Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009
Fei Yin A , Zijian Feng B and Xiaosong Li A C
+ Author Affiliations
- Author Affiliations
A Department of Health Statistics, West China School of Public Health, Sichuan University, No. 16 Section 3, Renminnan Road, Chengdu, Sichuan 610041, China.
B Office for Disease Control and Emergence Response, Chinese Center for Disease Control and Prevention, No. 155, Changbai Road, Changping, Beijing 102206, China.
C Corresponding author. Email: westsilverhx@163.com
Sexual Health 9(3) 227-232 https://doi.org/10.1071/SH11052
Submitted: 21 March 2011 Accepted: 19 July 2011 Published: 19 December 2011
Abstract
Background: Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. Methods: County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. Results: During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100 000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Conclusions: Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.
Additional keywords: Bayesian smoothing, cluster detection, spatial analysis.
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