Apis mellifera L.) was detected for the first time while foraging on a flower (a borage flower), most likely during an orientation flight before mating. The open, shallow corolla, and the excellent nectar secretion of the borage flower might have facilitated the queen bee activity. This new queen behaviour was based on the morphological traits of the specimen collected and photos taken in that moment. The observed foraging activity opens new and yet unexplored perspectives on the behaviour of queen bees outside the nest (or the hive), which could occasionally include tasks usually attributed only to workers.Reproduction is the only task normally attributed to the queen due to its specific morpho-functional characteristics, while foraging activities are exclusively carried out by workers bees in the honey bee colony. For example, the queen’s proboscis is shorter than that of workers and, therefore, less suitable for exploring the inside of flowers to collect nectar. Olfactory and visual detection is also less developed in the queen than in workers, and it is well known how important these stimuli are in order to search for appropriate flowers and find the food source within the flower. In the countryside of northern Sardinia, a honey bee queen (Apis mellifera L.) was detected while foraging on a borage  flower in Uri, Province of Sassari, Italy, most likely during an orientation flight before mating. Morphological details, detectable from photos with the naked eye and stereomicroscopic observations, confirmed that the honey bee queen was sucking nectar from a flower. The enormous development of the abdomen, lack of pollen-collecting structures in the legs and other characteristics such as the typical distally bilobed shape of the mandibles, with long hairs on their outer surface, proved the structural differences between the queen specimen and the other castes of bees. The queen’s proboscis, which is shorter compared to the workers, may have been counterbalanced by the shape and nectar production of the borage flower. This new observation proves that the queen can feed herself under natural conditions, likely to obtain the energy required for flying. Although we cannot exclude disturbing factors that could explain this foraging behaviour of a queen observed for the first time, this note opens a new scenario and discusses this new finding in the context of the available literature on the queen’s behaviour and questions to be answered.During a bee fauna survey in the countryside of northern Sardinia, a honey bee queen ( Apis mellifera L.) foraging on a flower in the field for the first time. The observed behaviour suggests that the queen can feed herself under natural conditions, probably to obtain the energy needed for flying.Borago officinalis L.) flower, and was then captured. Observing the details of the photos  on 23 April 2021, at 12:58. In a monitoring session, a honey bee queen was detected with naked-eye observation followed by a sequence of photos while feeding on a borage , with a reproductive division of labour in the colony, performed mainly by workers according to a sequence of activities ,5. AmongFrom a biological point of view, it is important to highlight that the worker honey bees need to train themselves by participating in pre-foraging flights before becoming foragers  and, simThe pre-foraging stage for workers, as the pre-mating stage for the queens, represents a critical phase which includes high mortality risks due to environmental hazards  ,9. HowevOrientation flights may also be crucial for the survival of virgin queens. Adequate nutritional conditions may help to improve flight performance and overcome possible threats. This could explain the queen’s need to forage on flowers during her orientation or mating flights. What is surprising is that queen bees are able to do it in the same way the worker bees do.Among the morpho-functional traits involved in foraging activity, the sensory structures of honey bees play a fundamental role. Although the olfaction of the queen has received less attention compared to that in drones and workers , there iThe placoid olfactory sensilla occupy most of the surface area of the antenna. Most of the placoid receptor cells respond to several compounds  and can be stim-ulated by a range of plant volatiles compounds in bees. However, because olfactory studies have focused mainly on the detection of sex and aggregation pheromones rather than on ordinary odours , little It is well known that the bee must collect its food at some distance from the nest (or the hive) by relying largely on visual cues to navigate to the foraging sites. Once the bee reaches the flowers, visual cues are needed to select appropriate flowers and to find the food source within the flower. For this kind of foraging behaviour to be successful, the bee must have sensory equipment to distinguish between flower species, based on the size, shape, colour and plane symmetry of the individual flowers, in addition to their scent . BecauseAnother type of additional information that needs to be gathered concerns drone flight. In our survey, we also detected the presence of drones on plants during the day . HoweverA. mellifera drones was monitored during their entire life in spring and summer using an optical bee counter placed at the entrance of the hive [Recently, the activity of the hive . Drones the hive . Drones,the hive ,17, theythe hive ,19. Befothe hive , usuallythe hive ,21,22.When drone activity was monitored for the first time during the whole day in northwest Argentina, several drones were active not only in the afternoon, as previously reported, but also in the morning and late morning. It was hypothesized that the morning activity of drones could be due to drifting, possibly when looking for food, or due to the presence of hives containing queen cells that attracted nearby drones .Considering that the queen and drones have an almost exclusive specialized function in the colony associated with reproduction, a better understanding of the behaviour of drones outside the hive before mating could be helpful to elucidate the queen’s behaviour.Honey bee queens perform a few short orientation flights before the nuptial mating flights ,8. MatinThe effects of the vibratory dance on the activities of virgin queens was investigated. It is known that virgin queens are forced by the workers to fly, often in the mid-afternoon or afternoon, and most of them take one or two orientation flights and from one to five mating flights in two to four days ,16. BaseBecause flying is costly in terms of energy expenditures , we can The queen foraging behaviour we observed on a flower for the first time may be explained by the pre-mating biology of the queen. In the pre-mating period, the newly emerged queen moves around in the brood area to destroy sealed queen cells, which would be potential competitors. Soon afterwards, the workers show an antagonistic behaviour towards the queen by pushing and biting the virgin queen and sometimes using “balling” behaviour against her. This forces the queen to fight back by producing sounds and vibrations that force the workers to stop this hostility. The peak of this aggressive behaviour occurs in the early afternoon, coinciding with the orientation or mating flights of the queens ,24,30. TThere is no doubt that we accidentally observed a queen bee sucking nectar on a borage flower. This most likely occurred during an orientation or mating flight, although we cannot exclude other possible disturbing factors. Certainly, the observed foraging behaviour needs to be confirmed by other observations and further investigated, e.g., by using advanced technology such as the most promising remote sensing methods . This wo


Agricultural land cover and its changing extent are directly related to human activities, which have an adverse impact on the environment and ecosystems. The historical knowledge of crop production and its cultivation area is a key element. Such data provide a base for monitoring and mapping spatio-temporal changes in agricultural land cover/use, which is of great significance to examine its impacts on environmental systems. Historical maps and related data obtained from historical archives can be effectively used for reconstruction purposes through using sample data from ground observations, government inventories, or other historical sources. This study considered historical population and cropland survey data obtained from Ottoman Archives and cropland suitability map, accessibility, and geophysical attributes as ancillary data to estimate non-irrigated crop production and its corresponding cultivation area in the 1840s Bursa Region, Turkey. We used the regression analysis approach to estimate agricultural land area and grain production for the unknown data points in the study region. We provide the spatial distribution of production and its cultivation area based on the estimates of regression models. The reconstruction can be used in line with future historical research aiming to model landscape, climate, and ecosystems to assess the impact of human activities on the environmental systems in preindustrial times in the Bursa Region context. The terrestrial biosphere has been continually changing to meet demands for food, feed, fiber, fuel, and habitation , 2. The 2 [The primary driver of agricultural land expansion is the growing human population. From 1800 to 2000, the world population has risen about six-fold from less than one billion to six billion . Agricul2 . Convers2 , 17. OthAgricultural production is a function of the land area under cultivation and the intensity of cropping on the cultivated land. Therefore, the volume of agricultural output is linked to changes in the total area under cultivation and changes in cropping intensity , 20. An It is essential to use quantitative information in the study of land cover/use pattern and cropland change analysis to examine the environmental impacts of such changes . NumericThese studies, in common, integrated remotely sensed data on the contemporary patterns of agriculture with historical data on agriculture and population to develop spatially explicit reconstructions of land cover/use  over the past centuries or the past decades. Though these datasets provide spatially and temporally continuous gridded data on agricultural land cover/use, they have coarse spatial resolution, which reduces their application potential in local study areas. Some argued that these data have been applied in a general context to examine historical cropland change patterns; therefore, they should only be used for country-to-global scale analysis and modeling , 39, 40.Local-scale analysis has contributed to the historical cropland reconstructions, given that local datasets can help verify global and regional scale datasets and models. Some examples of land use reconstructions based on detailed real data  for the local case study areas or smaller regions are Cousins et al. , BenitezBased on the methods employed to reconstruct historic land cover/use, this study aims to create a new dataset of total area of cultivation and total production volume for grains in our selected case study area, i.e. Bursa Region in Turkey in the 1840s. Bursa Region is located in the north-western part of Turkey, which has been considered as one of the most significant settlements starting from the Ottoman Era till modern times. The economic history of the late Ottoman Empire and/or the Turkish Republic has not used region as a unit of analysis adequately. Therefore, we severely lack empirically grounded historical studies on regions’ economic performances of today’s Turkey. The most recent and robust historical national accounts  are alsoHistorically, the most significant factor influencing agricultural product demand has been population growth , 63. RamThe income level of societies is another factor that is positively associated with agricultural land take. As income increases, households’ demand for goods, including food, increases, which require greater agricultural area to sustain the increasing demand of wealthy societies , 69. FooL,i,t is the agricultural land demand for settlement i at time t; Xi,t is a matrix of explanatory variables including socio-economic factors , location, accessibility and geo-physical variables, institutional/policy variables, and others; and vi,t is the random disturbance term. The land supply function is provided in Eq ; and random disturbance term .In Chen et al.’s  explanated in Eq  where agi,t, explicating the conditions of demand and supply in the agricultural land market can be formed as:Solving the equilibrium of demand  and supp…In the country above the plain they get a crop of wheat off a field and then leave it fallow for a year or two, saying that they have so much ground they need not over-fatigue it…". Spatial data on land zonings or protected land in the Bursa Region is not available for the 1840s; therefore, these variables were discarded from the analysis.Because land rent data is usually unavailable as it is in our case, it is common in the literature to approximate them using other variables . Therefotemettuat is the original Ottoman/Turkish name of the survey) which represents data at one point in time [Temettuat covers a wide variety of variables. This survey results from a tax reform aiming to register all income yielding assets per household, mainly under the headings of agricultural production, animal husbandry, occupational revenues, and rented property. In rural settings such as the Bursa Region under consideration, the survey has registered detailed agrarian data. The most important two are the cultivation area in units convertible to hectares and the volume of products to be taxed in kind in units convertible to tons. For this study, we extracted these two variables. One of the challenges to work with this survey is the impossibility of assessing its reliability. The data conveyed with the temettuat is unprecedented in detail, yet it provides only one single data point. The agricultural data it provides cannot be double-checked by any other contemporary or later source. It is assumed that it covers around one million households in the Ottoman Empire’s core regions in Southeast Europe and Anatolia. Approximately 18,000 registers of this survey are available in the Ottoman state archives since the 1990s, yet only on the very micro level handwritten data format as it was collected by the clerks on the field in the mid-nineteenth century. The survey’s results were never tabulated or subject to any systematic inquiry during the Ottoman era. Since the 1990s, there was no organized effort to utilize them in economic history either. These registers hitherto have been used almost exclusively in geographically limited case studies dedicated to individual cities, towns, or sets of villages. There are very few exceptions to the underutilization of this rich source.Our data source is an empire-wide tax survey from 1845  to read, extract and enter this information from handwritten Ottoman script archival sources into our MS Access relational database by using custom-made data entry tools. In the remaining 489 settlements, if we leave aside, the city of Bursa should have around 25,000 households. For a separate study, we already digitized and acquired data of 7,125 households registered in the city of Bursa. To extract necessary information on agricultural area and volume of production for the remaining settlements in the region, we would hypothetically need 625 workdays for the data entry. It would not be possible to conduct this total data entry since lack of complete sources in the archives. Therefore, with our estimations, we are modeling a total area and volume of crop production for a region, which cannot be reached via conventional historical methods. Covering the region totally ensures commensurability for longitudinal studies in agriculture. Ottoman statistical yearbooks from the late nineteenth and the first agriculture censuses from the early twentieth century and all successive agricultural censuses from the 1920s, 30s, and 40s of the Turkish Republic provide data on acreage and volume of production for grains for all sub-districts of Bursa. We want to make two explanatory notes on our methodology in making use of the 1840s survey. Firstly, there is a complication or a disconnect of data collection regarding agricultural production. The survey enumerates the total area of cultivation in Ottoman We opted for the Corine Land Cover (CLC) nomenclature of the European Union’s Earth Observation Programme (Copernicus). Since its initialization in 1985, the CLC inventory has been updated regularly, and we used the revised and supplemented nomenclature guidelines dated 10.05.2019 issued by the European Environment Agency . Althougtemettuat survey. The total population and household numbers of the settlements were obtained from the contemporary population registers from the 1840s, again available in the Ottoman Archives. Distance to main residential centers and settlement centers were computed from the geocoded spatial data, which represented the central points of main residential centers (these were identified as the settlements assigned with the highest population numbers in the Bursa Region) and 576 settlements of Bursa. Distance to water sources and soil quality were developed from the spatial data showing the natural land cover and soil capabilities of the Bursa Region. The road network accessibility was computed using the 1940’s transportation network map, and finally, the elevation is from the Digital Elevation Model (DEM) dataset . We used a random sampling script with multiple constraints to pick at least one settlement from each suitability group per sub-district based on these classifications. This selection of at least five settlements also had to correspond to at least 10% of that sub-district’s total population and at the same time to 10% of the total number of households within that sub-district. Finally, we determined a weighted suitability index value per settlement by dividing the sum of total suitability by the associated territory and categorized them into respective suitability classes , and extarchives   and Nonlinear Least Squares Regression (NLS) techniques and a linear OLS model to analyze the relationship between agricultural production and explanatory variables. Because agricultural production and the size of the agricultural land are correlated, we applied Zellner’s  well-knoRegarding the agricultural land area estimations, we only focus on linear models, including Truncated Poisson Regression (TPR), Quantile Regression (QREG), and Generalised Least Squares (GLS) methods. The reason for using the TPR model was to prevent zero and negative agricultural land area estimations. The TPR model details can be found in Grogger and Carson ; Long Sci is the ith observation of the response variable; Several model validation analyses were conducted for each of the regression models showing the relationship between the response variable and its determinants as specified in previous sections. These are Mean Error (ME), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Relative Difference (RD). The formulas of these measures are given asFinally, the steps followed in the methodological process are presented in To compare estimations and to evaluate the fitting performance of different models, we have considered NSUR (Models 1), NLS (Model2), TPR (Model3), QREG (Model4), OLS (Model5), and GLS (Model 6) estimators for each agricultural model where the agricultural product or agricultural land area are the response variables. The presented variables in In general, the estimates of agricultural land use and production determinants have consistent signs throughout all the models. Soil quality, agricultural land area, and population have positive and significant effects on agricultural production. In some cases, distance to settlement centers has a positive influence, whereas elevation negatively influences agricultural production. This implies that agricultural production is higher in locations that are more distant to settlement centers and lower in higher elevation locations. The reason can be the existence of high-quality agricultural land in the peripheral locations far from settlement centers. This is also the case for the locations of lower elevation.Similar to agricultural product estimates, soil quality and the number of households have positive impacts on agricultural land development; however, there are also negative estimates of the number of households in Models 1 and 6. This implies that the larger the number of households, the smaller the agricultural land area required for grain production implying that economies of scale could positively impact land use and result in higher yields per household per hectare. In Models 1 and 6, the number of households is negatively; in Models 3 and 4, it is positively related to agricultural land use. Though magnitudes of the household variable’s coefficient are the same in these models, they have differing signs, therefore failing to be robust estimates. Elevation is positively related to agricultural land use in Models 1 and 3. Therefore, agricultural land development was more common in locations of higher elevation in the study area. Distance to main residential centers negatively influences agricultural land development, indicating that agricultural land expansion is more likely in the locations close to main residential centers. Distance to roads also has a negative coefficient indicating that the closer to the road network, the larger the agricultural land development. The tax on agricultural products is positively related to both soil quality and agricultural land area. This implies that agricultural production and resulting agricultural product tax are higher in high soil quality locations and in the locations where agricultural land areas are larger compared to lower soil quality and smaller agricultural land counterparts.The scatter plots for the six models showing observed and fitted values are shown in The R-squared values range between 0.28 and 0.83, indicating that 28% to 83% of the agriculture variables’ variation can be explained by agricultural use determinants as given in Spatial autocorrelation refers to the presence of systematic spatial variation in a variable where the corresponding data values tend to be clustered or dispersed in space. We used Moran’s I index to detect spatial autocorrelation effects concerning the estimated residuals across the specified six models, which we estimated using different regression techniques. Based on the results from model validation analysis  and spatRegarding agricultural land estimations , Bursa, We used the estimated relationships between the response and explanatory variables from Model 2 and Model 4 to estimate the missing data points’ agricultural information. The observed and estimated agricultural land area values from Model 4 are presented in According to Model 4 estimations, Mihaliç, Yenişehir, İnegöl, and Bursa are the top sub-districts having the largest agricultural land area in the Region. These settlements are characterized by having the most fertile land in the Region. In particular, Mihaliç and Bursa are among the highly populated sub-districts in Bursa Region. By contrast, Gemlik and Mudanya are the sub-districts having the smallest agricultural land area. As summarised in We analyzed the relationship between population and estimated production values for all the 11 sub-districts included in the study for confirmation purposes. A statistically significant positive relationship was uncovered between population and estimated values for each of the 11 sub-districts in the Bursa Region , marketIn Von Thunen’s model, the most inner zone  is occupied by perishable products (e.g. vegetables and fresh milk); which is followed by woodland as both have high transportation costs. The following three zones are crop farming zones of gradually decreasing intensity. There is evidence in the literature that there are settlements accorded closely to Von Thunen’s principles both in historical periods and in underdeveloped regions in modern times. For instance, Ewald  studied From our regression models, the agricultural land area was positively related to elevation while grain production was related negatively. This indicates that at higher elevations, agricultural land area is increasing while production is decreasing. Jiang et al.  found thWe had inconsistency in the results regarding some variables such as elevation and household number that we estimated for grain production and agricultural land area. It is also important to note that the factors influencing grain production and its cultivation area are different across the models that we estimated. For instance, Model 2 indicates that elevation, population and land area are the factors explaining grain production. According to Model 4 findings, soil quality, number of households and distance to main residential centers are the significant determinants of grain cultivation area. The reason for these inconsistencies is that the data entries for the grain production do not match with those of the cultivation area. This raises the issue of data quality as we had to rely on the only available data where grain production data entries do not match with its cultivation area values. As we noted previously, this is the only data that is available at the greatest detail for the nineteenth century of the Bursa Region and it is impossible to have higher quality data in our case.In this study, we estimated the total area assigned to, and total volume of production of, non-irrigated crops, as the closest proxy for grain cultivation, for Bursa Region for all 576 (except the city of Bursa) settlements in the 1840s by using regression models based upon a geo-sampled total of 72 settlements. We used different nonlinear and linear models for the estimation of agricultural uses. By doing this, it was possible to select the best fitting models through the model evaluation criteria. Considering the issues of nonlinearity in agricultural production and the heterogeneous variances in agricultural land area data, we selected two specific models that proved to be effective in dealing with nonlinearity and heterogeneity issues. These models provided more accurate estimations and were better in considering sub-regional dynamics within our chosen area. However, our selected models have underestimated or overestimated the agricultural use variable, particularly for the regions associated with very low grain production levels or small cultivation areas, both of which correspond to highly populated settlements. For these settlements, our models significantly overestimated agricultural production and cultivation area.Our results, especially for the sub-districts of Gemlik and Mudanya with their administrative and economic centers on the shore, hints at the overlooked importance of grain trade which has not been explored in detail in historical literature for the 1840s. Similarly, we think we should model the economic and agricultural interplay of the city of Bursa with the remaining settlements in the region in our future studies. Further to this, the modeling already curated data on different agricultural land uses . In the future, this work will enable us to use the information that we developed in this study and combine it with the other agricultural land use data to reconstruct the spatially-explicit agricultural area and agricultural land cover for the Bursa Region in the 1840s. The historical reconstruction of agricultural land in Bursa will provide a base for future studies through offering possibilities to use these results alongside other scientific research conducted at regional or more local level in Bursa.With this study, we have developed a method to systematically use an underutilized historical source on agricultural production for our selected region and estimated crop yields for grains for the 1840s. Our approach has two major advantages for future studies on Ottoman agriculture. First, it is scalable as it is based upon sampled observations. Using the same methodology, when sample data is collected, the total volume of grain production and area of cultivation can also be estimated for the entire extent of the survey we used. The survey covers a massive territory in Southeast Europe and Anatolia, which includes today’s Bulgaria, Northern Macedonia, regions of Northern Greece and Southern Serbia, and the Western half of Turkey. By adding new regions following the same methodology, land productivity for grain production can be estimated for several regions with sub-units and inter- as well as intra-regional comparisons can be made for the 1840s Ottoman land productivity. Secondly and more relevant for the Bursa Region since also the population data for all 576 settlements in the region are available, as a second step labor productivity in grain production can also be estimated for rural settlements.S1 Data(ZIP)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


Refugees and asylum seekers living in reception centres tend to be not adequately included in population-based studies, routine medical data and official statistics. As part of the research project ‘Health and primary-care sentinel surveillance in reception- and accommodation-centres for asylum-seekers in Germany’ (PriCare), a health-monitoring approach was developed for the secondary use of routine medical data from on-site outpatient clinics in reception centres. To this end, a software application  for the digitisation and harmonisation of medical records was designed and implemented in reception centres in three German federal states. The approach of distributed computing in a surveillance network allows for the decentralised, harmonised analysis of the routine medical data stored in RefCare© in a manner that fully complies with data protection regulations and circumvents the need for centralised data storage. RefCare© provides an integrated surveillance feature that enables analyses of 64 indicators on population, morbidity, healthcare processes and quality of care to be undertaken across multiple facilities. This article describes the conceptual and practical approach and the technical procedures put in place to do so, and provides examples of the results that have been gained so far. The federal health monitoring is tasked with compiling robust data on health, health risks, and healthcare provision for the population in Germany from a broad range of sources, and making this information available to decision-makers and the general public. However, asylum seekers and refugees are insufficiently included in health-related data collection in Germany and other European countries . This shIn Germany, asylum seekers are not provided with statutory health insurance and commonly receive medical services on-site in the reception centres, with infrequent referrals to specialist outpatient medical practices. They thus receive healthcare largely outside of regular care provision structures and associated routine medical data sources. The centralisation of the asylum process over the last five years has increased the length of time that asylum applicants live in reception centres. Particularly individuals from ‘safe countries of origin’ may now remain in reception centres for the duration of their entire asylum process. Moreover, during the first 18 months of their stay in Germany, asylum seekers are only entitled to a limited range of medical care. The electronic health card, which facilitates access to healthcare in Germany and enables data on diagnoses and healthcare provision to be recorded digitally, is also not consistently made available . SpatialThe forms of accommodation used to house asylum seekers at the state level can be divided into registration and reception centres. When asylum applicants are first registered, they tend to be placed in registration centres, which only provide for a short-term stay. In contrast, reception centres provide medium-term accommodation, and asylum applicants may remain in these facilities for up to 18 months. In fact, depending on their country of origin, some applicants remain in reception centres accommodation during the entire application process and until a decision has been made on whether to transfer them to a district-level facility.Monitoring the health and healthcare provision for refugees in collective accommodation centres in this issue of the Journal of Health Monitoring).These facilities can be further distinguished from the accommodation centres provided at the district level, which tend to vary in size and are a temporary measure. Depending on the outcome of an asylum application, applicants would then be transferred to private housing , which was funded by the German Federal Ministry of Health, was established to improve the quality of medical records in reception centres and to set up a system that can be used to routinely monitor the health of and the healthcare provided to asylum seekers and refugees . The proReflecting the legal requirements for medical records as well as experiences gained from working with healthcare providers in reception centres for asylum seekers, we developed a prototype for the electronic medical records system RefCare©. The prototype provided the basic functions found in typical electronic medical records. Functionalities that were less relevant for care provision in reception centres, such as the accounting of medical services, were disregarded while others, such as vaccinations and multilingual communication, were added. The prototype underwent usability tests with eight doctors working in reception centres . UsabiliA pilot version was tested as of October 2017 in a clinic in a large reception centre in Bavaria. Feedback was systematically logged and recorded, before being checked for feasibility by the project and development team; ideas were then prioritised and built into the software wherever possible. Additional test sites followed in 2018 in Bavaria and Hamburg, with the collection of feedback from users and iterative software development continuing as a long-term process that went beyond the initial pilot phase. During this period, the software and the implementation process were further adapted and tailored for use in reception centres . This pRefCare© enables medical records to be digitised in a standardised manner, and, therefore, provides for cross-facility harmonisation of locally-stored routine data in participating facilities. In order to perform a cross-institutional analysis of this routine data, and comply with data protection regulations, a procedure was developed that enables decentralised analyses to be conducted without the need to disclose personal information to third parties (i.e. outside of the facilities themselves). This procedure is known as ‘networked distributed computing with the result of an anonymised indicator’. In the following, it is simply referred to as the ‘hive approach’ due to the large number of decentralised yet coordinated analytical processes involved . The hivThe PriCarenet research network consists of representatives from facilities that use RefCare©, the authorities involved, and academic partner institutions. The network jointly develops and adapts the indicator set used in the routine health surveillance. Each member of the network can submit and provide arguments in favour of proposals for new indicators. The scientific basis, feasibility and ethics of the proposals are then assessed by the elected Data Use and Access Committee (DUAC). The committee subsequently provides a recommendation and the indicators are presented to the network’s members at the network’s general assembly, which is its decision-making body. Finally, members vote on whether to include the indicator in the set; only representatives from the clinics are entitled to vote. The aim of the DUAC is not to secure access to the data ‘from the outside’, but to select and coordinate indicators and scientific research questions for analysis at the local level.The current health and healthcare indicator set, which has been approved by the PriCarenet network, consists of 64 indicators from the fields of population, morbidity, quality of care, healthcare process and syndromic surveillance .Once an indicator has been approved by the research network, it is operationalised by the project team at Heidelberg University Hospital. Operationalisation is based on the data fields available in RefCare©, particularly diagnosis , reason for seeking medical advice , prescriptions , vital parameters , medical referral forms, and personal data . If necessary, software updates can be used to provide new fields, responding to challenges such as the COVID-19 pandemic. To comply with the principle of data minimization, only patient data required for the immediate care provision can be recorded.Based on the indicator operationalisation, an analysis script is then produced in the programming language ‘R’. The script is internally validated by a second team member, using methods such as independent programming, in order to review the plausibility of its results. The script is then made available to the clinics for decentralised, automated analysis via a RefCare© software update .In principle, the analysis of the local routine medical data is conducted by the care providers on a voluntary basis. The analysis script can be executed locally through the integrated RefCare© surveillance module by a simple click on a button . The scrOnce the analyses have been completed, the results are immediately available locally. The results are saved in Excel files containing anonymised (i.e. aggregated) figures, such as absolute and relative frequencies or prevalence. Surveillance officers are also provided with an introduction and written instructions to reading and interpreting the output in Excel. This ensures that the healthcare providers have the skills needed to view the results on-site and to assess their plausibility.The surveillance officers then export the data for the defined surveillance periods from the facility to Heidelberg University Hospital. Exporting the results, too, is voluntary, and occurs independently of the local data analysis. The results are exported via a cryptography transfer module  integratIn this step, the anonymised indicator results stored on the surveillance server in Heidelberg undergo automatic graphical processing using R and JavaScript, and are then displayed on a dynamic reporting platform. In this manner, both the results of the facility-specific and cross-facility meta-analyses are made available on the reporting platform. Each facility has its own login details which they can use to view their own analysis results, as well as anonymised data points from other facilities for benchmarking purposes. In addition to automated reporting via the reporting platform, further meta-analyses can be carried out across institutions and are published in regular surveillance reports without providing the names of specific facilities. In order to promote the translation of the analysis results and their utilization for care provision, the results and their possible implications are discussed at the assembly of the research network PriCarenet. This also ensures that the plausibility of the results is assessed regularly and that the indicators can be expanded and supplemented. If needed, facility-specific results can also be made available to the authorities responsible for the reception centres and to higher-level political decision-makers, either through direct access to the reporting platform, or through the healthcare provider. Cross-facility data are published by the network without reference to individual facilities and can thus inform political decision-making processes.Data protection poses a major challenge to regular health monitoring across institutions, especially in the fragmented and heterogeneous structures found in care provision settings at reception centres for asylum seekers. At the same time, the workload faced by medical staff at the facilities, language issues, and the vulnerability of asylum applicants, means that it is practically impossible to obtain informed consent for research using routine medical data from each patient. However, these challenges can be overcome with the hive approach as it enables researchers to protect the sensitive, personal data of a highly vulnerable population while still conducting cross-institutional health monitoring at regular intervals. Furthermore, this approach also enables medical service providers to evaluate their routine medical data automatically and anonymously and to do so in their own facilities without the need to disclose personal data to third parties. Finally, the approach yields indicators that do not enable any conclusions to be made about specific individuals, and, therefore, the indicator results can be passed on to third parties while still complying with data protection regulations.The hive approach has a fundamental advantage over traditional surveillance that relies on centralised databases and analyses in remote research facilities: it requires no central storage of personal data. As the results from the various clinics are available in the same format (because they are produced by a standardised script) they can nonetheless be summarised through meta-analysis and comparisons can be made between facilities. The PriCarenet network provides an essential foundation for adherence to data protection regulations, and, therefore, for the use of distributed computing/the hive approach. It ensures that facilities have a say in the analysis of their data and the contents of the routine surveillance. Moreover, the local analysis of routine data through the surveillance module as well as the decision to export data are both voluntary. As the script used to analyse a facility’s data is run on-site, analyses can therefore be justified by a health provider’s legitimate interest in undertaking in-house research for healthcare planning and quality assurance. Depending on the type of healthcare setting and the way in which data protection responsibilities are organised, the legal basis for this type of data analysis is provided by data protection laws at the state or federal level . Since the analyses are conducted for in-house research with the aim of improving healthcare provision, and because the approach respects data minimisation and guarantees patient anonymity, there is no need to seek prior consent from the patients.Monitoring the health and healthcare provision for refugees in collective accommodation centres in this issue of the Journal of Health Monitoring). Since the length of time spent in these facilities, the spectrum of morbidity, and the countries of origin differ in each facility, they are grouped by accommodation type for ease of comparability. The following provides examples of facility-specific and cross-facility analyses that can be carried out automatically at regular intervals as part of the PriCare project. These examples illustrate the potential of the approach for monitoring the health of asylum seekers and refugees. The results are an excerpt of the information that can be routinely accessed via the reporting platform. The following describes both a facility-specific analysis from a sample facility for the period between 1 May 2018 and 31 August 2020 as well as a cross-facility analysis of a morbidity indicator using data from eleven facilities from the period beginning with the implementation of RefCare© until 31 October 2018. The facilities are grouped by level and include registration centres (level 1) and reception centres (level 2) at the state level as well as accommodation centres at the district level (level 3)  stratified by age and sex. Furthermore, morbidity profiles are generated for individual facilities using 29 morbidity indicators. This enables a period prevalence to be calculated for each indicator and each institution. When calculating prevalences, the total number of cases for each indicator serves as the numerator, with the total number of people acting as the denominator. In principle, the total number of people living in the facilities could also be used as the denominator. However, these statistics are not recorded directly in RefCare©, and, instead, are collected through a separate survey undertaken in each of the facilities participating in the network on the 15th of each month, stratified by age group and sex. As different facilities achieve different levels of completeness, the total number of people treated has proven a more reliable denominator.The weighted, pooled prevalence and the 95% confidence interval for the morbidity indicator ‘mental and behavioural disorders’ are provided here, stratified by age and sex. The estimator is calculated using a meta-analysis via a random effects model, in which variance between facilities is accounted for as a random variable. The facility-specific and the pooled estimators are depicted using a forest plot, stratified by age  and sex .Since the beginning of the project and the implementation of RefCare© in a pilot facility, the software has been implemented in 29 institutions in Baden-Württemberg, Bavaria and Hamburg. Due to facility closures and changes in service provider, as of 2 October 2020, the software is currently used by 24 facilities in these federal states.The PriCare project successfully developed and implemented the infrastructure required for distributed computing, the PriCarenet research network itself, the indicator set, the analysis script and the surveillance module. Each of the 24 facilities can perform automated analyses and utilise the results for on-site planning and reporting purposes. The results particularly enable service providers to meet their sometimes contractually agreed reporting obligations with the authorities and thus directly facilitate their work and improve communication. Sharing facility-specific and cross-facility results within the research network has proven fruitful and contributes to more robust interpretations of the results, enables the indicator set to be adapted, and encourages people to share good practices in the provision of medical care in reception centres.A total of 11,579 patients were recorded in RefCare© in the facility in question between May 2018 and August 2020. The patients comprised 9,853 adults (85.1%), of whom 3,980 (40.4%) were female, 5,870 (59.6%) were male, and 3 (0.03%) were missing information on sex. 1,726 were children and adolescents (14.9%), of whom 791 (45.8%) were female, 928 (53.8%) were male, and 7 (0.4%) were missing information on sex. Overall, a total of 38,171 patient contacts were recorded. The mean number of contacts per patient was 3.5 for adults; 2.3 for children; 3.9 for female patients; and 2.9 for male patients. The ten most frequent countries of origin among all patients in the observation period per month are shown in The morbidity profile of this facility shows a predominantly primary care typical spectrum . Among aBeyond the primary care spectrum, the data demonstrate that healthcare needs also extend to mental disorders (ICD-10: F00–F99) as well as consequences of external causes (ICD-10: S00–T98). Mental and behavioural disorders were diagnosed in 15.1% of men and 8.8% of women over the entire period. However, mental illnesses were also identified among girls (5.6%) and boys (6.5%). The morbidity indicator’ consequences of external causes’ includes injuries, burns and other conditions resulting from external causes such as accidents, assaults or operations of war. Men are particularly frequently affected, with a prevalence of 12.7%.In principle, monthly analyses of absolute case numbers and prevalences for all morbidity indicators are available locally at the facility level. As an example, Cross-facility analyses, particularly of morbidity indicators, can be conducted at regular intervals and the results are made available to the participating facilities for benchmarking purposes via the reporting platform. As an example, The PriCare project demonstrates that automated and timely health monitoring in reception centres for asylum seekers that is feasible and respects data protection regulations can be achieved through the innovative approach of networked distributed computing (the ‘hive approach’). For the first time, healthcare providers in reception centres for asylum seekers can work with an electronic medical records system that is tailored to their specific setting and provides for structured recording and analysis of morbidity, healthcare utilisation and other healthcare indicators. The facilities can now regularly analyse their routine medical data on-site without the need for specialist knowledge about statistical methods, compare their results with other facilities, and thus base healthcare planning on a solid data foundation. This approach also generates a body of data that can be used to aid political decision-makers and to support needs-based healthcare provision. However, if this is to be successful, the results not only need to be communicated in an appropriate manner, there also needs to be a willingness among politicians to consider data on healthcare needs in their decisions about healthcare provision in reception centres.The results presented here demonstrate that the patients receiving care in the sample facilities exhibit a largely primary care-typical morbidity profile. At the same time, the results also highlight particular needs in terms of mental illness and consequences of external causes. Regarding mental health needs, the results underscore a high degree of heterogeneity between facilities, which may be due to the type of facility, the range of care available, and a facility’s particular demographic. The results also suggest that demographic aspects such as country of origin and the prevalence of individual diseases change dynamically, which underscores the need for continuous health monitoring.This need is also clear from the noticeable decline over time in the indicator ‘mental and behavioural disorders’. Between April and May 2020, the respective facility was placed in quarantine for 16 days due to confirmed SARS-CoV-2 infections and all leisure and social support programmes were consequently cancelled. The decline remains stable even after fluctuations in the total number of occupants are taken into account, which means that changes in the total number of people living in the facility do not suffice as an explanation. However, nor does this descriptive analysis of the data demonstrate any clear association between what was happening in the facility during this period and an increased prevalence of mental illness. Instead, this increase could be due to random fluctuations over time or differences in coding practice resulting from personnel changes. Still, the results clearly illustrate the usefulness of health monitoring in this context: the descriptive time trend reveals a need for specific in-depth analyses that apply more complex procedures. This would involve examining possible associations in individual facilities and across facilities between, for example, measures put in place to contain the pandemic and the prevalence of psychological stress. Similar studies could be undertaken on the other morbidity and healthcare indicators, such as for vaccinations against influenza viruses and seasonal changes in the prevalence of respiratory infections.In principle, this approach faces the typical limitations associated with the use of routine medical data . These iMonitoring the health and healthcare provision for refugees in collective accommodation centres in this issue of the Journal of Health Monitoring). Moreover, the morbidity profile in protective facilities housing asylum seekers with special needs can be expected to differ from that found in registration centres, where people remain for a very short period of time. Therefore, additional information about the context and the facility itself are important in order to adequately conduct and interpret cross-facility meta-analyses. In the PriCare project, the research network fulfils this purpose by providing a forum for the context-specific interpretation of the results.Other challenges arise with the internal validation of diagnoses, especially when it comes to differentiating between suspected and confirmed diagnoses, as these differences are not always recorded. In addition, the spectrum of medical services provided and the function of the respective facilities have an impact on the range of diagnoses that will be recorded. It is fair to assume that illnesses that require specialised diagnostics will go underreported, not least because of the restricted entitlement to treatment set out in the Asylum Seekers Benefits Act. This becomes especially clear through comparisons between the prevalence of mental illnesses reported here and the prevalence identified using survey-based approaches .However, the hive approach offers a resource-saving approach to ongoing, timely and comprehensive health monitoring without the added burden of data collection. To compensate for the limitations associated with the secondary use of routine medical data, the routine health monitoring could be supplemented with survey-based approaches undertaken at longer intervals (e.g. every three to five years) (see also the article In comparison to other efforts to utilise routine medical data from refugee camps in Europe to analyse health and healthcare parameters, too, the hive approach has significant advantages. For example, routine medical data from reception centres in Denmark and the Netherlands have been used in research. However, these analyses are based on centrally-stored routine medical data, and do not provide for regular analyses; as such, they are selective and guided by the interests of individual researchers , 16. TheAs technology development, methods, processes and the structures required for the PriCare project were funded by the Federal Ministry of Health, the next challenge is consolidating these structures and ensuring that they remain in place in the long term. Bilateral, non-commercial utilisation and licensing agreements have been concluded with most facilities within the network, and this should enable the project to continue for the time being. However, optimal long-term use of the infrastructure and procedures established by the PriCare project would require their expansion to all accommodation facilities in all federal states and, above all, the development of sustainable health reporting. This would enable the health of and the healthcare provided to refugees to be monitored in all accommodation facilities throughout the country and would, therefore, permanently close existing data gaps.The hive approach can also be used in areas of health services research beyond the healthcare provision in reception centres for asylum seekers. The federal health system, with its fragmented healthcare provision and data landscape, poses similar challenges to those described above when using routine medical data for health monitoring and research. The application of distributed computing, therefore, could bean important tool for the Medical Informatics Initiative  as well In cases like the implementation of the hive approach in reception centres for asylum seekers, where routine medical data are analysed for all patients without obtaining written consent, additional issues need to be addressed in order to guarantee data-protection compliance. In particular, a decision-making body is required to ensure that medical service providers have a say regarding the indicators used in the analyses of the local routine data. Distributed computing could be implemented in other areas of health with great potential once these foundations have been put in place.In addition to the results from the statistical analysis, developing the infrastructure needed to implement the ‘hive approach’ in the heterogeneous settings of reception centres has led to positive side-effects. The implementation of standardised medical records that comply with data-protection regulations when transferring patient records between facilities, and provides customised outpatient administrative functions, contributes towards reducing the workload for its users and improving healthcare provision. Furthermore, the project encourages facilities to consider legal, administrative and organisational aspects relating to the protection of medical records in the often precarious and fragmented settings of care provision, and to clarify where data protection responsibilities lie within their facilities.Finally, in addition to developing the indicators used for health monitoring, the PriCarenet research network has also proven an important forum for sharing experiences between the participating institutions. This encourages members to discuss experiences, challenges and best practices. The interpretation of the results from health monitoring as well as discussion within the research network about possible implications for healthcare provision and planning also contribute to the further improvement of healthcare provision in reception centres for asylum seekers.Data on healthcare provision to refugees and asylum seekers in reception centres is essential for individual healthcare and needs-based care planning.Data are not yet systematically available for healthcare planning, research and reporting.A lack of routine medical data and differences between medical records currently preclude health monitoring across multiple regions.Digitisation of routine medical data is essential for the systematic health monitoring of refugees.Networks and distributed computing enable timely and data-protection compliant health monitoring to be undertaken in reception centres.In addition to primary medical conditions, asylum seekers in reception centres often require treatment due to mental illnesses and consequences of external causes, such as accidents, assault, or operations of war.Consolidating and integrating decentralised analyses into data collection and evaluation structures would close existing data gaps.


Potentially toxic plasticizers are commonly added to polyvinyl chloride medical devices for transfusion in order to improve their flexibility and workability. As the plasticizers are not chemically bonded to the PVC, they can be released into labile blood products (LBPs) during storage. Ideally, LBPs would be used in laboratory studies of plasticizer migration from the medical device. However, short supply  has prompted the development of specific simulants for each type of LBP in the evaluation of new transfusion devices. We performed a Delphi study with a multidisciplinary panel of 24 experts. In the first  phase, the panel developed consensus definitions of the specification criteria to be met by each migration simulant. Next, we reviewed the literature on techniques for simulating the migration of plasticizers into LBPs. A questionnaire was elaborated and sent out to the experts, and the replies were synthesized in order to obtain a consensus. The qualitative study established specifications for each biological matrix  and defined the criteria required for a suitable LBP simulant. Ten criteria were suggested: physical and chemical characteristics, opacity, form, stability, composition, ability to mimic a particular clinical situation, ease and safety of use, a simulant–plastic interaction correlated with blood, and compatibility with analytical methods. The questionnaire data revealed a consensus on the use of natural products (such as pig’s blood) to mimic the four LBPs. Opinions diverged with regard to synthetic products. However, an isotonic solution and a rheological property modifier were considered to be of value in the design of synthetic simulants. Consensus reached by the Delphi group could be used as a database for the development of simulants used to assess the migration of plasticizers from PVC bags into LBPs. The polymer polyvinyl chloride (PVC) is widely used in the manufacture of medical devices and, more specifically, in blood bags for the collection, preparation, and storage of labile blood products (LBPs). PVC’s flexibility is increased by the addition of plasticizers. However, given that the plasticizers are not chemically bonded to the PVC, they can migrate into the LBPs  and thusThe objectives of the present Delphi study were therefore to (i) draw up specification criteria for plasticizer migration simulators specifically for each LBP, (ii) rank natural or synthetic products cited in the literature and/or suggested by members of an expert panel, and thus (iii) build a reliable consensus of opinion in the field of transfusion.The Delphi method is based on structured communication between several experts  3,4]. T,4. T3,4]After having explained the study’s context and objectives to potential study participants , step 1,We next set up a “nominal group” qualitative study , step 3,The literature review was carried out between March and May 2020, in parallel with the qualitative study. The goal was to find technical solutions for use as simulants in plasticizer migration studies , step 3.All the criteria defined during the nominal group meeting and all the technical solutions extracted from the literature search were used to draw up the questionnaire , step 4.All 24 experts in the Delphi group participated in the questionnaire step , step 5.Each technical solution was assigned a value of x = 1 when it was judged to be relevant and x = 0 when it was judged to be irrelevant , step 6 The answers were not weighted with regard to the respondent’s field of expertise. When a participant did not feel knowledgeable enough to answer a question, he/she could request that the answer be discarded. Likewise, any answers that were not justified by the respondent were excluded from the final results. A consensus scale  was set Firstly, the nominal group meeting’s topic, objectives, and methodology were presented to the 13 participating experts. After each person had considered the issues individually, the experts suggested several criteria for characterization of the most suitable simulants in plasticizer migration studies. In total, 52, 46, 42, and 48 criteria were suggested for WB, RBC, plasma, and PC, respectively. Although the criteria were formulated differently, it was possible to group, rephrase, and/or delete some criteria by consensus; this reduced the number of criteria and facilitated their ranking. Hence, there were 10 reformulated criteria, each for WB and RBC, and nine each for plasma and PC .The reformulated criteria characterizing each LBP were then scored for relevance  for the most irrelevant criterion) by each expert in the nominal group. The relevance scores for each LBP were represented as box plots . WhateveAlthough the score obtained for each criterion differed according to the expert’s speciality, it was possible to establish an order of importance by summing the ranking scores given by each member of the nominal group for each LBP . It was The literature review was performed by combining the keywords defined in versus synthetic products  for each technical solution  and each LBP . The degFor WB, a high level of consensus was found for pig’s blood: all the experts agreed that this was a relevant technical solution for mimicking the migration of plasticizers into human WB. Bovine WB was also considered to be a relevant technical solution, albeit with a lower level of consensus (71%). The five other points of consensus attested to the irrelevance of canine, equine, ovine, goat, and rabbit WBs for mimicking the migration of plasticizers into human WB. Indeed, goat, and rabbit WBs had a moderate degree of consensus, and canine, equine, and ovine WBs had a low level of consensus.A moderate degree of consensus was found for pig RBC since 81% of the experts agreed that this technical solution was suitable for mimicking the migration of plasticizers into human RBCs. Regarding bovine RBCs, no consensus was observed because the experts’ opinions were divided (between 35% and 65%). With a moderate degree of consensus for canine, ovine, goat, and rabbit RBCs and a low degree of consensus for equine, these five technical solutions were irrelevant for mimicking the migration of plasticizers into human RBCs.For plasma, there was a high level of consensus on pig’s plasma: 88% of the experts agreed that this solution was a suitable technical solution for mimicking the migration of plasticizers into human plasma. Bovine plasma also led to a consensus, albeit at a lower level, since 65% of the experts considered this technical solution to be relevant. Canine, ovine, and goat plasmas had a low degree of consensus and rabbit plasma had a moderate degree of consensus with regard to mimicking the migration of plasticizers into human plasma. No consensus was observed for equine plasma because the experts’ opinions were divided.A moderate degree of consensus was found for pig PC since 81% of the experts agreed that it was a relevant technical solution for mimicking the migration of plasticizers into human PC. No consensus was observed for bovine PC because the experts’ opinions were divided (between 35% and 65%). Canine, equine, ovine, goat, and rabbit PCs had a low or a moderate degree of consensus and were found to be irrelevant for mimicking the migration of plasticizers into human PC.The relevance profiles were quite similar for the four LBPs. The majority of the experts were in favour of using pig LBPs for mimicking the migration of plasticizers into human LBPs. Indeed, the experts mentioned that pig’s blood was already used in several types of studies  because of its physical–chemical properties (notably the red blood cell size), its stability, and the immunologic similarity between pigs and humans. Bovine WB and plasma were also cited as relevant mimics of human WB and plasma. However, a consensus was not obtained for bovine WB because the red blood cell size stays too different from that of humans compared to the pig’s one. The other technical solutions were not considered to be relevant for simulating the migration of plasticizers into LBPs. Furthermore, the experts emphasized the ease of supply for pig and bovine blood relative to other animal blood , for which regulations on animal experiments may be stricter. The blood volume variable was also cited since it was preferable to use blood from an animal with a relatively large volume of blood. In particular, the use of rabbit blood was not recommended since the rather low volume might increase the risk of hemolysis and therefore influence the quality of the blood during sampling. It was mentioned that the use of mammalian plasma would be adequate for mimicking the migration of plasticizers into human plasma. The use of animal models with a fairly high platelet count is required to simulate the migration of plasticizers into human PC: the equine model was not thought to be a good candidate because its platelet count is very low.Eight points of consensus were reached for synthetic technical solutions. A high degree of consensus was found for the use of rheological property modifiers and trace elements, since respectively 90% and 85% of the experts agreed that these were suitable technical solutions for preparing a simulant that mimicked the migration of plasticizers into human WB. The use of isotonic solutions, surface tension reducing agents, buffer solutions, and organic compounds to formulate a WB simulant attracted a moderate level of consensus since 80% of the experts considered these technical solutions to be relevant. A lower consensus (70%) was found for the use of a lipid emulsion. With a very low score (30%), a water-soluble dye was found to be irrelevant for a synthetic simulant. It should be noted that no consensus was reached on the other technical solutions (with scores between 35% and 65%).Five points of consensus were obtained for RBC. A moderate level of consensus was found for rheological property modifiers since 75% of the experts agreed that the use of this type of agent was suitable for mimicking the migration of plasticizers into human RBC. Isotonic solutions and surface tension reducing agents attracted a lower level of consensus since 65% of the experts considered these technical solutions to be relevant. The use of desorbing agents and a water-soluble dye in a synthetic simulant was judged to be inappropriate, and the level of consensus was moderate . The experts’ opinions were divided with regard to the other technical solutions, which demonstrated a lack of consensus.Eleven points of consensus were obtained for plasma. A high degree of consensus was found for the use of buffer solutions because 90% of the experts agreed that these were relevant technical solutions for mimicking the migration of plasticizers into human plasma. A synthetic simulant supplemented with an isotonic solution, a lipid emulsion, a rheological property modifier, a surface tension reducing agent, and certain organic compounds attracted a moderate degree of consensus for relevance. With scores ranging from 15 to 35%, the four other points of consensus attested to the irrelevance of desorbing agents, insoluble particles, preservatives, and water-soluble dyes as components of synthetic simulants for mimicking the migration of plasticizers into human plasma. However, no consensus was observed on the use of stabilizing agents since the experts’ opinions were divided.For PC, six points of consensus were reached. A moderate level of consensus was highlighted for the use of rheology modifying agents and buffer solutions, where respectively 76% and 82% of the experts agreed on the suitability of these technical solutions for mimicking the migration of plasticizers into human PC. The use of an isotonic solution and trace elements led to a lower consensus since, respectively, 71% and 65% of the experts considered these technical solutions to be relevant. The two other points of consensus emphasized the irrelevance of the use of desorbing agents and soluble dyes in an aqueous phase for mimicking the migration of plasticizers into human PC; these technical solutions had scores of 35% and 24%, respectively. However, no consensus was observed for the other technical solutions since the experts’ opinions were divided.In contrast to the results for the simulants of natural origin, profiles for the four LBPs differed when considering the simulants of synthetic origin. However, it was noted that the use of an isotonic solution and a rheological property modifier might be of value in a simulant capable of mimicking the migration of plasticizers from a PVC bag into an LBP. The other technical solutions for simulants must be studied specifically for each LBP. The experts differed in their estimation of the value of synthetic simulants. Some experts considered that it is essential to use natural blood components, while others considered that simulation of the affinity between plasticizers and the LBP is most important—even if the simulant’s chemical composition does not match that of the LBP. Hence, the use of synthetic technical solutions appears to be relevant as long as the proportions of each of the constituents are considered carefully. For the development of simulants, particular attention was paid to the following parameters: pH, viscosity, osmolarity, ionic strength, hydrophobicity, and density. The notion of the complexity of a mixture was also raised by several experts. Indeed, it was often stated that only the components necessary for the development of plasticizer migration simulants should be used, i.e., so that the technical solution is as simple as possible. For example, the use of insoluble particles, water-soluble dyes, preservatives, and stabilizers was widely considered to be non-essential. Moreover, it was suggested that non-essential components might interfere with the essential components and might thus impair the simulant’s ability to mimic the migration of plasticizers into the LBP.Our Delphi working group was able to set out specifications for the development of human LBP simulants and evaluated technical solutions that might meet these specifications. Despite the Delphi method’s inherent limitations and the absence of a truly international context (our study was limited to France and Belgium), the study’s main strength was the multidisciplinary working group on the development of simulants. In contrast to most usual Delphi studies, we decided not to carry out a second survey after the initial questionnaires had been processed. Indeed, the proposals made by the experts were very precise and were easily integrated into the categories studied here. The comparison of a number of relevant natural or synthetic products with human blood is now warranted, with a view to assessing their experimental relevance and determining the amount of plasticizer that transfers from PVC medical devices to LBPs.The points of consensus highlighted by our qualitative study might constitute a database for a draft approach to the standardization of plasticizer migration tests, in which human blood would be replaced by a natural or synthetic simulant. Among all proposed technical solutions, pig’s blood could be the most suitable and convenient one. Indeed, pig’s blood possesses the closest physical–chemical and biological properties to human blood, and it can be processed to obtain plasma, PC, and RBC using the same protocol applied for human blood. The availability and standardization of pigs for experimental research also constitute two clear benefits. However, it could be necessary to check that pig’s blood is not contaminated by plasticizers before migration studies.This approach could also be extended to other types of biological tests in order to reduce the need for scarce human blood.


Coronavirus disease 2019 (COVID-19) emerged in late 2019, with the first case identified in Wuhan City, Hubei Province, China, on 12 December 2019. In order to perceive the comprehensive impact of this pandemic, we have to know that misinformation and denials about COVID-19 have surely exacerbated its diffusion and hindered the response against it. Turkmenistan remains one of the very few countries in the world that lacks reports about emerging cases of the novel coronavirus. Turkmen authorities claim that they have adopted all attainable measures required in order to combat the virus, asserting that COVID-19 has yet to reach their country. Despite the government’s reported absence of COVID-19 in the country, rumors, media reports and independent sources suggest the spread of the pandemic in Turkmenistan. By mid-June 2020, the outbreak was referred to as being serious with patients suffering extreme health risks, and following its state of disrepair and unethical practices, many of those anticipated to be COVID-19 infected tend to suffer at home, discouraging any interaction with the healthcare system. The civil society in Turkmenistan, for the time being, takes full part of the government’s duty in the process of informing and educating the public regarding the COVID-19 pandemic, and endeavors to keep the government and WHO accountable for behaving in such repressive ways that could lead to rather preventable loss of human life in Turkmenistan. Yet, efforts hang fire before unveiling the real situation, and Turkmenistan’s government owning up to the negations and roaming speculations, not only regarding the coronavirus crisis, but every public-related issue itself. Coronavirus disease 2019 (COVID-19) emerged in late 2019, with the first case identified in Wuhan City, Hubei Province, China, on 12 December 2019. It later expanded exponentially, precipitating an ongoing threat and postulating a global health pandemic affecting day to day life in many countries [https://www.hrw.org/world-report/2021/country-chapters/turkmenistan). Overall, the government keeps promoting a vagueness affecting the physical and mental health of people in the country, while continuing to apprehend the absence of confirmed COVID-19 cases [Turkmenistan remains one of the very few countries in the world that lacks reports about emerging cases of the novel coronavirus. Turkmen authorities claim that they have adopted all attainable measures required in order to combat the virus, asserting that COVID-19 has yet to reach their country , 3. Desp19 cases .This denial of the people’s right for the information, health care and accountability is very common within the borders of Turkmenistan. Adding on, the ongoing denial of an apparent COVID-19 outbreak that further jeopardizes the population’s public health.Turkmenistan is poorly positioned to cope with a pandemic, with public health conditions described as alarming as the country is being ranked 101 out of 195 in the 2019 Global Health Security Index. Turkmen citizens have lost faith in such a decaying healthcare system, and have no belief left in that their government will ever support its citizens’ health [Notably, the government realized the risk of COVID-19 early in the pandemic. In January 2020, flights to countries infected with the virus were suspended and later in February, flights from many infected countries were redirected to Turkmenabat International Airport where passengers were tested for signs of the virus, borders were then closed in March 2020 and those entering Turkmenistan were quarantined. Turkmenistan’s state-run railway declared in July 2020 the suspension of travel by local passenger trains. In August 2020, the suspension was extended, with the authorities announcing the requirement of COVID-free certificates prior to travel once the ban is lifted, such measurements had been implemented as well for air travel. RFE/RL later announced in late 2020 that what essentially amounted to a travel ban had been once again extended to January 2021 .Indeed, the spread of the virus can be ought to the country’s relatively small population and geographic isolation, but the unattainable data and knowledge placed remotely distant from the people aided in having the latter unaware of how to manage themselves and protect their own health, and further conveyed the government’s silence and inability to fulfill its obligations regarding the situation in the country , 8.www.Saglyk.org), a non-governmental organization established in 2009, has been providing science-based information on COVID-19 in the Turkmen language to the public since February 2020 [A WHO expert mission was declared to visit Turkmenistan in April 2020. The 10-day mission took place later in July 2020, as clarified by the organization that the 3-month delay was related to logistical issues. The mission backed up the government’s claims and issued that no confirmed cases are present in the country, but urged the government to behave as if the virus was present, however the WHO’s statement was disappointing and further widens the gap between the Turkmen people and their human rights. Whereupon and as it had been over the years, alternative networks take responsibility to provide the public related health information. SAGLYK .Rights and Freedoms of Turkmen Citizens, a Prague-based independent group, reported that health workers in Turkmenistan are lacking personal protective equipment (PPE), a shortage that endangers their lives and health. The group further elaborates that it had also received in June reports of Turkmen doctors and nurses being threatened by Turkmen authorities with criminal prosecution and the denial of their right to practice their professions if refusing to serve in facilities with isolated suspected COVID-19 cases. The group had also reported that in July 2020, authorities arrested seven doctors in one region upon their refusal to follow orders and force patients with COVID-19 symptoms to pay for treatment, however by October, the cases against them were dropped and they were released. Turkmen Initiative for Human Rights (TIHR) also reported in the same month a threat by authorities in Turkmenabat to 120 health workers with prosecution after their written plea to the regional administration regarding solving the issue of shortage in PPE and equipment to treat what was described as a pneumonia outbreak there (What worth is pointing out that Turkmenistan’s claim of being free of the coronavirus is not criticized by many of the countries already hit by the virus, at least not publicly. Guzide Uchkun; the widow of Kemal Uchkun, a Turkish diplomat that passed away in one of Turkmenistan’s hospitals on July 7, 2020, has recently filed a lawsuit against several Turkish government officials upon their failure to transport her husband from Turkmenistan to Turkey to receive proper medical care after the worsening of his symptoms , and is Following its state of disrepair and unethical practices, many of those anticipated to be COVID-19 infected tend to suffer at home, discouraging any interaction with the healthcare system . TestingMany studies on the previous SARS crisis gave much attention to the local organization’s relationship with its public and analyzed the latter’s strategies in implementing communication with respective publics, including employees, media and community –19. RoseThe government’s COVID-19 outbreak denial in Turkmenistan however, blocks the route for implementing such investigations, and further wards off expectations to shed light on health crisis communication and the impacts of health communication efforts demonstrated through the different emerging media. The collapse of communication and management has taken the confidence of the public watching neighboring countries’ governments supply their citizens with COVID-19 data, while they receive none to help keep them stay safe at such times of crisis. Efforts to prevent deaths in Turkmenistan are being made by the public and civil society through the WHO and UN agencies assistance in providing humanitarian cargo to medical institutions in the region, yet continue defying human rights and eradicating the people’s trust.The civil society in Turkmenistan, for the time being, takes full part of the government’s duty in the process of informing and educating the public regarding the COVID-19 pandemic, and endeavors to keep the government and WHO accountable for behaving in such repressive ways that could lead to rather preventable loss of human life in Turkmenistan.Practitioners, especially those at governmental levels, can acknowledge the challenges of crisis management, and suggest appropriate strategies to maintain the organization–public communication to resolve the crisis. From this perspective, it is essential to employ a strategy of conflict management in order to examine the history of a health-based social conflict and the actions developed to manage these conflicts. Moreover, it is cardinal to investigate how such social conflicts emerge and settle in a public health crisis, and how various parties involved select strategies to manage the crisis and conflicts. A key strength that allows to understand the dynamic nature of the crisis and to make judgements on what strategies are appropriate at every juncture. Yet, any effort down this path hangs fire before unveiling the real situation, and Turkmenistan’s government owning up to the negations and roaming speculations, not only regarding the coronavirus crisis, but every public-related issue itself.