Human Immunodeficiency Virus (HIV)-1 Transmission Among Persons With Acute HIV-1 Infection in Malawi: Demographic, Behavioral, and Phylogenetic Relationships

Using HIV and Hepatitis C Molecular Epidemiology to Investigate Assisted Partner Services Recruitment Among People Who Inject Drugs in Kenya

Sexual and/or injecting partners of people who inject drugs (PWID) may have an elevated risk of HIV infection either from sharing a transmission network or an epidemiological environment. We estimated the degree of similarity between HIV and hepatitis C (HCV) sequences from PWID and their partners to assess whether partner-based recruitment identifies sexual or injecting partners within transmission networks. We used assisted partner services (APS) to recruit sexual and injecting partners of PWID living with HIV in Kenya and evaluated trends in the TN93 distances (an adjusted measure of sequence similarity) of the HIV-1 and HCV sequences from partner pairs. Of 135 unique pairs identified, 2 sexual, 2 injecting, and 3 unique sexual and injecting partner pairs had HIV sequences within a TN93 distance of 0.045, and 4 unique partner pairs had HCV sequences with distances <0.015. Sexual but not injecting partner pairs had HIV sequences with significantly smaller distances than non-partners, on average, but injecting partner pairs did have significantly smaller HCV-4a patristic distances than non-partners. APS recruitment partly reflects the HIV transmission network among sexual, but not injecting, partners of PWID. The relationship between the injecting partner recruitment and molecular networks is stronger for HCV than HIV and may reflect some recent parenteral HCV transmission. Our results show the importance of continued focus on reducing sexual HIV transmission among PWID and on education and services to address HCV transmission through needle- and/or equipment-sharing.

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

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.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.