Cargando…
Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam
BACKGROUND: More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545569/ https://www.ncbi.nlm.nih.gov/pubmed/35920649 http://dx.doi.org/10.7554/eLife.76487 |
_version_ | 1784804848943759360 |
---|---|
author | Blenkinsop, Alexandra Monod, Mélodie van Sighem, Ard Pantazis, Nikos Bezemer, Daniela Op de Coul, Eline van de Laar, Thijs Fraser, Christophe Prins, Maria Reiss, Peter de Bree, Godelieve J Ratmann, Oliver |
author_facet | Blenkinsop, Alexandra Monod, Mélodie van Sighem, Ard Pantazis, Nikos Bezemer, Daniela Op de Coul, Eline van de Laar, Thijs Fraser, Christophe Prins, Maria Reiss, Peter de Bree, Godelieve J Ratmann, Oliver |
author_sort | Blenkinsop, Alexandra |
collection | PubMed |
description | BACKGROUND: More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014–2018 in Amsterdam that remained undiagnosed. METHODS: We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data. RESULTS: Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014–2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12–16%] of infections in Amsterdan MSM in 2014–2018 remained undiagnosed by 1 May 2019, and 41% [35–48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60–74%] of Amsterdam MSM infections in 2014–2018 had an Amsterdam resident as source, and 56% [41–70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37–49%] were in foreign-born MSM, 41% [35–47%] in Dutch-born MSM, 10% [6–18%] in foreign-born heterosexuals, and 5% [2–9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014–2018 originated in transmission chains that pre-existed by 2014. CONCLUSIONS: This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions. FUNDING: This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund. |
format | Online Article Text |
id | pubmed-9545569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-95455692022-10-08 Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam Blenkinsop, Alexandra Monod, Mélodie van Sighem, Ard Pantazis, Nikos Bezemer, Daniela Op de Coul, Eline van de Laar, Thijs Fraser, Christophe Prins, Maria Reiss, Peter de Bree, Godelieve J Ratmann, Oliver eLife Epidemiology and Global Health BACKGROUND: More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014–2018 in Amsterdam that remained undiagnosed. METHODS: We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data. RESULTS: Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014–2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12–16%] of infections in Amsterdan MSM in 2014–2018 remained undiagnosed by 1 May 2019, and 41% [35–48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60–74%] of Amsterdam MSM infections in 2014–2018 had an Amsterdam resident as source, and 56% [41–70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37–49%] were in foreign-born MSM, 41% [35–47%] in Dutch-born MSM, 10% [6–18%] in foreign-born heterosexuals, and 5% [2–9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014–2018 originated in transmission chains that pre-existed by 2014. CONCLUSIONS: This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions. FUNDING: This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund. eLife Sciences Publications, Ltd 2022-08-03 /pmc/articles/PMC9545569/ /pubmed/35920649 http://dx.doi.org/10.7554/eLife.76487 Text en © 2022, Blenkinsop et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Blenkinsop, Alexandra Monod, Mélodie van Sighem, Ard Pantazis, Nikos Bezemer, Daniela Op de Coul, Eline van de Laar, Thijs Fraser, Christophe Prins, Maria Reiss, Peter de Bree, Godelieve J Ratmann, Oliver Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title | Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title_full | Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title_fullStr | Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title_full_unstemmed | Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title_short | Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam |
title_sort | estimating the potential to prevent locally acquired hiv infections in a unaids fast-track city, amsterdam |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545569/ https://www.ncbi.nlm.nih.gov/pubmed/35920649 http://dx.doi.org/10.7554/eLife.76487 |
work_keys_str_mv | AT blenkinsopalexandra estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT monodmelodie estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT vansighemard estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT pantazisnikos estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT bezemerdaniela estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT opdecouleline estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT vandelaarthijs estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT fraserchristophe estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT prinsmaria estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT reisspeter estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT debreegodelievej estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam AT ratmannoliver estimatingthepotentialtopreventlocallyacquiredhivinfectionsinaunaidsfasttrackcityamsterdam |