The epidemiology of gonorrhoea in London: a Bayesian spatial modelling approach

Abstract

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.

Fig. 1

[colour online]. Chloropleth map of incidence rate (per 1000) of diagnosed gonorrhoea by MSOA in London over the 2-year period.

Fig. 2.

Plot by Middle-layer Super Output Area (MSOA) (statistical geographical area with a median population size of ≈7200) of the incidence rate ratio (IRR) for gonorrhoea by MSOA of residence, as predicted by (a) model covariates only; (b) the spatial effect only, London, 2009–2010.