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Integrating vector control across diseases

Overview of attention for article published in BMC Medicine, October 2015
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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 (91st percentile)

Mentioned by

policy
1 policy source
twitter
23 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
181 Mendeley
Title
Integrating vector control across diseases
Published in
BMC Medicine, October 2015
DOI 10.1186/s12916-015-0491-4
Pubmed ID
Authors

Nick Golding, Anne L. Wilson, Catherine L. Moyes, Jorge Cano, David M. Pigott, Raman Velayudhan, Simon J. Brooker, David L. Smith, Simon I. Hay, Steve W. Lindsay

Abstract

Vector-borne diseases cause a significant proportion of the overall burden of disease across the globe, accounting for over 10 % of the burden of infectious diseases. Despite the availability of effective interventions for many of these diseases, a lack of resources prevents their effective control. Many existing vector control interventions are known to be effective against multiple diseases, so combining vector control programmes to simultaneously tackle several diseases could offer more cost-effective and therefore sustainable disease reductions. The highly successful cross-disease integration of vaccine and mass drug administration programmes in low-resource settings acts a precedent for cross-disease vector control. Whilst deliberate implementation of vector control programmes across multiple diseases has yet to be trialled on a large scale, a number of examples of 'accidental' cross-disease vector control suggest the potential of such an approach. Combining contemporary high-resolution global maps of the major vector-borne pathogens enables us to quantify overlap in their distributions and to estimate the populations jointly at risk of multiple diseases. Such an analysis shows that over 80 % of the global population live in regions of the world at risk from one vector-borne disease, and more than half the world's population live in areas where at least two different vector-borne diseases pose a threat to health. Combining information on co-endemicity with an assessment of the overlap of vector control methods effective against these diseases allows us to highlight opportunities for such integration. Malaria, leishmaniasis, lymphatic filariasis, and dengue are prime candidates for combined vector control. All four of these diseases overlap considerably in their distributions and there is a growing body of evidence for the effectiveness of insecticide-treated nets, screens, and curtains for controlling all of their vectors. The real-world effectiveness of cross-disease vector control programmes can only be evaluated by large-scale trials, but there is clear evidence of the potential of such an approach to enable greater overall health benefit using the limited funds available.

Twitter Demographics

The data shown below were collected from the profiles of 23 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 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Brazil 2 1%
United Kingdom 1 <1%
Australia 1 <1%
Unknown 175 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 46 25%
Researcher 41 23%
Student > Ph. D. Student 22 12%
Student > Bachelor 20 11%
Unspecified 19 10%
Other 33 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 49 27%
Medicine and Dentistry 39 22%
Unspecified 23 13%
Environmental Science 17 9%
Nursing and Health Professions 12 7%
Other 41 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 01 January 2017.
All research outputs
#786,039
of 13,526,749 outputs
Outputs from BMC Medicine
#663
of 2,143 outputs
Outputs of similar age
#20,275
of 248,826 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 13,526,749 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,143 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.0. This one has gotten more attention than average, scoring higher than 69% 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 248,826 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them