Evidence map›Paper›PMID 25659112›Full record

ArticlePLoS neglected tropical diseases2015

Spatio-temporal transmission and environmental determinants of Schistosomiasis Japonica in Anhui Province, China.

Yi Hu, Rui Li, Robert Bergquist, Henry Lynn, Fenghua Gao, Qizhi Wang, Shiqing Zhang, Liqian Sun, Zhijie Zhang, Qingwu Jiang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PLoS neglected tropical diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 12% of its field
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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

  1. Pooled it
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  9. Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification ofInternational journal of environmental research and public health · 2021
    Article
  10. Article
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  12. Identifying and Predicting the Geographical Distribution Patterns ofInternational journal of environmental research and public health · 2019
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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 at 3 institutions in 1 country.

Yi HuDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Rui LiDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Robert BergquistIngerod, Brastad, Sweden.
Henry LynnDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China; Biomedical Statistical Center, Fudan University, Shanghai, China.
Fenghua GaoAnhui Institute of Parasitic Diseases, Wuhu, China.
Qizhi WangAnhui Institute of Parasitic Diseases, Wuhu, China.
Shiqing ZhangAnhui Institute of Parasitic Diseases, Wuhu, China.
Liqian SunDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Zhijie ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China; Biomedical Statistical Center, Fudan University, Shanghai, China.
Qingwu JiangDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Fudan University · CNJiangsu Institute of Parasitic Diseases · CNMinistry of Education of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchistosomiasis japonica still remains of public health and economic significance in China, especially in the lake and marshland areas along the Yangtze River Basin, where the control of transmission has proven difficult. In the study, we investigated spatio-temporal variations of S. japonicum infection risk in Anhui Province and assessed the associations of the disease with key environmental factors with the aim of understanding the mechanism of the disease and seeking clues to effective and sustainable schistosomiasis control. METHODOLOGY/PRINCIPAL

findingsInfection data of schistosomiasis from annual conventional surveys were obtained at the village level in Anhui Province, China, from 2000 to 2010 and used in combination with environmental data. The spatio-temporal kriging model was used to assess how these environmental factors affected the spatio-temporal pattern of schistosomiasis risk. Our results suggested that seasonal variation of the normalized difference vegetation index (NDVI), seasonal variation of land surface temperature at daytime (LSTD), and distance to the Yangtze River were negatively significantly associated with risk of schistosomiasis. Predictive maps showed that schistosomiasis prevalence remained at a low level and schistosomiasis risk mainly evolved along the Yangtze River. Schistosomiasis risk also followed a focal spatial pattern, fluctuating temporally with a peak (the largest spatial extent) in 2005 and then contracting gradually but with a scattered distribution until 2010.

conclusionThe fitted spatio-temporal kriging model can capture variations of schistosomiasis risk over space and time. Combined with techniques of geographic information system (GIS) and remote sensing (RS), this approach facilitates and enriches risk modeling of schistosomiasis, which in turn helps to identify prior areas for effective and sustainable control of schistosomiasis in Anhui Province and perhaps elsewhere in China.

Indexed as

ChinaClimateGeographic Information SystemsHumansLakesPrevalenceRisk FactorsRiversSchistosomiasis japonicaSeasonsSpatial AnalysisTemperature

Identifiers

PMID25659112
PMCPMC4319937
OpenAlexW2013738622

What OpenQuestion holds

Textmetadata
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.