Evidence map›Paper›PMID 38383355›Full record

ArticleBMC public health2024

Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018.

Jiaojiao Qian, Yifan Wu, Changqiang Zhu, Qiong Chen, Hongliang Chu, Licheng Liu, Chongcai Wang, Yizhe Luo, Na Yue, Wenhao Li and 8 more

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

18 authors.

Jiaojiao Qian *Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
Yifan Wu *Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Changqiang Zhu *Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Qiong Chen *Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Hongliang ChuCenter for Disease Prevention and Control of Jiangsu Province, Nanjing, Jiangsu, China.
Licheng LiuNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Chongcai WangHainan International Travel Healthcare Center, Haikou, Hainan, China.
Yizhe LuoDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
Na YueNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Wenhao LiNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Xiaohong YangNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Jing YiDepartment of Transfusion Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Fuqiang YeNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Ji HeXiamen International Travel Health Care Center (Xiamen Customs Port Outpatient Department), Xiamen, China.
Yong QiNanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
Fei LuCollege of Information Engineering, Zhejiang University of Technology, Liuhe Rd. 288, Hangzhou, 310023, China. Luf@zjut.edu.cn.
Chunhui WangDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China. 13912966353@139.com.
Weilong TanDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China. njcdc@163.com.

Funding

Tan Weilong BE2022682, BK20221196Wu Yifan 2023YQFH08Zhu Changqiang 2023YQFH08
6 · The paper itself

Abstract

backgroundLarge-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control.

methodsThis study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions.

resultsScrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882.

conclusionsThese results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.

Indexed as

Scrub TyphusBayes TheoremChinaEconomic FactorsHumansIncidenceSeasonsBayesian modelEnvironmentGeodetectorMeteorological and socio-economic factorsScrub typhusSpatiotemporal heterogeneity

Identifiers

PMID38383355
PMCPMC10880311

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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.