Hotspots of Transmission Driving the Local Hiv Epidemic in the Cologne-Bonn Region, Germany. Stecher, M., Hoenigl, M., Eis-Hübinger, A. M., Lehmann, C., Fätkenheuer, G., Wasmuth, J., Knops, E., Vehreschild, J. J., Mehta, S., & Chaillon, A. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, August, 2018. doi abstract bibtex Background: Geographical allocation of interventions focusing on hotspots of 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 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 (i.e. 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: 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=0.043), \textless30 years of age (p=0.009) and infected with HIV-1 subtype B (p=0.002). Clustering individuals were non-assortative by area of residency (-0.0026, p=0.046), indicating that clustering individuals tended to cluster with individuals from a different zip code. Geospatial analyses revealed a median distance between genetically linked individuals of 23.4 kilometers (km), lower than expected (p\textless0.001). Slatkin-Maddison analyses revealed increased gene flow from central Cologne toward the surrounding areas (p\textless0.001). Conclusion: Phylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. While 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.
@article{stecher_hotspots_2018,
title = {Hotspots of {Transmission} {Driving} the {Local} {Hiv} {Epidemic} in the {Cologne}-{Bonn} {Region}, {Germany}},
issn = {1537-6591},
doi = {10.1093/cid/ciy744},
abstract = {Background: Geographical allocation of interventions focusing on hotspots of 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 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 (i.e. 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: 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=0.043), {\textless}30 years of age (p=0.009) and infected with HIV-1 subtype B (p=0.002). Clustering individuals were non-assortative by area of residency (-0.0026, p=0.046), indicating that clustering individuals tended to cluster with individuals from a different zip code. Geospatial analyses revealed a median distance between genetically linked individuals of 23.4 kilometers (km), lower than expected (p{\textless}0.001). Slatkin-Maddison analyses revealed increased gene flow from central Cologne toward the surrounding areas (p{\textless}0.001).
Conclusion: Phylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. While 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.},
language = {eng},
journal = {Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America},
author = {Stecher, Melanie and Hoenigl, Martin and Eis-Hübinger, Anna Maria and Lehmann, Clara and Fätkenheuer, Gerd and Wasmuth, Jan-Christian and Knops, Elena and Vehreschild, Jörg Janne and Mehta, Sanjay and Chaillon, Antoine},
month = aug,
year = {2018},
pmid = {30169606},
pmcid = {PMC6481988},
}
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{"_id":"CFeJm2HYrr3EJaFZD","bibbaseid":"stecher-hoenigl-eishbinger-lehmann-ftkenheuer-wasmuth-knops-vehreschild-etal-hotspotsoftransmissiondrivingthelocalhivepidemicinthecolognebonnregiongermany-2018","downloads":0,"creationDate":"2019-04-03T17:38:58.446Z","title":"Hotspots of Transmission Driving the Local Hiv Epidemic in the Cologne-Bonn Region, Germany","author_short":["Stecher, M.","Hoenigl, M.","Eis-Hübinger, A. M.","Lehmann, C.","Fätkenheuer, G.","Wasmuth, J.","Knops, E.","Vehreschild, J. J.","Mehta, S.","Chaillon, A."],"year":2018,"bibtype":"article","biburl":"https://bibbase.org/zotero/ucsdpirc","bibdata":{"bibtype":"article","type":"article","title":"Hotspots of Transmission Driving the Local Hiv Epidemic in the Cologne-Bonn Region, Germany","issn":"1537-6591","doi":"10.1093/cid/ciy744","abstract":"Background: Geographical allocation of interventions focusing on hotspots of 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 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 (i.e. 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: 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=0.043), \\textless30 years of age (p=0.009) and infected with HIV-1 subtype B (p=0.002). Clustering individuals were non-assortative by area of residency (-0.0026, p=0.046), indicating that clustering individuals tended to cluster with individuals from a different zip code. Geospatial analyses revealed a median distance between genetically linked individuals of 23.4 kilometers (km), lower than expected (p\\textless0.001). Slatkin-Maddison analyses revealed increased gene flow from central Cologne toward the surrounding areas (p\\textless0.001). Conclusion: Phylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. While 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.","language":"eng","journal":"Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America","author":[{"propositions":[],"lastnames":["Stecher"],"firstnames":["Melanie"],"suffixes":[]},{"propositions":[],"lastnames":["Hoenigl"],"firstnames":["Martin"],"suffixes":[]},{"propositions":[],"lastnames":["Eis-Hübinger"],"firstnames":["Anna","Maria"],"suffixes":[]},{"propositions":[],"lastnames":["Lehmann"],"firstnames":["Clara"],"suffixes":[]},{"propositions":[],"lastnames":["Fätkenheuer"],"firstnames":["Gerd"],"suffixes":[]},{"propositions":[],"lastnames":["Wasmuth"],"firstnames":["Jan-Christian"],"suffixes":[]},{"propositions":[],"lastnames":["Knops"],"firstnames":["Elena"],"suffixes":[]},{"propositions":[],"lastnames":["Vehreschild"],"firstnames":["Jörg","Janne"],"suffixes":[]},{"propositions":[],"lastnames":["Mehta"],"firstnames":["Sanjay"],"suffixes":[]},{"propositions":[],"lastnames":["Chaillon"],"firstnames":["Antoine"],"suffixes":[]}],"month":"August","year":"2018","pmid":"30169606","pmcid":"PMC6481988","bibtex":"@article{stecher_hotspots_2018,\n\ttitle = {Hotspots of {Transmission} {Driving} the {Local} {Hiv} {Epidemic} in the {Cologne}-{Bonn} {Region}, {Germany}},\n\tissn = {1537-6591},\n\tdoi = {10.1093/cid/ciy744},\n\tabstract = {Background: Geographical allocation of interventions focusing on hotspots of HIV transmission has the potential to improve efficiency. We used phylogeographic analyses to identify hotspots of the HIV transmission in Cologne-Bonn, Germany.\nMethods: We included 714 HIV-1 infected individuals, followed 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 (i.e. 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).\nResults: 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=0.043), {\\textless}30 years of age (p=0.009) and infected with HIV-1 subtype B (p=0.002). Clustering individuals were non-assortative by area of residency (-0.0026, p=0.046), indicating that clustering individuals tended to cluster with individuals from a different zip code. Geospatial analyses revealed a median distance between genetically linked individuals of 23.4 kilometers (km), lower than expected (p{\\textless}0.001). Slatkin-Maddison analyses revealed increased gene flow from central Cologne toward the surrounding areas (p{\\textless}0.001).\nConclusion: Phylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. While 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.},\n\tlanguage = {eng},\n\tjournal = {Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America},\n\tauthor = {Stecher, Melanie and Hoenigl, Martin and Eis-Hübinger, Anna Maria and Lehmann, Clara and Fätkenheuer, Gerd and Wasmuth, Jan-Christian and Knops, Elena and Vehreschild, Jörg Janne and Mehta, Sanjay and Chaillon, Antoine},\n\tmonth = aug,\n\tyear = {2018},\n\tpmid = {30169606},\n\tpmcid = {PMC6481988},\n}\n\n","author_short":["Stecher, M.","Hoenigl, M.","Eis-Hübinger, A. M.","Lehmann, C.","Fätkenheuer, G.","Wasmuth, J.","Knops, E.","Vehreschild, J. 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