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The importance of human population characteristics in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases

Overview of attention for article published in Tropical Medicine & Health, November 2017
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About this Attention Score

  • Among the highest-scoring outputs from this source (#22 of 153)
  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
101 Mendeley
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Title
The importance of human population characteristics in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases
Published in
Tropical Medicine & Health, November 2017
DOI 10.1186/s41182-017-0078-1
Pubmed ID
Authors

Julie F. Obenauer, T. Andrew Joyner, Joseph B. Harris

Abstract

The mosquito Aedes aegypti has long been a vector for human illness in the Southeastern United States. In the past, it has been responsible for outbreaks of dengue, chikungunya, and yellow fever and, very recently, the Zika virus that has been introduced to the region. Multiple studies have modeled the geographic distribution of Ae. aegypti as a function of climate factors; however, this ignores the importance of humans to the anthropophilic biter. Furthermore, Ae. aegypti thrives in areas where humans have created standing water sites, such as water storage containers and trash. As models are developed to examine the potential impact of climate change, it becomes increasingly important to include the most comprehensive set of predictors possible. This study uses Maxent, a species distribution model, to evaluate the effects of adding poverty and population density to climate-only models. Performance was evaluated through model fit statistics, such as AUC, omission, and commission, as well as individual variable contributions and response curves. Models which included both population density and poverty exhibited better predictive power and produced more precise distribution maps. Furthermore, the two human population characteristics accounted for much of the model contribution-more so than climate variables. Modeling mosquito distributions without accounting for their dependence on local human populations may miss factors that are very important to niche realization and subsequent risk of infection for humans. Further research is needed to determine if additional human characteristics should be evaluated for model inclusion.

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

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 24%
Student > Master 17 17%
Other 11 11%
Student > Ph. D. Student 8 8%
Student > Bachelor 8 8%
Other 15 15%
Unknown 18 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 18%
Environmental Science 13 13%
Medicine and Dentistry 12 12%
Biochemistry, Genetics and Molecular Biology 7 7%
Social Sciences 5 5%
Other 23 23%
Unknown 23 23%

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 07 January 2018.
All research outputs
#3,688,327
of 13,607,891 outputs
Outputs from Tropical Medicine & Health
#22
of 153 outputs
Outputs of similar age
#121,990
of 394,309 outputs
Outputs of similar age from Tropical Medicine & Health
#8
of 27 outputs
Altmetric has tracked 13,607,891 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 153 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 85% 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 394,309 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 68% of its contemporaries.
We're also able to compare this research output to 27 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 70% of its contemporaries.