›PMID 41585528›Full record

ArticleFrontiers in veterinary science2025

An analysis of rodent density patterns and its spatial-temporal correlations using geographically and temporally weighted regression in southeastern China.

Mingyu Luo, Jinna Wang, Mingyong Tao, Hanran Ji, Guoqin Jiang, Qinmei Liu, Tianqi Li, Zhou Guan, Juan Hou, Zhenyu Gong

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mingyu Luo *Department of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Jinna Wang *Department of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Mingyong TaoDepartment of Communicable Disease Control and Prevention, Hangzhou Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Hanran JiCenter for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Guoqin JiangDepartment of Vectors Prevention and Control, Shaoxing Prefectural Center for Disease Control and Prevention, Shaoxing, Zhejiang, China.
Qinmei LiuDepartment of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Tianqi LiDepartment of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Zhou GuanDepartment of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Juan HouKey Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, Zhejiang, China.
Zhenyu GongDepartment of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Rodents are significant vectors, harboring diverse pathogenic microorganisms which can spread a variety of infectious diseases. Surveillance on rodent density patterns should be prioritized as early warning indicators for prevention and control of infectious diseases. We aimed to analyze spatial and temporal heterogeneity of rodent density patterns in Zhejiang Province, and analyze the spatial and temporal correlations between rodent density, meteorological, land use and vegetation factors. Methods: Collect rodent surveillance data, meteorological factors, and vegetation factors in Zhejiang Province from 2019 to 2023. Analyze the temporal and spatial distribution of rodent density patterns. Employ the GTWR model to analyze the spatial and temporal correlations between rodent density, meteorological, land use and vegetation factors. Results: The rodent density in southern Zhejiang Province was higher than that in northern Zhejiang Province, and the species richness of wild rodents also exceeded that in northern Zhejiang Province. The effects of meteorological and vegetation factors on rodent density varied across geographical spatial distributions, which might primarily be related to the distribution range of rodent species in different habitat sites. Discussions: Meteorological and vegetation factors could influence the rodent density, particularly that of wild rodents, by offering a suitable environment for growth and development as well as food sources.

Indexed as

GTWRmeteorologicalOne Healthpublic healthrodent densityvegetation

Identifiers

PMID41585528
PMCPMC12823992

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.