Evidence map›Paper›PMID 29471844›Full record

ArticleParasites & vectors2018

Spatiotemporal patterns and environmental drivers of human echinococcoses over a twenty-year period in Ningxia Hui Autonomous Region, China.

Angela M Cadavid Restrepo, Yu Rong Yang, Donald P McManus, Darren J Gray, Tamsin S Barnes, Gail M Williams, Ricardo J Soares Magalhães, Nicholas A S Hamm, Archie C A Clements

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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  11. Gastrointestinal parasite infestation in the alpine mountain hare (International journal for parasitology. Parasites and wildlife · 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

9 authors at 5 institutions in 3 countries.

Angela M Cadavid RestrepoResearch School of Population Health, The Australian National University, Canberra, ACT, Australia. angela.cadavid@anu.edu.au.
Yu Rong YangNingxia Medical University, Yinchuan, Ningxia Hui Autonomous Region, People's Republic of China.
Donald P McManusMolecular Parasitology Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Darren J GrayResearch School of Population Health, The Australian National University, Canberra, ACT, Australia.
Tamsin S BarnesSchool of Veterinary Science, The University of Queensland, Gatton, QLD, Australia.
Gail M WilliamsSchool of Public Health, The University of Queensland, Brisbane, QLD, Australia.
Ricardo J Soares MagalhãesSchool of Veterinary Science, The University of Queensland, Gatton, QLD, Australia.
Nicholas A S HammFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands.
Archie C A ClementsResearch School of Population Health, The Australian National University, Canberra, ACT, Australia.
University of Queensland · AUAustralian National University · AUQIMR Berghofer Medical Research Institute · AUNingxia Medical University · CNUniversity of Twente · NL

Funding

National Health and Medical Research Council APP1009539
6 · The paper itself

Abstract

backgroundHuman cystic (CE) and alveolar (AE) echinococcoses are zoonotic parasitic diseases that can be influenced by environmental variability and change through effects on the parasites, animal intermediate and definitive hosts, and human populations. We aimed to assess and quantify the spatiotemporal patterns of human echinococcoses in Ningxia Hui Autonomous Region (NHAR), China between January 1994 and December 2013, and examine associations between these infections and indicators of environmental variability and change, including large-scale landscape regeneration undertaken by the Chinese authorities.

methodsData on the number of human echinococcosis cases were obtained from a hospital-based retrospective survey conducted in NHAR for the period 1 January 1994 through 31 December 2013. High-resolution imagery from Landsat 4/5-TM and 8-OLI was used to create single date land cover maps. Meteorological data were also collected for the period January 1980 to December 2013 to derive time series of bioclimatic variables. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between annual cases of CE and AE and environmental variables.

resultsAnnual CE incidence demonstrated a negative temporal trend and was positively associated with winter mean temperature at a 10-year lag. There was also a significant, nonlinear effect of annual mean temperature at 13-year lag. The findings also revealed a negative association between AE incidence with temporal moving averages of bareland/artificial surface coverage and annual mean temperature calculated for the period 11-15 years before diagnosis and winter mean temperature for the period 0-4 years. Unlike CE risk, the selected environmental covariates accounted for some of the spatial variation in the risk of AE.

conclusionsThe present study contributes towards efforts to understand the role of environmental factors in determining the spatial heterogeneity of human echinococcoses. The identification of areas with high incidence of CE and AE may assist in the development and refinement of interventions for these diseases, and enhanced environmental change risk assessment.

Indexed as

AnimalsChinaEchinococcosis, HepaticEchinococcosis, PulmonaryEpidemiological MonitoringHospitalsHumansIncidenceRemote Sensing TechnologyRetrospective StudiesRiskSpatio-Temporal AnalysisAlveolar echinococcosisCystic echinococcosisEchinococcosisEnvironmental changeRemote sensingSpatial analysis

Identifiers

PMID29471844
PMCPMC5824458
OpenAlexW2801628625

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.