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PubMed1994

[Analysis of spatial clustering of disease].

It is difficult to determine whether there is spatial clustering of disease if the geographical distribution of population is unknown. Permutation test reported in the paper can be used as a method to judge the spatial clustering with unknown distribution of a random sample of cases. Comparison of difference in frequency of small distances between pairs of cases and controls can show whether there is spatial clustering of the disease.

Disease Outbreaks↗
PubMedDate not supplied

[Analysis of spatial frequency characteristics of complex receptive fields].

The difference fB2-fB1=deltaf and ratio fB2/fB1=R of the bandwidth boundary frequencies fB1, fB2 of spatial frequency characteristic of complex receptive field depends on the size of RF and spatial structure of excitatory and inhibitory zones. deltaf and r are independent of the weighting functions of excitatory and inhibitory zones. The theoretical value of r is similar to data which was obtained in psychophysical and physiologycal experiments. The dependence of contrast sensitivity on spatial frequency can be explained by dependence of the envelope of weighting functions of exitatory (inhibitory) zones on the spatial frequency.

Animals↗
PubMed1995

Spatial-temporal analysis of mortality using splines.

A method for constructing contour maps in disease mapping using smoothing splines is presented. Smoothing errors are discussed and error maps suggested. The approach is illustrated for mortality data on cardiovascular diseases in northwestern Germany (Lower Saxony and Bremen) 1970-1979.

Biometry↗
PubMed1999

Evaluating health service equity at a primary care clinic in Chilimarca, Bolivia.

Policy makers and health planners generally support the concept of equitable health care. A focus on who can use a health service, or its potential access, will not necessarily lead to equitable care if people are not willing to avail themselves of the health services offered. Because equity is difficult to operationalize, outcome-based indicators such as the actual utilization of services are advocated as a means to measure equal access. This paper evaluates the utility of linking the concept of equity with a temporal and spatial analysis of clinic users at a micro scale, supplemented by a community survey. Various spatial scales were employed in the analysis. Utilization of the primary care clinic in Chilimarca, Bolivia varied considerably during the first 25 months of operation. Spatially, utilization shifted away from the targeted service area. Within the targeted service area, usage was concentrated in a few blocks of the community and generally diminished with increasing distance from the clinic. The survey further revealed place of origin, length of residence, and language spoken at home as variables differentiating users from non-users. Failure to include the spatial dimension of utilization would lead to different conclusions if only aggregate data were employed. Spatial analysis of output measures is imperfect and does not necessarily deal with all of the access issues related to acceptability. They do, however, begin to isolate areas of a defined geographic area where further investigation would assist in ascertaining, and subsequently addressing, potential problems related to equal access.

Bolivia↗
PubMedDate not supplied

[Application of geographical information systems in epidemiological studies exemplified by the ISAAC study in Munich].

Geographical Information Systems (GIS) are increasingly applied as modern tools for analysis and visualization of health-related spatial data, especially in epidemiological research. GIS are used by medical researchers and executives in the public health service. A community-based survey was conducted according to the phase II protocol of the International Study of Asthma and Allergies in Childhood (ISAAC) in Munich. The spatial patterns of disease incidence were analysed and related to exposure data by GIS. The prevalence study on fourth-grade pupils (n = 3354) and school beginners (n = 2890) was conducted during the school term 1995/96 in Munich. Parental questionnaires and measurements of lung function and immunological parameters were used. The questionnaire data were integrated in a GIS database. In this paper we discuss methodological aspects of GIS-based spatial analysis related to epidemiological data. In addition, we investigate whether there were spatial clusters of children with wheeze in the last 12 months of a magnitude unlikely to occur by chance and which could indicate local health risks. The study was based on permutation tests where global and local methods were applied. No spatial clusters of children with asthma symptoms were identified in the city of Munich.

Asthma↗
PubMed2005

Understanding the spatial diffusion process of severe acute respiratory syndrome in Beijing.

OBJECTIVES: To measure the spatial contagion of severe acute respiratory syndrome (SARS) in Beijing and to test the different epidemic factors of the spread of SARS in different periods. METHODS: A join-count spatial statistic study was conducted and the given hypothetical processes of the spread of SARS in Beijing were tested using various definitions of 'joins'. RESULTS: The spatial statistics showed that of the six diffusion processes, the highest negative autocorrelation occurred in the doctor-number model (M-5) and the lowest negative autocorrelation was found in the population-amount model (M-3). The results also showed that in the whole 29-day research period, about hour or more days experienced a significant degree of contagion. CONCLUSIONS: Spatial analysis is helpful in understanding the spatial diffusion process of an epidemic. The geographical relationships were important during the early phase of the SARS epidemic in Beijing. The statistic based on the number of doctors was significant and more informative than that of the number of hospitals. It reveals that doctors were important in the spread of SARS in Beijing, and hospitals were not as important as doctors in the contagion period. People are the key to the spread of SARS, but the population density was more significant than the population size, although they were both important throughout the whole period.

China↗
PubMed2001

Integrating water-quality management and land-use planning in a watershed context.

The spatial relationships between land uses and river-water quality measured with biological, water chemistry, and habitat indicators were analyzed in the Little Miami River watershed, OH, USA. Data obtained from various federal and state agencies were integrated with Geographic Information System spatial analysis functions. After statistically analyzing the spatial patterns of the water quality in receiving rivers and land uses and other point pollution sources in the watershed, the results showed that the water biotic quality did not degrade significantly below wastewater treatment plants. However, significantly lower water quality was found in areas downstream from high human impact areas where urban land was dominated or near point pollution sources. The study exhibits the importance of integrating water-quality management and land-use planning. Planners and policy-makers at different levels should bring stakeholders together, based on the understanding of land-water relationship in a watershed, to prevent pollution from happening and to plan for a sustainable future.

Agriculture↗
PubMed1975

A spatial and temporal analysis of four cancers in African gold miners from Southern Africa.

The pattern of cancer in African gold miners over the 8-year period 1964-71, comprising 2,926,461 man-years of employment was studied. Of the 1344 cancers found, primary liver cancer accounted for 52-8%, oesophageal cancer 12-1%, cancer of the respiratory system 5-4% and cancer of the bladder 4-8%. Analysis of the spatial distribution of these four cancers, both on subcontinental and local scale, showed distinct gradients of occurrence between areas of significantly higher and lower incidence than expected. In the case of primary liver cancer in Mozambique and oesophageal cancer in the Transkei, the spatial distribution reflects closely that found in the general resident population of each territory. The crude incidence rate of primary liver cancer in gold miners from Mozambique dropped sharply over the period of the survey.

Africa, Southern↗
PubMed1998

Evaluation of skin- versus teeth-attached markers in wireless optoelectronic recordings of chewing movements in man.

This study evaluated the applicability of skin- and teeth-attached reflex markers fixed to the mandible and the head for optoelectronic recording of chewing movements. Markers were attached to the upper and lower incisors and to the skin on the forehead, the bridge of the nose, the tip of the nose and the chin in seven subjects. Chewing movements were recorded in three dimensions using a high-resolution system for wireless optoelectronic recording. Skin markers were systematically displaced due to skin stretch. The largest displacement was observed for the chin marker, whereas minor displacement was found for markers located on the forehead and the bridge of the nose. In repeated recordings, the smallest intra-individual variation in displacement was found for the marker on the bridge of the nose. In spite of relatively large displacement for the chin marker, the temporal estimates of the mandibular movement were not affected. Teeth markers were found to significantly increase the vertical mouth opening, although the duration of the chewing cycle was unaffected. This indicates an increase in chewing velocity. We suggest that markers located on the bridge of the nose are acceptable for recordings of chewing movements. Skin markers on the chin can be reliably used for temporal analysis. They are also acceptable for spatial analysis if an intra-individual variability of 2 mm is allowed. Teeth-attached markers may significantly influence the natural chewing behavior. Thus, both types of marker systems have advantages as well as disadvantages with regard to the accuracy of the chewing movement analysis. Selection of a marker system should be based on the aims of the study.

Adult↗
PubMed2025

Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review.

Tuberculosis remains a leading cause of infection-related mortality, and efforts to reduce its incidence have been hindered by an incomplete understanding of local Mycobacterium tuberculosis transmission dynamics. Advances in pathogen sequencing and spatial analysis have created new opportunities to map M tuberculosis transmission patterns more precisely. In this scoping review, we searched for studies combining pathogen genetics and location data to analyse the spatial patterns of M tuberculosis transmission and identified 142 studies published between 1994 and 2024. Secular changes in genetic methods were observed, with genome sequencing approaches largely replacing lower-resolution genotyping methods since 2020. The included studies addressed four primary research questions: how are tuberculosis cases and M tuberculosis transmission clusters geographically distributed; do spatially concentrated M tuberculosis clusters exist, and where are these areas located; when spatial concentration occurs, what host, pathogen, or environmental factors contribute to these patterns; and do identifiable relationships exist between the spatial proximity of tuberculosis cases and the genetic similarity of the M tuberculosis isolates infecting these individuals? Collectively, in this Review, we examined the available study data, evaluated the analytical requirements for addressing these questions, and discussed opportunities and challenges for future research. We found that the integration of spatial and genomic data can inform a detailed understanding of local M tuberculosis transmission patterns, but improved study designs and new analytical methods to address gaps in sampling completeness and to integrate additional movement data are needed to fully realise the potential of these tools.

Humans↗
PubMed2005

Spatial and temporal analysis of Clostridium difficile infection in patients at a pediatric hospital in California.

OBJECTIVE: To examine the usefulness of temporal and spatial analysis in identifying nosocomial transmission of Clostridium difficile among pediatric patients hospitalized on four wards at The Children's Hospital of Central California from September 8, 1998, to January 16, 1999. DESIGN: Stool specimens obtained from the clinical microbiology laboratory during the study period were tested by culture and latex agglutination for C. difficile. Polymerase chain reaction was used to identify toxin genes. Isolates obtained were mapped to a grid for each ward and were analyzed using the Knox test. Results were compared with DNA fingerprints generated by arbitrarily primed polymerase chain reaction. RESULTS: Total occupancy of these 4 wards was 438 during the study period. Stool specimens were available for 256 (58%) of these patients, yielding 67 C. difficile isolates and generating 2,211 case pairs for analysis by the Knox test. After stratification by toxin status, 5 clustered pairs of toxigenic isolates were identified on 1 of the wards by this method. Fingerprint analysis identified 4 clusters with indistinguishable banding patterns on 2 of the 4 wards. Two of the identified clusters were toxigenic and 2 were nontoxigenic. None of these clusters corresponded to clusters identified by the Knox test. CONCLUSIONS: The Knox test is an ineffective method for identifying cases resulting from nosocomial transmission of C. difficile in a pediatric setting due to the persistence of C. difficile spores and the unique environment of a pediatric hospital. Molecular analysis remains the most effective method.

California↗
PubMed2003

Using principal component analysis to monitor spatial and temporal changes in water quality.

Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted. The spatial analysis isolated two stations showing a possible point or non-point source of pollution. This study shows the importance of environmental monitoring associated with simple but powerful statistics to better understand a complex water system.

Environmental Monitoring↗
PubMed2007

Evaluation of PCA and ICA of simulated ERPs: Promax vs. Infomax rotations.

Independent components analysis (ICA) and principal components analysis (PCA) are methods used to analyze event-related potential (ERP) and functional imaging (fMRI) data. In the present study, ICA and PCA were directly compared by applying them to simulated ERP datasets. Specifically, PCA was used to generate a subspace of the dataset followed by the application of PCA Promax or ICA Infomax rotations. The simulated datasets were composed of real background EEG activity plus two ERP simulated components. The results suggest that Promax is most effective for temporal analysis, whereas Infomax is most effective for spatial analysis. Failed analyses were examined and used to devise potential diagnostic strategies for both rotations. Finally, the results also showed that decomposition of subject averages yield better results than of grand averages across subjects.

Algorithms↗
PubMed1991

Parkinsonism mortality in the US, 1. Time and space distribution.

We studied the time-space variations of mortality for parkinsonism in the US during the periods 1962-1985 and 1971-1978 from statistics on primary cause-of-death and multiple causes-of-death, respectively. Linear regression analysis and a test for significance of spatial clustering were used. For parkinsonism as a primary cause-of-death, up to the late 1970's there was a decrease in mortality for the age groups below 75 and stable rates for the age group 75 years and over. A moderate decrease among those below 75 years, and a sharp increase in mortality among those over 74, were observed for the period since the late 1970s. The variation of the age-specific mortality during the period 1962-1985 ranged from 100% in the age group 35-44 years to +98% in those aged over 84 years. Within the same age group, the variations across time of mortality due to, and related to parkinsonism, for the period 1971-1978, were similar. In the spatial analysis, an association between mortality related to parkinsonism and geographical latitude was found. We conclude that: 1) parkinsonism at death is widely distributed; 2) the changes across time can not be explained by a reduction in general mortality; 3) improvements in diagnostic ascertainment and reporting among the elderly may have particularly occurred during the last decade; and 4) the disorder has been progressively confined to the elderly by diminishing in the younger birth cohorts.

Adult↗
PubMed1990

A spatial power spectrum analysis of the electroencephalogram.

The method of spatial power-spectrum analysis has been applied to measurements of the distribution of rms alpha-band potential on the scalp. Data was recorded using the 31-Electrode System and spatial power-spectrum estimates (PSEs) were obtained from Mercator projections of the potential interpolated using the triangular method. PSEs were calculated using the Lim and Malik algorithm for maximum-entropy power-spectrum estimation. In order to investigate the utility of spatial power-spectrum analysis, PSEs were obtained from subjects in two conditions; resting with eyes closed (EC) and resting with eyes open and fixed on a single point (EO). A stepwise discriminant analysis was performed with features from the PSEs and the resultant discriminant function was applied to data not considered in the formulation of the function. Over 92% of test data was correctly classified. The features used in the discriminant function identify spatial waves which are most useful in separating data. The results demonstrate that waves oriented along front-back and right-left lines are most important in separating data into EC and EO groups.

Brain↗
PubMed2026

A Practical Workflow for Spatial Transcriptomics Data Analysis: From Data Acquisition to Advanced Analyses.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.

Spatial Transcriptomics↗
PubMed2002

The application of local measures of spatial autocorrelation for describing pattern in north Australian landscapes.

This paper tests the use of a spatial analysis technique, based on the calculation of local spatial autocorrelation, as a possible approach for modelling and quantifying structure in northern Australian savanna landscapes. Unlike many landscapes in the world, northern Australian savanna landscapes appear on the surface to be intact. They have not experienced the same large-scale land clearance and intensive land management as other landscapes across Australia. Despite this, natural resource managers are beginning to notice that processes are breaking down and declines in species are becoming more evident. With future declines of species looking more imminent it is particularly important that models are available that can help to assess landscape health, and quantify any structural change that takes place. GIS and landscape ecology provide a useful way of describing landscapes both spatially and temporally and have proved to be particularly useful for understanding vegetation structure or pattern in landscapes across the world. There are many measures that examine spatial structure in the landscape and most of these are now available in a GIS environment (e.g. FRAGSTATS* ARC, r.le, and Patch Analyst). All these methods depend on a landscape described in terms of patches, corridors and matrix. However, since landscapes in northern Australia appear to be relatively intact they tend to exist as surfaces of continuous variation rather than in clearly defined homogeneous units. As a result they cannot be easily described using entity-based models requiring patches and other essentially cartographic approaches. This means that more appropriate methods need to be developed and explored. The approach examined in this paper enables clustering and local pattern in the data to be identified and forms a generic method for conceptualising the landscape structure where patches are not obvious and where boundaries between landscape features are difficult to determine. Two sites are examined using this approach. They have been exposed to different degrees of disturbance by fire and grazing. The results show that savanna landscapes are very complex and that even where there is a high degree of disturbance the landscape is still relatively heterogeneous. This means that treating savanna landscapes as being made up of homogeneous units can limit analysis of pattern, as it can over simplify the structure present, and that methods such as the autocorrelation approach are useful tools for quantifying the variable nature of these landscapes.

Australia↗
PubMed2006

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Acoustic Stimulation↗