Evidence map›Paper›PMID 42231195›Full record

ArticleBMC infectious diseases2026

Spatiotemporal dynamics of dengue: a town level study in Guangdong, China.

Yingyin Deng, Chumin Liang, Huifang Lin, Zhe Liu, Ning Sun, Lina Tian, Qianqian Ruan, Ximing Hu, Huimin Chen, Xinxin Li and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2026. 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
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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

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

16 authors.

Yingyin Deng *School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Chumin Liang *Guangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Huifang LinGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Zhe LiuGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Ning SunGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Lina TianSchool of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China.
Qianqian RuanSchool of Public Health, Sun Yat-Sen University, Guangzhou, China.
Ximing HuGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Huimin ChenGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Xinxin LiGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Yueling ChenGuangdong Provincial Institute of Public Health, Guangzhou, 511430, China.
Diemei LiuThe Seventh Affiliated Hospital of Southern Medical University, Foshan, 528224, P.R. China.
Xiaoxue WeiThe Seventh Affiliated Hospital of Southern Medical University, Foshan, 528224, P.R. China.
Wenjun MaDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.
Qingfeng DuThe Seventh Affiliated Hospital of Southern Medical University, Foshan, 528224, P.R. China. dqf1689@smu.edu.cn.
Jiufeng SunSchool of Public Health, Sun Yat-Sen University, Guangzhou, China. sunjiuf@163.com.

Funding

Guangdong Science and Technology Program 2022B1111030002, 2022A1111090004, 2021B1212030007
6 · The paper itself

Abstract

backgroundDengue has been prevalent in Guangdong Province, China, for more than forty years and has shown an increasing trend over the past decade.

methodA fine-scale analysis of dengue clusters was conducted. The relationship between virus evolution time and spatial distance was analyzed, and a genetic algorithm was used to quantify the effects of environmental, social, and economic factors on the transmission of dengue.

resultsA retrospective study analyzed 172 confirmed dengue cases (April 2019 to April 2020) at the Seventh Affiliated Hospital of Southern Medical University. Whole-genome sequencing revealed a unique transmission origin in Lishui town, Guangdong Province (99.64% to 100% homology). Regardless of the duration of the outbreak (1, 3, or 6 months), the probability that cases within 5 km belonged to the same transmission chain decreased with distance, with a 60-70% probability observed within 200 m. Population density and income were more influential factors than vegetation and precipitation in terms of virus transmission.

conclusionThe geographical distance among cases and the population density are crucial for determining dengue transmission during fine-scale outbreaks, highlighting important implications for control and surveillance and informing precise prevention strategies for dengue and other vector-borne viruses in China and tropical regions globally as well. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

DengueDengue VirusChinaDisease OutbreaksHumansPopulation DensityRetrospective StudiesSpatio-Temporal AnalysisDengueFine-scale analysisSocial factorsSpatial-temporal clusteringVector control

Identifiers

PMID42231195
PMCPMC13455347

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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.