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1.
G. P. Patil J. A. Bishop W. L. Myers C. Taillie R. Vraney Denice Wardrop 《Environmental and Ecological Statistics》2004,11(2):139-164
Geographical surveillance for hotspot detection and delineation has become an important area of investigation both in geospatial ecosystem health and in geospatial public health. In order to find critical areas based on synoptic cellular data, geospatial ecosystem health investigations apply recently discovered echelon tools. In order to find elevated rate areas based on synoptic cellular data, geospatial public health investigations apply recently discovered spatial scan statistic tools. The purpose of this paper is to conceptualize a joint role for these together in the spirit of a cross-disciplinary cross-fertilization to accomplish more effective and efficient geographical surveillance for hotspot detection and delineation, and early warning system. 相似文献
2.
This paper presents a scan statistic, progressive upper level set (PULSE) scan statistic, for geospatial hotspot detection
and its software implementation. Like ULS, the PULSE scan statistic is based on the arbitrarily shaped scan window and can
be adapted for a network setting. PULSE is a refinement of the upper level set (ULS) scan statistic. Like some other likelihood
based scanning devices, the ULS scan statistic identifies maximum likelihood estimate (MLE) zones that tend to be ‘stringy’
and sprawling. Its search path increases possibility of inclusion of extraneous cells in its MLE zones and, to a smaller extent,
of exclusion of cells that belong to a true hotspot from its MLE zone. The PULSE scan statistic achieves improvement over
the ULS scan statistic in two ways. First, it begins its search for a most likely zone with a large population of candidate
zones obtained by modifying the ULS tree structure and continues its search using a genetic algorithm. Secondly, to reduce
chances of generating an MLE that is excessively stringy and that includes extraneous cells in the MLE zone, PULSE uses cardinality
and compactness of zones along with their likelihoods as the fitness function in the genetic algorithm and uses several pertinent
criteria including evenness of intra-zone cellular response ratios to determine the MLE zone. To reduce computation, Gumbel
distribution of extreme values is used to determine the p-value of the MLE zone. Better results come at the cost of increased processing time. An evaluative performance study is presented. 相似文献
3.
Recent years have witnessed the growth of new information technologies and their applications to various disciplines. The
goal of this paper is to demonstrate how the two innovative methods, upper level set scan (ULS) hotspot detection and the
multicriteria prioritization scheme, facilitate population health and break new ground in public health surveillance. It is
believed that the social environment (i.e. social conditions and social capital) is one of the determinants of human health.
Using infant health data and 10 additional indicators of social environment in the 159 counties of Georgia, ULS identified
52 counties that are in double jeopardy (high infant mortality and a high rate of low infant birth weight). The multicriteria
ranking scheme suggested that there was no conspicuous spatial cluster of ranking orders, which improved the traditional decision
making by visual geographic cluster. Both hotspot detection and ranking methods provided an empirical basis for re-allocating
limited resources and several policy implications could be drawn from these analytic results. 相似文献
4.
5.
Ronald E. Gangnon 《Environmental and Ecological Statistics》2010,17(1):55-71
The spatial scan statistic is a widely applied tool for cluster detection. The spatial scan statistic evaluates the significance
of a series of potential circular clusters using Monte Carlo simulation to account for the multiplicity of comparisons. In
most settings, the extent of the multiplicity problem varies across the study region. For example, urban areas typically have
many overlapping clusters, while rural areas have few. The spatial scan statistic does not account for these local variations
in the multiplicity problem. We propose two new spatially-varying multiplicity adjustments for spatial cluster detection,
one based on a nested Bonferroni adjustment and one based on local averaging. Geographic variations in power for the spatial
scan statistic and the two new statistics are explored through simulation studies, and the methods are applied to both the
well-known New York leukemia data and data from a case–control study of breast cancer in Wisconsin. 相似文献
6.
Anderson Ribeiro Duarte Luiz Duczmal Sabino José Ferreira André Luiz F. Cançado 《Environmental and Ecological Statistics》2010,17(2):203-229
The geographic delineation of irregularly shaped spatial clusters is an ill defined problem. Whenever the spatial scan statistic
is used, some kind of penalty correction needs to be used to avoid clusters’ excessive irregularity and consequent reduction
of power of detection. Geometric compactness and non-connectivity regularity functions have been recently proposed as corrections.
We present a novel internal cohesion regularity function based on the graph topology to penalize the presence of weak links
in candidate clusters. Weak links are defined as relatively unpopulated regions within a cluster, such that their removal
disconnects it. By applying this weak link cohesion function, the most geographically meaningful clusters are sifted through
the immense set of possible irregularly shaped candidate cluster solutions. A multi-objective genetic algorithm (MGA) has
been proposed recently to compute the Pareto-sets of clusters solutions, employing Kulldorff’s spatial scan statistic and
the geometric correction as objective functions. We propose novel MGAs to maximize the spatial scan, the cohesion function
and the geometric function, or combinations of these functions. Numerical tests show that our proposed MGAs has high power
to detect elongated clusters, and present good sensitivity and positive predictive value. The statistical significance of
the clusters in the Pareto-set are estimated through Monte Carlo simulations. Our method distinguishes clearly those geographically
inadequate clusters which are worse from both geometric and internal cohesion viewpoints. Besides, a certain degree of irregularity
of shape is allowed provided that it does not impact internal cohesion. Our method has better power of detection for clusters
satisfying those requirements. We propose a more robust definition of spatial cluster using these concepts. 相似文献
7.
Luiz Duczmal Ricardo Tavares Ganapati Patil André L. F. Cançado 《Environmental and Ecological Statistics》2010,17(2):183-202
We propose a novel tool for testing hypotheses concerning the adequacy of environmentally defined factors for local clustering
of diseases, through the comparative evaluation of the significance of the most likely clusters detected under maps whose
neighborhood structures were modified according to those factors. A multi-objective genetic algorithm scan statistic is employed
for finding spatial clusters in a map divided in a finite number of regions, whose adjacency is defined by a graph structure.
This cluster finder maximizes two objectives, the spatial scan statistic and the regularity of cluster shape. Instead of specifying
locations for the possible clusters a priori, as is currently done for cluster finders based on focused algorithms, we alter
the usual adjacency induced by the common geographical boundary between regions. In our approach, the connectivity between
regions is reinforced or weakened, according to certain environmental features of interest associated with the map. We build
various plausible scenarios, each time modifying the adjacency structure on specific geographic areas in the map, and run
the multi-objective genetic algorithm for selecting the best cluster solutions for each one of the selected scenarios. The
statistical significances of the most likely clusters are estimated through Monte Carlo simulations. The clusters with the
lowest estimated p-values, along with their corresponding maps of enhanced environmental features, are displayed for comparative analysis. Therefore
the probability of cluster detection is increased or decreased, according to changes made in the adjacency graph structure,
related to the selection of environmental features. The eventual identification of the specific environmental conditions which
induce the most significant clusters enables the practitioner to accept or reject different hypotheses concerning the relevance
of geographical factors. Numerical simulation studies and an application for malaria clusters in Brazil are presented. 相似文献
8.
André L. F. Cançado Cibele Q. da-Silva Michel F. da Silva 《Environmental and Ecological Statistics》2014,21(4):627-650
The scan statistic is widely used in spatial cluster detection applications of inhomogeneous Poisson processes. However, real data may present substantial departure from the underlying Poisson process. One of the possible departures has to do with zero excess. Some studies point out that when applied to data with excess zeros, the spatial scan statistic may produce biased inferences. In this work, we develop a closed-form scan statistic for cluster detection of spatial zero-inflated count data. We apply our methodology to simulated and real data. Our simulations revealed that the Scan-Poisson statistic steadily deteriorates as the number of zeros increases, producing biased inferences. On the other hand, our proposed Scan-ZIP and Scan-ZIP+EM statistics are, most of the time, either superior or comparable to the Scan-Poisson statistic. 相似文献
9.
Whether general environmental exposures to endocrine disrupting chemicals (including pesticides and dioxin) might induce decreased
sex ratios (male/female ratio at birth) is discussed. To address this issue, the authors looked for a space-time clustering
test which could detect local areas of significantly low risk, assuming a Bernoulli distribution. As a matter of fact, if the endocrine disruptor hypothesis holds true, and if the
sex ratio is a sentinel health event indicative of new reproductive hazards ascribed to environmental factors, then in a given
region, either a cluster of low male/female ratio among newborn babies would be expected in the vicinity of polluting municipal
solid waste incinerators (MSWIs) (supporting the dioxin hypothesis), or local clusters would be expected in some rural areas
where large amounts of pesticides are sprayed.
Among cluster detection tests, the spatial scan statistic has been widely used in various applications to scan for areas
with high rates, and rarely (if ever) with low rates. Therefore, the goal of this paper was to check the properties of the
scan statistics under a given scenario (Bernoulli distribution, search for clusters with low rates) and to assess its added
value in addressing the sex ratio issue.
This study took place in the Franche-Comté region (France), mainly rural, comprising three main MSWIs, among which only one
had high dioxin emissions level in the past. The study population consisted of 192,490 boys and 182,588 girls born during
the 1975–1999 period.
On the whole, the authors conclude that: (i) spatial and space-time scan statistics provide attractive features to address
the sex ratio issue; (ii) sex ratio is not markedly affected across space and does not provide a reliable screening measure
for detecting reproductive hazards ascribed to environmental factors. 相似文献
10.
Annalina Sarra Eugenia Nissi Sergio Palermi 《Environmental and Ecological Statistics》2012,19(2):219-247
Indoor radon is an important risk factor for human health. Indeed radon inhalation is considered the second cause of lung cancer after smoking. During the last decades, in many countries huge efforts have been made in order to measuring, mapping and predicting radon levels in dwellings. Various researches have been devoted to identify those areas within the country where high radon concentrations are more likely to be found. Data collected through indoor radon surveys have been analysed adopting various statistical approaches, among which hierarchical Bayesian models and geostatistical tools are worth noting. The essential goal of this paper regards the identification of high radon concentration areas (the so-called radon prone areas) in the Abruzzo Region (Italy). In order to accurately pinpoint zones deserving attention for mitigation purpose, we adopt spatial cluster detection techniques, traditionally employed in epidemiology. As a first step, we assume that indoor radon measurements do not arise from a continuous spatial process; thus the geographic locations of dwellings where the radon measurements have been taken can be viewed as a realization of a spatial point process. Following this perspective, we adopt and compare recent cluster detection techniques: the simulated annealing scan statistic, the case event approach based on distance regression on the selection order and the elliptic spatial scan statistic. The analysis includes data collected during surveys carried out by the Regional Agency for the Environment Protection of Abruzzo (ARTA) in 1,861 random sampled dwellings across 277 municipalities of the Abruzzo region. The radon prone areas detected by the selected approaches are provided along with the summary statistics of the methods. Finally, the methodologies considered in this paper are tested on simulated data in order to evaluate their power and the precision of cluster location detection. 相似文献
11.
12.
Angelo Pecci Ganapati Patil Orazio Rossi Pierfrancesca Rossi 《Environmental and Ecological Statistics》2010,17(4):473-502
The environmental decision-maker is aware of the increasing difficulties in finding sufficient financial resources for nature
conservation. So he must focus his attention on ecological situations that more than the others merit considering and defending
because of elevated value but also because of risk for their intrinsic characteristics and for human pressure acting on them.
Usually an ecological scientist focuses his attention on the natural patches of the landscape, analyzing their peculiar ecological
traits forgetting that, even if we want to protect some environmental critical situations, this can be done only moving to
the administrative partition of the territory since the central and local environmental stakeholders have primary interest
in providing funds to those involved in those critical situations. The present work shows a methodological approach, consisting
of a set of statistical and geoinformational tools, considering both ecological and socio-demographical indicators. The goal
is not simply to give some general guidelines for environmental policies to the involved stakeholders but focuses more on
finding out which administrative local partitions in a study area are more worthy to receive urgently the priority funds for
biodiversity protection to face critical environmental situations often due to a combination of intrinsic ecological parameters
and external human pressure ones. Obtaining results that cover 5% of the Communes involved in the area seems to be a realistic
result that a decision-maker can support and fund. Methodologically and geospatial data analytically, the investigation offers
interesting challenges for surveillance geoinformatics of hotspot detection and prioritization, because of the presence of
multiple hotspots and multiple sets of multiple indicators. 相似文献
13.
Air–water flows at hydraulic structures are commonly observed and called white waters. The free-surface aeration is characterised by some intense exchanges of air and water leading to complex air–water structures including some clustering. The number and properties of clusters may provide some measure of the level of particle-turbulence and particle–particle interactions in the high-velocity air–water flows. Herein a re-analysis of air–water clusters was applied to a highly aerated free-surface flow data set (Chanson and Carosi, Exp Fluids 42:385–401, 2007). A two-dimensional cluster analysis was introduced combining a longitudinal clustering criterion based on near-wake effect and a side-by-side particle detection method. The results highlighted a significant number of clustered particles in the high-velocity free-surface flows. The number of bubble/droplet clusters per second and the percentage of clustered particles were significantly larger using the two-dimensional cluster analysis than those derived from earlier longitudinal detection techniques only. A number of large cluster structures were further detected. The results illustrated the complex interactions between entrained air and turbulent structures in skimming flow on a stepped spillway, and the cluster detection method may apply to other highly aerated free-surface flows. 相似文献
14.
Multiple data sources are essential to provide reliable information regarding the emergence of potential health threats, compared to single source methods. Spatial Scan Statistics have been adapted to analyze multivariate data sources, but only ad hoc procedures have been devised to address the problem of selecting the most likely cluster and computing its significance. In this work, information from multiple data sources of disease surveillance is incorporated to achieve more coherent spatial cluster detection using tools from multi-criteria analysis. The best cluster solutions are found by maximizing two objective functions simultaneously, based on the concept of dominance. To evaluate the statistical significance of solutions, a statistical approach based on the concept of attainment function is used. The multi-criteria approach has several advantages: the representation of the evaluation function for each data source is clear, and does not suffer from an artificial, and possibly confusing mixture with the other data source evaluations; it is possible to attribute, in a rigorous way, the statistical significance of each candidate cluster; and it is possible to analyze and pick-up the best cluster solutions, as given naturally by the non-dominated set. The methodology is illustrated with real datasets. 相似文献
15.
Glen D. Johnson 《Environmental and Ecological Statistics》2008,15(3):293-311
Infectious disease surveillance has become an international top priority due to the perceived risk of bioterrorism. This is
driving the improvement of real-time geo-spatial surveillance systems for monitoring disease indicators, which is expected
to have many benefits beyond detecting a bioterror event. West Nile Virus surveillance in New York State (USA) is highlighted
as a working system that uses dead American Crows (Corvus brachyrhynchos) to prospectively indicate viral activity prior to human onset. A cross-disciplinary review is then presented to argue that
this system, and infectious disease surveillance in general, can be improved by complementing spatial cluster detection of
an outcome variable with predictive “risk mapping” that incorporates spatiotemporal data on the environment, climate and human
population through the flexible class of generalized linear mixed models.
相似文献
Glen D. JohnsonEmail: |
16.
Routine surveillance of a large geographic region for clusters of adverse health events, particularly cancers, often involves
small area health data, possibly controlling for exposure information. Many different methods have been proposed to test for
the presence of geographical clusters. Two of the most popular methods are the spatial scan method proposed by Kulldorff and
that using a fixed number of cases within scanning circles proposed by Besag and Newell. Although the second test is very
popular, it has some difficulties. While the scan test controls for the multiple testing problem, the Besag and Newell test
does not. Additionally, the latter method requires the setting of several tuning parameters whose values affect the test performance
and are subjectively chosen by the user. This creates a difficulty to make a fair comparison between the two methods and it
explains why there have been few formal studies evaluating their relative performances. In this paper, we modify the Besag
and Newell test allowing for the control of the error type I probability and compare its power with respect to that of the
spatial scan test. We used data sets from a publicly available simulated benchmark. We found that the two methods have similar
results, except for clusters located in sparsely populated regions, where the spatial scan method presented a better performance. 相似文献
17.
The purpose of this paper is to develop a set of associated statistical tests for spatial clustering. In particular, a set
of three associated tests will be developed; these will correspond to the three types of tests set out by Besag and Newell
(general tests, focused tests, and tests for the detection of clustering). The associated tests draw primarily, though not
exclusively, upon existing tests and results. The principal contributions are based upon the score statistic for focused tests,
which has been an important approach to testing for clustering around environmental hazards. The first contribution consists
of the formulation of a global statistic for general tests that corresponds to focused score statistics, along with an assessment
of the distribution of the statistic under the null hypothesis of no raised incidence. The local score statistics used for
focused tests will have the property of summing to the global statistic used for the corresponding general test. Attention
is also given to the maximum local score statistic for the “test for the detection of clustering”. The critical values of
this statistic which are required for testing the null hypothesis are described. Application of the methods is made to leukemia
data for central New York State. 相似文献
18.
Regional ecosystem monitoring is a central form of knowledge sharing and collaboration amongst scientists and decision makers on environmental health, land use change, and science-policy development. Despite the proliferation of such research networks on long-term monitoring on many continents, little has been achieved in Africa. This study aims to assess and examine the spatiotemporal trend and categorical patterns in ecosystem monitoring-related research in Africa for the benefits of conserving biodiversity and sustaining natural resource sectors for well-being and livelihood security, environmental planning, and ecological stewardship. A systematic review was conducted using bibliometric tools. Based on a set of search terms and peer-reviewed publications retrieved from various ecosystem monitoring networks and journal databases, further analysis was conducted using social network approaches, mapping tools, and content analysis. About 1442 scientific publications on ecosystem monitoring and related research were documented from 1987 to 2014 mostly published in English. The number of publication increased progressively since 1992 after the Convention on Biodiversity was signed and this trend peaked till 2008. South African Journal of Science was the most leading journal and Nature the most cited. Internationally coauthored and collaborative articles represented majority of the findings with the United Kingdom at the central position in the research network due to colonial relationships. Regional collaboration amongst countries is limited owing to language barriers and other institutional constraints such as funding and short-term projects. These findings have implication for prioritizing national and regional policies toward biodiversity science and its contribution to human well-being, food security, and global change responses. 相似文献
19.
The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis. 相似文献
20.
Laura Mannocci Sébastien Villon Marc Chaumont Nacim Guellati Nicolas Mouquet Corina Iovan Laurent Vigliola David Mouillot 《Conservation biology》2022,36(1):e13798
Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna. 相似文献