Evidence map›Paper›PMID 25491192›Full record

ArticleParasites & vectors2014

Fine scale Spatial-temporal cluster analysis for the infection risk of Schistosomiasis japonica using space-time scan statistics.

Feng-hua Gao, Eniola Michael Abe, Shi-zhu Li, Li-juan Zhang, Jia-Chang He, Shi-qing Zhang, Tian-ping Wang, Xiao-nong Zhou, Jing Gao

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
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

9 authors at 3 institutions in 2 countries.

Feng-hua GaoAnhui Provincial Institute of Schistosomiasis Control, Hefei, 230061, China. ahxfbb@126.com.
Eniola Michael AbeDepartment of Zoology, Federal University Lafia, P.M. B 146, Lafia, Nasarawa State, Nigeria. abeeniola11@gmail.com.
Shi-zhu LiNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China. Lisz@chinacdc.cn.
Li-juan ZhangNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China. zhanglijuan727@163.com.
Jia-Chang HeAnhui Provincial Institute of Schistosomiasis Control, Hefei, 230061, China. hejiachang2005@126.com.
Shi-qing ZhangAnhui Provincial Institute of Schistosomiasis Control, Hefei, 230061, China. zhangsq2820@163.com.
Tian-ping WangAnhui Provincial Institute of Schistosomiasis Control, Hefei, 230061, China. wangtianping@hotmail.com.
Xiao-nong ZhouNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China. xiaonongzhou1962@gmail.com.
Jing GaoNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China. lynntime7@gmail.com.
Anhui Provincial Center for Disease Control and Prevention · CNNational Institute for Parasitic Diseases · CNFederal University Lafia · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMarching towards the elimination of schistosomiasis in China, both the incidence and prevalence have witnessed profound decline over the past decades, with the strategy shifting from morbidity control to transmission control. The current challenge is to find out hotspots of transmission risk for precise targeted control in low-prevalence areas. This study assessed the risk at the village level, using the spatial and temporal characteristics of Schistosomiasis japonica in Anhui province from 2006 to 2012.

methodThe comprehensive database was generated from annual surveillance data at village level in Anhui province between 2006 and 2012, comprising schistosomiasis prevalence among humans and cattle, occurrence rate of infected environments and incidence rate of acute schistosomiasis. The database parameters were matched with geographic data of the study area and fine scale spatial-temporal cluster analysis based on retrospective space-time scan statistics was used to assess the clustering pattern of schistosomiasis. The analysis was conducted by using SaTScan 9.1.1 and ArcGIS 10.0. A spatial statistical modelling was carried out to determine the spatial dependency of prevalence of human infection by using Geoda 1.4.3.

resultA pronounced decline was found in the prevalence of human infection, cattle infection, occurrence rate of environment with infected vector snails and incidence rate of acute schistosomiasis from 2006 to 2012 by 48.6%, 71.5%, 91.9% and 96.4%, respectively. Meanwhile, all 4 indicators showed a statistically significant clustering pattern both in time and space, with a total of 16, 6, 8 and 4 corresponding clustering foci found respectively. However, the number of clustering foci declined with time, and none was found after year 2010. All clustering foci were mainly distributed along the Yangtze River and its connecting branches. The result shows that there is a direct spatial relationship between prevalence of human infection and the other indicators.

conclusionA decreasing trend in space-time clustering of schistosomiasis endemic status was observed between 2006 and 2012 in Anhui province. Nevertheless, giving the complexity in schistosomiasis control, areas within the upper-stream of Yangtze River in Anhui section and its connecting branches should be targeted for effective implementation of control strategies in the future.

Indexed as

AnimalsCattleCattle DiseasesChinaHumansModels, StatisticalRetrospective StudiesSchistosoma japonicumSchistosomiasis japonicaSnailsSpatio-Temporal Analysis

Identifiers

PMID25491192
PMCPMC4273478
OpenAlexW2164300719

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.