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

Dados Bibliográficos

ID12811751
AutoresShana D Hughes (0000-0002-1388-4103, University of California, San Francisco), William J Woods (0000-0002-7036-4155, University of California, San Francisco, autor correspondente), Kara J O’Keefe (San Francisco Department of Public Health), Viva Delgado (0000-0002-2609-4178, San Francisco Department of Public Health), Sharon Pipkin (San Francisco Department of Public Health), Susan Scheer (0000-0003-1060-3027, San Francisco Department of Public Health), Hong‐ha M Truong (0009-0001-0310-8872, University of California, San Francisco)
Ano2021
Volume15
Fascículo3
Páginas327-347
Data de publicação2021-05-08
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoJournal of Mixed Methods Research (JOURNAL)
Identificadores do periódicoISSN: 1558-6898 • E-ISSN: 1558-6901
EditoraSAGE Publishing (PUBLISHER • US)
DOI10.1177/15586898211012786
PMID38883973
OpenAlexW3161168872
IdiomaEN
Citações recebidas3
Referências citadas64

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

Computer security · Confidentiality · Data collection · Data mining · Data science · Environmental health · Machine learning · Population · Qualitative property · Qualitative research · Sampling (signal processing · Sampling frame · Statistics · Transmission (telecommunications · Computer Science · Data-Driven Disease Surveillance · HIV, Drug Use, Sexual Risk · Immune responses and vaccinations · Medicine