↓ Skip to main content

How Should We Best Estimate the Mean Recency Duration for the BED Method?

Overview of attention for article published in PLOS ONE, November 2012
Altmetric Badge

Mentioned by

twitter
1 X user
facebook
1 Facebook page

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
21 Mendeley
citeulike
1 CiteULike
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
How Should We Best Estimate the Mean Recency Duration for the BED Method?
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049661
Pubmed ID
Authors

John Hargrove, Hayden Eastwood, Guy Mahiane, Cari van Schalkwyk

Abstract

BED estimates of HIV incidence from cross-sectional surveys are obtained by restricting, to fixed time T, the period over which incidence is estimated. The appropriate mean recency duration (Ω(T)) then refers to the time where BED optical density (OD) is less than a pre-set cut-off C, given the patient has been HIV positive for at most time T. Five methods, tested using data for postpartum women in Zimbabwe, provided similar estimates of Ω(T) for C = 0.8: i) The ratio (r/s) of the number of BED-recent infections to all seroconversions over T = 365 days: 192 days [95% CI 168-216]. ii) Linear mixed modeling (LMM): 191 days [95% CI 174-208]. iii) Non-linear mixed modeling (NLMM): 196 days [95% CrI 188-204]. iv) Survival analysis (SA): 192 days [95% CI 168-216]. Graphical analysis: 193 days. NLMM estimates of Ω(T)--based on a biologically more appropriate functional relationship than LMM--resulted in best fits to OD data, the smallest variance in estimates of VT, and best correspondence between BED and follow-up estimates of HIV incidence, for the same subjects over the same time period. SA and NLMM produced very similar estimates of Ω(T) but the coefficient of variation of the former was .3 times as high. The r/s method requires uniformly distributed seroconversion events but is useful if data are available only from a single follow-up. The graphical method produces the most variable results, involves unsound methodology and should not be used to provide estimates of Ω(T). False-recent rates increased as a quadratic function of C: for incidence estimation C should thus be chosen as small as possible, consistent with an adequate resultant number of recent cases, and accurate estimation of Ω(T). Inaccuracies in the estimation of Ω(T) should not now provide an impediment to incidence estimation.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 43%
Student > Master 5 24%
Student > Ph. D. Student 3 14%
Lecturer 1 5%
Student > Postgraduate 1 5%
Other 0 0%
Unknown 2 10%
Readers by discipline Count As %
Medicine and Dentistry 7 33%
Mathematics 2 10%
Business, Management and Accounting 2 10%
Nursing and Health Professions 2 10%
Agricultural and Biological Sciences 2 10%
Other 3 14%
Unknown 3 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 December 2012.
All research outputs
#17,670,751
of 22,685,926 outputs
Outputs from PLOS ONE
#146,339
of 193,650 outputs
Outputs of similar age
#116,423
of 159,110 outputs
Outputs of similar age from PLOS ONE
#3,263
of 4,755 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,650 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 20th percentile – i.e., 20% 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 159,110 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4,755 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.