Evidence map›Paper›PMID 40376502›Full record

ArticleChina CDC weekly2025

Application of Remote Sensing Methods in Predicting the Dynamics of

Jingjing Jiang, Zijian Liu, Hongzheng Lu, Tao Zhang, Xiaofeng Lyu, Xian Xu, Shuqi Wang, Qinshu Chu, Weidong Li, Duoquan Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in China CDC weekly, 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

10 authors.

Jingjing Jiang *Anhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Zijian Liu *Anhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Hongzheng LuDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei City, Anhui Province, China.
Tao ZhangAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Xiaofeng LyuAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Xian XuAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Shuqi WangAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Qinshu ChuAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Weidong LiAnhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Duoquan WangNational Institute of Parasitic Diseases (Chinese Center for Tropical Diseases Research), Chinese Center for Disease Control and Prevention, NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Remote sensing information provides indirect insights into infectious disease dynamics. Public health practice has significantly benefited from the increasing availability and accessibility of remote sensing data. What is added by this report?: This study explores the relationship between meteorological and environmental factors and malaria vector abundance using remote sensing technology, establishing predictive models for What are the implications for public health practice?: Identifying reliable predictors of malaria vector abundance enables policymakers to allocate resources more efficiently to regions at high risk of malaria transmission. In areas where an abnormal increase in malaria vector populations is predicted, proactive measures can be implemented, including environmental management, enhancement of local malaria diagnostic capabilities, and strengthening of targeted public health education campaigns.

Indexed as

AnophelesPredictRemote sensing

Identifiers

PMID40376502
PMCPMC12075442

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.