伦敦淋病的流行病学:贝叶斯空间建模方法。
The epidemiology of gonorrhoea in London: a Bayesian spatial modelling approach.
机构信息
Health Protection Agency, London Region Epidemiology Unit, London, UK.
出版信息
Epidemiol Infect. 2014 Jan;142(1):211-20. doi: 10.1017/S0950268813000745. Epub 2013 Apr 8.
Data obtained from genitourinary medicine clinics through a comprehensive surveillance system were used in a Bayesian mixed-effects Poisson regression model to explore socio-demographic individual and ecological risk factors for gonorrhoea in London, as well as its spatial clustering. The spatial analysis was performed at the Middle-layer Super Output Area level (median population size 7200). A total of 12452 individuals were diagnosed during the 2-year study period (2009-2010). The study confirmed the presence of 'core areas' of high incidence, and identified 'core' high-risk groups, in particular young adults (16-29 years), males, black Caribbeans and more deprived areas. The individual (age, sex, ethnicity) and area-level (deprivation, teenage pregnancies, students) model covariates accounted for 48% of the variance. Most of the remaining variance was explained by the spatial effect, thus capturing other spatially distributed factors associated with gonorrhoea, such as local sexual networks. These findings will be useful in identifying areas for targeted interventions, such as STI testing and health promotion.
利用综合监测系统从生殖医学诊所获得的数据,采用贝叶斯混合效应泊松回归模型,探索了伦敦淋病的社会人口学个体和生态风险因素及其空间聚集性。空间分析在中层次超级输出区(中位数人口规模为 7200)进行。在 2 年的研究期间(2009-2010 年),共诊断出 12452 名患者。研究证实了存在高发的“核心区域”,并确定了“核心”高危人群,特别是年轻人(16-29 岁)、男性、黑人加勒比人和较贫困地区。个体(年龄、性别、种族)和地区水平(贫困、青少年怀孕、学生)模型协变量解释了 48%的变异。其余大部分变异由空间效应解释,从而捕捉到与淋病相关的其他空间分布因素,如局部性网络。这些发现将有助于确定目标干预的区域,如性传播感染检测和健康促进。