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Better estimating vaccine coverage: Vaccination coverage estimates can be improved by combining administrative data with survey data

Date:
October 26, 2011
Source:
Johns Hopkins University Bloomberg School of Public Health
Summary:
Immunizations are a valuable tool for controlling infectious diseases among populations both in the U.S. and globally. Routine immunizations and supplemental immunization activities, such as immunization campaigns, are designed to provide immunization coverage to entire populations. Current measurements used to determine the success and rates of immunization can be flawed and inconsistent. According to a new study, estimates of vaccination coverage can be significantly improved by combining administrative data with survey data.

Immunizations are a valuable tool for controlling infectious diseases among populations both in the U.S. and globally. Routine immunizations and supplemental immunization activities, such as immunization campaigns, are designed to provide immunization coverage to entire populations. Current measurements used to determine the success and rates of immunization can be flawed and inconsistent. According to a new study led by researchers from the Johns Hopkins Bloomberg School of Public Health, estimates of vaccination coverage can be significantly improved by combining administrative data with survey data.

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The results are featured in the October 2011 issue of PLoS Medicine.

"Reliable estimates of vaccination coverage are key to managing population immunization status," said Justin Lessler, lead author of the study and an assistant professor with the Bloomberg School's Department of Epidemiology. "Currently, the performance of routine and supplemental immunization activities is measured by the administrative method, which leads to coverage estimates that are often inconsistent with the proportion reporting vaccination in cross-sectional surveys. Furthermore, administrative coverage does not tell you how many people are systematically missed by vaccination activities. We estimated that the size of the population never reached by any activity was high in Sierra Leone and Madagascar, 31 percent and 21percent respectively. But it was much lower in Ghana, only 7 percent. "

The widely used administrative method divides the number of doses distributed by the size of the target population. Lessler, along with colleagues from Johns Hopkins, University of Oxford, Epicentre, and Princeton University developed a method for estimating the effective coverage of vaccination programs using cross-sectional surveys of vaccine coverage combined with administrative data. The method was applied using demographic health survey and administrative coverage data reported to the WHO from measles vaccinations in Ghana, Madagascar and Sierra Leone. They found estimates of routine supplemental immunization activities coverage are substantially lower than administrative estimates for Madagascar and Sierra Leone, and only slightly lower for Ghana. In addition, their estimates of routine coverage are, in general, lower than WHO and United Nations Children's Fund (UNICEF) estimates.

"This method not only attempts to correct coverage estimates, but also distinguishes between issues of overall coverage and vaccine within activity inefficiencies. For our technique to be useful, countries must have cross-sectional data on vaccine coverage for children across a range of ages, some of an age where they have been exposed to multiple vaccination activities," said Derek Cummings.

"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," adds Lessler.

"Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis" was written by Justin Lessler, C. Jessica E. Metcalf, Rebecca F. Grais, Francisco J. Luquero, Derek A. T. Cummings and Bryan T. Grenfell.

This research was supported by grants from the Vaccine Modeling Initiative of the Bill and Melinda Gates Foundation, the Department for Homeland Security, the NIH, the Burroughs Welcome Fund and the Royal Society.


Story Source:

The above story is based on materials provided by Johns Hopkins University Bloomberg School of Public Health. Note: Materials may be edited for content and length.


Journal Reference:

  1. Justin Lessler, C. Jessica E. Metcalf, Rebecca F. Grais, Francisco J. Luquero, Derek A. T. Cummings, Bryan T. Grenfell. Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis. PLoS Medicine, 2011; 8 (10): e1001110 DOI: 10.1371/journal.pmed.1001110

Cite This Page:

Johns Hopkins University Bloomberg School of Public Health. "Better estimating vaccine coverage: Vaccination coverage estimates can be improved by combining administrative data with survey data." ScienceDaily. ScienceDaily, 26 October 2011. <www.sciencedaily.com/releases/2011/10/111026143729.htm>.
Johns Hopkins University Bloomberg School of Public Health. (2011, October 26). Better estimating vaccine coverage: Vaccination coverage estimates can be improved by combining administrative data with survey data. ScienceDaily. Retrieved December 22, 2014 from www.sciencedaily.com/releases/2011/10/111026143729.htm
Johns Hopkins University Bloomberg School of Public Health. "Better estimating vaccine coverage: Vaccination coverage estimates can be improved by combining administrative data with survey data." ScienceDaily. www.sciencedaily.com/releases/2011/10/111026143729.htm (accessed December 22, 2014).

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