Evidence map›Paper›PMID 31703720›Full record

ArticleParasites & vectors2019

Risk factors and predicted distribution of visceral leishmaniasis in the Xinjiang Uygur Autonomous Region, China, 2005-2015.

Fangyu Ding, Qian Wang, Jingying Fu, Shuai Chen, Mengmeng Hao, Tian Ma, Canjun Zheng, Dong Jiang

Abstract read
In one paragraph

Article in Parasites & vectors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Recurrence and Driving Factors of Visceral Leishmaniasis in Central China.International journal of environmental research and public health · 2021
    Article
  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

8 authors.

Fangyu DingState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Qian WangState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Jingying FuState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Shuai ChenState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Mengmeng HaoState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Tian MaState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Canjun ZhengNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Beijing, 102206, China. zhengcj@chinacdc.cn.
Dong JiangState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. jiangd@igsnrr.ac.cn.

Funding

the Ministry of Science and Technology of China 2016YFC1201300the Strategic Priority Research Program of the Chinese Academy of Sciences XDA19040305
6 · The paper itself

Abstract

backgroundVisceral leishmaniasis (VL) is a neglected disease that is spread to humans by the bites of infected female phlebotomine sand flies. Although this vector-borne disease has been eliminated in most parts of China, it still poses a significant public health burden in the Xinjiang Uygur Autonomous Region. Understanding of the spatial epidemiology of the disease remains vague in the local community. In the present study, we investigated the spatiotemporal distribution of VL in the region in order to assess the potential threat of the disease.

methodsBased on comprehensive infection records, the spatiotemporal patterns of new cases of VL in the region between 2005 and 2015 were analysed. By combining maps of environmental and socioeconomic correlates, the boosted regression tree (BRT) model was adopted to identify the environmental niche of VL.

resultsThe fitted BRT models were used to map potential infection risk zones of VL in the Xinjiang Uygur Autonomous Region, revealing that the predicted high infection risk zones were mainly concentrated in central and northern Kashgar Prefecture, south of Atushi City bordering Kashgar Prefecture and regions of the northern Bayingolin Mongol Autonomous Prefecture. The final result revealed that approximately 16.64 million people inhabited the predicted potential infection risk areas in the region.

conclusionsOur results provide a better understanding of the potential endemic foci of VL in the Xinjiang Uygur Autonomous Region with a 1 km spatial resolution, thereby enhancing our capacity to target the potential risk areas, to develop disease control strategies and to allocate medical supplies.

Indexed as

Topography, MedicalChinaClimateHumansLeishmaniasis, VisceralNeglected DiseasesRisk FactorsSocioeconomic FactorsSpatio-Temporal AnalysisVector Borne DiseasesEnvironmental nicheInfection riskSpatiotemporal patternsVisceral leishmaniasis

Identifiers

PMID31703720
PMCPMC6839266

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.