Estimation of Phylogenetic Clustering Rates in the Presence of Missing Data

• Activity Number: 320
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Nicole Carnegie*+ and Rui Wang and Victor DeGruttola and Vladimir Novitsky
• Companies: Harvard University and Harvard School of Public Health and Harvard University and Harvard School of Public Health
• Keywords: Genetic linkage ; phylogenetic clustering ; HIV

Abstract

HIV genetic linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them. Estimates of probabilities of genetic linkage between infected people in different groups based on observed data can be biased downward in the presence of informative missingness; we develop an approach to adjust for this bias.

We first show that the probability that randomly selected sequences are linked can be estimated consistently from observed data. We then develop maximum likelihood estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across dyads. Recognizing that the independence assumption is likely to be violated, we further develop a resampling approach that adjusts for the presence of correlation within individuals, and provide diagnostics for assessing the reliability of the method.

We apply the methods to investigate whether rates at which subjects' HIV genotypes link to others depends on their viral load levels (low/high) or ART status using samples from a household survey in Mochudi, Botswana.