Area Of Bavaria Research Articles

Post‐2015 refugees in Germany: “Culture of welcome”, solidarity or exclusion?

Post‐2015 refugees in Germany: “Culture of welcome”, solidarity or exclusion?

Modelling potential biotope composition on a regional scale revealed that climate variables are stronger drivers than soil variables

AbstractAimEnvironmental conditions define the suitability of an area for biotopes, and any area can be suitable for several biotopes. However, most previous studies modelled the distribution of single biotopes ignoring the potential co‐occurrence of biotopes in one area, which limits the usefulness of such models for conservation and restoration planning. In this study, we described the potential biotope composition of an area in response to environmental conditions.LocationBavaria, Federal State of Germany.MethodsBased on the Bavarian biotope mapping data, we modelled the distribution of 29 terrestrial biotopes based on six climate variables and six chemical and four physical soil properties using the species distribution modelling algorithm Maxent.ResultsFor most biotopes, we found that climate variables were more important than soil variables for the biotope distribution and that the area of the predicted biotope distribution was larger than the observed distribution. The potential biotope composition illustrated that while 8% of the area in Bavaria was not sufficiently suitable for any analysed biotope, 92% of the modelled area in Bavaria was suitable for at least one biotope, 84% for two and 77% for at least three biotopes. The difference in suitability between the most suitable biotopes in composition was minor. Further, over one‐quarter of the modelled area was suitable for 6–8 different biotopes.Main ConclusionsOur study showed that considering a composition of potentially suitable biotopes in a raster cell, instead of only the most suitable biotope, provides valuable information to identify conservation priorities and restoration opportunities.

Programs to encourage working as a general practitioner in rural areas: why do medical students not want to participate? A cross-sectional study

BackgroundIn many countries, not enough students are interested to work as general practitioners in rural areas. To solve this problem, several, sometimes partly extracurricular, programs have been developed. Most of these programs are based on continuity, which means that students stay in a rural region for an extended period of time, by completing clerkships. Although the effects of these programs are positive, it is often difficult to motivate students to participate. The purpose of the present study is to get insight into the reasons why students choose not to participate in these programs.MethodsWe carried out a questionnaire study among medical students in the clinical phase of the Technical University of Munich in Germany. First, we asked the students whether they actively informed themselves about the program which aims to reduce the shortage of general practitioners in rural areas in Bavaria. Furthermore, the questionnaire focused on the reasons for not participating in this program.ResultsBased on the answers of 442 students from study years 3–6, the most frequently chosen reason for not participating in the program is “identification with another discipline” with 61.0%, directly followed by “not willing to commit long-term” (56.1%). In third place is “personal connections to another region” with 30.5%. In the open comments, we find the same reasons: many students do not want to commit to a certain direction too early. In addition, students indicate that the number of regions where this program is offered is too limited for them.ConclusionsOffering programs to prepare and motivate students for work as general practitioners in rural areas can contribute to increasing the pool of future general practitioners. To encourage students to participate in such a program, it is important to consider the motives of students. Many students who might be interested in general practice do not choose to take part in such a program because they do not want to commit to a particular specialty or region at an early stage. It is important to take these insights into account when designing and implementing these programs.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis.

BackgroundArea deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.MethodsIn this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.ResultsDeprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.ConclusionsIn more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

Cognitive and Non-Cognitive, Doctor-Relevant Competencies for the Selection of Prospective Country Doctors in Bavaria: Corona-Compliant Selection Process Across Institutes

The challenge is to counteract the undersupply of doctors in rural areas in Bavaria. As one possibility, the "Country Doctor Quota" measure provides for the allocation of dedicated medical study places for prospective specialists with general practice activities. A specific selection process for future medical students was established and safely implemented under the safety and hygiene conditions of the corona pandemic. In Bavaria, a two-stage selection process was developed and used in full for the first time in 2021 for the selection of students. Due to the corona pandemic, only the results of stage 1 of the process for the selection of prospective students were taken into account in the previous year. Cognitive and non-cognitive criteria were included in a 2-stage selection process. In the second stage, physician-relevant competencies (e. g. resilience, problem-solving ability, empathy and compassion, communication skills, ethical decision-making, as well as consulting and social skills) were assessed by Bavarian family doctors in four multiple mini interviews and a 10-minute, semi-structured individual interview. A maximum of 100 points could be achieved. A digital, contact-free selection process was established and successfully implemented to ensure protection and hygiene conditions in the context of the interviews. A total of 436 people applied as part of the Bavarian country doctor quota for the 2021/2022 winter semester; 226 applicants were invited to the selection interviews at the second stage, of which 115 applicants received a place at the university. 64% of the participants had already completed medical vocational training, the high school graduation grade average was 2.4. The developed selection process identified applicants as part of the Bavarian country doctor quota and selected using objective criteria. All available medical study places were filled with the 115 finally selected applicants. To what extent the selected applicants (can) counteract the impending shortage of prospective specialists with general practitioner work remains to be seen.

Plural valuation in space: mapping values of grasslands and their ecosystem services

ABSTRACT The agricultural management of grasslands not only is strongly linked to fodder production but also provides other valuable ecosystem services such as carbon sequestration, nutrient regulation, and recreation. Capturing the values that society places on such ecosystem services is a step to provide management recommendations. To elicit the societal value of grasslands and their ecosystem services, it is important to consider multiple dimensions, namely, instrumental, intrinsic, and relational values. We conducted surveys with citizens in 2018 and 2020 in two study areas in Bavaria, Germany: one grassland-dominated and one with mixed agricultural land use. In the surveys, the respondents were invited to map up to seven points in their respective regions where they perceived grasslands to be ‘especially valuable’. Also, the respondents could provide reasons for this selection. These verbatims were classified into instrumental, intrinsic, and several sub-types of relational values using Qualitative Content Analysis. Next, we conducted a hotspot analysis that revealed spatial hotspots and coldspots for each value type . Besides some overlaps, we found that hotspots of instrumental, intrinsic, and relational values varied in space. A Constrained Correspondence Analysis underlined the trade-offs between instrumentally valued grasslands that are perceived as suitable to supply provisioning services and intrinsically valued grasslands that are closely related to relational values such as care. The results show that grasslands and their ecosystem services are valued for a variety of reasons on different locations, and point out the need for further investigations of the spatial distribution of values associated with ecosystem services.

Disparities in accessibility to evidence-based breast cancer care facilities by rural and urban areas in Bavaria, Germany.

Breast cancer (BC), which is most common in elderly women, requires a multidisciplinary and continuous approach to care. With demographic changes, the number of patients with chronic diseases such as BC will increase. This trend will especially hit rural areas, where the majority of the elderly live, in terms of comprehensive health care. Accessibility to several cancer facilities in Bavaria, Germany, was analyzed with a geographic information system. Facilities were identified from the national BC guideline and from 31 participants in a proof-of-concept study from the Breast Cancer Care for Patients With Metastatic Disease registry. The timeframe for accessibility was defined as 30 or 60 minutes for all population points. The collection of address information was performed with different sources (eg, a physician registry). Routine data from the German Census 2011 and the population-based Cancer Registry of Bavaria were linked at the district level. Females from urban areas (n = 2,938,991 [ie, total of females living in urban areas]) had a higher chance for predefined accessibility to the majority of analyzed facilities in comparison with females from rural areas (n = 3,385,813 [ie, total number of females living in rural areas]) with an odds ratio (OR) of 9.0 for cancer information counselling, an OR of 17.2 for a university hospital, and an OR of 7.2 for a psycho-oncologist. For (inpatient) rehabilitation centers (OR, 0.2) and genetic counselling (OR, 0.3), women from urban areas had lower odds of accessibility within 30 or 60 minutes. Disparities in accessibility between rural and urban areas exist in Bavaria. The identification of underserved areas can help to inform policymakers about disparities in comprehensive health care. Future strategies are needed to deliver high-quality health care to all inhabitants, regardless of residence.

Dermacentor reticulatus and Babesia canis in Bavaria (Germany)-A Georeferenced Field Study with Digital Habitat Characterization.

The hard tick Dermacentor reticulatus transmits Babesia canis, the causative agent of canine babesiosis. Both the occurrence and local distribution of D. reticulatus as well as infection rates of questing ticks with B. canis are thus far poorly known in Bavaria, Germany. The objectives of this study were to conduct (1) a georeferenced field study on the occurrence of D. reticulatus with digital habitat characterization and (2) a PCR analysis of D. reticulatus collected in Bavaria for infection with B. canis. Dermacentor reticulatus were collected by flagging at 60 sites specifically selected according to habitat conditions and screened individually for Babesia DNA. A digital habitat characterization for D. reticulatus was performed according to results of the field analysis including the parameters land use, proximity to water, “potential natural vegetation”, red deer corridors and climate data. Altogether, 339 D. reticulatus ticks (214 females and 125 males) were collected between 2010 and 2013 at 12 out of 60 sampling sites. All 12 sites were characterized by high humidity with marshy areas. Babesia canis DNA was detected in 1 out of 301 (0.3%) questing D. reticulatus in Bavaria. The digital habitat characterization revealed 15 forest areas in Bavaria with similar ecological characteristics as the sites positive for D. reticulatus.

So close and yet so different: The importance of considering temporal dynamics to understand habitat selection

Habitat selection of animals is influenced by spatial heterogeneity as well as temporal environmental dynamics. In addition, human activities potentially have severe influences on the habitat selection of animals, often resulting in more nocturnal behavior. We investigated seasonal and circadian habitat selection patterns of red deer (Cervus elaphus) on a military training area in Bavaria (Germany). Individual deer ranged on two neighboring, but non-overlapping sites differing in landscape composition and human activity. Using GPS telemetry data, we visually investigated selection patterns and then fitted step-selection functions to assess multiple approaches to account for temporal (i.e., diel and seasonal) effects and for the impact of habitat conditions on selection. We first showed that the way in which time of day is considered in step-selection functions is essential for obtaining ecologically meaningful results, and that the usual ways of including time (i.e., either based on clock-time or based on night vs. day categories) can lead to incomplete or misleading conclusions. Furthermore, we found that individuals followed either circadian or seasonal habitat selection patterns, depending on the site they inhabited. This can be explained by differences in disturbance between the two sites. Except in winter, individuals selected for open habitats during the night irrespective of human activity level, but only individuals from the more disturbed site selected for covered habitats during the day. Our results highlight the importance of carefully considering the appropriate temporal scale for habitat selection analyses. Our findings also indicate that red deer are not a crepuscular or nocturnal species per se, as is often observed in human-dominated landscapes. Instead, our results imply that nocturnality in red deer is an effect of adaption to human activities.

Abstract P6-11-12: Access to certified breast cancer centers in the mainly rural state of Bavaria, Germany: A structural health geographical analysis

Abstract Background: In Germany, evidence- and consensus-based recommendations for the treatment of breast cancer patients are available from the national guideline. To ensure implementation of these standards in clinical routine care, two different certification programs for breast cancer exist in Germany: 1) accreditation ‘Organ Cancer Center’ of the German Cancer Society (“Deutsche Krebsgesellschaft” DKG); 2) Disease Management Program (DMP) developed by Health Insurance Companies. For our analysis we focused on Bavaria due to its mainly rural character, which can lead to challenges in patients’ medical supply with long travel distances. We aimed to investigate the accessibility of certified Breast Cancer Centers (cBCC) in rural and urban areas of Bavaria and to estimate how many inhabitants and potentially breast cancer patients might be affected. Methods: Accessibility of cBCC was defined according to travel time by car (or taxi) within 30 minutes. Addresses of cBCCs were identified through the homepages of the DKG, the Bavarian Association of Statutory Health Insurance Physicians (KVB), and a health insurance company. Data collection took place between August and December 2018. Only cBCC located in Bavaria with valid certification at point of search were eligible. Using ArcGIS, a routing network was created to identify clear catchment areas for each facility. The modeled speeds on which the traffic is based are street specific and consider the average regional traffic situations. The latter was then combined with the disaggregated 100 × 100 meters population data for the Census 2011, which allowed analyzing absolute population on a fine spatial resolution. Aggregated data on incident and prevalent breast cancer rates (women only) were obtained from the Epidemiological Bavarian Cancer Registry and merged on district level. As only aggregated data from the Bavarian Cancer Registry were utilized, a formal ethics committee (EC) review was not required. A declaration of no objection by the EC of the University of Würzburg is available (#2019042402). Results: A total of 58 cBCC (both DKG/DMP: n=44, DMP only: n=14) were identified and included in our analysis. The predefined accessibility coverage comprises 76% of Bavaria. Focusing on all Bavarian administrative areas (n=96) we identified following categories: n=38 had full access, n=56 partial access and n=2 no access. On population level, n=5,533,166 (87.5%) females reach a cBCC within 30min travel time. Whereas about 800.000 (12.5%) women have hampered access with about 3/4 living in rural regions. Data from the Bavarian Cancer Registry reveal that non-accessibility might affect ca. 5.000 prevalent and ca. 1.500 newly-diagnosed female breast cancer patients - based on a hypothetical stable age-standardized (EU) incidence and 5-yrs prevalence rate. Conclusion: Our analysis revealed that there is no Bavaria-wide accessibility to cBCC and that disparities between rural and urban areas exist. Integrating GIS methods to health care service research allows 1) identifying regions with limited access to evidence-based structures (e.g. cBCC) and 2) planning of structures needed from a public health point of view. Our findings can be used to inform policy makers about injustice regarding health care accessibility. Furthermore, results can serve for developing and evaluating telemedical strategies to deliver high quality health care to all inhabitants regardless of residence. Citation Format: Stephanie Stangl, Sebastian Rauch, Jürgen Rauh, Martin Meyer, Jacqueline Müller-Nordhorn, Manfred Wildner, Peter U. Heuschmann, Achim Wöckel. Access to certified breast cancer centers in the mainly rural state of Bavaria, Germany: A structural health geographical analysis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-11-12.

Die Ermordung und das „Sterben-Lassen“ von psychisch und physisch kranken ausländischen ZivilarbeiterInnen im „Gau Oberdonau“

In Second World War 8.4 million foreign civilian workers were used for labour in theGerman Reich, many of them were forced labourers. Civilian workers from Polandand the Soviet Union, who became mentally or physically ill and could not be cured inshort time, were sent back to their home countries. In May 1943 the transports ofmentally ill forced labourers to their home countries were stopped, as the NationalSocialist „euthanasia“ bureaucracy intervened and brought the labourers from “mentalinstitutions” to special facilities where they were killed. In 1943 and 1944 severaltransports with mentally ill forced labourers from mental institutions in the area ofBavaria and Austria are documented. In most of these cases the destinations of thetransports are unknown. The working hypothesis of this article is that the transportswent to Hartheim castle, which served as “killing centre” from 1940 to 1944. Physicallyill civilian workers were detained in camps, where many of them died because of lackof food and medical care and because of the bad hygienic situation.

Forest Damage Assessment Using Deep Learning on High Resolution Remote Sensing Data

Storms can cause significant damage to forest areas, affecting biodiversity and infrastructure and leading to economic loss. Thus, rapid detection and mapping of windthrows are crucially important for forest management. Recent advances in computer vision have led to highly-accurate image classification algorithms such as Convolutional Neural Network (CNN) architectures. In this study, we tested and implemented an algorithm based on CNNs in an ArcGIS environment for automatic detection and mapping of damaged areas. The algorithm was trained and tested on a forest area in Bavaria, Germany. . It is a based on a modified U-Net architecture that was optimized for the pixelwise classification of multispectral aerial remote sensing data. The neural network was trained on labeled damaged areas from after-storm aerial orthophotos of a ca. 109 k m 2 forest area with RGB and NIR bands and 0.2-m spatial resolution. Around 10 7 pixels of labeled data were used in the process. Once the network is trained, predictions on further datasets can be computed within seconds, depending on the size of the input raster and the computational power used. The overall accuracy on our test dataset was 92 % . During visual validation, labeling errors were found in the reference data that somewhat biased the results because the algorithm in some instance performed better than the human labeling procedure, while missing areas affected by shadows. Our results are very good in terms of precision, and the methods introduced in this paper have several additional advantages compared to traditional methods: CNNs automatically detect high- and low-level features in the data, leading to high classification accuracies, while only one after-storm image is needed in comparison to two images for approaches based on change detection. Furthermore, flight parameters do not affect the results in the same way as for approaches that require DSMs and DTMs as the classification is only based on the image data themselves, and errors occurring in the computation of DSMs and DTMs do not affect the results with respect to the z component. The integration into the ArcGIS Platform allows a streamlined workflow for forest management, as the results can be accessed by mobile devices in the field to allow for high-accuracy ground-truthing and additional mapping that can be synchronized back into the database. Our results and the provided automatic workflow highlight the potential of deep learning on high-resolution imagery and GIS for fast and efficient post-disaster damage assessment as a first step of disaster management.

QoI Fungicide Resistance Mutations in Alternaria solani and Alternaria alternata are Fully Established in Potato Growing Areas in Bavaria and Dual Resistance against SDHI Fungicides is Upcoming

Alternaria leaf spots caused by Alternaria solani and Alternaria alternata are a major foliar disease of potatoes. Reduced sensitivity of A. solani and A. alternata towards Quinone outside inhibitors (QoI) fungicides has been observed in Europe. QoI-insensitive A. alternata isolates carry a G143A amino acid exchange caused by a single nucleotide polymorphism (SNP) in the cytochrome b gene. A. solani evolved a similar F129L mutation. A shift from the predominant A. solani genotype I to genotype II, which was exclusively associated with the F129L mutation, was observed in Germany after QoI approval for Alternaria control. Here, we found QoI mutations to be highly abundant in A. solani and A. alternata field isolates, collected in 2016 in Bavaria, located in southeastern Germany. The frequency of the F129L mutation, but not of A. solani genotype II, was higher than in the last available study. This might be due to that we also found the F129L mutation in genotype I, indicating QoI resistance progression through the previously unaffected genotype. In contrast to previous data, QoI mutations were present in all examined areas. An analysis of SNP diversity pointed to the region of Lower Bavaria as a hotspot for F129L mutation evolution. Reduced sensitivity of Alternaria spp. towards succinate dehydrogenase inhibitors (SDHI) fungicides is an emerging issue in Europe. We observed the presence of SDHI mutations, but only in combination with QoI mutations, indicating a further adaption to applied fungicides and a selection for dual fungicide resistance.

Using data from online geocoding services for the assessment of environmental obesogenic factors: a feasibility study

BackgroundThe increasing prevalence of obesity is a major public health problem in many countries. Built environment factors are known to be associated with obesity, which is an important risk factor for type 2 diabetes. Online geocoding services could be used to identify regions with a high concentration of obesogenic factors. The aim of our study was to examine the feasibility of integrating information from online geocoding services for the assessment of obesogenic environments.MethodsWe identified environmental factors associated with obesity from the literature and translated these factors into variables from the online geocoding services Google Maps and OpenStreetMap (OSM). We tested whether spatial data points can be downloaded from these services and processed and visualized on maps. True- and false-positive values, false-negative values, sensitivities and positive predictive values of the processed data were determined using search engines and in-field inspections within four pilot areas in Bavaria, Germany.ResultsSeveral environmental factors could be identified from the literature that were either positively or negatively correlated with weight outcomes in previous studies. The diversity of query variables was higher in OSM compared with Google Maps. In each pilot area, query results from Google showed a higher absolute number of true-positive hits and of false-positive hits, but a lower number of false-negative hits during the validation process. The positive predictive value of database hits was higher in OSM and ranged between 81 and 100% compared with a range of 63–89% for Google Maps. In contrast, sensitivities were higher in Google Maps (between 59 and 98%) than in OSM (between 20 and 64%).ConclusionsIt was possible to operationalize obesogenic factors identified from the literature with data and variables available from geocoding services. The validity of Google Maps and OSM was reasonable. The assessment of environmental obesogenic factors via geocoding services could potentially be applied in diabetes surveillance.

Impacts of climate and demographic change on future skier demand and its economic consequences – Evidence from a ski resort in the German Alps

Over the next decades the ski tourism industry in the Alps must deal with two major challenges. First, demographic change will lead to aging skiers and declining skier demand. Second, climate change will result in a decreasing number of operating days and optimal ski days, reduced snow reliability and increasing operating costs in some destinations. Both impact factors cause a change in travel behavior of ski tourists. Effects on skier demand have been quantified for Austria, though not for the German Alps, but previous publications lack any quantification of the resulting consequences on future turnover at destinations or compensation for losses. This demand side study addresses this gap using the example of the Sudelfeld ski area in Bavaria, German Alps. It estimates the impact of climate and demographic change on skier days (first entries) and future turnover at the destination. Furthermore, it presents a rough indication on how many non-skiing tourists have to be won by the destination to substitute for the calculated changes in demand. The results demonstrate that climate change will have a solely negative impact on skier demand for the 2030s and 2040s (−13.5% to −31.1%) compared to demographic change (+1.6% to −31.1%). This causes a change of the destination's turnover from +11.8% up to −56.4% (values adjusted to inflation) in the same period compared to the average of the last four winter seasons. Thus, adaptation measures need to be identified to reduce potential economic losses in the next decades.

Registration of Multi-Sensor Bathymetric Point Clouds in Rural Areas Using Point-to-Grid Distances

This article proposes a method for registration of two different point clouds with different point densities and noise recorded by airborne sensors in rural areas. In particular, multi-sensor point clouds with different point densities are considered. The proposed method is marker-less and uses segmented ground areas for registration.Therefore, the proposed approach offers the possibility to fuse point clouds of different sensors in rural areas within an accuracy of fine registration. In general, such registration is solved with extensive use of control points. The source point cloud is used to calculate a DEM of the ground which is further used to calculate point to raster distances of all points of the target point cloud. Furthermore, each cell of the raster DEM gets a height variance, further addressed as reconstruction accuracy, by calculating the grid. An outlier removal based on a dynamic threshold of distances is used to gain more robustness against noise and small geometry variations. The transformation parameters are calculated with an iterative least-squares optimization of the distances weighted with respect to the reconstruction accuracies of the grid. Evaluations consider two flight campaigns of the Mangfall area inBavaria, Germany, taken with different airborne LiDAR sensors with different point density. The accuracy of the proposed approach is evaluated on the whole flight strip of approximately eight square kilometers as well as on selected scenes in a closer look. For all scenes, it obtained an accuracy of rotation parameters below one tenth degrees and accuracy of translation parameters below the point spacing and chosen cell size of the raster. Furthermore, the possibility of registration of airborne LiDAR and photogrammetric point clouds from UAV taken images is shown with a similar result. The evaluation also shows the robustness of the approach in scenes where a classical iterative closest point (ICP) fails.

Use of pre-hospital emergency medical services in urban and rural municipalities over a 10\u2009year period: an observational study based on routinely collected dispatch data

BackgroundPre-hospital emergency medical services (EMS) are an integral part of emergency medical care. EMS planning can be achieved by analyzing patterns of use. However, long-term time trends of EMS use have rarely been studied. The objective of this retrospective study was to investigate utilization patterns over a ten year period, and to compare utilization trends between urban and rural municipalities and between events with and without prehospital emergency physician (PEP) dispatch.MethodsRoutine data collected by 26 dispatch centers in the federal state of Bavaria, Germany, from 2007 to 2016 was analyzed. Emergency locations were classified into five levels of rurality. Negative binomial mixed effects regression models were fitted to predict emergency rates and to investigate differences in rates and utilization trends. Graphical representation methods were used to compare distribution of transport rates and distribution across daytime and weekday.ResultsTwelve million two hundred thousand one hundred fifty-five dispatches assigned to 7,725,636 single emergencies were included. The mean number of emergencies per year and 1000 population (emergency rate) was 42.8 (±16.0) in rural municipalities and 80.7 (±9.3) in large cities. Compared to rural municipalities, cities had higher emergency rates without (IRR = 3.0, CI 2.2–4.0) and with pre-hospital physicians (IRR = 1.5, CI 1.2–2.0). Between 2007 and 2016, the absolute number of emergencies increased by 49.1%. Estimated annual percent change of emergency rates without physician activation ranged from 5.7% (CI 4.3–7.1) in cities to 7.8% (CI 7.6–7.9) in rural areas. Changes in emergency rates with physician attendance were lower, with estimated increases between 1.3 and 2.4%. The average proportion of patients transported to a hospital was lower in cities and remained unchanged. There were no considerable differences or changes in the distribution across daytime and weekdays.ConclusionDifferences between cities and other areas suggest that the planning of EMS should be targeted to regional characteristics. A substantial increase in emergency rates was observed across all areas of Bavaria, but did not impact transport rates or temporal distributions. Further research is needed to better understand the urgency of emergency events and reasons behind increasing EMS utilization.

Skryptoria klasztorne i średniowieczne ustawodawstwo cysterskie o książce

The oldest book which was on the territory of the early Piast in the second half of the tenth century derived, comes from the Benedictine scriptoria from the area of Bavaria, Saxony, Rhineland and Lorraine and contained the biblical texts and established liturgical canon necessary for the celebration of the Mass. Preserved from the twelfth century regulations of Cistercian chapters which decided that in each monastery there should be: missal, epistolary, Gospel Book, gradual, antiphonary, liber hymnarius, psaltery, lectionary and calendar. These regulations made the copywriter’s work particularly important. The importance attributed to their work is attested to, for example, by their release by the General Chapter of the Order from other dutiesin favor of the monastery, and by the permission in some cases to work at night. In Cistercian scriptoria apart from copying of the liturgical texts, the memorials so-called libri virorum et mortuorum, there were preparing documents for the current administrative and economic work of the monastery; in addition there were writing yearbooks, obituaries, monastery chronicles or epitaphs poem. There were recording notes of daily life outside the walls of the enclosure,names and functions of friars particularly events that took place away from the monastery or notes about elementary disasters happening in the proximate areas, the damages of monastery caused by floods, fires or epidemics. The preserved manuscript codes are an priceless source for learning the minds, interpersonal relationships prevailing in the small communities, their relations with their nearest surrounding and medieval way of seeing the world.

Designing a Vissim-Model for a motorway network with systematic calibration on the basis of travel time measurements

Abstract This paper describes a systematic calibration process of a motorway network in Vissim, based on travel time measurements that were derived from limited number of Bluetooth detectors. The case study that is developed, establishes an example for practitioners that are interested in designing motorway networks with microscopic simulation tools. The three-hour microscopic traffic simulation model that will be analyzed, replicates a motorway network which is located in the wider area of Bavaria in Germany and consists of 500 links, 113 nodes and 1820 origin-destination pairs. Model’s systematic calibration and validation under the suggested approach show very good results in 96.5 % of the created intervals, for both cars and heavy vehicles.

Health-Monitoring-Units (GME) in Bavaria: standardized and repeated data collection of children’s health status and influential factors

Introduction Supported by the Bavarian State Ministry of health, in 2004 health monitoring units (GME) were established by the Bavarian Health and Food Safety Authority. The aim is to collect health data of children. Methods: During school entrance examinations, the parents of preschool children complete GME provided questionnaires regarding different health topics. This data is analyzed as 1) cross-sectional studies and 2) cohort studies, in which the parents and the children are repeatedly questioned. These surveys are conducted in three urban (Munich, Ingolstadt, Bamberg city) and three rural regions (Schwandorf, Günzburg, Bamberg rural district) within Bavaria. Main topics of the GME are widespread diseases like asthma and allergies and influencing factors. Results Recent analyses of the GME data indicate that the prevalence of asthma and allergies and the symptoms of preschool children were fairly stable from 2004 to 2012. Furthermore no differences between city and rural prevalence were present. After the introduction of the smoking ban in public areas in Bavaria, the passive smoke exposure of children at home decreased from 14,3% (2004) to 7,2% (2012). Respiratory diseases showed no clear association with exposure to passive smoking at home, except in 2012, were asthma was associated with the general smoking behavior (includes smoking outside) of parents (OR=1.6; 95% KI [1.1-2.3]). Conclusion The GME provide standardized and repeated cross-sectional as well as longitudinal data that allow monitoring the health status of children and influencing factors. In the past, prevention programs regarding obesity and ultraviolet radiation exposure have already been evaluated using GME. Furthermore with the GME it is possible to monitor potential health effects of relevant changes in legislation, such as the smoking ban. The potential of GME data is underlined by its current use in the analysis of associations between pollen records and children’s allergic sensitization.