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Measuring the performance of vaccination programs using cross-sectional surveys: a likelihood framework and
Justin Lessler1, C Jessica E Metcalf, Rebecca F Grais
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America. jlessler@jhsph.edu
Plos Medicine
|November 1, 2011
Summary
This study introduces a new method combining survey and administrative data for accurate vaccination coverage estimates. The findings reveal significant variations in vaccination program efficiency across Ghana, Madagascar, and Sierra Leone.
Area of Science:
- Public Health
- Epidemiology
- Biostatistics
Background:
- Traditional administrative methods for measuring immunization coverage provide inconsistent estimates compared to survey data.
- Existing methods often yield impossible coverage figures (e.g., >100%) and do not account for program inefficiencies.
- Demographic and Health Surveys (DHS) provide valuable on-the-ground data but require integration with administrative data for comprehensive analysis.
Purpose of the Study:
- To develop and validate a novel statistical framework for estimating effective vaccination coverage.
- To assess vaccination program accessibility and within-campaign inefficiencies using combined data sources.
- To provide more accurate and consistent vaccination coverage estimates for public health interventions.
Main Methods:
- Developed a likelihood framework integrating cross-sectional vaccine coverage survey data with administrative coverage data.
- Applied the framework to measles vaccination data from Ghana, Madagascar, and Sierra Leone using DHS and WHO administrative data.
- Compared model-estimated coverage with age-specific coverage levels observed in DHS data.
Main Results:
- Estimated effective measles vaccination coverage: 93% in Ghana, 77% in Madagascar, and 69% in Sierra Leone.
- Quantified 'within-activity' inefficiencies, finding them lower in Ghana and higher in Madagascar and Sierra Leone.
- The developed model accurately fits age-specific vaccination coverage from DHS data, outperforming traditional extrapolation methods.
Conclusions:
- Combining administrative and survey data significantly enhances the accuracy of vaccination coverage estimates.
- Estimating program inefficiencies and uncovered populations aids in predicting future activity success.
- This integrated approach offers critical insights into vaccination program performance and areas for improvement.
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