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Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions

Overview of attention for article published in Population Health Metrics, May 2016
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  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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8 X users

Citations

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77 Dimensions

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156 Mendeley
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Title
Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions
Published in
Population Health Metrics, May 2016
DOI 10.1186/s12963-016-0085-1
Pubmed ID
Authors

Adam D. M. Briggs, Jane Wolstenholme, Tony Blakely, Peter Scarborough

Abstract

Non-communicable diseases are the leading global causes of mortality and morbidity. Growing pressures on health services and on social care have led to increasing calls for a greater emphasis to be placed on prevention. In order for decisionmakers to make informed judgements about how to best spend finite public health resources, they must be able to quantify the anticipated costs, benefits, and opportunity costs of each prevention option available. This review presents a taxonomy of epidemiological model structures and applies it to the economic evaluation of public health interventions for non-communicable diseases. Through a novel discussion of the pros and cons of model structures and examples of their application to public health interventions, it suggests that individual-level models may be better than population-level models for estimating the effects of population heterogeneity. Furthermore, model structures allowing for interactions between populations, their environment, and time are often better suited to complex multifaceted interventions. Other influences on the choice of model structure include time and available resources, and the availability and relevance of previously developed models. This review will help guide modelers in the emerging field of public health economic modeling of non-communicable diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
United States 2 1%
Chile 1 <1%
Unknown 151 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 18%
Student > Ph. D. Student 25 16%
Student > Master 20 13%
Student > Bachelor 9 6%
Student > Doctoral Student 8 5%
Other 26 17%
Unknown 40 26%
Readers by discipline Count As %
Medicine and Dentistry 35 22%
Economics, Econometrics and Finance 13 8%
Nursing and Health Professions 11 7%
Engineering 10 6%
Social Sciences 7 4%
Other 32 21%
Unknown 48 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 09 May 2018.
All research outputs
#6,535,413
of 23,798,792 outputs
Outputs from Population Health Metrics
#187
of 391 outputs
Outputs of similar age
#89,854
of 300,677 outputs
Outputs of similar age from Population Health Metrics
#6
of 12 outputs
Altmetric has tracked 23,798,792 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 391 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 52% 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 300,677 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 12 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 58% of its contemporaries.