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Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

Overview of attention for article published in International Journal of Health Geographics, December 2011
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1 Google+ user

Citations

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81 Dimensions

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239 Mendeley
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Title
Spatially explicit multi-criteria decision analysis for managing vector-borne diseases
Published in
International Journal of Health Geographics, December 2011
DOI 10.1186/1476-072x-10-70
Pubmed ID
Authors

Valerie Hongoh, Anne Gatewood Hoen, Cécile Aenishaenslin, Jean-Philippe Waaub, Denise Bélanger, Pascal Michel, The Lyme-MCDA Consortium

Abstract

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 239 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Tanzania, United Republic of 2 <1%
Brazil 2 <1%
Switzerland 1 <1%
Australia 1 <1%
France 1 <1%
Sweden 1 <1%
India 1 <1%
Canada 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 227 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 18%
Researcher 41 17%
Student > Master 37 15%
Other 23 10%
Professor > Associate Professor 13 5%
Other 41 17%
Unknown 42 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 14%
Environmental Science 31 13%
Engineering 25 10%
Medicine and Dentistry 24 10%
Veterinary Science and Veterinary Medicine 15 6%
Other 56 23%
Unknown 54 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 February 2012.
All research outputs
#16,046,765
of 25,373,627 outputs
Outputs from International Journal of Health Geographics
#416
of 654 outputs
Outputs of similar age
#163,007
of 249,539 outputs
Outputs of similar age from International Journal of Health Geographics
#9
of 14 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 654 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one is in the 33rd percentile – i.e., 33% 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 249,539 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.