Epidemiology of Lyme borreliosis based on outpatient claims data of all people with statutory health insurance, Germany, 2019

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Abstract

Introduction: Evidence of nationwide and regional morbidity of Lyme borreliosis (LB) in Germany is lacking. Aims: We calculated the total number of incident LB cases in Germany in 2019, compared regional variations, investigated the extent of possible underreporting in notification data and examined the association between high incidence areas and land cover composition. Methods: We used outpatient claims data comprising information for people with statutory health insurance who visited a physician at least once between 2010 and 2019 in Germany (n=71,411,504). The ICD-10 code A69.2 was used to identify incident LB patients. Spatial variations of LB were assessed by means of Global and Local Moran’s Index at district level. Notification data were obtained for nine federal states with mandatory notification from the Robert Koch Institute (RKI). Results: Of all insured, 128,177 were diagnosed with LB in 2019, corresponding to an incidence of 179 per 100,000 insured. The incidence varied across districts by a factor of 16 (range: 40–646 per 100,000). We identified four spatial clusters with high incidences. These clusters were associated with a significantly larger proportion of forests and agricultural areas than low incidence clusters. In 2019, 12,264 LB cases were reported to the RKI from nine federal states, while 69,623 patients with LB were found in claims data for those states. This difference varied considerably across districts. Conclusions: These findings serve as a solid basis for regionally tailored population-based intervention programmes and can support modelling studies assessing the development of LB epidemiology under various climate change scenarios.

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APA

Akmatov, M. K., Holstiege, J., Dammertz, L., Heuer, J., Kohring, C., Lotto-Batista, M., … Bätzing, J. (2022). Epidemiology of Lyme borreliosis based on outpatient claims data of all people with statutory health insurance, Germany, 2019. Eurosurveillance, 27(32). https://doi.org/10.2807/1560-7917.ES.2022.27.32.2101193

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