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Background Ticks are the primary vectors of numerous zoonotic pathogens, transmitting more pathogens than any other blood-feeding arthropod. In the northern hemisphere, tick-borne disease cases in humans, such as Lyme borreliosis and tick-borne encephalitis, have risen in recent years, and are a significant burden on public healthcare systems. The spread of these diseases is further reinforced by climate change, which leads to expanding tick habitats. Switzerland is among the countries in which tick-borne diseases are a major public health concern, with increasing incidence rates reported in recent years. Methods In response to these challenges, the “Tick Prevention” app was developed by the Zurich University of Applied Sciences and operated by A&K Strategy Ltd. in Switzerland. The app allows for the collection of large amounts of data on tick attachment to humans through a citizen science approach. In this study, citizen science data were utilized to map tick attachment to humans in Switzerland at a 100 m spatial resolution, on a monthly basis, for the years 2015 to 2021. The maps were created using a state-of-the-art modeling approach with the software extension spatialMaxent, which accounts for spatial autocorrelation when creating Maxent models. Results Our results consist of 84 maps displaying the risk of tick attachments to humans in Switzerland, with the model showing good overall performance, with median AUC ROC values ranging from 0.82 in 2018 to 0.92 in 2017 and 2021 and convincing spatial distribution, verified by tick experts for Switzerland. Our study reveals that tick attachment to humans is particularly high at the edges of settlement areas, especially in sparsely built-up suburban regions with green spaces, while it is lower in densely urbanized areas. Additionally, forested areas near cities also show increased risk levels. Conclusions This mapping aims to guide public health interventions to reduce human exposure to ticks and to inform the resource planning of healthcare facilities. Our findings suggest that citizen science data can be valuable for modeling and mapping tick attachment risk, indicating the potential of citizen science data for use in epidemiological surveillance and public healthcare planning. Graphical Abstract

To ensure the safe and sustainable use of water, it is crucial to assess the quality of the groundwater. Utilizing the water quality index (WQI), an attempt has been made to understand the groundwater quality in three Talukas of the Sindhudurg District of Maharashtra State. The groundwater samples were collected from 37 observation wells located in study area in post-monsoon season. The overall groundwater quality of study area was assessed using the water quality index (WQI). Spatial distribution maps of pH, turbidity, TDS, hardness, alkalinity, Na, K, Fe, Zn, Cl, Ca, Cl − and NO 3 have been prepared using the Inverse Distance Weighted (IDW) approach using QGIS 3.22.1 software. The water samples in the study region have been categorized from excellent to good, according to the water quality index map. Vengurla and Vadakhol have water quality index ratings of 25 and 26.23, respectively indicating the maximum value of the water quality index in the study area. The elevated levels of total dissolved solids (TDS), sodium, iron, zinc and turbidity in groundwater can indeed contribute to a high-water quality index value at monitoring stations and it indicates over-exploitation and anthropogenic activities such as more agricultural and domestic uses. The higher values of chlorine, total dissolved solids, turbidity and hardness indicate the contamination of groundwater due to seawater intrusion near these stations.

The number of visible global navigation satellite system (GNSS) satellites is an important indicator for evaluating positioning accuracy. In urban areas, buildings and trees cause serious satellite signal obstruction and attenuation. Studies have used three-dimensional (3D) city models or 2D panoramic imagery to calculate the visibility of satellites in some areas at a certain time. However, the production of accurate 3D models involves heavy manual work and is expensive, while public panoramic imagery mainly spreads over roads and cannot support 3D analysis. Also, the existing studies seldom consider the impact of urban on satellite signals. We thus propose a method that considers the influence of both trees and buildings. A full-path propagation model for GNSS signals is established. Then, a fast visibility analysis of satellites using an airborne laser scanning point cloud is performed. Hence, the number of visible satellites at a specific time can be mapped. In addition, real-time and forecast visibility maps are generated according to the GNSS ephemeris. To verify the effectiveness of the proposed method, we collected field measurement data for qualitative and quantitative evaluation of experiments. The experiments demonstrated that the proposed method provides an easy-to-use and high-precision solution to map the spatio-temporal visibility of satellites in 3D urban space, which serves as an important reference for applications like unmanned aerial vehicles route planning.

This paper aims to understand spatial and temporal trends in pregabalin prescribing and the relationship with deprivation across England at both general practice and clinical commissioning group (CCG) levels. A set of 207 independent generalised additive models are employed to model the spatiotemporal trend of pregabalin prescribed and dispensed per 1000 population, adjusting for deprivation. The response variable is pregabalin prescribed in milligrams, with weighted Index of Multiple Deprivation (IMD), geographical location and time as predictors. The set of active prescribing facilities grouped within CCG is the unit of analysis. National Health Service open prescribing data; all general practices in England, UK between January 2015 and June 2017. All patients registered to general practices in England, UK. Adjusting for deprivation, a North-South divide is shown in terms of prescribing trends, with the North of England showing increasing prescribing rates during the study period on average, while in the South of England rates are on average decreasing. Approximately 60% of general practices showed increasing prescribing rate, with the highest being 4.03 (1.75 for the most decreasing). There were no apparent spatial patterns in baseline prescription rates at the CCG level. Weighted IMD score proved to be statistically significant in 138 of 207 CCGs. Two-thirds of CCGs showed more pregabalin prescribed in areas of greater deprivation. Whether the prescribing rate is high due to high baseline prescription rate or increasing rates needs to be specifically looked at. The spatial temporal modelling demonstrated that the North of England has a significantly higher chance to see increase in pregablin prescriptions compared with the South, adjusted for weighted IMD. Weighted IMD has shown positive impact on pregabalin prescriptions for 138 CCGs.

Not only do university campuses consist of a variety of social and educational buildings, they also create an integrated system with their outdoor spaces and furniture, recreation and landscape areas. Outdoors have the potential to create social interaction, rest and relaxation, recreation, exchange of ideas and a strong sense of ownership and belonging. Creating a common identity for social life by enabling people to communicate and socialize with each other is the most important function of outdoor spaces. However, although the rationality of external spaces is designed, it is possible to use other than what is expected in practice. The relationship between the external spaces and the building groups, the adequacy, the duration of use, the accessibility and the interaction of the physical environment should be examined with a holistic approach to understand the difference between expectations and reality. In order to identify user needs in outdoor spaces as a way to assess if human use and design intentions are in fact successful, post occupancy evaluation (POE) is recommended as the most significant advanced method. Unfortunately, although studies on the evaluation of indoor spaces have been increasing day by day, there is no comprehensive study of POE that can be applied to the outdoor spaces, especially in university campuses. In this study, a POE method which discusses the variables that affect the use of outdoor space and the interaction between these variables is introduced. The proposed method was applied in a suburban university campus and the results were evaluated in terms of outdoor use.

Effective indoor localization largely relies on the fingerprint database (model) of Received Signal Strength (RSS) in connection with Radio Frequency sources, such as the most widely used Bluetooth Low Energy (BLE) iBeacons. RSSs exhibit significant random variations in both the spatial and temporal domains. It is a notoriously onerous and challenging task to construct the fingerprint database for accurate localization, as the BLE RSSs must be captured via a full space scan from one point to another every few meters in a certain period of time. In order to tackle this problem, this study proposes an approach to fast fingerprints construction that only requires a sparse sampling of RSS of the space. First, a smartphone records the time series of RSS over a designated path, and a radio map for the path is then generated by a spatio-temporal mapping method using the Pedestrian Dead Reckoning algorithm. Second, the radio map of the entire space can be obtained via Gauss Process Regression (GPR), with outliers reduced to improve the reliability of the fingerprint database. Experiments have been performed in an underground carpark (38 m × 14 m), and the experimental results indicate that the proposed approach can construct the fingerprint database 300% faster than the conventional approach does. The localization accuracy of both approaches is quite similar (80% error in 2.8 m). The proposed approach offers potential for the construction of a large-scale fingerprint database for a wide-area Location Based Service (LBS) of Smart City indoor and outdoor integration, where big RSS data processing is a must.

Holocene mean July (TJul) and mean January (TJan) temperatures were reconstructed at Lake Trehörningen in southwest Sweden using pollen–climate calibration functions and converted into anomalies relative to modern temperatures. The anomalies were applied to 28 meteorological stations in Denmark, with each station adjusted to account for spatial variability in both TJul and TJan. The resulting reconstructions were merged to create composite TJul and TJan records. The individual reconstructions were also used to establish the parameterization of the TJul and TJan values, resulting in Holocene temperature maps for all of Denmark. Low TJul values characterised southern Sweden and Denmark at the start of the Holocene, followed by an increase during the early Holocene. Likewise, TJan was initially low at the start of the Holocene, followed by an increase between 10 500 and 9900 cal. BP. Thereafter, TJan was relatively stable between 9900 and 8000 cal. BP. The general increase in temperature during the early Holocene was accompanied by a decrease in the amplitude of the mean monthly temperature record, indicating that a maritime climate was established at this time. Maximum TJul and TJan are recorded during the mid-Holocene interval from 8000 to 4500 cal. BP, with consistently high July temperatures (>18°C) between 6700 and 5400 cal. BP. During the late Holocene, both TJul and TJan gradually decreased. The Holocene temperature maps of Denmark reveal spatial patterns in both summer and winter temperature. In the summer, an east–west decreasing temperature gradient, related to a maritime effect, has persisted in Denmark throughout the Holocene. In contrast, the temperature in winter has varied spatially along subtle coastal–inland and topographical gradients. Various mechanisms have been invoked to explain the Holocene trends in temperature, including the melting of the Scandinavian Ice Sheet, changes in insolation, and changes in the dominant type of atmospheric circulation affecting northern Europe.

The light use efficiency (LUE) of photosynthesis dynamically adapts to environmental factors, and this leads to complex spatio-temporal variations of photosynthesis on various scales from the leaf to the canopy level. These spatio-temporal pattern formations not only help to understand the regulatory properties of photosynthesis, but may also have a constructive role in maintaining stability in metabolic pathways and during development. Optical remote sensing techniques have the potential to detect physiological and biochemical changes in plant ecosystems, and non-invasive detection of changes in photosynthetic energy conversion may be of great potential for managing agricultural production in a future bio-based economy. Here we review the results from selected remote sensing projects for their potential to quantify LUE from the level of single leaves to the canopy scale. In a case study with soybean grown under elevated CO₂ conditions at the SoyFACE facility, we tested the photochemical reflectance index (PRI) for its capacity to quantify higher photosynthetic efficiency. In this study the PRI failed to detect differences in photosynthetic light conversion, most likely because of the variable canopy structure of the soybean canopy. We thus conclude that at the current state of the art the PRI cannot serve as an easy remote sensing approach to detect changes in photosynthetic energy conversion in agriculture. As an alternative we present approaches that aim to quantify the fluorescence signal of chlorophyll and thus estimate photosynthetic efficiency. In a second case study, using avocado as a model species, an active laser induced fluorescence transient (LIFT) method was applied to deliver maps of different photosynthetic efficiency within the canopy. Cold-induced down-regulation of photosynthesis in the upper canopy was detected, so active fluorescence may prove its potential for non-invasive monitoring of crops. With a view to the future, we present a method for large scale managing of agricultural practices within the framework of the FLuorescence EXplorer (FLEX) mission, which proposed launching a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. This mission was selected for inclusion in pre-phase A by the European Space Agency.

Accurate mapping of landslides and the reliable identification of areas most affected by landslides are essential for advancing the understanding of landslide erosion processes. Remote sensing data provides a valuable source of information on the spatial distribution and location of landslides. In this paper we present an approach for identifying landslide-prone “hotspots” and their spatio-temporal variability by analyzing historical and recent aerial photography from five different dates, ranging from 1944 to 2011, for a study site near the town of Pahiatua, southeastern North Island, New Zealand. Landslide hotspots are identified from the distribution of semi-automatically detected landslides using object-based image analysis (OBIA), and compared to hotspots derived from manually mapped landslides. When comparing the overlapping areas of the semi-automatically and manually mapped landslides the accuracy values of the OBIA results range between 46% and 61% for the producer’s accuracy and between 44% and 77% for the user’s accuracy. When evaluating whether a manually digitized landslide polygon is only intersected to some extent by any semi-automatically mapped landslide, we observe that for the natural-color images the landslide detection rate is 83% for 2011 and 93% for 2005; for the panchromatic images the values are slightly lower (67% for 1997, 74% for 1979, and 72% for 1944). A comparison of the derived landslide hotspot maps shows that the distribution of the manually identified landslides and those mapped with OBIA is very similar for all periods; though the results also reveal that mapping landslide tails generally requires visual interpretation. Information on the spatio-temporal evolution of landslide hotspots can be useful for the development of location-specific, beneficial intervention measures and for assessing landscape dynamics.

Plasmodium vivax exacts a significant toll on health worldwide, yet few efforts to date have quantified the extent and temporal trends of its global distribution. Given the challenges associated with the proper diagnosis and treatment of P vivax, national malaria programmes—particularly those pursuing malaria elimination strategies—require up to date assessments of P vivax endemicity and disease impact. This study presents the first global maps of P vivax clinical burden from 2000 to 2017. In this spatial and temporal modelling study, we adjusted routine malariometric surveillance data for known biases and used socioeconomic indicators to generate time series of the clinical burden of P vivax. These data informed Bayesian geospatial models, which produced fine-scale predictions of P vivax clinical incidence and infection prevalence over time. Within sub-Saharan Africa, where routine surveillance for P vivax is not standard practice, we combined predicted surfaces of Plasmodium falciparum with country-specific ratios of P vivax to P falciparum. These results were combined with surveillance-based outputs outside of Africa to generate global maps. We present the first high-resolution maps of P vivax burden. These results are combined with those for P falciparum (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The burden of P vivax malaria decreased by 41·6%, from 24·5 million cases (95% uncertainty interval 22·5–27·0) in 2000 to 14·3 million cases (13·7–15·0) in 2017. The Americas had a reduction of 56·8% (47·6–67·0) in total cases since 2000, while South-East Asia recorded declines of 50·5% (50·3–50·6) and the Western Pacific regions recorded declines of 51·3% (48·0–55·4). Europe achieved zero P vivax cases during the study period. Nonetheless, rates of decline have stalled in the past five years for many countries, with particular increases noted in regions affected by political and economic instability. Our study highlights important spatial and temporal patterns in the clinical burden and prevalence of P vivax. Amid substantial progress worldwide, plateauing gains and areas of increased burden signal the potential for challenges that are greater than expected on the road to malaria elimination. These results support global monitoring systems and can inform the optimisation of diagnosis and treatment where P vivax has most impact. Bill & Melinda Gates Foundation and the Wellcome Trust.