Método de estratificación de territorios basado en sistemas de información geográfica y medidas de similitud geométrica / Territory Stratification Method based on Geographic Information Systems and Geometric Similarity Measures

Una meta del sistema de salud es la prevención de enfermedades, por ello cobra especial importancia el estudio de la relación de enfermedades con el espacio. Existen evidencias del empleo de los Sistemas de Información Geográfica en estudios sobre la distribución espacial de problemas de salud. A pesar de esto, los trabajos reportados en la literatura consultada no explotan la componente espacial de los datos, lo que limita su integralidad. Por otra parte, existe dispersión en las metodologías, herramientas y técnicas para abordar estudios de este tipo. En esta investigación se presenta un método de estratificación de territorios basado en Sistemas de Información Geográfica y medidas de similitud geométrica, definidas a partir de los criterios: distancia, tamaño y conectividad. La propuesta permite realizar estudios estratificados según la primera ley de la geografía y garantiza la obtención de estratos más compactos. El método propuesto cuenta con cinco etapas: Selección de indicadores y territorios, Preprocesamiento de indicadores, Agrupamiento, Postprocesamiento y Visualización, soportado en una solución informática basada en software libre. Como parte de la validación se aplica el método en un caso de estudio y se realiza el análisis de índices de validación que avalan la efectividad y competitividad de la propuesta(AU)

A goal of the health system is the prevention of diseases, which is why the study of the relationship of diseases with space is of special importance. There is evidence of the use of Geographic Information Systems in studies on the spatial distribution of health problems. Despite this, the works reported in the consulted literature do not exploit the spatial component of the data, which limits its comprehensiveness. On the other hand, there is dispersion in the methodologies, tools and techniques to approach studies of this type. This research presents a method of stratification of territories based on Geographic Information Systems and geometric similarity measures, defined from the criteria: distance, size and connectivity. The proposal allows for stratified studies according to the first law of geography and guarantees the obtaining of more compact strata. The proposed method has five stages: Selection of indicators and territories, Pre-processing of indicators, Grouping, Post-processing and Visualization, supported by a computer solution based on free software. As part of the validation, the method is applied in a case study and the analysis of validation indices is carried out that guarantee the effectiveness and competitiveness of the proposal(AU)

Epi InfoTM en los sistemas de información en salud para COVID-19 / Epi InfoTM in Health Information Systems for COVID-19

La COVID-19 ha desatado una emergencia internacional en Salud Pública al afectar millones de personas, provocar muertes, y causar una crisis humanitaria nunca antes vista. Esto ha saturado los sistemas de información en salud de los países afectados, donde resultan de utilidad las herramientas informáticas para el manejo de un gran número de casos, al menor costo económico posible. En este contexto resalta el paquete de programas epidemiológicos Epi InfoTM, que permite crear formularios electrónicos para la recolección de datos. La presente investigación tiene como objetivo describir las ventajas y facilidades de implementar Epi InfoTM para los casos de COVID-19. Con módulos para analizar la información mediante cálculos y representaciones de medidas epidemiológicas, además de crear mapas de casos sospechosos o confirmados, Epi InfoTM cuenta también con complementos para dispositivos móviles y la web; todos con experiencias probadas en situaciones de epidemias como la del Ébola, VIH y el MERS. Por lo que Epi InfoTM es una aplicación robusta y libre de costo muy útil para su implementación en los sistemas de información en salud para el manejo adecuado de casos de COVID-19(AU)

COVID-19 has unleashed an international Public Health emergency by affecting millions of people, causing deaths, and a humanitarian crisis never seen before. This has saturated the health information systems of the affected countries, where computer tools are useful for managing a large number of cases, at the lowest possible economic cost. In this context, the Epi InfoTM package of epidemiological programs which allows creating electronic forms for data collections, stands out in addition with modules to analyze the information through calculations and representations of epidemiological measures. It also allows creating maps of suspected or confirmed cases and has applications for mobile devices and web; all with proven experiences in epidemic situations such as Ebola, HIV, and the previous outbreaks of Coronavirus. Therefore, Epi InfoTM is a robust and free of cost application, very useful for its implementation in health information systems for the adequate management of COVID-19 cases(AU)

Real-time dispersal of malaria vectors in rural Africa monitored with lidar.

Lack of tools for detailed, real-time observation of mosquito behavior with high spatio-temporal resolution limits progress towards improved malaria vector control. We deployed a high-resolution entomological lidar to monitor a half-kilometer static transect positioned over rice fields outside a Tanzanian village. A quarter of a million in situ insect observations were classified, and several insect taxa were identified based on their modulation signatures. We observed distinct range distributions of male and female mosquitoes in relation to the village periphery, and spatio-temporal behavioral features, such as swarming. Furthermore, we observed that the spatial distributions of males and females change independently of each other during the day, and were able to estimate the daily dispersal of mosquitoes towards and away from the village. The findings of this study demonstrate how lidar-based monitoring could dramatically improve our understanding of malaria vector ecology and control options.

The Accuracy of a Low-Cost GPS System during Football-Specific Movements.

An affordable player monitoring solution could make the evaluation of external loading more accessible across multiple levels of football (soccer). The present study aimed to determine the accuracy of a newly designed and low-cost Global Positioning System (GPS) whilst performing match-specific movement patterns. Sixteen professional male football players (24 ± 3 years) were assigned a GPS device (TT01, Tracktics GmbH, Hofheim, Germany) and completed two experimental trials. In each trial, a continuous protocol including seven movements (sideways cornering, diagonal cornering, accelerating, decelerating, backwards jogging, shuttle running, and skipping) adding up to 500 m, was completed. Time-motion data was compared with criterion distance and velocity (photo-cell timing gates and radar). Validity was assessed through the standard error of the estimate (SEE) and reliability through the coefficient of variation (CV; both with 95% confidence limits). For the total distance covered during the protocol, the system was found to be valid (SEE = 3.1% [2.2; 5.8]) and reliable (intra-device CV = 2.0% [1.2; 7.6]). Similar results were found for velocity (SEE = 3.4% [2.6; 4.8], CV = 4.7% [3.2; 8.5]). In conclusion, the present GPS system, a low-cost solution, was found to be a valid and reliable tool for measuring physical loading during football-specific movements.

The Validity and Reliability of Global Positioning System Units for Measuring Distance and Velocity During Linear and Team Sport Simulated Movements.

Huggins, RA, Giersch, GEW, Belval, LN, Benjamin, CL, Curtis, RM, Sekiguchi, Y, Peltonen, J, and Casa, DJ. The validity and reliability of GPS units for measuring distance and velocity during linear and team sport simulated movements. J Strength Cond Res 34(11): 3070-3077, 2020-This experimental study aimed to assess the validity and reliability of shirt-mounted 10-Hz global positioning system (GPS) units (Polar Team Pro) for measuring total distance (TD), constant velocity (VelC), and instantaneous velocity (VelI) during linear running and a team sport simulation circuit (TSSC). Fifteen male soccer athletes completed linear tasks (40 and 100 m) at various velocities: walk (W) (4.8-7.9 km·h), jog (J) (8.0-12.7 km·h), run (R) (12.9-19.9 km·h), and sprint (S) (>20.0 km·h) and a 120-m TSSC. Global positioning system validity and reliability for TD, VelC, and VelI were compared with criterion measures using 2 methods (a and b) of GPS raw data extraction. When measuring TD for the Polar Team Pro device, validity and reliability measures were <5% error at all velocities during the 40-m (with the exception of the S [%CV = 8.03]) and 100-m linear trial (both extraction methods) and TSSC. The GPS mean difference (±SD) for TD during the TSSC using extraction methods (a) and (b) was 0.2 ± 1.2 and 2.2 ± 2.2 m, respectively. The validity of the device in measuring VelC was significantly different (p < 0.05) at all velocities during the 40 m (exception W) and the 100 m, with effect sizes ranging from trivial to small (exception of 100 m S). VelI was similar (p > 0.05) at all velocities, except for the W (p = 0.001). The reliability of the device when measuring VelC during the 40 and 100 m was <5% CV; however, during the 100 m, VelI ranged from 1.4 to 12.9%. Despite trivial to large effect sizes for validity of TD, this device demonstrated good reliability <5% CV during linear and TSSC movements. Similarly, effect sizes ranged from trivial to large for VelC, and yet VelI reliability was good for VelC, but good to poor for VelI.

COVID-19 Waves: Importance of Accumulative Mortality per Million Inhabitants.

The reported number of new cases underestimates the real spread of COVID-19 pandemic because of non-tested asymptomatic people and limited global access to reliable diagnostic tests. In this context, COVID-19 mortality with confirmed diagnosis becomes an attractive source of information to be included in the analysis of perspectives and proposals. Objective data are required to calculate the capacity of resources provided by health systems. New strategies are needed to stabilize or minimize the mortality surge. However, we will not afford this goal until more alternatives were available. We still need an effective treatment, an affordable vaccine, or a collective achievement of sufficient immunity (reaching up to 70% of the whole population). At any time, the arriving waves of the pandemic are testing the capacity of governments. The health services struggle to keep the plateau in a steady-state below 100 deaths per million inhabitants. Therefore, it is necessary to increase the alternatives and supplies based on the current and near-future expected demands imposed by the number of deaths by COVID-19. Estimating COVID-19 mortality in various scenarios with the gradual release of social constraints will help predict the magnitude of those arriving waves.

Current State of Geospatial Methodologic Approaches in Canadian Population Oncology Research.

Geospatial analyses are increasingly used in population oncology. We provide a first review of geospatial analysis in Canadian population oncology research, compare to international peers, and identify future directions. Geospatial-focused peer-reviewed publications from 1992-2020 were compiled using PubMed, MEDLINE, Web of Science, and Google Scholar. Abstracts were screened for data derived from a Canadian cancer registry and use of geographic information systems. Studies were classified by geospatial methodology, geospatial unit, location, cancer site, and study year. Common limitations were documented from article discussion sections. Our search identified 71 publications using data from all provincial and national cancer registries. Thirty-nine percent (N = 28) were published in the most recent 5-year period (2016-2020). Geospatial methodologies included exposure assessment (32.4%), identifying spatial associations (21.1%), proximity analysis (16.9%), cluster detection (15.5%), and descriptive mapping (14.1%). Common limitations included confounding, ecologic fallacy, not accounting for residential mobility, and small case/population sizes. Geospatial analyses are increasingly used in Canadian population oncology; however, efforts are concentrated among a few provinces and common cancer sites, and data are over a decade old. Limitations were similar to those documented internationally, and more work is needed to address them. Organized efforts are needed to identify common challenges, develop leading practices, and identify shared priorities.

Type D personality and global positioning system tracked social behavior in patients with cardiovascular disease.

OBJECTIVE: Social behavior (e.g., loneliness, isolation) has been indicated as an important risk factor for cardiovascular disease. Recent studies show that Type D personality might be an important predictor of social behavior. Hence, the current exploratory study aims to examine, using ecological assessment, whether Type D personality is associated with a lower likelihood to engage in social encounters in patients with cardiovascular disease. METHOD: Cardiac patients who participated in the Do CHANGE (Phase 2) trial were included in current analysis. As part of the Do CHANGE intervention, real-life data were collected in the intervention group using the MOVES app, which was installed on patients' mobile phones. For a period of 6 months, Global Positioning System (GPS) data from the participating patients were collected. From the GPS data, 3 target variables were computed: (a) general activity level, (b) social variety, and (c) social opportunity. RESULTS: A total of 70 patients were included in the analysis. Patients with a Type D personality had lower scores on the "social opportunity" variable compared to non-Type D patients (F = 6.72; p = .01). Type D personality was associated with lower social participation after adjusting for depression and anxiety. No association between Type D personality and general activity or behavioral variety was observed. CONCLUSIONS: This is the first study to use an ecological measure to assess social behavior of cardiac patients with a Type D personality. Results show that Type D personality might be associated with lower social engagement, which could, in turn, partly explain its association with adverse health outcomes. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A Systematic Methodology to Evaluate Prediction Models for Driving Style Classification.

Identifying driving styles using classification models with in-vehicle data can provide automated feedback to drivers on their driving behavior, particularly if they are driving safely. Although several classification models have been developed for this purpose, there is no consensus on which classifier performs better at identifying driving styles. Therefore, more research is needed to evaluate classification models by comparing performance metrics. In this paper, a data-driven machine-learning methodology for classifying driving styles is introduced. This methodology is grounded in well-established machine-learning (ML) methods and literature related to driving-styles research. The methodology is illustrated through a study involving data collected from 50 drivers from two different cities in a naturalistic setting. Five features were extracted from the raw data. Fifteen experts were involved in the data labeling to derive the ground truth of the dataset. The dataset fed five different models (Support Vector Machines (SVM), Artificial Neural Networks (ANN), fuzzy logic, k-Nearest Neighbor (kNN), and Random Forests (RF)). These models were evaluated in terms of a set of performance metrics and statistical tests. The experimental results from performance metrics showed that SVM outperformed the other four models, achieving an average accuracy of 0.96, F1-Score of 0.9595, Area Under the Curve (AUC) of 0.9730, and Kappa of 0.9375. In addition, Wilcoxon tests indicated that ANN predicts differently to the other four models. These promising results demonstrate that the proposed methodology may support researchers in making informed decisions about which ML model performs better for driving-styles classification.

Assessing Google Street View Image Availability in Latin American Cities.

Virtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (- 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.

Tracking In-Match Movement Demands Using Local Positioning System in World-Class Men's Ice Hockey.

Douglas, AS and Kennedy, CR. Tracking in-match movement demands using local positioning system in world-class men's ice hockey. J Strength Cond Res 34(3): 639-646, 2020-While the global positioning system has been used in field sports for a decade, local positioning systems are newly available in indoor sports for the tracking of velocity and distance during competition. World-class male ice hockey players (n = 20) were monitored during 5 international matches. Speed and distance outputs were analyzed to determine the differences between positions, periods, and in-shift demands. Defense had a difference between forwards at distances covered at very slow (p < 0.001), slow (p < 0.001), and moderate (p < 0.001) speed. Forwards were found to cover a greater distance at very fast speed (p = 0.001) and sprint speed (p < 0.001). Defense had a decrease in skating distance at very fast (p < 0.001) and sprint skating speeds (p = 0.02). Forwards had an increase in very slow skating (p = 0.02) and a decrease in sprint skating distance (p = 0.02). Game situational differences were found for defense and forwards in average speeds for defense (p < 0.001) and forwards (p < 0.001). Local positioning systems data have the potential to accurately inform coaches of the position-specific demands of game situations and the training needs by position. Specifically, forwards performed more high-intensity skating than defensemen, whereas powerplay and penalty kill situations offered specific demands for the 2 positional groups. Finally, the intensity of skating was reduced in the third period for both defensemen and forwards. Further research can evaluate whether this is related to tactical decisions, or the metabolic cost of ice hockey.

Addressing the data guardian and geospatial scientist collaborator dilemma: how to share health records for spatial analysis while maintaining patient confidentiality.

BACKGROUND: The utility of being able to spatially analyze health care data in near-real time is a growing need. However, this potential is often limited by the level of in-house geospatial expertise. One solution is to form collaborative partnerships between the health and geoscience sectors. A challenge in achieving this is how to share data outside of a host institution's protection protocols without violating patient confidentiality, and while still maintaining locational geographic integrity. Geomasking techniques have been previously championed as a solution, though these still largely remain an unavailable option to institutions with limited geospatial expertise. This paper elaborates on the design, implementation, and testing of a new geomasking tool Privy, which is designed to be a simple yet efficient mechanism for health practitioners to share health data with geospatial scientists while maintaining an acceptable level of confidentiality. The basic premise of Privy is to move the important coordinates to a different geography, perform the analysis, and then return the resulting hotspot outputs to the original landscape. RESULTS: We show that by transporting coordinates through a combination of random translations and rotations, Privy is able to preserve location connectivity among spatial point data. Our experiments with typical analytical scenarios including spatial point pattern analysis and density analysis shows that, along with protecting spatial privacy, Privy maintains the spatial integrity of data which reduces information loss created due to data augmentation. CONCLUSION: The results from this study suggests that along with developing new mathematical techniques to augment geospatial health data for preserving confidentiality, simple yet efficient software solutions can be developed to enable collaborative research among custodians of medical and health data records and GIS experts. We have achieved this by developing Privy, a tool which is already being used in real-world situations to address the spatial confidentiality dilemma.

A comparison of a GPS device and a multi-camera video technology during official soccer matches: Agreement between systems.

The aim of this study was to compare the agreement of the movement demands data during a soccer match (total distance, distance per minute, average speed, maximum speed and distance covered in different speed sectors) between an optical tracking system (Mediacoach System) and a GPS device (Wimu Pro). Participants were twenty-six male professional soccer players (age: 21.65 ± 2.03 years; height: 180.00 ± 7.47 cm; weight: 73.81 ± 5.65 kg) from FC Barcelona B, of whom were recorded a total of 759 measurements during 38 official matches in the Spanish second division. The Mediacoach System and the Wimu Pro were compared using the standardized mean bias, standard error of estimate, intraclass correlation coefficients (ICC), coefficient of variation (%), and the regression equation to estimate data for each variable. In terms of agreement between systems, the magnitude of the ICC was almost perfect (> 0.90-1.00) for all variables analyzed. The coefficient of the variations between devices was close to zero (< 5%) for total distance, distance per minute, average speed, maximum speed, and walking and jogging, and between 9% and 15% for running, intense running, and sprinting at low and at high intensities. It can be observed that, compared to Wimu Pro the Mediacoach System slightly overestimated all the variables analyzed except for average speed, maximum speed, and walking variables. In conclusion, both systems can be used, and the information they provide in the analyzed variables can be interchanged, with the benefits implied for practitioners and researchers.

A fine granularity based user collaboration algorithm for location privacy protection.

As the location trajectory contains more spatial-temporal information about the user, it will be even dangerous for jeopardizing the privacy of the user. In order to cope with the correlation, an algorithm that utilizes the query division had been proposed. In this algorithm, random blocks of query context was used, so as the adversary was obfuscated and difficult to correlate the real result. However, this algorithm fails to dispose the size of each query block, as once same size blocks were obtained by the adversary continuously, so the adversary can regard them as blocks from the same query context, and then obtains the query context to correlate the discrete locations. In view of above conditions, in this paper we propose a fine granularity block division algorithm based on the conception of granularity measurement as well as granularity layer division, so with the help of collaborative users the location privacy of the user will be protected. In this algorithm, the query context will be divided into fine granularity size of information blocks that difficult to be distinguished with others, and then these blocks will be exchanged with other collaborative users to eliminate the difference in block size. In addition, as each block is divided into fine granularity size, the adversary will be difficult to correlate the discrete locations into location trajectory, so the location privacy will be protected. At last, through security analysis and experimental verification, this granularity indistinguishable algorithm is analyzed and verified at both theoretical and practical levels, which further demonstrate the superiority of the proposed algorithm compared with other similar algorithms.

Development of a Sensor-Based Behavioral Monitoring Solution to Support Dementia Care.

BACKGROUND: Mobile and wearable technology presents exciting opportunities for monitoring behavior using widely available sensor data. This could support clinical research and practice aimed at improving quality of life among the growing number of people with dementia. However, it requires suitable tools for measuring behavior in a natural real-life setting that can be easily implemented by others. OBJECTIVE: The objectives of this study were to develop and test a set of algorithms for measuring mobility and activity and to describe a technical setup for collecting the sensor data that these algorithms require using off-the-shelf devices. METHODS: A mobility measurement module was developed to extract travel trajectories and home location from raw GPS (global positioning system) data and to use this information to calculate a set of spatial, temporal, and count-based mobility metrics. Activity measurement comprises activity bout extraction from recognized activity data and daily step counts. Location, activity, and step count data were collected using smartwatches and mobile phones, relying on open-source resources as far as possible for accessing data from device sensors. The behavioral monitoring solution was evaluated among 5 healthy subjects who simultaneously logged their movements for 1 week. RESULTS: The evaluation showed that the behavioral monitoring solution successfully measures travel trajectories and mobility metrics from location data and extracts multimodal activity bouts during travel between locations. While step count could be used to indicate overall daily activity level, a concern was raised regarding device validity for step count measurement, which was substantially higher from the smartwatches than the mobile phones. CONCLUSIONS: This study contributes to clinical research and practice by providing a comprehensive behavioral monitoring solution for use in a real-life setting that can be replicated for a range of applications where knowledge about individual mobility and activity is relevant.

GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology.

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.

Driving while navigating: On-road driving performance using GPS or printed instructions.

BACKGROUND.: Route navigation is a high-level skill and requires intact executive functioning to successfully find one's way while driving in unfamiliar environments. PURPOSE.: Driving performances were compared while navigating using electronic devices and printed directions on unfamiliar driving routes as well as in an interactive driving simulator. METHOD.: Twenty-four participants drove two on-road routes using GPS and printed directions, and navigated using printed directions in the simulator, using a point system to evaluate performance. The two unfamiliar routes, order of simulator and on-road driving, and use of GPS and printed directions were counterbalanced. Paired t test were used to compare both GPS versus printed directions and performance between on-road driving and the simulator. FINDINGS.: Participants' performance using GPS on the road was significantly better than with printed directions. There was no significant difference between performance in the simulator and on the road. IMPLICATIONS.: Using GPS may be an effective strategy for improving safety. Using a driving simulator may be an efficient means of evaluating the strategic level of driving, executive function, and readiness to drive.

Validity and Reliability of 15 Hz Global Positioning System Units for Assessing the Activity Profiles of University Football Players.

Barr, M, Beaver, T, Turczyn, D, and Cornish, S. Validity and reliability of 15 Hz global positioning system units for assessing the activity profiles of university football players. J Strength Cond Res 33(5): 1371-1379, 2019-Global positioning system (GPS) units have recently become popular for monitoring and assessing the workloads of football players. Currently, there is a lack of studies examining the validity and reliability of these systems for that purpose, so the aim of the current study was to determine whether 15 Hz units (SPI HPU; GPSports, Canberra, Australia) could accurately be used to describe the physical demands of football. A series of cohort studies were conducted with Canadian university football players (n = 28). To assess the accuracy of the units' ability to measure high-velocity sprinting, 12 players performed multiple electronically timed 36.6 m sprints while wearing the units. To assess the interunit reliability, 5 players wore 2 units each during a training session. An analysis of the units' validity for measuring collisions was performed by comparing the correct number of tackles and blocks notated on video by an expert rater in 2 games with the number of collisions recorded by the units. The units were accurate for measuring high-sprinting velocities (coefficient of variation [CV] = 0.9%) and had good interunit reliability for recording distances at velocities between walking and sprinting CV (1.4-7.8%). The collision algorithm filter the accompanying software uses was found to have its best balance between precision and recall using a cut-off of 2.65g for linemen and 2.9g for nonlinemen. The devices used are effective at providing acceptably valid and reliable information to describe the physical demands of football. Position-specific locomotor zones are recommended when using GPS units with football players.

Evaluation of geoimputation strategies in a large case study.

BACKGROUND: Health data usually has missing or incomplete location information, which impacts the quality of research. Geoimputation methods are used by health professionals to increase the spatial resolution of address information for more accurate analyses. The objective of this study was to evaluate geo-imputation methods with respect to the demographic and spatial characteristics of the data. METHODS: We evaluated four geoimputation methods for increasing spatial resolution of records with known locational information at a coarse level. In order to test and rigorously evaluate two stochastic and two deterministic strategies, we used the Texas Sex Offender registry database with over 50,000 records with known demographic and coordinate information. We reduced the spatial resolution of each record to a census block group and attempted to recover coordinate information using the four strategies. We rigorously evaluated the results in terms of the error distance between the original coordinates and recovered coordinates by studying the results by demographic sub groups and the characteristics of the underlying geography. RESULTS: We observed that in estimating the actual location of a case, the weighted mean method is the most superior for each demographic group followed by the maximum imputation centroid, the random point in matching sub-geographies and the random point in all sub-geographies methods. Higher accuracies were observed for minority populations because minorities tend to cluster in certain neighborhoods, which makes it easier to impute their location. Results are greatly affected by the population density of the underlying geographies. We observed high accuracies in high population density areas, which often exist within smaller census blocks, which makes the search space smaller. Similarly, mapping geoimputation accuracies in a spatially explicit manner reveals that metropolitan areas yield higher accuracy results. CONCLUSIONS: Based on gains in standard error, reduction in mean error and validation results, we conclude that characteristics of the estimated records such as the demographic profile and population density information provide a measure of certainty of geographic imputation.

Optimizing location of variable message signs using GPS probe vehicle data.

A multi-objective optimization model is proposed to allocate the location of VMSs by maximizing the average traffic guidance utility of VMSs and the number of benefited links, while minimizing information redundancy. The traffic guidance utility is defined to quantitatively measure the value of an installed VMS, which is calculated from passively collected GPS data and the physical topology of road network. The number of benefited links is to measure how many links are covered by upstream VMS to disseminate information. Information redundancy is introduced to quantify the mutual impairing between any two VMSs. A heuristic search algorithm is developed to solve the optimization model, which can calculate the saturated number of VMS for a road network and optimize the project schedule of VMS installation process based on the proposed objectives. A real-world case study is conducted in Beijing to illustrate the validity of the proposed approach, where taxis are used as probe vehicles to provide GPS data. The results show the effectiveness of the proposed multi-objective optimization model and it is promising to use the emerging GPS data to help agencies to allocate the locations of VMSs on both urban roads and highway networks, instead of relying on the subjective judgment from practitioners.