O'Reilly K M, Cori A, Durry E, Wadood M Z, Bosan A, Aylward R B, Grassly N C
Am J Epidemiol. 2015 Dec 1;182(11):961-70. doi: 10.1093/aje/kwv199. Epub 2015 Nov 14.
Mass vaccination campaigns with the oral poliovirus vaccine targeting children aged <5 years are a critical component of the global poliomyelitis eradication effort. Monitoring the coverage of these campaigns is essential to allow corrective action, but current approaches are limited by their cross-sectional nature, nonrandom sampling, reporting biases, and accessibility issues. We describe a new Bayesian framework using data augmentation and Markov chain Monte Carlo methods to estimate variation in vaccination coverage from children's vaccination histories investigated during surveillance for acute flaccid paralysis. We tested the method using simulated data with at least 200 cases and were able to detect undervaccinated groups if they exceeded 10% of all children and temporal changes in coverage of ±10% with greater than 90% sensitivity. Application of the method to data from Pakistan for 2010-2011 identified undervaccinated groups within the Balochistan/Federally Administered Tribal Areas and Khyber Pakhtunkhwa regions, as well as temporal changes in coverage. The sizes of these groups are consistent with the multiple challenges faced by the program in these regions as a result of conflict and insecurity. Application of this new method to routinely collected data can be a useful tool for identifying poorly performing areas and assisting in eradication efforts.
针对5岁以下儿童开展的口服脊髓灰质炎疫苗大规模免疫接种运动是全球根除脊髓灰质炎努力的关键组成部分。监测这些运动的覆盖率对于采取纠正措施至关重要，但目前的方法受到其横断面性质、非随机抽样、报告偏差和可及性问题的限制。我们描述了一种新的贝叶斯框架，该框架使用数据增强和马尔可夫链蒙特卡罗方法，根据在急性弛缓性麻痹监测期间调查的儿童疫苗接种史来估计疫苗接种覆盖率的变化。我们使用至少有200个病例的模拟数据对该方法进行了测试，如果未接种疫苗的群体超过所有儿童的10%，并且覆盖率的时间变化为±10%，则能够以大于90%的灵敏度检测到这些群体。将该方法应用于巴基斯坦2010 - 2011年的数据，确定了俾路支省/联邦直辖部落地区和开伯尔-普赫图赫瓦省地区内未接种疫苗的群体以及覆盖率的时间变化。这些群体的规模与该计划在这些地区因冲突和不安全而面临的多重挑战相一致。将这种新方法应用于常规收集的数据可以成为识别表现不佳地区并协助根除工作的有用工具。
