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Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation

INTRODUCTION: In France, oral pre‐exposure prophylaxis (PrEP) for HIV prevention has been publicly available since 2016, mainly targeting at men who have sex with men (MSM). Reliable and robust estimations of the actual PrEP uptake among MSM on a localized level can provide additional insights to id...

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Autores principales: Wang, Haoyi, Molina, Jean‐Michel, Dray‐Spira, Rosemary, Schmidt, Axel J., Hickson, Ford, van de Vijver, David, Jonas, Kai J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10206410/
https://www.ncbi.nlm.nih.gov/pubmed/37221971
http://dx.doi.org/10.1002/jia2.26089
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author Wang, Haoyi
Molina, Jean‐Michel
Dray‐Spira, Rosemary
Schmidt, Axel J.
Hickson, Ford
van de Vijver, David
Jonas, Kai J.
author_facet Wang, Haoyi
Molina, Jean‐Michel
Dray‐Spira, Rosemary
Schmidt, Axel J.
Hickson, Ford
van de Vijver, David
Jonas, Kai J.
author_sort Wang, Haoyi
collection PubMed
description INTRODUCTION: In France, oral pre‐exposure prophylaxis (PrEP) for HIV prevention has been publicly available since 2016, mainly targeting at men who have sex with men (MSM). Reliable and robust estimations of the actual PrEP uptake among MSM on a localized level can provide additional insights to identify and better reach marginalized MSM within current HIV prevention service provision. This study used national pharmaco‐epidemiology surveillance data and regional MSM population estimations to model the spatio‐temporal distribution of PrEP uptake among MSM in France 2016–2021 to identify marginalized MSM at risk for HIV and increase their PrEP uptake. METHODS: We first applied Bayesian spatial analyses with survey‐surveillance‐based HIV incidence data as a spatial proxy to estimate the size of (1) regional HIV‐negative MSM populations and (2) MSM who could be eligible for PrEP use according to French PrEP guidelines. We then applied Bayesian spatio‐temporal ecological regression modelling to estimate the regional prevalence and relative probability of the overall‐ and new‐PrEP uptake from 2016 to 2021 across France. RESULTS: HIV‐negative and PrEP‐eligible MSM populations vary regionally across France. Île‐de‐France was estimated to have the highest MSM density compared to other French regions. According to the final spatio‐temporal model, the relative probability of overall PrEP uptake was heterogeneous across France but remained stable over time. Urban areas have higher‐than‐average probabilities of PrEP uptake. The prevalence of PrEP use increased steadily (ranging from 8.8% [95% credible interval 8.5%;9.0%] in Nouvelle‐Aquitaine to 38.2% [36.5%;39.9%] in Centre‐Val‐de‐Loire in 2021). CONCLUSIONS: Our results show that using Bayesian spatial analysis as a novel methodology to estimate the localized HIV‐negative MSM population is feasible and applicable. Spatio‐temporal models showed that despite the increasing prevalence of PrEP use in all regions, geographical disparities and inequalities of PrEP uptake continued to exist over time. We identified regions that would benefit from greater tailoring and delivery efforts. Based on our findings, public health policies and HIV prevention strategies could be adjusted to better combat HIV infections and to accelerate ending the HIV epidemic.
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spelling pubmed-102064102023-05-25 Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation Wang, Haoyi Molina, Jean‐Michel Dray‐Spira, Rosemary Schmidt, Axel J. Hickson, Ford van de Vijver, David Jonas, Kai J. J Int AIDS Soc Research Articles INTRODUCTION: In France, oral pre‐exposure prophylaxis (PrEP) for HIV prevention has been publicly available since 2016, mainly targeting at men who have sex with men (MSM). Reliable and robust estimations of the actual PrEP uptake among MSM on a localized level can provide additional insights to identify and better reach marginalized MSM within current HIV prevention service provision. This study used national pharmaco‐epidemiology surveillance data and regional MSM population estimations to model the spatio‐temporal distribution of PrEP uptake among MSM in France 2016–2021 to identify marginalized MSM at risk for HIV and increase their PrEP uptake. METHODS: We first applied Bayesian spatial analyses with survey‐surveillance‐based HIV incidence data as a spatial proxy to estimate the size of (1) regional HIV‐negative MSM populations and (2) MSM who could be eligible for PrEP use according to French PrEP guidelines. We then applied Bayesian spatio‐temporal ecological regression modelling to estimate the regional prevalence and relative probability of the overall‐ and new‐PrEP uptake from 2016 to 2021 across France. RESULTS: HIV‐negative and PrEP‐eligible MSM populations vary regionally across France. Île‐de‐France was estimated to have the highest MSM density compared to other French regions. According to the final spatio‐temporal model, the relative probability of overall PrEP uptake was heterogeneous across France but remained stable over time. Urban areas have higher‐than‐average probabilities of PrEP uptake. The prevalence of PrEP use increased steadily (ranging from 8.8% [95% credible interval 8.5%;9.0%] in Nouvelle‐Aquitaine to 38.2% [36.5%;39.9%] in Centre‐Val‐de‐Loire in 2021). CONCLUSIONS: Our results show that using Bayesian spatial analysis as a novel methodology to estimate the localized HIV‐negative MSM population is feasible and applicable. Spatio‐temporal models showed that despite the increasing prevalence of PrEP use in all regions, geographical disparities and inequalities of PrEP uptake continued to exist over time. We identified regions that would benefit from greater tailoring and delivery efforts. Based on our findings, public health policies and HIV prevention strategies could be adjusted to better combat HIV infections and to accelerate ending the HIV epidemic. John Wiley and Sons Inc. 2023-05-23 /pmc/articles/PMC10206410/ /pubmed/37221971 http://dx.doi.org/10.1002/jia2.26089 Text en © 2023 The Authors. Journal of the International AIDS Society published by John Wiley & Sons Ltd on behalf of the International AIDS Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Wang, Haoyi
Molina, Jean‐Michel
Dray‐Spira, Rosemary
Schmidt, Axel J.
Hickson, Ford
van de Vijver, David
Jonas, Kai J.
Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title_full Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title_fullStr Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title_full_unstemmed Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title_short Spatio‐temporal changes in pre‐exposure prophylaxis uptake among MSM in mainland France between 2016 and 2021: a Bayesian small area approach with MSM population estimation
title_sort spatio‐temporal changes in pre‐exposure prophylaxis uptake among msm in mainland france between 2016 and 2021: a bayesian small area approach with msm population estimation
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10206410/
https://www.ncbi.nlm.nih.gov/pubmed/37221971
http://dx.doi.org/10.1002/jia2.26089
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