Nadine Bachmann1,2, Katharina Kusejko1,2, Huyen Nguyen1,2, Sandra E Chaudron1,2, Claus Kadelka1,2, Teja Turk1,2, Jürg Böni2, Matthieu Perreau3, Thomas Klimkait4, Sabine Yerly5, Manuel Battegay6, Andri Rauch7, Alban Ramette7, Pietro Vernazza8, Enos Bernasconi9, Matthias Cavassini10, Huldrych F Günthard1,2, Roger D Kouyos1,2. 1. Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland. 2. University of Zurich, Institute of Medical Virology, Zurich, Switzerland. 3. Division of Immunology and Allergy, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland. 4. Molecular Virology, Department Biomedicine-Petersplatz, University of Basel, Basel, Switzerland. 5. Laboratory of Virology, Geneva University Hospital, Geneva, Switzerland. 6. Department of Infectious Diseases and Hospital Epidemiology, University Hospital Basel and University of Basel, Basel, Switzerland. 7. Institute for Infectious Diseases, Bern University Hospital and University of Bern, Bern, Switzerland. 8. Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital of St Gallen, St Gallen, Switzerland. 9. Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland. 10. Division of Infectious Diseases, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland.
Abstract
BACKGROUND: Identifying local outbreaks and their drivers is a key step toward curbing human immunodeficiency virus (HIV) transmission and potentially achieving HIV elimination. Such outbreaks can be identified as transmission clusters extracted from phylogenetic trees constructed of densely sampled viral sequences. In this study, we combined phylogenetic transmission clusters with extensive data on virological suppression and behavioral risk of cluster members to quantify the drivers of ongoing transmission over 10 years. METHODS: Using the comprehensive Swiss HIV Cohort Study and its drug-resistance database, we reconstructed phylogenetic trees for each year between 2007 and 2017. We identified HIV transmission clusters dominated by men who have sex with men (MSM) and determined their annual growth. We used Poisson regression to assess if cluster growth was associated with a per-cluster infectivity and behavioral risk score. RESULTS: Both infectivity and behavioral risk scores were significantly higher in growing MSM transmission clusters compared to nongrowing clusters (P ≤ .01). The fraction of transmission clusters without infectious members acquiring new infections increased significantly over the study period. The infectivity score was significantly associated with per-capita incidence of MSM transmission clusters in 8 years, while the behavioral risk score was significantly associated with per-capita incidence of MSM transmission clusters in 3 years. CONCLUSIONS: We present a phylogenetic method to identify hotspots of ongoing transmission among MSM. Our results demonstrate the effectiveness of treatment as prevention at the population level. However, the significantly increasing number of new infections among transmission clusters without infectious members highlights a relative shift from diagnosed to undiagnosed individuals as drivers of HIV transmission in Swiss MSM.
BACKGROUND: Identifying local outbreaks and their drivers is a key step toward curbing human immunodeficiency virus (HIV) transmission and potentially achieving HIV elimination. Such outbreaks can be identified as transmission clusters extracted from phylogenetic trees constructed of densely sampled viral sequences. In this study, we combined phylogenetic transmission clusters with extensive data on virological suppression and behavioral risk of cluster members to quantify the drivers of ongoing transmission over 10 years. METHODS: Using the comprehensive Swiss HIV Cohort Study and its drug-resistance database, we reconstructed phylogenetic trees for each year between 2007 and 2017. We identified HIV transmission clusters dominated by men who have sex with men (MSM) and determined their annual growth. We used Poisson regression to assess if cluster growth was associated with a per-cluster infectivity and behavioral risk score. RESULTS: Both infectivity and behavioral risk scores were significantly higher in growing MSM transmission clusters compared to nongrowing clusters (P ≤ .01). The fraction of transmission clusters without infectious members acquiring new infections increased significantly over the study period. The infectivity score was significantly associated with per-capita incidence of MSM transmission clusters in 8 years, while the behavioral risk score was significantly associated with per-capita incidence of MSM transmission clusters in 3 years. CONCLUSIONS: We present a phylogenetic method to identify hotspots of ongoing transmission among MSM. Our results demonstrate the effectiveness of treatment as prevention at the population level. However, the significantly increasing number of new infections among transmission clusters without infectious members highlights a relative shift from diagnosed to undiagnosed individuals as drivers of HIV transmission in Swiss MSM.
Authors: Luisa Salazar-Vizcaya; Katharina Kusejko; Huldrych F Günthard; Jürg Böni; Karin J Metzner; Dominique L Braun; Dunja Nicca; Enos Bernasconi; Alexandra Calmy; Katharine E A Darling; Gilles Wandeler; Roger D Kouyos; Andri Rauch Journal: Viruses Date: 2022-04-10 Impact factor: 5.818