Wariri Oghenebrume, Muhammad Abdul Khalie, Sowe Alieu, Strandmark Julia, Utazi Chigozie Edson, Metcalf C Jessica E, Kampmann Beate
Vaccines and Immunity Theme, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Glob Health Action. 2025 Dec;18(1):2540135. doi: 10.1080/16549716.2025.2540135. Epub 2025 Aug 20.
Vaccine coverage and disease surveillance data are valuable for monitoring protection against vaccine-preventable diseases; however, they do not directly measure population immunity. High-quality, representative serological studies can provide key insights into immunity gaps, outbreak susceptibility, and inform targeted vaccination strategies, even in high-performing immunization programs. This study aims to estimate location-specific and age-specific immunity profiles for measles and rubella while evaluating the predictive value of indirect immunity estimates derived from vaccination and surveillance data against direct serological measurements. Additionally, it seeks to model the risk of measles outbreaks and assess the impact of mitigation strategies. A multi-stage, stratified cluster sampling design will be implemented across six districts in The Gambia's North Bank and Upper River Regions. Survey clusters (i.e. 5 km × 5 km areas) encompassing all settlements within their boundaries will be selected, proportionally to district population sizes. Cluster selection ensures representativeness of both the population and vaccine coverage within each district. Based on detecting a 10% difference in protective immunity across vaccine coverage levels, power analysis assumes an intraclass correlation coefficient (ICC) of 0.01. In each cluster, 70 children aged 9 months to 14 years will be recruited, yielding a total sample size of 1,750 children across 25 selected clusters. Dried blood samples will be collected and tested for anti-measles and anti-rubella IgG using enzyme immunoassays (EIA). District-specific measles seroprevalence will be estimated using a hierarchical spatial model. This study will generate key evidence needed to refine immunization strategies and reduce the risk of measles and rubella outbreaks.
疫苗接种覆盖率和疾病监测数据对于监测针对疫苗可预防疾病的保护效果很有价值；然而，它们并不能直接衡量人群免疫力。即使在高效的免疫规划中，高质量、具有代表性的血清学研究也能为了解免疫差距、疫情易感性提供关键见解，并为有针对性的疫苗接种策略提供依据。本研究旨在估计麻疹和风疹在特定地点和特定年龄的免疫情况，同时评估从疫苗接种和监测数据得出的间接免疫估计值相对于直接血清学测量的预测价值。此外，它还试图模拟麻疹疫情的风险并评估缓解策略的影响。将在冈比亚北岸和上河区的六个地区实施多阶段分层整群抽样设计。将按地区人口规模成比例地选择包含其边界内所有定居点的调查群（即5公里×5公里的区域）。群的选择确保了每个地区内人口和疫苗接种覆盖率的代表性。基于检测到不同疫苗接种覆盖率水平下保护性免疫有10%的差异，功效分析假设组内相关系数（ICC）为0.01。在每个群中，将招募70名年龄在9个月至14岁之间的儿童，从而在25个选定群中获得总共1750名儿童的样本量。将采集干血样本，并使用酶免疫测定法（EIA）检测抗麻疹和抗风疹IgG。将使用分层空间模型估计特定地区的麻疹血清阳性率。本研究将生成完善免疫策略和降低麻疹和风疹疫情风险所需的关键证据。
