Augmented Cross-Sectional Studies with Abbreviated Follow-Up for Estimating HIV Incidence

• Activity Number: 257
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Brian Claggett*+
• Companies: Harvard School of Public Health
• Keywords: Augmented ; cross-sectional studies ; incidence estimators ; HIV incidence

Abstract

Within the context of estimating HIV incidence through the use of augmented cross-sectional design, we generalize the work of Wang and Lagakos (2009a) by allowing the length of follow-up to vary and propose a new estimator based on abbreviated follow-up time (AF). We show earlier estimators to be MLEs derived from special cases of a more general likelihood function and assess the robustness of the estimators to the underlying assumptions. The AF estimator requires shorter follow-up time than the original estimator based on the augmented design, and does not require the estimation of the mean window period. The AF estimator is shown to have good performance in a wide range of settings. We provide guidance on when the AF estimator would be expected to perform well as well as design considerations for an augmented cross-sectional study with abbreviated follow-up.