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.

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.

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.

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.

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.

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.

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.

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.

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.

Differences in physical environmental characteristics between adolescents' actual and shortest cycling routes: a study using a Google Street View-based audit.

BACKGROUND: The objective evaluation of the physical environmental characteristics (e.g. speed limit, cycling infrastructure) along adolescents' actual cycling routes remains understudied, although it may provide important insights into why adolescents prefer one cycling route over another. The present study aims to gain insight into the physical environmental characteristics determining the route choice of adolescent cyclists by comparing differences in physical environmental characteristics between their actual cycling routes and the shortest possible cycling routes. METHODS: Adolescents (n = 204; 46.5% boys; 14.4 ± 1.2 years) recruited at secondary schools in and around Ghent (city in Flanders, northern part of Belgium) were instructed to wear a Global Positioning System device in order to identify cycling trips. For all identified cycling trips, the shortest possible route that could have been taken was calculated. Actual cycling routes that were not the shortest possible cycling routes were divided into street segments. Segments were audited with a Google Street View-based tool to assess physical environmental characteristics along actual and shortest cycling routes. RESULTS: Out of 160 actual cycling trips, 73.1% did not differ from the shortest possible cycling route. For actual cycling routes that were not the shortest cycling route, a speed limit of 30 km/h, roads having few buildings with windows on the street side and roads without cycle lane were more frequently present compared to the shortest possible cycling routes. A mixed land use, roads with commercial destinations, arterial roads, cycle lanes separated from traffic by white lines, small cycle lanes and cycle lanes covered by lighting were less frequently present along actual cycling routes compared to the shortest possible cycling routes. CONCLUSIONS: Results showed that distance mainly determines the route along which adolescents cycle. In addition, adolescents cycled more along residential streets (even if no cycle lane was present) and less along busy, arterial roads. Local authorities should provide shortcuts free from motorised traffic to meet adolescents' preference to cycle along the shortest route and to avoid cycling along arterial roads.

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.

Measurement of the potential geographic accessibility from call to definitive care for patient with acute stroke.

BACKGROUND: The World Health Organization refers to stroke, the second most frequent cause of death in the world, in terms of pandemic. Present treatments are only effective within precise time windows. Only 10% of thrombolysis patients are eligible. Late assessment of the patient resulting from admission and lack of knowledge of the symptoms is the main explanation of lack of eligibility. METHODS: The aim is the measurement of the time of access to treatment facilities for stroke victims, using ambulances (firemen ambulances or EMS ambulances) and private car. The method proposed analyses the potential geographic accessibility of stroke care infrastructure in different scenarios. The study allows better considering of the issues inherent to an area: difficult weather conditions, traffic congestion and failure to respect the distance limits of emergency transport. RESULTS: Depending on the scenario, access times vary considerably within the same commune. For example, between the first and the second scenario for cities in the north of Rhône county, there is a 10 min difference to the nearest Primary Stroke Center (PSC). For the first scenario, 90% of the population is 20 min away of the PSC and 96% for the second scenario. Likewise, depending on the modal vector (fire brigade or emergency medical service), overall accessibility from the emergency call to admission to a Comprehensive Stroke Center (CSC) can vary by as much as 15 min. CONCLUSIONS: The setting up of the various scenarios and modal comparison based on the calculation of overall accessibility makes this a new method for calculating potential access to care facilities. It is important to take into account the specific pathological features and the availability of care facilities for modelling. This method is innovative and recommendable for measuring accessibility in the field of health care. This study makes possible to highlight the patients' extension of care delays. Thus, this can impact the improvement of patient care and rethink the healthcare organization. Stroke is addressed here but it is applicable to other pathologies.

Using meta-quality to assess the utility of volunteered geographic information for science.

BACKGROUND: Volunteered geographic information (VGI) has strong potential to be increasingly valuable to scientists in collaboration with non-scientists. The abundance of mobile phones and other wireless forms of communication open up significant opportunities for the public to get involved in scientific research. As these devices and activities become more abundant, questions of uncertainty and error in volunteer data are emerging as critical components for using volunteer-sourced spatial data. METHODS: Here we present a methodology for using VGI and assessing its sensitivity to three types of error. More specifically, this study evaluates the reliability of data from volunteers based on their historical patterns. The specific context is a case study in surveillance of tsetse flies, a health concern for being the primary vector of African Trypanosomiasis. RESULTS: Reliability, as measured by a reputation score, determines the threshold for accepting the volunteered data for inclusion in a tsetse presence/absence model. Higher reputation scores are successful in identifying areas of higher modeled tsetse prevalence. A dynamic threshold is needed but the quality of VGI will improve as more data are collected and the errors in identifying reliable participants will decrease. CONCLUSIONS: This system allows for two-way communication between researchers and the public, and a way to evaluate the reliability of VGI. Boosting the public's ability to participate in such work can improve disease surveillance and promote citizen science. In the absence of active surveillance, VGI can provide valuable spatial information given that the data are reliable.

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields.

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce.

Comparison of methods to estimate water access: a pilot study of a GPS-based approach in low resource settings.

BACKGROUND: Most water access studies involve self-reported measures such as time spent or simple spatial measures such as Euclidean distance from home to source. GPS-based measures of access are often considered actual access and have shown little correlation with self-reported measures. One main obstacle to widespread use of GPS-based measurement of access to water has been technological limitations (e.g., battery life). As such, GPS-based measures have been limited by time and in sample size. METHODS: The aim of this pilot study was to develop and test a novel GPS unit, (≤4-week battery life, waterproof) to measure access to water. The GPS-based method was pilot-tested to estimate number of trips per day, time spent and distance traveled to source for all water collected over a 3-day period in five households in south-western Uganda. This method was then compared to self-reported measures and commonly used spatial measures of access for the same households. RESULTS: Time spent collecting water was significantly overestimated using a self-reported measure, compared to GPS-based (p < 0.05). In contrast, both the GIS Euclidean distances to nearest and actual primary source significantly underestimated distances traveled, compared to the GPS-based measurement of actual travel paths to water source (p < 0.05). Households did not consistently collect water from the source nearest their home. Comparisons between the GPS-based measure and self-reported meters traveled were not made, as respondents did not feel that they could accurately estimate distance. However, there was complete agreement between self-reported primary source and GPS-based. CONCLUSIONS: Reliance on cross-sectional self-reported or simple GIS measures leads to misclassification in water access measurement. This new method offers reductions in such errors and may aid in understanding dynamic measures of access to water for health studies.

Performance analysis of multiple Indoor Positioning Systems in a healthcare environment.

BACKGROUND: The combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems (IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital. METHODS: To remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the "Sint-Jozefs kliniek Izegem" hospital in Belgium. The evaluation (data-collecting and data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared. RESULTS: Several trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98%) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results. CONCLUSION: As a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.

Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps.

Adverse neighborhood conditions play an important role beyond individual characteristics. There is increasing interest in identifying specific characteristics of the social and built environments adversely affecting health outcomes. Most research has assessed aspects of such exposures via self-reported instruments or census data. Potential threats in the local environment may be subject to short-term changes that can only be measured with more nimble technology. The advent of new technologies may offer new opportunities to obtain geospatial data about neighborhoods that may circumvent the limitations of traditional data sources. This overview describes the utility, validity and reliability of selected emerging technologies to measure neighborhood conditions for public health applications. It also describes next steps for future research and opportunities for interventions. The paper presents an overview of the literature on measurement of the built and social environment in public health (Google Street View, webcams, crowdsourcing, remote sensing, social media, unmanned aerial vehicles, and lifespace) and location-based interventions. Emerging technologies such as Google Street View, social media, drones, webcams, and crowdsourcing may serve as effective and inexpensive tools to measure the ever-changing environment. Georeferenced social media responses may help identify where to target intervention activities, but also to passively evaluate their effectiveness. Future studies should measure exposure across key time points during the life-course as part of the exposome paradigm and integrate various types of data sources to measure environmental contexts. By harnessing these technologies, public health research can not only monitor populations and the environment, but intervene using novel strategies to improve the public health.

[Impacts of geocoding quality in environmental epidemiology studies: two case-studies in Tuscany Region (Central Italy)]. / L'impatto della qualità della georeferenziazione negli studi di epidemiologia ambientale: due casi studio in Toscana.

OBJECTIVES: Geographical Information Systems (GIS) are widely used in environmental epidemiology studies to locate study population by geocoding addresses and to evaluate exposures and relationship with health outcomes. Despite this, Italian environmental epidemiologists poorly discuss quality of address geocoding results. DESIGN: two case-studies have been carried out in Tuscany Region (Central Italy): one in the mountain area in the Municipality of Piancastagnaio (Siena Province) and one in the urban area around the airport of Florence. Three geocoding systems have been compared: the geographical database produced by Tuscany Region and two commercial systems (Google and Bing-Microsoft); 1,549 addresses in Piancastagnaio and 2,946 addresses in Florence have been tested. RESULTS: Tuscan geographical database showed better performance than the two commercial systems, with bigger differences in Piancastagnaio. In this area, mean difference between regional system and Google service is more than 300 mt, with peaks of 7-8 km. Bing- Microsoft system does not provide any information on addresses in Piancastagnaio: all input addresses were geocoded in the centroid of the municipality or in the centre of a few principal streets. Lowest differences among the three methods were observed in the urban area of Florence: mean difference between Tuscany and Goggle systems was 150 mt, with less than 2 km peaks; between Tuscany and Bing-Microsoft mean difference was 100 mt with 3 km peaks. In both case-studies, but especially in Piancastagnaio area, these differences gave rise to great misclassification in the evaluation of individual exposure and health outcome. CONCLUSION: the study highlighted the impacts of address geocoding process in exposure assessment in environmental health research and pointed out the need of specifically evaluate the quality of cartographic data.

Accuracy and reliability of SPI ProX global positioning system devices for measuring movement demands of team sports.

AIM: The aim of this study was to determine the accuracy and reliability of SPI ProX global positioning system (GPS) devices for measuring movement at various speeds and movement patterns as evident in team sport demands. METHODS: Eleven amateur soccer players performed a 40 m straight sprint test (with 10-20-30 m split times), a zigzag test, 30 m walking, jogging and moderate intensity runs. RESULTS: Results indicated that the SPI ProX GPS measurements showed acceptable accuracy for all movement patterns for distance (coefficient of variation [CV]=0.14% to 3.73%; 95% ratio limits of agreement [95% ratio LOA]=0.97 x / ÷ 1.09 to 1.00 x / ÷ 1.05) and speed (CV=4.22% to 9.52%; 95%LOA=-0.17 ± 1.70 km h-1 to 2.30 ± 1.17 km h-1) compared with the measured distance and speed determined from timing gates, respectively. Furthermore, acceptable reliability of SPI ProX GPS measures for distance (CV=0.34% to 3.81%; 95%LOA=-0.09 ± 0.23 m to -0.34 ± 2.31 m) and speed (CV=3.19% to 6.95%; 95%LOA=-0.05 ± 3.90 km h-1 to 0.42 ± 3.68 km h-1) were also evident. CONCLUSION: Whilst SPI ProX GPS devices were within acceptable ranges of reliability, they remained significantly different to criterion measures of team sport movement demands.

Assessing the environmental characteristics of cycling routes to school: a study on the reliability and validity of a Google Street View-based audit.

BACKGROUND: Google Street View provides a valuable and efficient alternative to observe the physical environment compared to on-site fieldwork. However, studies on the use, reliability and validity of Google Street View in a cycling-to-school context are lacking. We aimed to study the intra-, inter-rater reliability and criterion validity of EGA-Cycling (Environmental Google Street View Based Audit - Cycling to school), a newly developed audit using Google Street View to assess the physical environment along cycling routes to school. METHODS: Parents (n = 52) of 11-to-12-year old Flemish children, who mostly cycled to school, completed a questionnaire and identified their child's cycling route to school on a street map. Fifty cycling routes of 11-to-12-year olds were identified and physical environmental characteristics along the identified routes were rated with EGA-Cycling (5 subscales; 37 items), based on Google Street View. To assess reliability, two researchers performed the audit. Criterion validity of the audit was examined by comparing the ratings based on Google Street View with ratings through on-site assessments. RESULTS: Intra-rater reliability was high (kappa range 0.47-1.00). Large variations in the inter-rater reliability (kappa range -0.03-1.00) and criterion validity scores (kappa range -0.06-1.00) were reported, with acceptable inter-rater reliability values for 43% of all items and acceptable criterion validity for 54% of all items. CONCLUSIONS: EGA-Cycling can be used to assess physical environmental characteristics along cycling routes to school. However, to assess the micro-environment specifically related to cycling, on-site assessments have to be added.