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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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3 X users

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24 Dimensions

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72 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.

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

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
Unknown 70 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 15%
Student > Bachelor 11 15%
Student > Ph. D. Student 8 11%
Student > Master 6 8%
Other 5 7%
Other 14 19%
Unknown 17 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 19%
Medicine and Dentistry 13 18%
Nursing and Health Professions 5 7%
Biochemistry, Genetics and Molecular Biology 3 4%
Social Sciences 3 4%
Other 16 22%
Unknown 18 25%
Attention Score in Context

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
#14,908,193
of 22,940,083 outputs
Outputs from BMC Infectious Diseases
#4,113
of 7,703 outputs
Outputs of similar age
#243,528
of 421,590 outputs
Outputs of similar age from BMC Infectious Diseases
#92
of 165 outputs
Altmetric has tracked 22,940,083 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,703 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one is in the 41st percentile – i.e., 41% 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 421,590 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.