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Antipathogen genes and the replacement of disease‐vectoring mosquito populations: a model‐based evaluation

Overview of attention for article published in Evolutionary Applications, October 2014
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Title
Antipathogen genes and the replacement of disease‐vectoring mosquito populations: a model‐based evaluation
Published in
Evolutionary Applications, October 2014
DOI 10.1111/eva.12219
Pubmed ID
Authors

Michael A Robert, Kenichi W Okamoto, Fred Gould, Alun L Lloyd

Abstract

Recently, genetic strategies aimed at controlling populations of disease-vectoring mosquitoes have received considerable attention as alternatives to traditional measures. Theoretical studies have shown that female-killing (FK), antipathogen (AP), and reduce and replace (R&R) strategies can each decrease the number competent vectors. In this study, we utilize a mathematical model to evaluate impacts on competent Aedes aegypti populations of FK, AP, and R&R releases as well as hybrid strategies that result from combinations of these three approaches. We show that while the ordering of efficacy of these strategies depends upon population life history parameters, sex ratio of releases, and switch time in combination strategies, AP-only and R&R/AP releases typically lead to the greatest long-term reduction in competent vectors. R&R-only releases are often less effective at long-term reduction of competent vectors than AP-only releases or R&R/AP releases. Furthermore, the reduction in competent vectors caused by AP-only releases is easier to maintain than that caused by FK-only or R&R-only releases even when the AP gene confers a fitness cost. We discuss the roles that density dependence and inclusion of females play in the order of efficacy of the strategies. We anticipate that our results will provide added impetus to continue developing AP strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 6%
United States 2 4%
Sweden 1 2%
Brazil 1 2%
Unknown 42 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Researcher 11 22%
Student > Bachelor 7 14%
Student > Master 3 6%
Student > Doctoral Student 2 4%
Other 7 14%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 39%
Medicine and Dentistry 6 12%
Environmental Science 5 10%
Biochemistry, Genetics and Molecular Biology 5 10%
Economics, Econometrics and Finance 2 4%
Other 6 12%
Unknown 6 12%
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 02 December 2014.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Evolutionary Applications
#1,503
of 1,578 outputs
Outputs of similar age
#229,395
of 268,351 outputs
Outputs of similar age from Evolutionary Applications
#21
of 21 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.