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Risk assessment of malaria transmission at the border area of China and Myanmar

Overview of attention for article published in Infectious Diseases of Poverty, July 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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7 tweeters
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1 Facebook page

Citations

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5 Dimensions

Readers on

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22 Mendeley
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Title
Risk assessment of malaria transmission at the border area of China and Myanmar
Published in
Infectious Diseases of Poverty, July 2017
DOI 10.1186/s40249-017-0322-2
Pubmed ID
Authors

Benyun Shi, Jinxin Zheng, Hongjun Qiu, Guo-Jing Yang, Shang Xia, Xiao-Nong Zhou

Abstract

In order to achieve the goal of malaria elimination, the Chinese government launched the National Malaria Elimination Programme in 2010. However, as a result of increasing cross-border population movements, the risk of imported malaria cases still exists at the border areas of China, resulting in a potential threat of local transmission. The focus of this paper is to assess the Plasmodium vivax incidences in Tengchong, Yunnan Province, at the border areas of China and Myanmar. Time series of P. vivax incidences in Tengchong from 2006 to 2010 are collected from the web-based China Information System for Disease Control and Prevention, which are further separated into time series of imported and local cases. First, the seasonal and trend decomposition are performed on time series of imported cases using Loess method. Then, the impact of climatic factors on the local transmission of P. vivax is assessed using both linear regression models (LRM) and generalized additive models (GAM). Specifically, the notion of vectorial capacity (VCAP) is used to estimate the transmission potential of P. vivax at different locations, which is calculated based on temperature and rainfall collected from China Meteorological Administration. Comparing with Ruili County, the seasonal pattern of imported cases in Tengchong is different: Tengchong has only one peak, while Ruili has two peaks during each year. This may be due to the different cross-border behaviors of peoples in two locations. The vectorial capacity together with the imported cases and the average humidity, can well explain the local incidences of P. vivax through both LRM and GAM methods. Moreover, the maximum daily temperature is verified to be more suitable to calculate VCAP than the minimal and average temperature in Tengchong County. To achieve malaria elimination in China, the assessment results in this paper will provide further guidance in active surveillance and control of malaria at the border areas of China and Myanmar.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 18%
Researcher 4 18%
Student > Master 4 18%
Student > Ph. D. Student 4 18%
Student > Bachelor 3 14%
Other 3 14%
Readers by discipline Count As %
Medicine and Dentistry 5 23%
Unspecified 4 18%
Environmental Science 2 9%
Social Sciences 2 9%
Agricultural and Biological Sciences 2 9%
Other 7 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 April 2018.
All research outputs
#4,009,493
of 13,786,654 outputs
Outputs from Infectious Diseases of Poverty
#153
of 484 outputs
Outputs of similar age
#91,049
of 263,418 outputs
Outputs of similar age from Infectious Diseases of Poverty
#3
of 14 outputs
Altmetric has tracked 13,786,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 484 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 67% of its peers.
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 263,418 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.