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Approaches to Refining Estimates of Global Burden and Economics of Dengue

Overview of attention for article published in PLoS Neglected Tropical Diseases, November 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)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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14 X users
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3 Facebook pages

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340 Mendeley
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Article details
Title
Approaches to Refining Estimates of Global Burden and Economics of Dengue
Published in
PLoS Neglected Tropical Diseases, November 2014
DOI 10.1371/journal.pntd.0003306
Pubmed ID
Authors
Abstract

Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 340 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 3 <1%
Mexico 2 <1%
United Kingdom 2 <1%
Brazil 2 <1%
Singapore 1 <1%
Portugal 1 <1%
Japan 1 <1%
India 1 <1%
Indonesia 1 <1%
Other 1 <1%
Unknown 325 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 55 16%
Researcher 46 14%
Student > Ph. D. Student 41 12%
Student > Bachelor 38 11%
Student > Doctoral Student 21 6%
Other 53 16%
Unknown 86 25%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 78 23%
Agricultural and Biological Sciences 47 14%
Biochemistry, Genetics and Molecular Biology 28 8%
Nursing and Health Professions 17 5%
Immunology and Microbiology 17 5%
Other 63 19%
Unknown 90 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 12 December 2014.
All research outputs
#3,894,376
of 31,758,295 outputs
Outputs from PLoS Neglected Tropical Diseases
#2,398
of 10,621 outputs
Outputs of similar age
#44,986
of 402,838 outputs
Outputs of similar age from PLoS Neglected Tropical Diseases
#35
of 167 outputs
Altmetric has tracked 31,758,295 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,621 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has done well, scoring higher than 76% 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 402,838 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 167 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.