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BackgroundTick-borne encephalitis (TBE) is the most important tick-borne viral disease in Eurasia and causes disease in humans and in a number of animals, among them dogs and horses. There is still no good correlation between tick numbers, weather conditions and human cases. There is the hypothesis that co-feeding due to simultaneous occurrence of larvae and nymphs may be a factor for the increased transmission of the virus in nature and for human disease. Based on long-term data from a natural TBEV focus, phylogenetic results and meteorological data we sought to challenge this hypothesis.MethodsTicks from an identified TBE natural focus were sampled monthly from 04/2009 to 12/2018. Ticks were identified and pooled. Pools were tested by RT-qPCR. Positive pools were confirmed by virus isolation and/or sequencing of additional genes (E gene, NS2 gene). Temperature data such as the decadal (10-day) mean daily maximum air temperature (DMDMAT) were obtained from a nearby weather station and statistical correlations between tick occurrence and minimal infection rates (MIR) were calculated.ResultsIn the study period from 04/2009 to 12/2018 a total of 15,530 ticks (2,226 females, 2,268 males, 11,036 nymphs) were collected. The overall MIR in nymphs over the whole period was 77/15,530 (0.49%), ranging from 0.09% (2009) to 1.36% (2015). The overall MIR of female ticks was 0.76% (17/2,226 ticks), range 0.14% (2013) to 3.59% (2016). The overall MIR of males was 0.57% (13/2,268 ticks), range from 0.26% (2009) to 0.97% (2015). The number of nymphs was statistically associated with a later start of spring/vegetation period, indicated by the onset of forsythia flowering.ConclusionThere was no particular correlation between DMDMAT dynamics in spring and/or autumn and the MIR of nymphs or adult ticks detected. However, there was a positive correlation between the number of nymphs and the number of reported human TBE cases in the following months, but not in the following year. The hypothesis of the importance of co-feeding of larvae and nymphs for the maintenance of transmission cycle of TBEV in nature is not supported by our findings.

Background Little is known regarding the changing seasonality of infections with the tick-borne encephalitis virus (TBEV) and the incidence of the resulting disease over the last two decades. Seasonal patterns have to our knowledge not previously been systematically investigated and are poorly understood. We investigate emerging seasonal changes in clinical aspects like potentially increasing hospitalization during the year, variations in clinical symptoms and disease severity during the season and seasonal dynamics of fatal outcomes. Material and methods TBEV infection became a notifiable disease in Germany in 2001. We used the national reporting dataset spanning from 2001–2018, provided by the Robert Koch-Institute (RKI). There were general epidemiological variables available, including “symptom onset”, “age” and “sex”. Furthermore, several variables documented disease severity. These included “CNS symptoms”, “myelitis”, “fatal outcome” and “hospitalization”. Potential factors influencing the occurrence of CNS symptoms, myelitis, hospitalizations and fatal outcome were analyzed using logistic regression models. Linear trends, including the “time point in year” at which TBEV infection related symptoms were detected, were tested using calendar year as a continuous covariate. In addition, seasonal trends and age and sex specific differences were exploratively tested for non-linear effects using restricted cubic splines with knot locations based on Harrell's recommended percentiles. Finally, the dynamic relationship between in-seasonal trends year of detection, sex and age was tested using interaction terms. Results 6,073 TBEV infection cases from 2001–2018 were included in our analysis. We find that from 2001–2018 TBEV infections are reported 0.69 days earlier each year (p

Objectives We examine the volume–outcome relationship in isolated transcatheter aortic valve implantations (TAVI). Our interest was whether the volume–outcome relationship for TAVI exists on the centre level, whether it occurs equally for different outcomes and how it develops over time. Design Secondary data analysis of electronic health records. The comprehensive German Federal Bureau of Statistics Diagnosis Related Groups database was queried for data on all isolated TAVI procedures performed in Germany between 2008 and 2014. Logistic and linear regression analyses were carried out. Risk adjustment was applied using a predefined set of patient characteristics to account for differences in the risk factor composition of the patient populations between centres and over time. Centres performing TAVI were stratified into groups performing 48 hours, length of hospital stay and reimbursement. Results Between 2008 and 2014, a total of 43 996 TAVI procedures were performed in 113 different centres in Germany with a total of 2532 cases of in-hospital mortality. Risk-adjusted in-hospital mortality decreases over the years and is lower the higher the annual procedure volume at the centre is. The magnitude of the latter effect declines over the observation period. Our results indicate a ceiling effect in the volume–outcome relationship: the volume–outcome relationship is eminent in circumstances of relatively unfavourable outcomes. Alongside improving outcomes, however, the volume–outcome relationship decreases. Also, a volume–outcome relationship seems to be absent in circumstances of constantly low event rates. Conclusions The hypothesised volume–outcome relationship for TAVI exists but diminishes and may disappear over time. This should be taken into account when considering mandatory minimum thresholds.

Marginal effects for the two parts of the two-part model separately. Marginal effects are shown for the two parts of the two-part model separately. As shown in Table 2, two-part models with one (time: month 1 vs. month 2–24, or month 1–12 vs month 13–24) or two (time and sex or procedure or ...) categorical covariates are conducted with a logistic regression analysis for part one and a generalised linear model with the log link and gamma distribution for the second part. Marginal effects for the combined models are shown on the raw scale (€ per month). 95% confidence intervals in brackets. All estimated prices reflect cost estimates in Euro (basis year 2011) from a societal perspective. (DOCX 38 kb)

Two year monthly cost estimates of patients treated for aortic valve stenosis (including also patients receiving drug-based therapy). Separate two-part models, with one (only time: month 1 vs. month 2–24, or month 1–12 vs month 13–24) or two (time and sex or procedure or ...) categorical covariates are conducted with a logistic regression analysis for part one and a generalised linear model with the log link and gamma distribution for the second part. Marginal effects for the combined models are shown on the raw scale (€ per month). 95% confidence intervals in brackets. All estimates reflect cost estimates in Euro (basis year 2011) from a societal perspective. (DOCX 25 kb)