↓ Skip to main content

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

Overview of attention for article published in Frontiers in Veterinary Science, September 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
12 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
49 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health
Published in
Frontiers in Veterinary Science, September 2017
DOI 10.3389/fvets.2017.00155
Pubmed ID
Authors

Rebecca Mancy, Patrick M. Brock, Rowland R. Kao

Abstract

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Researcher 9 18%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Student > Bachelor 3 6%
Other 5 10%
Unknown 13 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 24%
Veterinary Science and Veterinary Medicine 9 18%
Computer Science 3 6%
Medicine and Dentistry 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 7 14%
Unknown 13 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 November 2017.
All research outputs
#4,325,721
of 24,625,114 outputs
Outputs from Frontiers in Veterinary Science
#763
of 7,511 outputs
Outputs of similar age
#71,750
of 325,214 outputs
Outputs of similar age from Frontiers in Veterinary Science
#18
of 67 outputs
Altmetric has tracked 24,625,114 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,511 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done well, scoring higher than 89% 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 325,214 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 77% of its contemporaries.
We're also able to compare this research output to 67 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 74% of its contemporaries.