An Immunization Strategy for Hidden Populations.
An Immunization Strategy for Hidden Populations.
复制标题
隐藏人群的免疫策略
DOI：
10.1038/s41598-017-03379-4
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发表时间：
2017-06-12
影响因子：
4.6
通讯作者：
Lu X
中科院分区：
文献类型：
--
作者：
Chen S;Lu X
注射毒品使用者（IDUs）、性工作者（SW）和男男性行为者（MSM）等隐蔽人群被认为是感染和传播艾滋病、淋病、梅毒等传染病的高风险人群。然而，由于对隐私的强烈关注和缺乏全球信息，禁止对这些群体进行公共卫生干预，这对于诸如靶向免疫和熟人免疫的传统策略是必需的。在这项研究中，我们引入了一种创新的干预策略，与广泛用于隐藏人群的抽样方法，即响应者驱动抽样（RDS）相结合。RDS策略分两步实现：首先，RDS用于估计样本数据的目标人群的平均度（个人网络规模）和度分布。第二，计算临界值，并用于筛选接种对象。在模型网络和真实网络上的仿真表明，RDS策略的效率接近目标策略。由于新策略可以与RDS抽样过程一起实施，因此为隐藏人群的疾病干预和控制提供了一种经济有效的可行方法。
Hidden populations, such as injecting drug users (IDUs), sex workers (SWs) and men who have sex with men (MSM), are considered at high risk of contracting and transmitting infectious diseases such as AIDS, gonorrhea, syphilis etc. However, public health interventions to such groups are prohibited due to strong privacy concerns and lack of global information, which is a necessity for traditional strategies such as targeted immunization and acquaintance immunization. In this study, we introduce an innovative intervention strategy to be used in combination with a sampling approach that is widely used for hidden populations, Respondent-driven Sampling (RDS). The RDS strategy is implemented in two steps: First, RDS is used to estimate the average degree (personal network size) and degree distribution of the target population with sample data. Second, a cut-off threshold is calculated and used to screen the respondents to be immunized. Simulations on model networks and real-world networks reveal that the efficiency of the RDS strategy is close to that of the targeted strategy. As the new strategy can be implemented with the RDS sampling process, it provides a cost-efficient and feasible approach for disease intervention and control for hidden populations.