Related Experiment Video
Updated: Mar 18, 2026
High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
Published on: July 25, 2014
Inferring HIV-1 Transmission Dynamics in Germany From Recently Transmitted Viruses
Kaveh Pouran Yousef1, Karolin Meixenberger, Maureen R Smith
1*Department of Mathematics and Computer Science, Systems Pharmacology and Disease Control, Freie Universität, Berlin, Germany; †Department of Infectious Diseases, FG18 HIV and Other Retroviruses, Robert Koch Institute, Berlin, Germany; ‡Department of Hazardous Substances and Biological Agents, Biological Agents, Federal Institute for Occupational Safety and Health, Berlin, Germany; §Department of Infectious Disease Epidemiology, FG34 HIV/AIDS, STI and Blood-Borne Infections, Robert Koch Institute, Berlin, Germany; and ‖Department of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.
Background:
Although HIV continues to spread globally, novel intervention strategies such as treatment as prevention (TasP) may bring the epidemic to a halt. However, their effective implementation requires a profound understanding of the underlying transmission dynamics.
Methods:
We analyzed parameters of the German HIV epidemic based on phylogenetic clustering of viral sequences from recently infected seroconverters with known infection dates. Viral baseline and follow-up pol sequences (n = 1943) from 1159 drug-naïve individuals were selected from a nationwide long-term observational study initiated in 1997. Putative transmission clusters were computed based on a maximum likelihood phylogeny. Using individual follow-up sequences, we optimized our clustering threshold to maximize the likelihood of co-clustering individuals connected by direct transmission.
Results:
The sizes of putative transmission clusters scaled inversely with their abundance and their distribution exhibited a heavy tail. Clusters based on the optimal clustering threshold were significantly more likely to contain members of the same or bordering German federal states. Interinfection times between co-clustered individuals were significantly shorter (26 weeks; interquartile range: 13-83) than in a null model.
Conclusions:
Viral intraindividual evolution may be used to select criteria that maximize co-clustering of transmission pairs in the absence of strong adaptive selection pressure. Interinfection times of co-clustered individuals may then be an indicator of the typical time to onward transmission. Our analysis suggests that onward transmission may have occurred early after infection, when individuals are typically unaware of their serological status. The latter argues that TasP should be combined with HIV testing campaigns to reduce the possibility of transmission before TasP initiation.
