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Hotspots of Transmission Driving the Local Human Immunodeficiency Virus Epidemic in the Cologne-Bonn Region, Germany.

  • Author(s): Stecher, Melanie
  • Hoenigl, Martin
  • Eis-Hübinger, Anna Maria
  • Lehmann, Clara
  • Fätkenheuer, Gerd
  • Wasmuth, Jan-Christian
  • Knops, Elena
  • Vehreschild, Jörg Janne
  • Mehta, Sanjay
  • Chaillon, Antoine
  • et al.

Published Web Location

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481988/
No data is associated with this publication.
Abstract

Background

Geographical allocation of interventions focusing on hotspots of human immunodeficiency virus (HIV) transmission has the potential to improve efficiency. We used phylogeographic analyses to identify hotspots of the HIV transmission in Cologne-Bonn, Germany.

Methods

We included 714 HIV-1 infected individuals, followed up at the University Hospitals Cologne and Bonn. Distance-based molecular network analyses were performed to infer putative relationships. Characteristics of genetically linked individuals and assortativity (shared characteristics) were analyzed. Geospatial diffusion (ie, viral gene flow) was evaluated using a Slatkin-Maddison approach. Geospatial dispersal was determined by calculating the average distance between the residences of linked individuals (centroids of 3-digit zip code).

Results

In sum, 217/714 (30.4%) sequences had a putative genetic linkage, forming 77 clusters (size range: 2-8). Linked individuals were more likely to live in areas surrounding the city center (P = .043), <30 years of age (P = .009). and infected with HIV-1 subtype B (P = .002). Clustering individuals were nonassortative by area of residency (-.0026, P = .046). Geospatial analyses revealed a median distance between genetically linked individuals of 23.4 kilometers (km), lower than expected (P < .001). Slatkin-Maddison analyses revealed increased gene flow from central Cologne toward the surrounding areas (P < .001).

Conclusion

Phylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. Although clustering individuals lived closer than unlinked individuals, they were less likely to be linked to others from their same zip code. These results could help public health entities better understand transmission dynamics, facilitating allocation of resources to areas of greatest need.

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