Koyuncu Aybüke, Ishizumi Atsuyoshi, Daniels Danni, Jalloh Mohamed F, Wallace Aaron S, Prybylski Dimitri
Global Immunization Division, Centers for Disease Control and Prevention (CDC), Atlanta, GA 30329, USA.
Vaccines (Basel). 2023 Feb 13;11(2):424. doi: 10.3390/vaccines11020424.
Vaccines prevent 4-5 million deaths every year, but inequities in vaccine coverage persist among key disadvantaged subpopulations. Under-immunized subpopulations (e.g., migrants, slum residents) may be consistently missed with conventional methods for estimating immunization coverage and assessing vaccination barriers. Adaptive sampling, such as respondent-driven sampling, may offer useful strategies for identifying and collecting data from these subpopulations that are often "hidden" or hard-to-reach. However, use of these adaptive sampling approaches in the field of global immunization has not been systematically documented. We searched PubMed, Scopus, and Embase databases to identify eligible studies published through November 2020 that used an adaptive sampling method to collect immunization-related data. From the eligible studies, we extracted relevant data on their objectives, setting and target population, and sampling methods. We categorized sampling methods and assessed their frequencies. Twenty-three studies met the inclusion criteria out of the 3069 articles screened for eligibility. Peer-driven sampling was the most frequently used adaptive sampling method (57%), followed by geospatial sampling (30%), venue-based sampling (17%), ethnographic mapping (9%), and compact segment sampling (9%). Sixty-one percent of studies were conducted in upper-middle-income or high-income countries. Data on immunization uptake were collected in 65% of studies, and data on knowledge and attitudes about immunizations were collected in 57% of studies. We found limited use of adaptive sampling methods in measuring immunization coverage and understanding determinants of vaccination uptake. The current under-utilization of adaptive sampling approaches leaves much room for improvement in how immunization programs calibrate their strategies to reach "hidden" subpopulations.
疫苗每年可预防400万至500万人死亡，但在关键的弱势群体中，疫苗接种覆盖率仍存在不平等现象。免疫接种不足的亚人群（如移民、贫民窟居民）可能会一直被传统的免疫接种覆盖率估算方法和疫苗接种障碍评估方法所遗漏。诸如应答驱动抽样等适应性抽样方法，可能为从这些经常“隐藏”或难以接触到的亚人群中识别和收集数据提供有用策略。然而，这些适应性抽样方法在全球免疫领域的应用尚未得到系统记录。我们检索了PubMed、Scopus和Embase数据库，以识别截至2020年11月发表的使用适应性抽样方法收集免疫相关数据的合格研究。从合格研究中，我们提取了有关其目标、背景和目标人群以及抽样方法的相关数据。我们对抽样方法进行了分类并评估了其使用频率。在筛选的3069篇符合资格的文章中，有23项研究符合纳入标准。同伴驱动抽样是最常用的适应性抽样方法（57%），其次是地理空间抽样（30%）、基于场所的抽样（17%）、民族志绘图（9%）和紧凑片段抽样（9%）。61%的研究在中高收入或高收入国家进行。65%的研究收集了免疫接种率数据，57%的研究收集了有关免疫接种的知识和态度数据。我们发现适应性抽样方法在测量免疫接种覆盖率和了解疫苗接种率的决定因素方面使用有限。目前适应性抽样方法利用不足，这使得免疫规划在调整其策略以覆盖“隐藏”亚人群方面有很大的改进空间。
