Yin Fei, Feng Zijian, Li Xiaosong
Department of Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
Sex Health. 2012 Jul;9(3):227-32. doi: 10.1071/SH11052.
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.
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.
During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 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).
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.
淋病是中国大陆最常见的性传播感染之一。对淋病发病率进行有效的空间监测对于成功实施控制和预防计划至关重要。通过检查空间模式对中国大陆所有县级淋病发病率进行了监测。
2004年至2009年县级淋病病例数据来自中国疾病预防控制信息系统。采用贝叶斯平滑和探索性空间数据分析（ESDA）方法来描述淋病病例的空间分布模式。
在6年研究期间，淋病年平均发病率为每10万人12.41例。使用经验贝叶斯平滑率，局部莫兰检验确定了一个显著的单中心聚集区和两个显著的多中心高淋病风险聚集区（所有P值<0.01）。
贝叶斯平滑和ESDA方法可协助公共卫生官员利用淋病监测数据识别高风险地区。向这些地区分配更多资源可有效降低淋病发病率。
