Department of Work and Social Psychology, Maastricht University, Maastricht, the Netherlands.
Health Psychology, University of Aberdeen, Aberdeen, United Kingdom.
Spat Spatiotemporal Epidemiol. 2023 Jun;45:100577. doi: 10.1016/j.sste.2023.100577. Epub 2023 Feb 1.
Despite close monitoring of HIV infections amongst MSM (MSMHIV), the true prevalence can be masked for areas with small population density or lack of data. This study investigated the feasibility of small area estimation with a Bayesian approach to improve HIV surveillance. Data from EMIS-2017 (Dutch subsample, n = 3,459) and the Dutch survey SMS-2018 (n = 5,653) were utilized. We applied a frequentist calculation to compare the observed relative risk of MSMHIV per Public Health Services (GGD) region in the Netherlands and a Bayesian spatial analysis and ecological regression to quantify how spatial heterogeneity in HIV amongst MSM is related to determinants while accounting for spatial dependence to obtain more robust estimates. Both estimations converged and confirmed that the prevalence is heterogenous across the Netherlands with some GGD regions having a higher-than-average risk. Our Bayesian spatial analysis to assess the risk of MSMHIV was able to close data gaps and provide more robust prevalence and risk estimations.
尽管对男男性行为者中的艾滋病毒感染（MSMHIV）进行了密切监测，但对于人口密度较小或缺乏数据的地区，实际流行率可能被掩盖。本研究探讨了使用贝叶斯方法进行小区域估计以改善艾滋病毒监测的可行性。该研究使用了 EMIS-2017 数据（荷兰子样本，n=3459）和荷兰 SMS-2018 调查（n=5653）的数据。我们应用了频率计算来比较荷兰公共卫生服务（GGD）区域中男男性行为者中艾滋病毒的观察相对风险，以及贝叶斯空间分析和生态回归，以量化男男性行为者中艾滋病毒的空间异质性与决定因素之间的关系，同时考虑空间依赖性以获得更稳健的估计。这两种估计都收敛了，并证实了荷兰各地的流行率存在异质性，一些 GGD 区域的风险高于平均水平。我们的贝叶斯空间分析评估男男性行为者中艾滋病毒的风险，能够弥补数据差距，并提供更稳健的流行率和风险估计。
