TY - JOUR
T1 - The epidemiology of gonorrhoea in London
T2 - A Bayesian spatial modelling approach
AU - Le Polain De Waroux, O.
AU - Harris, R. J.
AU - Hughes, Gwenda
AU - Crook, Paul
PY - 2014/1
Y1 - 2014/1
N2 - SUMMARY 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.
AB - SUMMARY 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.
KW - Epidemiology
KW - Gonorrhoea
KW - Infectious disease control
KW - Surveillance
UR - http://www.scopus.com/inward/record.url?scp=84890101646&partnerID=8YFLogxK
U2 - 10.1017/S0950268813000745
DO - 10.1017/S0950268813000745
M3 - Article
AN - SCOPUS:84890101646
SN - 0950-2688
VL - 142
SP - 211
EP - 220
JO - Epidemiology and Infection
JF - Epidemiology and Infection
IS - 1
ER -