scholarly journals Spatial point pattern analysis of prehospital naloxone administrations

2017 ◽  
Author(s):  
Christopher Ryan
Keyword(s):  
United States ◽  
Monte Carlo Simulation ◽  
Spatial Distribution ◽  
Pattern Analysis ◽  
Spatial Clustering ◽  
The United States ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Opioid Overdose ◽  
Spatial Point

AbstractObjectivesThe increasing problem in the United States with opioid dependence and overdose, often fatal, is well-recognized. As naloxone has only one clinical use—the treatment of opioid overdose—its administration by EMS personnel can serve as a surveillance indicator for opioid overdose. This study uses specific locations of EMS calls, and methods of point pattern analysis, to detect overall spatial clustering among EMS naloxone administrations compared to EMS calls in general.Study DesignA cross-sectional study of incident locations of EMS responses in a three-county EMS region in the United States.MethodsRepeated random samples from the spatial distribution of all EMS calls were used, in a Monte Carlo simulation, to represent the background inhomogeneity of the population. Observed F, G, and inhomogeneous K and L functions from the spatial distribution of naloxone-involved calls were compared to their null sampling distributions obtained from the Monte Carlo simulation.ResultsCases of naloxone administration demonstrated spatial clustering in the range of 0 to 5000 meters, and particularly around 2500 meters, beyond what could be attributable to the spatial heterogeneity of all EMS calls.ConclusionsEfforts to understand the fundamental nature of opioid overdose as a spatial point process could yield innovative public health interventions to control the epidemic.

scholarly journals Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mariem Ben-Said
Keyword(s):  
Spatial Patterns ◽  
Pattern Analysis ◽  
Biotic Interactions ◽  
Plant Ecology ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Summary Statistics ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis

Abstract Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

scholarly journals Analyzing the Spatial Distribution of Drumlins: A Two-Phase Mosaic Approach

1984 ◽  
Vol 30 (106) ◽  
pp. 302-307
Author(s):  
B. N. Boots ◽  
R. K. Burns
Keyword(s):  
Spatial Distribution ◽  
Pattern Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Statistical Bias ◽  
Two Phase ◽  
Alternative Approach ◽  
Mosaic Approach ◽  
The Individual

AbstractResearchers have analyzed various properties of drumlins within individual drumlin fields in order to provide evidence to help in identifying the processes involved in drumlin formation. One property which has been examined is the spatial distribution of drumlins within a field. Traditionally, in such endeavours the individual drumlins have been represented as points and their distribution examined using techniques of point-pattern analysis. We suggest that not only is such a representation inappropriate at this scale, it also introduces statistical bias which makes the results of such analyses questionable. Consequently, we propose an alternative approach which involves representing individual drumlins as areal phenomena and considering their pattern as a two-phase mosaic. The advantages of such an approach are discussed and it is illustrated by applying it to two different drumlin fields.

scholarly journals Analysis of conditional colocalization relationships and hierarchies from three-color microscopy images

2021 ◽  
Author(s):  
Jesus Vega-Lugo ◽  
Bruno da Rocha-Azevedo ◽  
Aparajita Dasgupta ◽  
Nicolas Touret ◽  
Khuloud Jaqaman
Keyword(s):  
Molecular Interactions ◽  
Cell Biology ◽  
Pattern Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis ◽  
Cellular Context ◽  
Microscopy Images

Colocalization is a cornerstone approach in cell biology for the analysis of multicolor microscopy images. It provides information on the localization of molecules within various subcellular compartments and allows the interrogation of molecular interactions in their spatiotemporal cellular context. However, the overwhelming majority of colocalization analyses are designed for two-color microscopy images, which limits their applicability and the type of information that they may reveal, leading to underutilization of multicolor microscopy images. Here we describe an approach for analyzing the colocalization relationships between three molecular entities, termed 'conditional colocalization analysis,' based on spatial point pattern analysis of detected objects in microscopy images. Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two molecular entities is influenced, positively or negatively, by their respective colocalization with a third entity. We showcase two applications of conditional colocalization analysis, one addressing the question of the compartmentalization of molecular interactions, and one investigating the hierarchy of molecular interactions in a multimolecular complex. The software for conditional colocalization analysis is freely accessible online at https://github.com/kjaqaman/conditionalColoc.

scholarly journals Investigate human responses to Late-Holocene changes of fluvial landforms through Spatial Point Pattern Analysis (Po Plain, N Italy)

2020 ◽  
Author(s):  
Filippo Brandolini ◽  
Francesco Carrer
Keyword(s):  
Pattern Analysis ◽  
Flood Hazard ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Spatial Point Pattern ◽  
Po Valley ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis ◽  
Settlement Strategies ◽  
Alluvial Geomorphology

<p>In fluvial environments, alluvial geomorphological features had a huge influence on settlement strategies during the Holocene. However, a few projects investigate this topic through quantitative and question-driven analyses of the human-landscape correlation. The Po Valley (N Italy) – located between the Mediterranean regions and continental Europe – is as a key area for the investigation of environmental and cultural influences on settlement strategies since prehistoric times. For instance, the transition from Roman to Medieval times represented a crucial moment for the reorganisation of human settlement strategies in the Po Valley; the process was mainly driven by climate changes and socio-political factors. Spatial Point Pattern Analysis (SPPA) was here employed to provide a solid statistical assessment of these dynamics in the two historical phases. A point pattern (PP) corresponds to the location of spatial events generated by a stochastic process within a bounded region. The density of the PP is proportional to the intensity of the underlying process. The intensity, in turn, can be constant within the region or spatially variable, thus influencing the uniformity of distribution of spatial events. SPPA provides powerful techniques for the statistical analysis of PP data that consist of a complete set of locations of archaeological sites/findings within an observation window. The use of spatial covariates enables the investigation of environmental and non-environmental factors influencing the spatial homogeneity of the point process. Archaeologists have increasingly analyzed such datasets to quantify the characteristics of observed spatial patterns with the aims of deriving hypotheses on the underlying processes or testing hypotheses derived from archaeological theory. The aim of this paper is to assess whether a shift in water management strategies between the Roman and Medieval periods influenced the spatial distribution of settlements, and to evaluate the relative importance of agricultural suitability over flood risks in each historical phase. In particular, the variability settlement patterns between Roman and Medieval phases has been assessed against two related proxies for alluvial geomorphology and agricultural suitability: flood hazard and soil texture. The SPPA performed shows that Roman and Medieval settlement patterns mirror two different human responses to the geomorphological dynamics of the area. Roman land- and water-management were able to minimize the flood hazard, to drain the floodplain and organize a complex land use on different soil types. In the Medieval period, the alluvial geomorphology of the area, characterised by wide swampy meadows and frequent flood events, affected the spatial organisation of settlement, which privileged topographically prominent positions. Social and cultural dynamics played a crucial role in responding to alluvial geomorphological environmental challenges in different times.</p>

scholarly journals Spatial point pattern analysis of urban retail stores: the case of twelve large- and medium-sized Greek cities

2020 ◽  
Vol 11 (4) ◽  
pp. 36-63
Author(s):  
Michail-Christos TSOUTSOS ◽  
◽  
Yorgos Photis
Keyword(s):  
Spatial Patterns ◽  
Pattern Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Retail Stores ◽  
High Population Density ◽  
Spatial Point Pattern ◽  
Professional Activities ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis

The retailers’ profitability and the consumers’ satisfaction depend on finding the optimal location for a retail store. When considering the stores’ spatial distribution, business potential can be understood and a squandering planning of resources can be avoided. In this paper we identify the spatial patterns of retail stores located in the traditional commercial centers of twelve large -and medium-sized Greek cities, aiming to explain why such patterns exist. The type of retail activities was determined using the image of the ground-floor stores provided by the Google Street View (GSV) service and thus 7322 stores were recorded in a geodatabase as point features. The results reveal that the retail stores’ distribution has a clustered and random spatial pattern at least in one city, where the high population density and the increase in rental prices of premises for professional activities constitute the factors that form these spatial patterns respectively.

scholarly journals Spatial point pattern analysis identifies mechanisms shaping the skin parasite landscape in Leishmania donovani infection

2021 ◽  
Author(s):  
Johannes S.P. Doehl ◽  
Helen Ashwin ◽  
Najmeeyah Brown ◽  
Audrey Romano ◽  
Samuel Carmichael ◽  
...  
Keyword(s):  
Image Analysis ◽  
Leishmania Donovani ◽  
Pattern Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis ◽  
Causative Agents ◽  
Ecological Pattern

Increasing evidence suggests that infectiousness of hosts carrying parasites of the Leishmania donovani complex, the causative agents of visceral leishmaniasis, is linked to parasite repositories in the host skin. This is particularly true for asymptomatic to moderately symptomatic hosts with no or minimally detectable parasitemia. However, a detailed description of the dispersal and dispersion of parasites and parasitized host phagocytes in the skin is still lacking. Here, we combined image analysis with spatial point pattern models borrowed from ecology, providing a new route to predicting modes of skin parasite dispersal and characterizing their dispersion. Our results suggest that, after initial parasite seeding in the skin, parasites form self-propagating networks of parasite patch clusters in the skin that may contribute to parasite outward transmission. This combination of imaging and ecological pattern analysis to identify mechanisms driving the skin parasite landscape offers new perspectives on parasitism by Leishmania donovani and may also be applicable to elucidating the behavior of other intracellular tissue-resident pathogens.

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