Journal article
Measuring the performance of vaccination programs using cross-sectional surveys: a likelihood framework and retrospective analysis.
Background: The performance of routine and supplemental immunization activities is usually measured by the
administrative method: dividing the number of doses distributed by the size of the target population. This method leads to
coverage estimates that are sometimes impossible (e.g., vaccination of 102% of the target population), and are generally
inconsistent with the proportion found to be vaccinated in Demographic and Health Surveys (DHS). We describe a method
that estimates the fraction of the population accessible to vaccination activities, as well as within-campaign inefficiencies,
thus providing a consistent estimate of vaccination coverage.
Methods and Findings: We developed a likelihood framework for estimating the effective coverage of vaccination
programs using cross-sectional surveys of vaccine coverage combined with administrative data. We applied our method to
measles vaccination in three African countries: Ghana, Madagascar, and Sierra Leone, using data from each country’s most
recent DHS survey and administrative coverage data reported to the World Health Organization. We estimate that 93% (95%
CI: 91, 94) of the population in Ghana was ever covered by any measles vaccination activity, 77% (95% CI: 78, 81) in
Madagascar, and 69% (95% CI: 67, 70) in Sierra Leone. ‘‘Within-activity’’ inefficiencies were estimated to be low in Ghana,
and higher in Sierra Leone and Madagascar. Our model successfully fits age-specific vaccination coverage levels seen in DHS
data, which differ markedly from those predicted by naı¨ve extrapolation from country-reported and World Health
Organization–adjusted vaccination coverage.
Conclusions: Combining administrative data with survey data substantially improves estimates of vaccination coverage.
Estimates of the inefficiency of past vaccination activities and the proportion not covered by any activity allow us to more
accurately predict the results of future activities and provide insight into the ways in which vaccination programs are failing
to meet their goals.
Authors
Languages
- English
Journal
PLoS Med
Volume
8(10):e1001110. doi: 10.1371/journal.pmed.1001110 PMID: 22039353
Type
Journal article
Categories
- Data
Topic references
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