[Geographic analyses as a foundation for evidence-based public health interventions: the example identification and typology of risk clusters for mumps, measles, and rubella].

backgroundIdeally, health services and interventions to improve immunization rates should be tailored to local target populations, such as spatial clusters. However, to date, little attention has been paid to spatial clusters of underimmunization and have instead been typified based on small-scale data.

aimUsing the example of vaccination against measles, mumps, and rubella (MMR) in children, the present study aims to (1) identify the spatial distribution of insufficient MMR vaccination in Westphalia-Lippe on a small scale, (2) identify specific, spatial risk clusters with insufficient vaccination protection, and (3) describe spatial-neighborhood influencing factors of the different risk clusters as starting points for public health interventions. MATERIAL AND

methodsAccount data from the Kassenärztliche Vereinigung Westfalen-Lippe (KVWL) were used as a basis. Birth cohorts 2013-2016 of children with statutory health insurance were formed and aggregated at postcode level (n = 410). Statistically significant, spatially compact clusters and relative risks (RRs) of underimmunization were identified. Local risk models were estimated in binary logistic regressions based on spatial-neighborhood variables. RESULTS AND DISCUSSION: Two significant clusters of underimmunization were identified for each of the vaccination rates "at least one MMR vaccination" and "both MMR vaccinations." Significant risk factors for low immunization rates included age structure, socioeconomic variables, population density, medical coverage, and value attitude. The proposed methodology is suitable for describing spatial variations in vaccination behavior based on identified typologies for targeted evidence-based interventions.