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Epidemiological and molecular characteristics of emergent dengue virus in Yunnan Province near the China-Myanmar-Laos border, 2013–2015

Overview of attention for article published in BMC Infectious Diseases, May 2017
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  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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3 tweeters

Citations

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12 Dimensions

Readers on

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20 Mendeley
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Title
Epidemiological and molecular characteristics of emergent dengue virus in Yunnan Province near the China-Myanmar-Laos border, 2013–2015
Published in
BMC Infectious Diseases, May 2017
DOI 10.1186/s12879-017-2401-1
Pubmed ID
Authors

Ting-Song Hu, Hai-Lin Zhang, Yun Feng, Jian-Hua Fan, Tian Tang, Yong-Hua Liu, Liu Zhang, Xiao-Xiong Yin, Gang Chen, Hua-Chang Li, Jin Zu, Hong-Bin Li, Yuan-Yuan Li, Jing Yu, Fu-Qiang Zhang, Quan-Shui Fan

Abstract

Yunnan Province is located in southwestern China and neighbors the Southeast Asian countries, all of which are dengue-endemic areas. In 2000-2013, sporadic imported cases of dengue fever (DF) were reported almost annually in Yunnan Province. During 2013-2015, we confirmed that a large-scale indigenous DF outbreak emerged in cities of Yunnan Province near the China-Myanmar-Laos border. Epidemiological characteristics of DF in Yunnan Province during 2013-2015 were evaluated by retrospective analysis. A total of 232 dengue virus (DENV)-positive sera were randomly collected for sequence analysis of the capsid/premembrane region of DENV from patients with DF in Yunnan Province. The envelope gene of DENV isolates was also amplified and sequenced. Phylogenetic analyses were performed using the neighbor-joining method with the Tajima-Nei model. Phylogenetically, all DENV-positive samples could be classified into DENV-1 genotype I and DENV-2 Asian I genotype during 2013-2015 and DENV-4 genotype I in 2015 from Ruili City; and DENV-3 genotype II in 2013 and DENV-2 Cosmopolitan genotype in 2015 from Xishuangbanna Prefecture. Our results indicated that imported DF from patients from Laos and Myanmar was the primary cause of the DF epidemic in Yunnan Province. Additionally, DENV strains of all four serotypes were identified in indigenous cases in Yunnan Province during the same time period, while the dengue epidemic pattern observed in southwestern Yunnan showed characteristics of a hypoendemic nature: circulation of DENV-1 and DENV-2 over consecutive years.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 30%
Unspecified 5 25%
Researcher 4 20%
Student > Postgraduate 2 10%
Student > Ph. D. Student 2 10%
Other 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 25%
Unspecified 5 25%
Agricultural and Biological Sciences 3 15%
Immunology and Microbiology 3 15%
Medicine and Dentistry 2 10%
Other 2 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2017.
All research outputs
#4,991,229
of 9,821,976 outputs
Outputs from BMC Infectious Diseases
#1,923
of 4,163 outputs
Outputs of similar age
#125,417
of 264,149 outputs
Outputs of similar age from BMC Infectious Diseases
#52
of 128 outputs
Altmetric has tracked 9,821,976 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,163 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,149 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.