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Combining Fungal Biopesticides and Insecticide-Treated Bednets to Enhance Malaria Control

Overview of attention for article published in PLoS Computational Biology, October 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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1 blog
twitter
1 X user
facebook
1 Facebook page

Citations

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40 Dimensions

Readers on

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119 Mendeley
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Title
Combining Fungal Biopesticides and Insecticide-Treated Bednets to Enhance Malaria Control
Published in
PLoS Computational Biology, October 2009
DOI 10.1371/journal.pcbi.1000525
Pubmed ID
Authors

Penelope A. Hancock

Abstract

In developing strategies to control malaria vectors, there is increased interest in biological methods that do not cause instant vector mortality, but have sublethal and lethal effects at different ages and stages in the mosquito life cycle. These techniques, particularly if integrated with other vector control interventions, may produce substantial reductions in malaria transmission due to the total effect of alterations to multiple life history parameters at relevant points in the life-cycle and transmission-cycle of the vector. To quantify this effect, an analytically tractable gonotrophic cycle model of mosquito-malaria interactions is developed that unites existing continuous and discrete feeding cycle approaches. As a case study, the combined use of fungal biopesticides and insecticide treated bednets (ITNs) is considered. Low values of the equilibrium EIR and human prevalence were obtained when fungal biopesticides and ITNs were combined, even for scenarios where each intervention acting alone had relatively little impact. The effect of the combined interventions on the equilibrium EIR was at least as strong as the multiplicative effect of both interventions. For scenarios representing difficult conditions for malaria control, due to high transmission intensity and widespread insecticide resistance, the effect of the combined interventions on the equilibrium EIR was greater than the multiplicative effect, as a result of synergistic interactions between the interventions. Fungal biopesticide application was found to be most effective when ITN coverage was high, producing significant reductions in equilibrium prevalence for low levels of biopesticide coverage. By incorporating biological mechanisms relevant to vectorial capacity, continuous-time vector population models can increase their applicability to integrated vector management.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Germany 1 <1%
Netherlands 1 <1%
France 1 <1%
Portugal 1 <1%
Brazil 1 <1%
Australia 1 <1%
Spain 1 <1%
United States 1 <1%
Other 0 0%
Unknown 109 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 20%
Researcher 24 20%
Student > Master 15 13%
Professor > Associate Professor 7 6%
Student > Doctoral Student 7 6%
Other 22 18%
Unknown 20 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 39%
Medicine and Dentistry 15 13%
Social Sciences 7 6%
Environmental Science 4 3%
Mathematics 4 3%
Other 13 11%
Unknown 30 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 04 March 2013.
All research outputs
#4,235,368
of 25,411,814 outputs
Outputs from PLoS Computational Biology
#3,475
of 8,976 outputs
Outputs of similar age
#16,472
of 106,561 outputs
Outputs of similar age from PLoS Computational Biology
#17
of 53 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,976 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 61% 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 106,561 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 53 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 67% of its contemporaries.