Modelling Immunization Coverage in Nigeria Using Bayesian Structured Additive Regression

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Abstract

About ten million children under the age of five die every year worldwide. One quarter of these deaths are caused by diseases that are preventable with vaccines. According to the World Health Organisation, immunization currently saves between two and three million lives per year. It is one of the most successful and cost-effective public health interventions. In developing countries in particular, infant and childhood mortalities are related to childhood diseases. Therefore, low vaccination coverage increases the risks of a child being exposed to various diseases such as diarrhoea, measles, malaria, etc. In spite of the efforts from government and many donor agencies, Nigeria still remains the country with least vaccination coverage in Africa. However, empirical evidence revealed substantial geographical variations on immunization coverage in Nigeria. In attempt to address the menace of low vaccination coverage in Nigeria, this Chapter aims at providing policymakers with tools to design effective interventions which can lead to frugal utilization of the scarce resources, which is a major challenge in many developing countries, including Nigeria. Findings from this work revealed substantial significant spatial effect and nonlinear effect of mother’s age at birth on vaccination coverage in Nigeria. Mother’s enhanced educational attainment and that of her partner also improve the rate of immunization in Nigeria. Furthermore, children who were delivered in hospitals, children that reside in urban areas and firstborn children are more likely to be fully immunised in Nigeria. In conclusion, since unavailability of basic needed resources have been identified as a major challenge towards successful implementation of interventions that would boost vaccination coverage in sub-Saharan African countries, including Nigeria, this study therefore provides policy-makers with tools that would aid appropriate policy formulation towards improving access to and coverage of immunisation in Nigeria. This would immensely assist in proper allocation of available resources to states or districts where such resources can be effectively utilized.

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APA

Adebayo, S. B., & Yahya, W. B. (2014). Modelling Immunization Coverage in Nigeria Using Bayesian Structured Additive Regression. In Springer Series on Demographic Methods and Population Analysis (Vol. 34, pp. 123–145). Springer Science and Business Media B.V. https://doi.org/10.1007/978-94-007-6778-2_7

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