Wang, HaoyiDaas, Chantal dende Coul, Eline OpJonas, Kai J.2023-06-132023-06-132023-06Wang, H, Daas, C D, de Coul, E O & Jonas, K J 2023, 'MSM with HIV : Improving prevalence and risk estimates by a Bayesian small area estimation modelling approach for public health service areas in the Netherlands', Spatial and Spatio-temporal Epidemiology, vol. 45, 100577. https://doi.org/10.1016/j.sste.2023.1005771877-5845ORCID: /0000-0003-0955-3691/work/136883029https://hdl.handle.net/2164/20839Acknowledgement: We thank all participants of the surveys and the individuals involved in preparation, execution and analysis of the surveys. We thank Wim Zuilhof, Bouko Bakker, Aryanti Radyowijati, Koenraad Vermey, Arjan van Bijnen and the EMIS board for their invaluable help for the EMIS-2017 data. In addition, we thank John de Wit, Philippe Adam, and Wim Zuilhof, for their role in the development and collection of SMS-2018 data. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.3934055engSDG 3 - Good Health and Well-beingBayesian spatial analysisHIV surveillanceMSMSmall area estimationR MedicineEpidemiologyGeography, Planning and DevelopmentInfectious DiseasesHealth, Toxicology and MutagenesisSupplementary InformationRJournal article10.1016/j.sste.2023.100577https://www.scopus.com/pages/publications/85150894694