METHODS: We used data from the 2021 Nigeria Multiple Indicator Cluster Survey/National Immunization Coverage Survey to identify zero-dose and underimmunized children. Geospatial modeling techniques were employed to determine the prevalence of zero-dose children and predict risk areas with underimmunized children at a high resolution (1 × 1 km).
RESULTS: Zero-dose and underimmunized children are more prevalent in socially deprived groups. Univariate and multivariate bayesian analyses showed positive correlations between the prevalence of zero-dose and underimmunized children and factors such as stunting, contraceptive prevalence, and literacy. The prevalence of zero-dose and underimmunized children varies significantly by region and ethnicity, with higher rates observed in the country\'s northern parts. Significant heterogeneity in the distribution of undervaccinated children was observed.
CONCLUSIONS: Nigeria needs to enhance its immunization system and coverage. Geospatial modeling can help deliver vaccines effectively to underserved communities. By adopting this approach, countries can ensure equitable vaccine access and contribute to global vaccination objectives.
方法:我们使用了2021年尼日利亚多指标类集调查/国家免疫覆盖率调查的数据来识别零剂量和免疫不足的儿童。采用地理空间建模技术来确定零剂量儿童的患病率,并以高分辨率(1×1km)预测免疫不足儿童的风险区域。
结果:零剂量和免疫不足的儿童在社会贫困群体中更为普遍。单变量和多变量贝叶斯分析显示,零剂量和免疫不足儿童的患病率与发育迟缓等因素之间呈正相关。避孕普及率,和识字。零剂量和免疫不足儿童的患病率因地区和种族而异,在该国北部地区观察到更高的比率。观察到接种疫苗不足儿童的分布存在显着异质性。
结论:尼日利亚需要加强其免疫系统和覆盖率。地理空间建模可以帮助有效地向服务不足的社区提供疫苗。通过采用这种方法,各国可以确保公平获得疫苗,并为实现全球疫苗接种目标做出贡献。