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Vector-Borne Disease Intelligence: Strategies to Deal with Disease Burden and Threats

Overview of attention for article published in Frontiers in Public Health, December 2014
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

policy
2 policy sources
twitter
10 X users
facebook
1 Facebook page

Citations

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40 Dimensions

Readers on

mendeley
102 Mendeley
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Title
Vector-Borne Disease Intelligence: Strategies to Deal with Disease Burden and Threats
Published in
Frontiers in Public Health, December 2014
DOI 10.3389/fpubh.2014.00280
Pubmed ID
Authors

Marieta Braks, Jolyon M. Medlock, Zdenek Hubalek, Marika Hjertqvist, Yvon Perrin, Renaud Lancelot, Els Duchyene, Guy Hendrickx, Arjan Stroo, Paul Heyman, Hein Sprong

Abstract

Owing to the complex nature of vector-borne diseases (VBDs), whereby monitoring of human case patients does not suffice, public health authorities experience challenges in surveillance and control of VBDs. Knowledge on the presence and distribution of vectors and the pathogens that they transmit is vital to the risk assessment process to permit effective early warning, surveillance, and control of VBDs. Upon accepting this reality, public health authorities face an ever-increasing range of possible surveillance targets and an associated prioritization process. Here, we propose a comprehensive approach that integrates three surveillance strategies: population-based surveillance, disease-based surveillance, and context-based surveillance for EU member states to tailor the best surveillance strategy for control of VBDs in their geographic region. By classifying the surveillance structure into five different contexts, we hope to provide guidance in optimizing surveillance efforts. Contextual surveillance strategies for VBDs entail combining organization and data collection approaches that result in disease intelligence rather than a preset static structure.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 <1%
United States 1 <1%
Netherlands 1 <1%
Australia 1 <1%
Unknown 98 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 21%
Student > Master 16 16%
Student > Ph. D. Student 14 14%
Student > Bachelor 7 7%
Student > Doctoral Student 6 6%
Other 21 21%
Unknown 17 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 19%
Veterinary Science and Veterinary Medicine 16 16%
Medicine and Dentistry 15 15%
Environmental Science 8 8%
Biochemistry, Genetics and Molecular Biology 6 6%
Other 22 22%
Unknown 16 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 20 October 2022.
All research outputs
#2,750,209
of 23,555,482 outputs
Outputs from Frontiers in Public Health
#1,077
of 11,240 outputs
Outputs of similar age
#39,247
of 356,690 outputs
Outputs of similar age from Frontiers in Public Health
#9
of 60 outputs
Altmetric has tracked 23,555,482 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,240 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done particularly well, scoring higher than 90% 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 356,690 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 88% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.