Evidence map›Paper›PMID 25644986›Full record

ArticleBMC infectious diseases2015

Human brucellosis occurrences in inner mongolia, China: a spatio-temporal distribution and ecological niche modeling approach.

Peng Jia, Andrew Joyner

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
9.1field-weighted citation impact, top 2% 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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 69 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Peng JiaDepartment of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, USA. jiapengff@hotmail.com.
Andrew JoynerDepartment of Geosciences, East Tennessee State University, Johnson City, TN, USA. joynert@etsu.edu.
East Tennessee State University · USLouisiana State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBrucellosis is a common zoonotic disease and remains a major burden in both human and domesticated animal populations worldwide. Few geographic studies of human Brucellosis have been conducted, especially in China. Inner Mongolia of China is considered an appropriate area for the study of human Brucellosis due to its provision of a suitable environment for animals most responsible for human Brucellosis outbreaks.

methodsThe aggregated numbers of human Brucellosis cases from 1951 to 2005 at the municipality level, and the yearly numbers and incidence rates of human Brucellosis cases from 2006 to 2010 at the county level were collected. Geographic Information Systems (GIS), remote sensing (RS) and ecological niche modeling (ENM) were integrated to study the distribution of human Brucellosis cases over 1951-2010.

resultsResults indicate that areas of central and eastern Inner Mongolia provide a long-term suitable environment where human Brucellosis outbreaks have occurred and can be expected to persist. Other areas of northeast China and central Mongolia also contain similar environments.

conclusionsThis study is the first to combine advanced spatial statistical analysis with environmental modeling techniques when examining human Brucellosis outbreaks and will help to inform decision-making in the field of public health.

Indexed as

EnvironmentModels, BiologicalAnimalsAnimals, DomesticBrucellosisDisease OutbreaksGeographic Information SystemsHumansMongoliaTopography, MedicalZoonoses

Identifiers

PMID25644986
PMCPMC4319220
OpenAlexW2002660476

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.