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How robust are the natural history parameters used in chlamydia transmission dynamic models? A systematic review

Overview of attention for article published in Theoretical Biology and Medical Modelling, January 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 287)
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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2 policy sources
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5 X users

Citations

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22 Dimensions

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70 Mendeley
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Title
How robust are the natural history parameters used in chlamydia transmission dynamic models? A systematic review
Published in
Theoretical Biology and Medical Modelling, January 2014
DOI 10.1186/1742-4682-11-8
Pubmed ID
Authors

Bethan Davies, Sarah-Jane Anderson, Katy ME Turner, Helen Ward

Abstract

Transmission dynamic models linked to economic analyses often form part of the decision making process when introducing new chlamydia screening interventions. Outputs from these transmission dynamic models can vary depending on the values of the parameters used to describe the infection. Therefore these values can have an important influence on policy and resource allocation. The risk of progression from infection to pelvic inflammatory disease has been extensively studied but the parameters which govern the transmission dynamics are frequently neglected. We conducted a systematic review of transmission dynamic models linked to economic analyses of chlamydia screening interventions to critically assess the source and variability of the proportion of infections that are asymptomatic, the duration of infection and the transmission probability. We identified nine relevant studies in Pubmed, Embase and the Cochrane database. We found that there is a wide variation in their natural history parameters, including an absolute difference in the proportion of asymptomatic infections of 25% in women and 75% in men, a six-fold difference in the duration of asymptomatic infection and a four-fold difference in the per act transmission probability. We consider that much of this variation can be explained by a lack of consensus in the literature. We found that a significant proportion of parameter values were referenced back to the early chlamydia literature, before the introduction of nucleic acid modes of diagnosis and the widespread testing of asymptomatic individuals. In conclusion, authors should use high quality contemporary evidence to inform their parameter values, clearly document their assumptions and make appropriate use of sensitivity analysis. This will help to make models more transparent and increase their utility to policy makers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Switzerland 1 1%
Unknown 68 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 13%
Student > Master 8 11%
Other 7 10%
Student > Ph. D. Student 6 9%
Student > Doctoral Student 5 7%
Other 17 24%
Unknown 18 26%
Readers by discipline Count As %
Medicine and Dentistry 19 27%
Social Sciences 6 9%
Mathematics 5 7%
Nursing and Health Professions 4 6%
Agricultural and Biological Sciences 4 6%
Other 11 16%
Unknown 21 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 13 November 2018.
All research outputs
#3,615,891
of 22,741,406 outputs
Outputs from Theoretical Biology and Medical Modelling
#49
of 287 outputs
Outputs of similar age
#44,113
of 307,435 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#1
of 6 outputs
Altmetric has tracked 22,741,406 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done well, scoring higher than 82% 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 307,435 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 85% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them