School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Epidemiology. 2012 Nov;23(6):845-51. doi: 10.1097/EDE.0b013e31826c2b7e.
Sexually transmitted infections (STIs) spread along sexual networks whose structural characteristics promote transmission that routine surveillance may not capture. Cases who have partners from multiple localities may operate as spatial network bridges, thereby facilitating geographical dissemination. We investigated how surveillance, sexual networks, and spatial bridges relate to each other for syphilis outbreaks in rural counties of North Carolina.
We selected from the state health department's surveillance database cases diagnosed with primary, secondary, or early latent syphilis during October 1998 to December 2002 and who resided in central and southeastern North Carolina, along with their sex partners and their social contacts irrespective of infection status. We applied matching algorithms to eliminate duplicate names and create a unique roster of partnerships from which networks were compiled and graphed. Network members were differentiated by disease status and county of residence.
In the county most affected by the outbreak, densely connected networks indicative of STI outbreaks were consistent with increased incidence and a large case load. In other counties, the case loads were low with fluctuating incidence, but network structures suggested the presence of outbreaks. In a county with stable, low incidence and a high number of cases, the networks were sparse and dendritic, indicative of endemic spread. Outbreak counties exhibited densely connected networks within well-defined geographic boundaries and low connectivity between counties; spatial bridges did not seem to facilitate transmission.
Simple visualization of sexual networks can provide key information to identify communities most in need of resources for outbreak investigation and disease control.
性传播感染(STIs)通过性网络传播,这些网络的结构特征促进了常规监测可能无法捕捉到的传播。具有来自多个地方的性伴侣的病例可能充当空间网络桥梁,从而促进地理传播。我们调查了监测、性网络和空间桥梁如何相互关联,以了解北卡罗来纳州农村县的梅毒爆发情况。
我们从州卫生部门的监测数据库中选择了 1998 年 10 月至 2002 年 12 月期间在北卡罗来纳州中南部和东南部诊断出原发性、二期或早期潜伏梅毒的病例,以及他们的性伴侣和他们的社交联系人,无论其感染状况如何。我们应用匹配算法消除重复的姓名,并创建一个独特的伙伴名单,从中编制和绘制网络。网络成员按疾病状况和居住县进行区分。
在受疫情影响最严重的县,密集连接的网络表明存在性传播感染疫情,与发病率增加和大量病例有关。在其他县,发病率波动但病例数较低,但网络结构表明存在疫情。在发病率稳定、低且病例数高的县,网络稀疏且呈树突状,表明存在地方性传播。爆发县的网络在明确的地理边界内密集连接,县与县之间的连接性较低;空间桥梁似乎没有促进传播。
性网络的简单可视化可以提供关键信息,以确定最需要资源进行疫情调查和疾病控制的社区。