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A computer simulation model of Wolbachia invasion for disease vector population modification

Overview of attention for article published in BMC Bioinformatics, October 2015
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Title
A computer simulation model of Wolbachia invasion for disease vector population modification
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/s12859-015-0746-2
Pubmed ID
Authors

Mauricio Guevara-Souza, Edgar E. Vallejo

Abstract

Wolbachia invasion has been proved to be a promising alternative for controlling vector-borne diseases, particularly Dengue fever. Creating computer models that can provide insight into how vector population modification can be achieved under different conditions would be most valuable for assessing the efficacy of control strategies for this disease. In this paper, we present a computer model that simulates the behavior of native mosquito populations after the introduction of mosquitoes infected with the Wolbachia bacteria. We studied how different factors such as fecundity, fitness cost of infection, migration rates, number of populations, population size, and number of introduced infected mosquitoes affect the spread of the Wolbachia bacteria among native mosquito populations. Two main scenarios of the island model are presented in this paper, with infected mosquitoes introduced into the largest source population and peripheral populations. Overall, the results are promising; Wolbachia infection spreads among native populations and the computer model is capable of reproducing the results obtained by mathematical models and field experiments. Computer models can be very useful for gaining insight into how Wolbachia invasion works and are a promising alternative for complementing experimental and mathematical approaches for vector-borne disease control.

X Demographics

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

Geographical breakdown

Country Count As %
United Kingdom 3 6%
Brazil 2 4%
United States 1 2%
Unknown 46 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Bachelor 11 21%
Student > Ph. D. Student 8 15%
Student > Doctoral Student 4 8%
Student > Master 4 8%
Other 6 12%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 37%
Medicine and Dentistry 9 17%
Biochemistry, Genetics and Molecular Biology 5 10%
Computer Science 3 6%
Mathematics 3 6%
Other 9 17%
Unknown 4 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 April 2016.
All research outputs
#17,774,664
of 22,829,683 outputs
Outputs from BMC Bioinformatics
#5,936
of 7,287 outputs
Outputs of similar age
#186,979
of 277,499 outputs
Outputs of similar age from BMC Bioinformatics
#111
of 139 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 277,499 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.