Abstract
ObjectiveTo illustrate how data triangulation involving routine data sources can optimize data usage and provide insights into vaccine programme effectiveness by considering measles vaccination and disease incidence data in England.MethodsWe obtained data on measles, mumps and rubella (MMR) vaccine coverage in birth cohorts from 1985 to 2016 from child health records and adjusted for under-ascertainment and catch-up campaigns. We assumed that the population had no natural immunity and that vaccine effectiveness was 95% for one dose and 99.75% for two doses. Vaccinations done outside the routine schedule and in people who entered England after the age of immunization were identified from primary care records. Measles susceptibility was defined as the percentage of individuals who were not immune despite all vaccination activities. We triangulated measles susceptibility and incidence data.FindingsMedian susceptibility was 4.6% (range: 1.2–9.2). Among cohorts eligible for two MMR vaccine doses, those born between 1998 and 2004 were most susceptible. Measles incidence was highest in these cohorts. Data from primary care and child health records were comparable for cohorts after 2000, suggesting that little supplementary vaccination took place. For cohorts before 2000, primary care data quality was insufficient for accurately estimating coverage.ConclusionTriangulating routine data on measles vaccination coverage and disease surveillance provided new insights into population immunity and helped identify vulnerable groups, which was useful for prioritizing public health actions to close gaps in immunity. This approach could be applied in any country that routinely records vaccine coverage and disease incidence.
Highlights
A considerable amount of immunization coverage and surveillance data are available nationally, regionally and globally.[1]
We used the example of measles in England to illustrate how the triangulation of routine data sources, namely different sources on coverage of the combined measles, mumps and rubella (MMR) vaccine and measles incidence data, can help evaluate data quality and provide estimates of population immunity, which can be used to inform a national measles elimination strategy
We used data collected at the second birthday for individuals in birth cohorts after 2012–2013, who were too young during our study period to have had coverage of two doses assessed at 5 years of age, and for individuals in birth cohorts before 1992–1993, who were born before the second dose was included in the vaccination schedule
Summary
A considerable amount of immunization coverage and surveillance data are available nationally, regionally and globally.[1]. Where a disease is close to being eliminated and the remaining few percent of susceptible individuals are being targeted, the need for accurate data increases as vaccine coverage increases.[2] Synthesizing data from two or more sources (i.e. data triangulation) is a pragmatic approach to optimizing the use of existing data, thereby improving data quality and gaining insights into the performance of vaccine programmes.[1] In this study, we used the example of measles in England to illustrate how the triangulation of routine data sources, namely different sources on coverage of the combined measles, mumps and rubella (MMR) vaccine and measles incidence data, can help evaluate data quality and provide estimates of population immunity, which can be used to inform a national measles elimination strategy. As these data sources are available in most settings and for many diseases, with varying degrees of granularity and quality, our approach should be broadly replicable
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