Estimating HIV Incidence from Changes in HIV Prevalence

• Activity Number: 139
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Jacob Konikoff*+ and Ron Brookmeyer
• Companies: and University of California at Los Angeles
• Keywords: HIV epidemiology ; incidence ; prevalence ; sample size

Abstract

Methods for estimating HIV incidence are critical for tracking the epidemic and evaluating HIV prevention efforts. We consider statistical issues with estimating HIV incidence from changes in HIV prevalence from two population-based surveys conducted at two points in time. We determine needed sample sizes of prevalence surveys to precisely estimate incidence. If the baseline prevalence is large, the relative survival rate is near 1, or the population incidence is small, prohibitively large prevalence surveys are required to produce reliable estimates. We evaluate the sensitivity of estimates to incorrect assumptions about the relative survival rate, and show how small errors can create large biases. Because information on the relative survival rate may be limited, we suggest a method of empirically estimating this critical parameter by augmenting the prevalence surveys with a mortality follow-up sub-study. We determine the necessary sample sizes for this augmented design. We conclude that using changes in prevalence to determine HIV incidence must be done cautiously because of the method's sensitivity to mortality assumptions and the potential need for large sample sizes.