An Approach to Quantifying the Interaction between Behavioral and Transmission Clusters.
Luisa Salazar-VizcayaKatharina KusejkoHuldrych F GunthardKatharina KusejkoKarin J MetznerDominique L BraunDunja NiccaEnos BernasconiAlexandra CalmyKatharine E A DarlingGilles WandelerRoger D KouyosAndri Rauchnull The Swiss Hiv Cohort StudyPublished in: Viruses (2022)
We hypothesize that patterns of sexual behavior play a role in the conformation of transmission networks, i.e., the way you behave might influence whom you have sex with. If that was the case, behavioral grouping might in turn correlate with, and potentially predict transmission networking, e.g., proximity in a viral phylogeny. We rigorously present an intuitive approach to address this hypothesis by quantifying mapped interactions between groups defined by similarities in sexual behavior along a virus phylogeny while discussing power and sample size considerations. Data from the Swiss HIV Cohort Study on condom use and hepatitis C virus (HCV) sequences served as proof-of-concept. In this case, a strict inclusion criteria contrasting with low HCV prevalence hindered our possibilities to identify significant relationships. This manuscript serves as guide for studies aimed at characterizing interactions between behavioral patterns and transmission networks. Large transmission networks such as those of HIV or COVID-19 are prime candidates for applying this methodological approach.
Keyphrases
- hepatitis c virus
- human immunodeficiency virus
- antiretroviral therapy
- sars cov
- hiv infected
- hiv positive
- coronavirus disease
- hiv testing
- men who have sex with men
- hiv aids
- mental health
- molecular dynamics simulations
- electronic health record
- big data
- sensitive detection
- south africa
- artificial intelligence
- data analysis
- living cells
- deep learning
- single molecule
- respiratory syndrome coronavirus