Evidence map›Paper›PMID 27993171›Full record

ArticleMalaria journal2016

Spatial and space-time distribution of Plasmodium vivax and Plasmodium falciparum malaria in China, 2005-2014.

Samuel H Hundessa, Gail Williams, Shanshan Li, Jinpeng Guo, Linping Chen, Wenyi Zhang, Yuming Guo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Malaria journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Parasite epidemiology and control · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Spatial and Temporal Analysis ofInternational journal of environmental research and public health · 2020
    Article
  9. Article
  10. Article
  11. Spatial and Temporal Patterns of Malaria in Phu Yen Province, Vietnam, from 2005 to 2016.The American journal of tropical medicine and hygiene · 2020
    Article
  12. Article
  13. Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan.International journal of environmental research and public health · 2018
    Article
  14. 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

7 authors.

Samuel H HundessaDivision of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Herston Rd, Herston, QLD, 4006, Australia.
Gail WilliamsDivision of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Herston Rd, Herston, QLD, 4006, Australia.
Shanshan LiDivision of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Herston Rd, Herston, QLD, 4006, Australia.
Jinpeng GuoInstitute for Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
Linping ChenDivision of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Herston Rd, Herston, QLD, 4006, Australia.
Wenyi ZhangInstitute for Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China. zwy0419@126.com.
Yuming GuoDivision of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Herston Rd, Herston, QLD, 4006, Australia. y.guo1@uq.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the declining burden of malaria in China, the disease remains a significant public health problem with periodic outbreaks and spatial variation across the country. A better understanding of the spatial and temporal characteristics of malaria is essential for consolidating the disease control and elimination programme. This study aims to understand the spatial and spatiotemporal distribution of Plasmodium vivax and Plasmodium falciparum malaria in China during 2005-2009.

methodsGlobal Moran's I statistics was used to detect a spatial distribution of local P. falciparum and P. vivax malaria at the county level. Spatial and space-time scan statistics were applied to detect spatial and spatiotemporal clusters, respectively.

resultsBoth P. vivax and P. falciparum malaria showed spatial autocorrelation. The most likely spatial cluster of P. vivax was detected in northern Anhui province between 2005 and 2009, and western Yunnan province between 2010 and 2014. For P. falciparum, the clusters included several counties of western Yunnan province from 2005 to 2011, Guangxi from 2012 to 2013, and Anhui in 2014. The most likely space-time clusters of P. vivax malaria and P. falciparum malaria were detected in northern Anhui province and western Yunnan province, respectively, during 2005-2009.

conclusionThe spatial and space-time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Contrary to P. vivax, the high-risk areas for P. falciparum malaria shifted from the west to the east of China. Further studies are required to examine the spatial changes in risk of malaria transmission and identify the underlying causes of elevated risk in the high-risk areas.

Indexed as

Topography, MedicalChinaHumansMalaria, FalciparumMalaria, VivaxPrevalenceSpatio-Temporal AnalysisMalariaPlasmodium falciparumPlasmodium vivaxSpace–time clusteringSpatial clustering

Identifiers

PMID27993171
PMCPMC5168843

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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.