+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'



Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'



Statistical Communications in Infectious Diseases 9(1):



The application of biomarkers for 'recent' infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) - the average time in the 'recent' state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the 'recent' state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best - while 'random effects' describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing 'recent'/'non-recent' classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects' (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.

Please choose payment method:






(PDF emailed within 1 workday: $29.90)

Accession: 057280449

Download citation: RISBibTeXText

PMID: 29527254


Related references

Estimating the incidence of hiv infection using cross sectional marker surveys. Viii International Conference on Aids And The Iii Std World Congress Viii International Conference on Aids And The Iii Std World Congress; Harvard-Amsterdam Conference, Amsterdam, Netherlands, July 19-24, Pagination Varies Viii International Conference on Aids And The Iii Std World Congress: Amsterdam, Netherlands Paper : c325, 1992

Estimating HIV Incidence Using a Cross-Sectional Survey: Comparison of Three Approaches in a Hyperendemic Setting, Ndhiwa Subcounty, Kenya, 2012. Aids Research and Human Retroviruses 33(5): 472-481, 2017

Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data. Plos Medicine 8(10): E1001103, 2011

A Simplified Formula for Inferring HIV Incidence from Cross-Sectional Surveys Using a Test for Recent Infection. Aids Research and Human Retroviruses 25(1): 125-126, 2009

Intestinal parasites in a rural community in Kenya: cross-sectional surveys with emphasis on prevalence, incidence, duration of infection, and polyparasitism. East African Medical Journal 68(2): 112-123, 1991

Specificity of four laboratory approaches for cross-sectional HIV incidence determination: analysis of samples from adults with known nonrecent HIV infection from five African countries. Aids Research and Human Retroviruses 28(10): 1177-1183, 2012

HIV type 1 incidence estimates by detection of recent infection from a cross-sectional sampling of injection drug users in Bangkok: use of the IgG capture BED enzyme immunoassay. Aids Research and Human Retroviruses 19(9): 727-730, 2003

Estimating Disease Duration in Cross-sectional Surveys. Epidemiology 26(6): 839-845, 2015

Estimating cholera incidence with cross-sectional serology. Science Translational Medicine 11(480):, 2019

Augmented cross-sectional prevalence testing for estimating HIV incidence. Biometrics 66(3): 864-874, 2010

Sample size methods for estimating HIV incidence from cross-sectional surveys. Biometrics 71(4): 1121-1129, 2015

Augmented cross-sectional studies with abbreviated follow-up for estimating HIV incidence. Biometrics 68(1): 62-74, 2012

Implementation of multimodal infection control and hand hygiene strategies in acute-care hospitals in Greece: A cross-sectional benchmarking survey. American Journal of Infection Control 46(10): 1097-1103, 2018

Estimating HIV Incidence for Identification of Microbicide Trial Sites in India: A Cross-sectional Study. Aids Research and Human Retroviruses 30(S1): A215-A215, 2014

Estimating the incidence rate ratio in cross-sectional studies using a simple alternative to logistic regression. Annals Of Epidemiology. 8(1): 52-55,., 1998