Evidence map›Paper›PMID 40852662›Full record

ArticleFrontiers in public health2025

Predicting the potential distribution areas of

Qunzheng Mu, Fengfeng Li, Wenyu Li, Xiaoxia Wang, Mingyuan Tang, Kehan Chen, Yihao Jiang, Jingqi Liu, Shirong Zhang, Qiyong Liu and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Qunzheng Mu *West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Fengfeng Li *School of Public Health, Shandong Second Medical University, Weifang, Shandong, China.
Wenyu LiState Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoxia WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Mingyuan TangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Kehan ChenWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Yihao JiangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Jingqi LiuWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Shirong ZhangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Qiyong LiuState Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Chuan WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Methods: Fifty-seven potential influencing factors were evaluated. The maximum entropy (MaxEnt) model projected potential distribution areas for near current and future climate scenarios. Occurrence records were extracted from published literature. The selection of environmental variables was conducted using a multi-stage analytical approach, consisting of contribution rate assessment, jackknife tests, and correlation analyses. Model parameters were optimized via feature class and regularization multiplier adjustments. Results: The MaxEnt model demonstrated high predictive accuracy (AUC = 0.997) with minimal training omission error. July precipitation (prec7) and elevation (elev) were identified as the primary environmental determinants. Projections indicate near current suitable areas are concentrated in southern China, with potential northward expansion under future climate scenarios. Conclusion:

Indexed as

Climate ChangeDisease VectorsAnimalsChinaForecastingHumanschigger miteclimate changeLeptotrombidium rubellumMaxEntpotential distribution areas

Identifiers

PMID40852662
PMCPMC12367748

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.