Viral Genetic Linkage Analyses in the Presence of Missing Data

Viral genetic linkage based on data from HIV prevention trials at the community level can provide insight into HIV transmission dynamics and the impact of prevention interventions. Analyses of clustering which utilize phylogenetic methods have the potential to inform whether recently-infected individuals are infected by viruses circulating within or outside a community. In addition, they have the potential to identify characteristics of chronically infected individuals that make their viruses likely to cluster with others circulating within a community. Such clustering can be related to the potential of such individuals to contribute to the spread of the virus, either directly through transmission to their partners or indirectly through further spread of HIV from those partners. Assessment of the extent to which individual (incident or prevalent) viruses are clustered within a community will be biased if only a subset of subjects are observed, especially if that subset is not representative of the entire HIV infected population. To address this concern, we develop a multiple imputation framework in which missing sequences are imputed based on a biological model for the diversification of viral genomes. Data from a household survey conducted in a village in Botswana are used to illustrate these methods.