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Application of the analytic hierarchy approach to the risk assessment of Zika virus disease transmission in Guangdong Province, China

Overview of attention for article published in BMC Infectious Diseases, January 2017
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Mentioned by

twitter
3 tweeters

Citations

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18 Dimensions

Readers on

mendeley
66 Mendeley
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Title
Application of the analytic hierarchy approach to the risk assessment of Zika virus disease transmission in Guangdong Province, China
Published in
BMC Infectious Diseases, January 2017
DOI 10.1186/s12879-016-2170-2
Pubmed ID
Authors

Xing Li, Tao Liu, Lifeng Lin, Tie Song, Xiaolong Du, Hualiang Lin, Jianpeng Xiao, Jianfeng He, Liping Liu, Guanghu Zhu, Weilin Zeng, Lingchuan Guo, Zheng Cao, Wenjun Ma, Yonghui Zhang

Abstract

An international spread of Zika virus (ZIKV) infection has attracted global attention in 2015. The infection also affected Guangdong province, which is located in southern China. Multiple factors, including frequent communication with South America and Southeast Asia, suitable climate (sub-tropical) for the habitat of Aedes species, may increase the risk of ZIKV disease transmission in this region. An analytic hierarchy process (AHP) method was used to develop a semi-quantitative ZIKV risk assessment model. After selecting indicators, we invited experts in related professions to identify the index weight and based on that a hierarchical structure was generated. Then a series of pairwise comparisons were used to determine the relative importance of the criteria. Finally, the optimal model was established to estimate the spatial and seasonal transmission risk of ZIKV. A total of 15 factors that potentially influenced the risk of ZIKV transmission were identified. The factor that received the largest weight was epidemic of ZIKV in Guangdong province (combined weight [CW] =0.37), followed by the mosquito density (CW = 0.18) and the epidemic of DENV in Guangdong province (CW = 0.14). The distribution of 123 districts/counties' RIs of ZIKV in Guangdong through different seasons were presented, respectively. Higher risk was observed within Pearl River Delta including Guangzhou, Shenzhen and Jiangmen, and the risk is greater in summer and autumn compared to spring and winter.

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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
Unknown 64 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 17%
Student > Bachelor 11 17%
Student > Ph. D. Student 8 12%
Student > Master 6 9%
Other 5 8%
Other 12 18%
Unknown 13 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 21%
Medicine and Dentistry 13 20%
Nursing and Health Professions 5 8%
Social Sciences 3 5%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 14 21%
Unknown 15 23%

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 08 July 2017.
All research outputs
#6,842,800
of 11,438,239 outputs
Outputs from BMC Infectious Diseases
#2,157
of 4,256 outputs
Outputs of similar age
#176,718
of 344,427 outputs
Outputs of similar age from BMC Infectious Diseases
#84
of 155 outputs
Altmetric has tracked 11,438,239 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,256 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 44th percentile – i.e., 44% 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 344,427 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.