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 under-reporting 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.

No abstract

Background Research has shown that the risk for a severe course of COVID-19 is increased in the elderly population and among patients with chronic conditions. The aim of this study was to provide estimates of the size of vulnerable populations at high risk for a severe COVID-19 course in Germany based on the currently available risk factor data. Methods We used nationwide outpatient claims data from the years 2010 to 2019 collected according to § 295 of the Code of Social Law V, covering data for all statutory health insurees (SHI) which is nearly 87% of the entire German population. We considered 15 chronic disorders based on the current state of knowledge about clinically relevant risk factors. Three risk groups for a severe COVID-19 course were defined: 1. individuals in the age group 15 to 59 years with at least two comorbid disorders; 2. individuals aged 60 to 79 years with at least one disorder and 3. all individuals 80 years and older irrespective of the presence of chronic conditions. Regional analysis was conducted at the level of administrative districts (n = 401). Results Overall, 26% of individuals over 15 years were at high risk for a severe COVID-19 course in 2019 amounting to a total number of nearly 18.5 million individuals in Germany. This included 3.8 million individuals in risk group 1, 9.2 million in risk group 2, and 5.4 million in risk group 3, corresponding to 8, 50 and 100% of German inhabitants in the respective age groups. On the level of the 17 administrative regions formed by the Association of SHI Physicians (ASHIP regions), the proportion of individuals at high risk ranged between 21% in Hamburg and 35% in Saxony-Anhalt. Small-area estimates varied between 18% in Freiburg (Baden-Württemberg) and 39% in the district Elbe-Elster (Brandenburg). Conclusions The present study provides small-area estimates of populations at high risk for a severe COVID-19 course. These data are of particular importance for planning of preventive measures such as vaccination. Trial registration not applicable.

The aim of the study was to examine whether the COVID-19 pandemic had any effect on antibiotic prescription rates in children in Germany. Using the nationwide outpatient prescription data from the Statutory Health Insurance from 2010 to 2021, changes in the monthly prescriptions of systemic antibiotics dispensed to children aged 0–14 years were examined (n = 9,688,483 in 2021). Interrupted time series analysis was used to assess the effect of mitigation measures against SARS-COV-2, introduced in March and November 2020, on antibiotic prescription rates. In the pre-pandemic period, the antibiotic prescription rates displayed a linear decrease from 2010 to 2019 (mean annual decrease, –6%). In 2020, an immediate effect of mitigation measures on prescription rates was observed; in particular, the rate decreased steeply in April (RR 0.24, 95% CI: 0.14–0.41) and November 2020 (0.44, 0.27–0.73). The decrease was observed in all ages and for all antibiotic subgroups. However, this effect was temporary. Regionally, prescription rates were highly correlated between 2019 and 2020/2021. Substantial reductions in antibiotic prescription rates following the mitigation measures may indicate limited access to medical care, changes in care-seeking behavior and/or a decrease of respiratory infections. Despite an all-time low of antibiotic use, regional variations remained high and strongly correlated with pre-pandemic levels.

No abstract