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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Balancing geo-privacy and spatial patterns in epidemiological studies

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.

The Role of Health Information Management Professionals in the Use of Geographic Information Systems

In recent years the use of geographic information systems (GIS) in healthcare has expanded rapidly. Although the use of GIS has increased quickly, very little consensus has been reached on which healthcare professionals are best suited to be trained in and use GIS. A moderate amount of research has addressed the use of GIS in healthcare, but very little research has addressed selecting and training healthcare professionals in the area of GIS. As the use of GIS becomes more closely tied to electronic health records (EHRs), the thought arises that those best versed in EHRs, health information management (HIM) professionals, would be best suited to take on the GIS role. This mixed-methods study explored the current status of HIM professionals' role in GIS as well as the extent to which GIS is being taught in health information educational programs. Although the findings indicate that few HIM professionals are currently using GIS in their jobs and few HIM programs are currently teaching GIS, there is interest in GIS in the future for HIM professionals and in HIM educational programs.

Misclassification errors from postal code-based geocoding to assign census geography in Nova Scotia, Canada

OBJECTIVES

Postal codes are often the only available geographic identifiers in many sources of health data in Canada. In order to conduct geographic analyses, postal codes are routinely geocoded to census geography to link to ecological data. Despite common use of this method, the extent of geographic misclassification errors is poorly understood. We estimated misclassification errors in the geocoding of postal codes to assign census geography in Nova Scotia, Canada.

METHODS

We examined differences between counts and match rates for postal-code geocoded and actual locations of buildings in Nova Scotia at two census administrative area levels: dissemination areas (DAs) and census subdivisions (CSDs). Actual locations were based on the data collected by the provincial government containing actual latitude/longitude of buildings. Variation in misclassification by rurality, using Statistics Canada's classification, was also assessed.

RESULTS

Outside two urban areas (Halifax Metro and Sydney) which had <10% differences in counts, many DAs had >30% differences. Match rates showed similar patterns, with the vast majority of non-urban DAs having <40% match rates. Even in major urban areas, 10% of DAs had large misclassification errors. Misclassification errors at the CSD level were still too great to estimate counts or rates without further area aggregation.

CONCLUSION

Routine use of postal code geocoding should be replaced with geocoding of location information using additional identifiers such as civic addresses or latitude and longitude. If data holders did this in-house before providing data to researchers, the accuracy and capacity of geographic analysis would be enhanced while protecting confidentiality.

Is missing geographic positioning system data in accelerometry studies a problem, and is imputation the solution?

The main purpose of the present study was to assess the impact of global positioning system (GPS) signal lapse on physical activity analyses, discover any existing associations between missing GPS data and environmental and demographics attributes, and to determine whether imputation is an accurate and viable method for correcting GPS data loss. Accelerometer and GPS data of 782 participants from 8 studies were pooled to represent a range of lifestyles and interactions with the built environment. Periods of GPS signal lapse were identified and extracted. Generalised linear mixed models were run with the number of lapses and the length of lapses as outcomes. The signal lapses were imputed using a simple ruleset, and imputation was validated against person-worn camera imagery. A final generalised linear mixed model was used to identify the difference between the amount of GPS minutes pre- and post-imputation for the activity categories of sedentary, light, and moderate-to-vigorous physical activity. Over 17% of the dataset was comprised of GPS data lapses. No strong associations were found between increasing lapse length and number of lapses and the demographic and built environment variables. A significant difference was found between the pre- and postimputation minutes for each activity category. No demographic or environmental bias was found for length or number of lapses, but imputation of GPS data may make a significant difference for inclusion of physical activity data that occurred during a lapse. Imputing GPS data lapses is a viable technique for returning spatial context to accelerometer data and improving the completeness of the dataset.

Comparing GPS, Log, Survey, and Accelerometry to Measure Physical Activity

OBJECTIVES

We explored how objectively measured global positioning system (GPS) and accelerometer data match with travel logs and questionnaires in predicting trip duration and physical activity (PA).

METHODS

99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors.

RESULTS

There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported.

CONCLUSIONS

It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.

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.

A novel angle computation and calibration algorithm of bio-inspired sky-light polarization navigation sensor

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.

An evaluation framework for comparing geocoding systems

BACKGROUND

Geocoding, the process of converting textual information describing a location into one or more digital geographic representations, is a routine task performed at large organizations and government agencies across the globe. In a health context, this task is often a fundamental first step performed prior to all operations that take place in a spatially-based health study. As such, the quality of the geocoding system used within these agencies is of paramount concern to the agency (the producer) and researchers or policy-makers who wish to use these data (consumers). However, geocoding systems are continually evolving with new products coming on the market continuously. Agencies must develop and use criteria across a number axes when faced with decisions about building, buying, or maintaining any particular geocoding systems. To date, published criteria have focused on one or more aspects of geocode quality without taking a holistic view of a geocoding system's role within a large organization. The primary purpose of this study is to develop and test an evaluation framework to assist a large organization in determining which geocoding systems will meet its operational needs.

METHODS

A geocoding platform evaluation framework is derived through an examination of prior literature on geocoding accuracy. The framework developed extends commonly used geocoding metrics to take into account the specific concerns of large organizations for which geocoding is a fundamental operational capability tightly-knit into its core mission of processing health data records. A case study is performed to evaluate the strengths and weaknesses of five geocoding platforms currently available in the Australian geospatial marketplace.

RESULTS

The evaluation framework developed in this research is proven successful in differentiating between key capabilities of geocoding systems that are important in the context of a large organization with significant investments in geocoding resources. Results from the proposed methodology highlight important differences across all axes of geocoding system comparisons including spatial data output accuracy, reference data coverage, system flexibility, the potential for tight integration, and the need for specialized staff and/or development time and funding. Such results can empower decisions-makers within large organizations as they make decisions and investments in geocoding systems.

The role of VGI and PGI in supporting outdoor activities

This paper explored the question of how volunteered and professional geographic information (VGI and PGI) can be used together in an outdoor recreation context. In particular, consideration is given to what makes each information source valuable to the user, and how this can be used to help developers of GIS provide more useful, usable and satisfying products. The assumption that VGI is inferior to PGI is shown to be unfounded; rather each has its own strengths in describing particular aspects of the user information landscape. Considering the opportunities to influence user activities, both VGI and PGI have a greater ability to influence the user in the planning phase than actually during the activity. The importance of the author of the information (volunteer or professional) is shown to be of less importance to the end-user than the characteristics which describe the information in terms of communication, frequency of updates and accessibility.

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis

BACKGROUND

The growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.

METHODS

We compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a "gold standard" residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.

RESULTS

Median positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0-50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0-50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.

CONCLUSIONS

These findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.

Geographical variability of environmental parameters versus GPS precision: toward a better sampling strategy

To characterize a sedimentary environment, it is risky to take a single sample when the spatial variability is unknown. A reference station has to reflect the natural variations in order to allow the creation of long time series. However, it can remain unclear whether the temporal changes are real or due to a spatial variation. We highlight here the importance of spatial variability at the scale of precision of the GNSS. It appears that the number and arrangement of replicates depend on the environment and the studied parameters. InC, TOC and TS show a sufficiently low spatial variability to allow temporal tracking using GNSS without multiplying samples. The fine fraction percent shows a high spatial variability over small distances. The study of this parameter in the framework of temporal tracking requires a knowledge of its spatial variability during each period of sampling, and hence leads to the multiplication of samples.

Precision, accuracy, and application of diver-towed underwater GPS receivers

Diver-towed global positioning systems (GPS) handhelds have been used for a few years in underwater monitoring studies. We modeled the accuracy of this method using the software KABKURR originally developed by the University of Rostock for fishing and marine engineering. Additionally, three field experiments were conducted to estimate the precision of the method and apply it in the field: (1) an experiment of underwater transects from 5 to 35 m in the Southern Chile fjord region, (2) a transect from 5 to 30 m under extreme climatic conditions in the Antarctic, and (3) an underwater tracking experiment at Lake Ranco, Southern Chile. The coiled cable length in relation to water depth is the main error source besides the signal quality of the GPS under calm weather conditions. The forces used in the model resulted in a displacement of 2.3 m in a depth of 5 m, 3.2 m at a 10-m depth, 4.6 m in a 20-m depth, 5.5 m at a 30-m depth, and 6.8 m in a 40-m depth, when only an additional 0.5 m cable extension was used compared to the water depth. The GPS buoy requires good buoyancy in order to keep its position at the water surface when the diver is trying to minimize any additional cable extension error. The diver has to apply a tensile force for shortening the cable length at the lower cable end. Repeated diving along transect lines from 5 to 35 m resulted only in small deviations independent of water depth indicating the precision of the method for monitoring studies. Routing of given reference points with a Garmin 76CSx handheld placed in an underwater housing resulted in mean deviances less than 6 m at a water depth of 10 m. Thus, we can confirm that diver-towed GPS handhelds give promising results when used for underwater research in shallow water and open a wide field of applicability, but no submeter accuracy is possible due to the different error sources.

A research agenda: does geocoding positional error matter in health GIS studies?

Until recently, little attention has been paid to geocoding positional accuracy and its impacts on accessibility measures; estimates of disease rates; findings of disease clustering; spatial prediction and modeling of health outcomes; and estimates of individual exposures based on geographic proximity to pollutant and pathogen sources. It is now clear that positional errors can result in flawed findings and poor public health decisions. Yet the current state-of-practice is to ignore geocoding positional uncertainty, primarily because of a lack of theory, methods and tools for quantifying, modeling, and adjusting for geocoding positional errors in health analysis. This paper proposes a research agenda to address this need. It summarizes the basics of the geocoding process, its assumptions, and empirical evidence describing the magnitude of geocoding positional error. An overview of the impacts of positional error in health analysis, including accessibility, disease clustering, exposure reconstruction, and spatial weights estimation is presented. The proposed research agenda addresses five key needs: (1) a lack of standardized, open-access geocoding resources for use in health research; (2) a lack of geocoding validation datasets that will allow the evaluation of alternative geocoding engines and procedures; (3) a lack of spatially explicit geocoding positional error models; (4) a lack of resources for assessing the sensitivity of spatial analysis results to geocoding positional error; (5) a lack of demonstration studies that illustrate the sensitivity of health policy decisions to geocoding positional error.

Applying GIS and fine-resolution digital terrain models to assess three-dimensional population distribution under traffic impacts

Pollution exhibits significant variations horizontally and vertically within cities; therefore, the size and three-dimensional (3D) spatial distribution of population are significant determinants of urban health. This paper presents a novel methodology, 3D digital geography (3DIG) methodology, for investigating 3D spatial distributions of population in close proximity to traffic, thus the potential highly exposed population under traffic impacts. 3DIG applies geographic information system and fine-resolution (5 m) digital terrain models to obtain the number of building floors in residential zones of the Taipei metropolis; the vertical distribution of population at different floors was estimated based on demographic data in each census tract. In addition, population within 5, 10, 20, 50, and 100 m from the roadways was estimated. Field validation indicated that model results were reliable and accurate; the final population estimation differs only by 0.88% from the demographic database. The results showed that among the total 6.5 million Taipei residents, 0.8 (12.3%), 1.5 (22.9%), 2.3 (34.9), and 2.7 (41.1%) million residents live on the first or second floor within 5, 10, 20, and 50 m, respectively, of municipal roads. There are 22 census tracts with more than half of their residents living on the first or second floor within 5 m of municipal roads. In addition, half of the towns in Taipei city and county with >13.9% and 12.1% of residents live on the first and second floors within 5 m of municipal roads, respectively. These findings highlight the huge number of Taipei residents in close proximity to traffic and have significant implications for exposure assessment and environmental epidemiological studies. This study demonstrates that 3DIG is a versatile methodology for various research and policy planning in which 3D spatial population distribution is the central focus.

Evaluation of the positional difference between two common geocoding methods

Geocoding, the process of matching addresses to geographic coordinates, is a necessary first step when using geographical information systems (GIS) technology. However, different geocoding methodologies can result in different geographic coordinates. The objective of this study was to compare the positional (i.e. longitude/latitude) difference between two common geocoding methods, i.e. ArcGIS (Environmental System Research Institute, Redlands, CA, USA) and Batchgeo (freely available online at http://www.batchgeo.com). Address data came from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programmes located in four geographically diverse metropolitan areas in the USA. Our analyses include baseline addresses (n = 748) collected from the parents of the children in the after school sites. Addresses were first geocoded to the street level and assigned longitude and latitude coordinates with ArcGIS, version 9.3, then the same addresses were geocoded with Batchgeo. For this analysis, the ArcGIS minimum match score was 80. The resulting geocodes were projected into state plane coordinates, and the difference in longitude and latitude coordinates were calculated in meters between the two methods for all data points in each of the four metropolitan areas. We also quantified the descriptions of the geocoding accuracy provided by Batchgeo with the match scores from ArcGIS. We found a 94% match rate (n = 705), 2% (n = 18) were tied and 3% (n = 25) were unmatched using ArcGIS. Forty-eight addresses (6.4%) were not matched in ArcGIS with a match score ≥80 (therefore only 700 addresses were included in our positional difference analysis). Six hundred thirteen (87.6%) of these addresses had a match score of 100. Batchgeo yielded a 100% match rate for the addresses that ArcGIS geocoded. The median for longitude and latitude coordinates for all the data was just over 25 m. Overall, the range for longitude was 0.04-12,911.8 m, and the range for latitude was 0.02-37,766.6 m. Comparisons show minimal differences in the median and minimum values, while there were slightly larger differences in the maximum values. The majority (>75%) of the geographic differences were within 50 m of each other; mostly <25 m from each other (about 49%). Only about 4% overall were ≥400 m apart. We also found geographic differences in the proportion of addresses that fell within certain meter ranges. The match-score range associated with the Batchgeo accuracy level "approximate" (least accurate) was 84-100 (mean = 92), while the "rooftop" Batchgeo accuracy level (most accurate) delivered a mean of 98.9 but the range was the same. Although future research should compare the positional difference of Batchgeo to criterion measures of longitude/latitude (e.g. with global positioning system measurement), this study suggests that Batchgeo is a good, free-of-charge option to geocode addresses.

Geocoding rural addresses in a community contaminated by PFOA: a comparison of methods

BACKGROUND

Location is often an important component of exposure assessment, and positional errors in geocoding may result in exposure misclassification. In rural areas, successful geocoding to a street address is limited by rural route boxes. Communities have assigned physical street addresses to rural route boxes as part of E911 readdressing projects for improved emergency response. Our study compared automated and E911 methods for recovering and geocoding valid street addresses and assessed the impact of positional errors on exposure classification.

METHODS

The current study is a secondary analysis of existing data that included 135 addresses self-reported by participants of a rural community study who were exposed via public drinking water to perfluorooctanoate (PFOA) released from a DuPont facility in Parkersburg, West Virginia. We converted pre-E911 to post-E911 addresses using two methods: automated ZP4 address-correction software with the U.S. Postal Service LACS database and E911 data provided by Wood County, West Virginia. Addresses were geocoded using TeleAtlas, an online commercial service, and ArcView with StreetMap Premium North America NAVTEQ 2008 enhanced street dataset. We calculated positional errors using GPS measurements collected at each address and assessed exposure based on geocoded location in relation to public water pipes.

RESULTS

The county E911 data converted 89% of the eligible addresses compared to 35% by ZP4 LACS. ArcView/NAVTEQ geocoded more addresses (n = 130) and with smaller median distance between geocodes and GPS coordinates (39 meters) than TeleAtlas (n = 85, 188 meters). Without E911 address conversion, 25% of the geocodes would have been more than 1000 meters from the true location. Positional errors in TeleAtlas geocoding resulted in exposure misclassification of seven addresses whereas ArcView/NAVTEQ methods did not misclassify any addresses.

CONCLUSIONS

Although the study was limited by small numbers, our results suggest that the use of county E911 data in rural areas increases the rate of successful geocoding. Furthermore, positional accuracy of rural addresses in the study area appears to vary by geocoding method. In a large epidemiological study investigating the health effects of PFOA-contaminated public drinking water, this could potentially result in exposure misclassification if addresses are incorrectly geocoded to a street segment not serviced by public water.

An innovative procedure for calibration of strapdown electro-optical sensors onboard unmanned air vehicles

This paper presents an innovative method for estimating the attitude of airborne electro-optical cameras with respect to the onboard autonomous navigation unit. The procedure is based on the use of attitude measurements under static conditions taken by an inertial unit and carrier-phase differential Global Positioning System to obtain accurate camera position estimates in the aircraft body reference frame, while image analysis allows line-of-sight unit vectors in the camera based reference frame to be computed. The method has been applied to the alignment of the visible and infrared cameras installed onboard the experimental aircraft of the Italian Aerospace Research Center and adopted for in-flight obstacle detection and collision avoidance. Results show an angular uncertainty on the order of 0.1° (rms).

Local indicators of geocoding accuracy (LIGA): theory and application

BACKGROUND

Although sources of positional error in geographic locations (e.g. geocoding error) used for describing and modeling spatial patterns are widely acknowledged, research on how such error impacts the statistical results has been limited. In this paper we explore techniques for quantifying the perturbability of spatial weights to different specifications of positional error.

RESULTS

We find that a family of curves describes the relationship between perturbability and positional error, and use these curves to evaluate sensitivity of alternative spatial weight specifications to positional error both globally (when all locations are considered simultaneously) and locally (to identify those locations that would benefit most from increased geocoding accuracy). We evaluate the approach in simulation studies, and demonstrate it using a case-control study of bladder cancer in south-eastern Michigan.

CONCLUSION

Three results are significant. First, the shape of the probability distributions of positional error (e.g. circular, elliptical, cross) has little impact on the perturbability of spatial weights, which instead depends on the mean positional error. Second, our methodology allows researchers to evaluate the sensitivity of spatial statistics to positional accuracy for specific geographies. This has substantial practical implications since it makes possible routine sensitivity analysis of spatial statistics to positional error arising in geocoded street addresses, global positioning systems, LIDAR and other geographic data. Third, those locations with high perturbability (most sensitive to positional error) and high leverage (that contribute the most to the spatial weight being considered) will benefit the most from increased positional accuracy. These are rapidly identified using a new visualization tool we call the LIGA scatterplot.Herein lies a paradox for spatial analysis: For a given level of positional error increasing sample density to more accurately follow the underlying population distribution increases perturbability and introduces error into the spatial weights matrix. In some studies positional error may not impact the statistical results, and in others it might invalidate the results. We therefore must understand the relationships between positional accuracy and the perturbability of the spatial weights in order to have confidence in a study's results.

Evaluating geographic imputation approaches for zip code level data: an application to a study of pediatric diabetes

BACKGROUND

There is increasing interest in the study of place effects on health, facilitated in part by geographic information systems. Incomplete or missing address information reduces geocoding success. Several geographic imputation methods have been suggested to overcome this limitation. Accuracy evaluation of these methods can be focused at the level of individuals and at higher group-levels (e.g., spatial distribution).

METHODS

We evaluated the accuracy of eight geo-imputation methods for address allocation from ZIP codes to census tracts at the individual and group level. The spatial apportioning approaches underlying the imputation methods included four fixed (deterministic) and four random (stochastic) allocation methods using land area, total population, population under age 20, and race/ethnicity as weighting factors. Data included more than 2,000 geocoded cases of diabetes mellitus among youth aged 0-19 in four U.S. regions. The imputed distribution of cases across tracts was compared to the true distribution using a chi-squared statistic.

RESULTS

At the individual level, population-weighted (total or under age 20) fixed allocation showed the greatest level of accuracy, with correct census tract assignments averaging 30.01% across all regions, followed by the race/ethnicity-weighted random method (23.83%). The true distribution of cases across census tracts was that 58.2% of tracts exhibited no cases, 26.2% had one case, 9.5% had two cases, and less than 3% had three or more. This distribution was best captured by random allocation methods, with no significant differences (p-value > 0.90). However, significant differences in distributions based on fixed allocation methods were found (p-value < 0.0003).

CONCLUSION

Fixed imputation methods seemed to yield greatest accuracy at the individual level, suggesting use for studies on area-level environmental exposures. Fixed methods result in artificial clusters in single census tracts. For studies focusing on spatial distribution of disease, random methods seemed superior, as they most closely replicated the true spatial distribution. When selecting an imputation approach, researchers should consider carefully the study aims.

The importance of accurate road data for spatial applications in public health: customizing a road network

BACKGROUND

Health researchers have increasingly adopted the use of geographic information systems (GIS) for analyzing environments in which people live and how those environments affect health. One aspect of this research that is often overlooked is the quality and detail of the road data and whether or not it is appropriate for the scale of analysis. Many readily available road datasets, both public domain and commercial, contain positional errors or generalizations that may not be compatible with highly accurate geospatial locations. This study examined the accuracy, completeness, and currency of four readily available public and commercial sources for road data (North Carolina Department of Transportation, StreetMap Pro, TIGER/Line 2000, TIGER/Line 2007) relative to a custom road dataset which we developed and used for comparison.

METHODS AND RESULTS

A custom road network dataset was developed to examine associations between health behaviors and the environment among pregnant and postpartum women living in central North Carolina in the United States. Three analytical measures were developed to assess the comparative accuracy and utility of four publicly and commercially available road datasets and the custom dataset in relation to participants' residential locations over three time periods. The exclusion of road segments and positional errors in the four comparison road datasets resulted in between 5.9% and 64.4% of respondents lying farther than 15.24 meters from their nearest road, the distance of the threshold set by the project to facilitate spatial analysis. Agreement, using a Pearson's correlation coefficient, between the customized road dataset and the four comparison road datasets ranged from 0.01 to 0.82.

CONCLUSION

This study demonstrates the importance of examining available road datasets and assessing their completeness, accuracy, and currency for their particular study area. This paper serves as an example for assessing the feasibility of readily available commercial or public road datasets, and outlines the steps by which an improved custom dataset for a study area can be developed.

Quantitative assessment of the benefits of specific information technologies applied to clinical studies in developing countries

Clinical studies and trials require accessibility of large amounts of high-quality information in a timely manner, often daily. The integrated application of information technologies can greatly improve quality control as well as facilitate compliance with established standards such as Good Clinical Practice (GCP) and Good Laboratory Practice (GLP). We have customized and implemented a number of information technologies, such as personal data assistants (PDAs), geographic information system (GIS), and barcode and fingerprint scanning, to streamline a pediatric dengue cohort study in Managua, Nicaragua. Quantitative data was obtained to assess the actual contribution of each technology in relation to processing time, accuracy, real-time access to data, savings in consumable materials, and time to proficiency in training sessions. In addition to specific advantages, these information technologies benefited not only the study itself but numerous routine clinical and laboratory processes in the health center and laboratories of the Nicaraguan Ministry of Health.

Utility of Global Positioning System to Measure Active Transport in Urban Areas

PURPOSE

The purpose of this study was to determine test-retest reliability of global positioning system (GPS) units for measuring distance traveled when walking and cycling (AT), and to determine whether GPS unit placement influences accuracy.

METHODS

Participants (N = 19) completed two walking and cycling trials at self-selected speeds on a measured 1489-m course wearing two Garmin GPS units, worn in lanyard and waistband placements. GPS estimates of travel distance were compared with actual distance, and test-retest reliability was examined. Data-cleaning protocols were developed to remove signal noise. Results are presented for both raw and cleaned data.

RESULTS

For both raw and cleaned data, no significant differences were observed between trials (trial 1 vs trial 2), unit placement (lanyard vs waistband), or AT mode (walk vs cycle) (P >or= 0.05). Both lanyard and waistband units significantly overestimated distance traveled during walking trials (P <or= 0.05), but not cycling trials (P >or= 0.05). The relative technical error of measurement (TEM) of the raw data ranged from 3.74 to 15.51%, and average absolute errors ranged from 5.03 to 8.53% for all trials. A significant position by AT mode interaction was observed for clean data (P < 0.05). Relative TEM for the clean data ranged from 1.42 to 1.98%, and average absolute errors ranged from 0.32 to 1.97%. Intraclass correlations (ICC) were poor to fair for all trials using raw and cleaned data.

CONCLUSION

Signal noise during unit initialization may adversely affect unit performance; however, application of data-cleaning procedures to remove data associated with signal noise improves unit ability to measure distance. Results suggest that the lanyard position is the optimal placement for units during data collection.

Quantifying geocode location error using GIS methods

BACKGROUND

The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health Information and Policy (OHIP) and (2) a commercial vendor. Geographic information system (GIS) methods were used to quantify uncertainty in the two sets of geocodes using orthoimagery and tax parcel datasets.

METHODS

We sampled 599 infants and fetuses with birth defects delivered during 1994-2002 with maternal residence in either Fulton or Gwinnett County. Tax parcel datasets were obtained from the tax assessor's offices of Fulton and Gwinnett County. High-resolution orthoimagery for these counties was acquired from the U.S. Geological Survey. For each of the 599 addresses we attempted to locate the tax parcel corresponding to the maternal address. If the tax parcel was identified the distance and the angle between the geocode and the residence were calculated. We used simulated data to characterize the impact of geocode location error. In each county 5,000 geocodes were generated and assigned their corresponding Census 2000 tract. Each geocode was then displaced at a random angle by a random distance drawn from the distribution of observed geocode location errors. The census tract of the displaced geocode was determined. We repeated this process 5,000 times and report the percentage of geocodes that resolved into incorrect census tracts.

RESULTS

Median location error was less than 100 meters for both OHIP and commercial vendor geocodes; the distribution of angles appeared uniform. Median location error was approximately 35% larger in Gwinnett (a suburban county) relative to Fulton (a county with urban and suburban areas). Location error occasionally caused the simulated geocodes to be displaced into incorrect census tracts; the median percentage of geocodes resolving into incorrect census tracts ranged between 4.5% and 5.3%, depending upon the county and geocoding agency.

CONCLUSION

Geocode location uncertainty can be estimated using tax parcel databases in a GIS. This approach is a viable alternative to global positioning system field validation of geocodes.

Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree?

Background

Geocoding methods vary among spatial epidemiology studies. Errors in the geocoding process and differential match rates may reduce study validity. We compared two geocoding methods using 8,157 Washington State addresses. The multi-stage geocoding method implemented by the state health department used a sequence of local and national reference files. The single-stage method used a single national reference file. For each address geocoded by both methods, we measured the distance between the locations assigned by each method. Area-level characteristics were collected from census data, and modeled as predictors of the discordance between geocoded address coordinates.

Results

The multi-stage method had a higher match rate than the single-stage method: 99% versus 95%. Of 7,686 addresses were geocoded by both methods, 96% were geocoded to the same census tract by both methods and 98% were geocoded to locations within 1 km of each other by the two methods. The distance between geocoded coordinates for the same address was higher in sparsely populated and low poverty areas, and counties with local reference files.

Conclusion

The multi-stage geocoding method had a higher match rate than the single-stage method. An examination of differences in the location assigned to the same address suggested that study results may be most sensitive to the choice of geocoding method in sparsely populated or low-poverty areas.

The accuracy of address coding and the effects of coding errors

Studies that estimate the influence of characteristics of place on health often use geocoded addresses to identify location of study subjects. This study uses housing built before 1990 selected for the 1995-2001 National Health Interview Survey (N=252,421) to develop a standard against which geocodes obtained from an address-coding program are compared. The results show that geocoding is generally accurate and is more successful in urban areas. Blockgroups with missing codes are more rural and somewhat poorer than blockgroups with correct codes. The effect of incorrect codes on statistical analyses depends on the proportion rural in a study population.

Validation of a geographic information system model for mapping the risk of fasciolosis in cattle and buffaloes in Cambodia

Maps showing gradations of risk of fasciolosis due to Fasciola gigantica in Cambodia were produced using geographic information systems (GIS) technology in conjunction with determinants of fasciolosis. A comparison between levels of risk predicted by the maps and field measurements of prevalence in 11 provinces (n=1406) showed general agreement, which suggested the epidemiological determinants and weightings used to produce the maps were appropriate. However, due to logistical constraints, prevalence was measured at the provincial level and animals were not randomly sampled (and thus were unlikely to be representative of variability within provinces). To address this, additional field work was carried out to measure prevalence in more detail--faecal samples were collected from a randomly selected set of animals in four districts across a representative province for areas predicted to be at high risk (n=311), moderate risk (n=268) and no risk (n=262). As with the original field survey, the results show general agreement between prevalence and risk predicted by the maps, with the best fit found for areas predicted to be at high risk.

[Spacial modeling of cutaneous leishmaniasis risk zones]

OBJECTIVE

To spatially delimit cutaneous leishmaniasis (CL) human contact risk zones (CoRZ) using remote sensing and geoprocessing techniques.

METHODS

A total of 27 CL cases reported from 1992 to 1997 in the municipality Itapira, Brazil, were studied. The influence of some important environmental variables related to CL such as altitude and vegetation density measured by normalized difference vegetation index (NDVI) images were analyzed for each CoRZ.

RESULTS

The results showed that about 50% of the dwellings where CL cases were reported were located less than 200 meters from the limits of forest remnant area; more than 70% of the total area of the CoRZ, for each criterion, were in altitudes lower than 750 meters; and about 50% of the CoRZ, for each criterion, were located in a very dense green area (NDVI ranging from 0.45 to 1.00).

CONCLUSIONS

The study shows there may be three transmission modes in the study area: intra-forest, extra-forest (in this setting, transmission might be influenced by the vegetation density surrounding forest remnants); or domiciliary.

[Development and application of geographic information system of Aedes vector in Chaozhou city, Guangdong province]

OBJECTIVE

To explore the spatial distribution character of dengue fever and the change of Aedes' population, so as to provide macroscopical decision-making evidences of prevention and supervision on dengue fever.

METHODS

(1) Collecting data on morbidity of dengue and supervision on vector's population in the corresponding period. (2) Drawing digitized map of Chaozhou in scale of 1:50,000, including elements of boundary, residential areas, road and traffic, altitude, water systems etc. (3) Measuring the latitude and longitude of center position of surveillance safes on the scene. (4) Processing spatial analysis by the ArcGIS 8.5 software.

RESULTS

Distribution of Aedes showed spatial cluster in Chaozhou, while its density was related to the distance to the watersides. The closer to the watersides, the higher the density was. Map on spatial distribution showed that although the Aedes epidemic situation changed yearly, but primarily be kept in high, middle, low regions. Cross-validation effects of the distribution maps were satisfactory.

CONCLUSION

Geographic information system was promising in analyzing data on dengue fever, and better than other routine research methods.

Quality assurance and quality control methodologies used within the Austrian UV monitoring network

The Austrian UVB monitoring network is operational since 1997. Nine detectors for measuring erythemally weighted solar UV irradiance are distributed over Austria in order to cover the main populated areas as well as different levels of altitude. The detectors are calibrated to indicate the UV-Index, the internationally agreed unit for erythemally weighted solar UV irradiance. Calibration is carried out in the laboratory for determination of spectral sensitivity of each detector, and under the sun for absolute comparison with a well-calibrated, double-monochromator spectroradiometer. For the conversion from detector-weighted units to erythemally weighted units a lookup table is used, which is calculated using a radiative transfer model and which reflects the dependence of the conversion on the solar zenith angle and total ozone content of the atmosphere. The uncertainty of the calibration is about +/-7%, dominated by the uncertainty of the calibration lamp for the spectroradiometer (+/-4%). The long-term stability of this type of detectors has been found to be not satisfactory. Therefore, routinely every year all detectors are completely recalibrated. Variations of the calibration factors up to +/-10% are found. Thus, during routine operation, several measures take place for quality control. The measured data are compared to results of model calculations with a radiative transfer model, where clear sky and an aerosol-free atmosphere are assumed. At each site, the UV data are also compared with data from a co-located pyranometer measuring total solar irradiance. These two radiation quantities are well correlated, especially on clear days and when the ozone content is taken into account. If suspicious measurements are found for one detector in the network, a well-calibrated travelling reference detector of the same type is set up side-by-side, allowing the identification of relative differences of approximately 3%. If necessary, a recalibration is carried out. As the main aim for the Austrian UV monitoring network is the information of the public about the actual levels of UVB irradiance, the measurement results are published on-line in the Internet (http://www.uibk.ac.at/projects/uv-index). For the previous day and backwards approximately 2 years, the distribution of maximal UVB levels over Austria is shown on a regional map. Additionally, near real-time data of most of the measurement stations are presented with a delay of usually less than half-an-hour. Together with these actually measured data there is also shown the diurnal variation of the maximal expected value of the UV-Index under ideal clear conditions.

An algorithm for assessing the risk of traffic accident

INTRODUCTION

This study is aimed at developing an algorithm to estimate the number of traffic accidents and assess the risk of traffic accidents in a study area.

METHOD

The algorithm involves a combination of mapping technique (Geographical Information System (GIS) techniques) and statistical methods (cluster analysis and regression analysis). Geographical Information System is used to locate accidents on a digital map and realize their distribution. Cluster analysis is used to group the homogeneous data together. Regression analysis is performed to realize the relation between the number of accident events and the potential causal factors. Negative binomial regression model is found to be an appropriate mathematical form to mimic this relation. Accident risk of the area, derived from historical accident records and causal factors, is also determined in the algorithm. The risk is computed using the Empirical Bayes (EB) approach. A case study of Hong Kong is presented to illustrate the effectiveness of the proposed algorithm.

RESULTS

The results show that the algorithm improves accident risk estimation when comparing to the estimated risk based on only the historical accident records. The algorithm is found to be more efficient, especially in the case of fatality and pedestrian-related accident analysis.

IMPACT ON INDUSTRY

The output of the proposed algorithm can help authorities effectively identify areas with high accident risk. In addition, it can serve as a reference for town planners considering road safety.