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Spatiotemporal dynamics of HIV-1 transmission in France (1999–2014) and impact of targeted prevention strategies

Published Web Location

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322782/
No data is associated with this publication.
Creative Commons 'BY-ND' version 4.0 license
Abstract

Background

Characterizing HIV-1 transmission networks can be important in understanding the evolutionary patterns and geospatial spread of the epidemic. We reconstructed the broad molecular epidemiology of HIV from individuals with primary HIV-1 infection (PHI) enrolled in France in the ANRS PRIMO C06 cohort over 15 years.

Results

Sociodemographic, geographic, clinical, biological and pol sequence data from 1356 patients were collected between 1999 and 2014. Network analysis was performed to infer genetic relationships, i.e. clusters of transmission, between HIV-1 sequences. Bayesian coalescent-based methods were used to examine the temporal and spatial dynamics of identified clusters from different regions in France. We also evaluated the use of network information to target prevention efforts. Participants were mostly Caucasian (85.9%) and men (86.7%) who reported sex with men (MSM, 71.4%). Overall, 387 individuals (28.5%) were involved in clusters: 156 patients (11.5%) in 78 dyads and 231 participants (17%) in 42 larger clusters (median size: 4, range 3-41). Compared to individuals with single PHI (n = 969), those in clusters were more frequently men (95.9 vs 83%, p < 0.01), MSM (85.8 vs 65.6%, p < 0.01) and infected with CRF02_AG (20.4 vs 13.4%, p < 0.01). Reconstruction of viral migrations across time suggests that Paris area was the major hub of dissemination of both subtype B and CRF02_AG epidemics. By targeting clustering individuals belonging to the identified active transmission network before 2010, 60 of the 143 onward transmissions could have been prevented.

Conclusion

These analyses support the hypothesis of a recent and rapid rise of CRF02_AG within the French HIV-1 epidemic among MSM. Combined with a short turnaround time for sample processing, targeting prevention efforts based on phylogenetic monitoring may be an efficient way to deliver prevention interventions but would require near real time targeted interventions on the identified index cases and their partners.

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