Developing a systematic approach to better monitor vaccine coverage using multiple data sources

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Johns Hopkins University
Immunization is one of the most cost-effective ways of preventing child and adult morbidity and mortality due to infectious diseases. Vaccine coverage monitoring at the national and sub-national levels is critical to identify under-vaccinated populations and to improve the performance of immunization services to reach them. Despite substantial improvements since the invention of the Expanded Program on Immunization (EPI) cluster survey method in the 1970s, measuring vaccination coverage with high accuracy and precision remains a very challenging, but often neglected, global problem, especially in low-resource settings. Since household surveys are currently an essential tool for vaccine coverage monitoring in developing countries, this study has focused on survey-based vaccine coverage estimates. Innovative household survey sampling methods (Chapter 3) and data quality inspection approaches (Chapter 5) were explored and designed to improve the quality and operational feasibility of vaccine coverage surveys. In order to overcome the information biases of survey-based vaccine coverage estimates, novel statistical methods were developed (Chapter 4) to incorporate additional evidence from immune marker assessments with survey results for triangulation and adjustments. These approaches to improve vaccine coverage monitoring were integrated and demonstrated through a proof of concept study in Karachi, Pakistan. This dissertation has demonstrated a systematic approach to improve survey-based vaccine coverage monitoring through methodological innovations in survey sampling designs, enhanced quality assurance activities, and incorporation of additional evidence from non-survey data sources.
vaccine coverage, immunization monitoring, biomarker, data quality