Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An Example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era

Abstract

Mixed methods studies of human disease that combine surveillance, biomarker, and qualitative data can help elucidate what drives epidemiological trends. Viral genetic data are rarely coupled with other types of data due to legal and ethical concerns about patient privacy. We developed a novel approach to integrate phylogenetic and qualitative methods in order to better target HIV prevention efforts. The overall aim of our mixed methods study was to characterize HIV transmission clusters. We combined surveillance data with HIV genomic data to identify cases whose viruses share enough similarities to suggest a recent common source of infection or participation in linked transmission chains. Cases were recruited through a multi-phase process to obtain consent for recruitment to semi-structured interviews. Through linkage of viral genetic sequences with epidemiological data, we identified individuals in large transmission clusters, which then served as a sampling frame for the interviews. In this article, we describe the multi-phase process and the limitations and challenges encountered. Our approach contributes to the mixed methods research field by demonstrating that phylogenetic analysis and surveillance data can be harnessed to generate a sampling frame for subsequent qualitative data collection, using an explanatory sequential design. The process we developed also respected protections of patient confidentiality. The novel method we devised may offer an opportunity to implement a sampling frame that allows for the recruitment and interview of individuals in high-transmission clusters to better understand what contributes to spread of other infectious diseases, including COVID-19.