Coverage of the 2011 Q Fever Vaccination Campaign in the Netherlands, Using Retrospective Population-Based Prevalence Estimation of Cardiovascular Risk-Conditions for Chronic Q Fever
Background
In 2011, a unique Q fever vaccination campaign targeted people at risk for chronic Q fever in the southeast of the Netherlands. General practitioners referred patients with defined cardiovascular risk-conditions (age >15 years). Prevalence rates of those risk-conditions were lacking, standing in the way of adequate planning and coverage estimation. We aimed to obtain prevalence rates retrospectively in order to estimate coverage of the Q fever vaccination campaign.
Methods
With broad search terms for these predefined risk-conditions, we extracted patient-records from a large longitudinal general-practice research-database in the Netherlands (IPCI-database). After validation of these records, obtained prevalence rates (stratified for age and sex) extrapolated to the Q fever high-incidence area population, gave an approximation of the size of the targeted patient-group. Coverage calculation addressed people actually screened by a pre-vaccination Q fever skin test and serology (coverage) and patients referred by their general practitioners (adjusted-coverage) in the 2011 campaign.
Results
Our prevalence estimate of any risk-condition was 3.1% (lower-upper limits 2.9-3.3%). For heart valve defects, aorta aneurysm/prosthesis, congenital anomalies and endocarditis, prevalence was 2.4%, 0.6%, 0.4% and 0.1%, respectively. Estimated number of eligible people in the Q fever high-incidence area was 11,724 (10,965-12,532). With 1330 people screened for vaccination, coverage of the vaccination campaign was 11%. For referred people, the adjusted coverage was 18%. Coverage was lowest among the very-old and highest for people aged 50–70 years.
Conclusion
The estimated coverage of the vaccination campaign was limited. This should be interpreted in the light of the complexity of this target-group with much co-morbidity, and of the vaccine that required invasive pre-vaccination screening. Calculation of prevalence rates of risk-conditions based on the IPCI-database was feasible. This procedure proved an efficient tool for future use, when prevalence estimates for policy, implementation or surveillance of subgroup-vaccination or other health-care interventions are needed.
