ResearchPad - General Business, Management and Accounting https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[An evaluation framework for comparing geocoding systems]]> https://www.researchpad.co/product?articleinfo=5989daeeab0ee8fa60bc03dc

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.

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<![CDATA[Characteristics of residential areas and transportational walking among frail and non-frail Dutch elderly: does the size of the area matter?]]> https://www.researchpad.co/product?articleinfo=5989dab3ab0ee8fa60bac1d6

Background

A residential area supportive for walking may facilitate elderly to live longer independently. However, current evidence on area characteristics potentially important for walking among older persons is mixed. This study hypothesized that the importance of area characteristics for transportational walking depends on the size of the area characteristics measured, and older person’s frailty level.

Methods

The study population consisted of 408 Dutch community-dwelling persons aged 65 years and older participating in the Elderly And their Neighborhood (ELANE) study in 2011–2012. Characteristics (aesthetics, functional features, safety, and destinations) of areas surrounding participants’ residences ranging from a buffer of 400 meters up to 1600 meters (based on walking path networks) were linked with self-reported transportational walking using linear regression analyses. In addition, interaction effects between frailty level and area characteristics were tested.

Results

An increase in functional features (e.g. presence of sidewalks and benches) within a 400 meter buffer, in aesthetics (e.g. absence of litter and graffiti) within 800 and 1200 meter buffers, and an increase of one destination per buffer of 400 and 800 meters were associated with more transportational walking, up to 2.89 minutes per two weeks (CI 1.07-7.32; p < 0.05). No differences were found between frail and non-frail elderly.

Conclusions

Better functional and aesthetic features, and more destinations in the residential area of community-dwelling older persons were associated with more transportational walking. The importance of area characteristics for transportational walking differs by area size, but not by frailty level. Neighbourhood improvements may increase transportational walking among older persons, thereby contributing to living longer independently.

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<![CDATA[Utility of passive photography to objectively audit built environment features of active transport journeys: an observational study]]> https://www.researchpad.co/product?articleinfo=5989da78ab0ee8fa60b975f6

Background

Active transport can contribute to physical activity accumulation and improved health in adults. The built environment is an established associate of active transport behaviours; however, assessment of environmental features encountered during journeys remains challenging. The purpose of this study was to examine the utility of wearable cameras to objectively audit and quantify environmental features along work-related walking and cycling routes.

Methods

A convenience sample of employed adults was recruited in New Zealand, in June 2011. Participants wore a SenseCam for all journeys over three weekdays and completed travel diaries and demographic questionnaires. SenseCam images for work-related active transport journeys were coded for presence of environmental features hypothesised to be related to active transport. Differences in presence of features by transport mode and in participant-reported and SenseCam-derived journey duration were determined using two-sample tests of proportion and an independent samples t-test, respectively.

Results

Fifteen adults participated in the study, yielding 1749 SenseCam images from 30 work-related active transport journeys for coding. Significant differences in presence of features were found between walking and cycling journeys. Almost a quarter of images were uncodeable due to being too dark to determine features. There was a non-significant tendency for respondents to under-report their journey duration.

Conclusion

This study provides proof of concept for the use of the SenseCam to capture built environment data in real time that may be related to active transportation. Further work is required to test and refine coding methodologies across a range of settings, travel behaviours, and demographic groups.

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<![CDATA[An objective index of walkability for research and planning in the Sydney Metropolitan Region of New South Wales, Australia: an ecological study]]> https://www.researchpad.co/product?articleinfo=5989da00ab0ee8fa60b73df4

Background

Walkability describes the capacity of the built environment to support walking for various purposes. This paper describes the construction and validation of two objective walkability indexes for Sydney, Australia.

Methods

Walkability indexes using residential density, intersection density, land use mix, with and without retail floor area ratio were calculated for 5,858 Sydney Census Collection Districts in a geographical information system. Associations between variables were evaluated using Spearman’s rho (ρ). Internal consistency and factor structure of indexes were estimated with Cronbach’s alpha and principal components analysis; convergent and predictive validity were measured using weighted kappa (κw) and by comparison with reported walking to work at the 2006 Australian Census using logistic regression. Spatial variation in walkability was assessed using choropleth maps and Moran’s I.

Results

A three-attribute abridged Sydney Walkability Index comprising residential density, intersection density and land use mix was constructed for all Sydney as retail floor area was only available for 5.3% of Census Collection Districts. A four-attribute full index including retail floor area ratio was calculated for 263 Census Collection Districts in the Sydney Central Business District. Abridged and full walkability index scores for these 263 areas were strongly correlated (ρ=0.93) and there was good agreement between walkability quartiles (κw=0.73). Internal consistency ranged from 0.60 to 0.71, and all index variables loaded highly on a single factor. The percentage of employed persons who walked to work increased with increasing walkability: 3.0% in low income-low walkability areas versus 7.9% in low income-high walkability areas; and 2.1% in high income-low walkability areas versus 11% in high income-high walkability areas. The adjusted odds of walking to work were 1.05 (0.96–1.15), 1.58 (1.45–1.71) and 3.02 (2.76–3.30) times higher in medium, high and very high compared to low walkability areas. Associations were similar for full and abridged indexes.

Conclusions

The abridged Sydney Walkability Index has predictive validity for utilitarian walking, will inform urban planning in Sydney, and will be used as an objective measure of neighbourhood walkability in a large population cohort. Abridged walkability indexes may be useful in settings where retail floor area data are unavailable.

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<![CDATA[GIS-aided planning of insecticide spraying to control dengue transmission]]> https://www.researchpad.co/product?articleinfo=5989dacbab0ee8fa60bb4158

Background

The purpose of this paper is to integrate a multi-objective integer programming formulation and geographic information system (GIS) into dynamically planning the insecticide spraying area for preventing the transmission of dengue fever.

Methods

The optimal spraying area to combat dengue infections is calculated by the multi-objective integer programming model using the dengue epidemic in 2007 in Tainan City of southern Taiwan and is compared with the areas actually sprayed by the local health department. The dynamic epidemic indicators (i.e. frequency, intensity and duration) that identify major temporal characteristics of the dynamic process of an epidemic are all incorporated into the model.

Results

The results indicate that the model can design the spraying area effectively when the trade-off between the coverage of dengue epidemics risk and area compactness is considered.

Conclusions

The model provides an alternative way to obtain a cost-effective spraying area in controlling future dengue epidemics. The proposed model in this study will be beneficial for strategically allocating dengue control resources.

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<![CDATA[A linear programming model for preserving privacy when disclosing patient spatial information for secondary purposes]]> https://www.researchpad.co/product?articleinfo=5989da74ab0ee8fa60b95ee7

Background

A linear programming (LP) model was proposed to create de-identified data sets that maximally include spatial detail (e.g., geocodes such as ZIP or postal codes, census blocks, and locations on maps) while complying with the HIPAA Privacy Rule’s Expert Determination method, i.e., ensuring that the risk of re-identification is very small. The LP model determines the transition probability from an original location of a patient to a new randomized location. However, it has a limitation for the cases of areas with a small population (e.g., median of 10 people in a ZIP code).

Methods

We extend the previous LP model to accommodate the cases of a smaller population in some locations, while creating de-identified patient spatial data sets which ensure the risk of re-identification is very small.

Results

Our LP model was applied to a data set of 11,740 postal codes in the City of Ottawa, Canada. On this data set we demonstrated the limitations of the previous LP model, in that it produces improbable results, and showed how our extensions to deal with small areas allows the de-identification of the whole data set.

Conclusions

The LP model described in this study can be used to de-identify geospatial information for areas with small populations with minimal distortion to postal codes. Our LP model can be extended to include other information, such as age and gender.

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<![CDATA[Spatial autocorrelation in uptake of antenatal care and relationship to individual, household and village-level factors: results from a community-based survey of pregnant women in six districts in western Kenya]]> https://www.researchpad.co/product?articleinfo=5989da75ab0ee8fa60b96546

Background

The majority of maternal deaths, stillbirths, and neonatal deaths are concentrated in a few countries, many of which have weak health systems, poor access to health services, and low coverage of key health interventions. Early and consistent antenatal care (ANC) attendance could significantly reduce maternal and neonatal morbidity and mortality. Despite this, most Kenyan mothers initiate ANC care late in pregnancy and attend fewer than the recommended visits.

Methods

We used survey data from 6,200 pregnant women across six districts in western Kenya to understand demand-side factors related to use of ANC. Bayesian multi-level models were developed to explore the relative importance of individual, household and village-level factors in relation to ANC use.

Results

There is significant spatial autocorrelation of ANC attendance in three of the six districts and considerable heterogeneity in factors related to ANC use between districts. Working outside the home limited ANC attendance. Maternal age, the number of small children in the household, and ownership of livestock were important in some districts, but not all. Village proportions of pregnancy in women of child-bearing age was significantly correlated to ANC use in three of the six districts. Geographic distance to health facilities and the type of nearest facility was not correlated with ANC use. After incorporating individual, household and village-level covariates, no residual spatial autocorrelation remained in the outcome.

Conclusions

ANC attendance was consistently low across all the districts, but factors related to poor attendance varied. This heterogeneity is expected for an outcome that is highly influenced by socio-cultural values and local context. Interventions to improve use of ANC must be tailored to local context and should include explicit approaches to reach women who work outside the home.

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<![CDATA[Using simple agent-based modeling to inform and enhance neighborhood walkability]]> https://www.researchpad.co/product?articleinfo=5989dacdab0ee8fa60bb4d4f

Background

Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate.

Methods

This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input.

Results

The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections.

Conclusions

The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) ‘learning’ and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).

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<![CDATA[Spatial heterogeneity of type I error for local cluster detection tests]]> https://www.researchpad.co/product?articleinfo=5989db02ab0ee8fa60bc7008

Background

Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect.

Methods

A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect.

Results

The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated.

Conclusions

In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance.

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<![CDATA[Evaluation of the neighborhood environment walkability scale in Nigeria]]> https://www.researchpad.co/product?articleinfo=5989da3eab0ee8fa60b8920b

Background

The development of reliable and culturally sensitive measures of attributes of the built and social environment is necessary for accurate analysis of environmental correlates of physical activity in low-income countries, that can inform international evidence-based policies and interventions in the worldwide prevention of physical inactivity epidemics. This study systematically adapted the Neighborhood Environment Walkability Scale (NEWS) for Nigeria and evaluated aspects of reliability and validity of the adapted version among Nigerian adults.

Methods

The adaptation of the NEWS was conducted by African and international experts, and final items were selected for NEWS-Nigeria after a cross-validation of the confirmatory factor analysis structure of the original NEWS. Participants (N = 386; female = 47.2%) from two cities in Nigeria completed the adapted NEWS surveys regarding perceived residential density, land use mix – diversity, land use mix – access, street connectivity, infrastructure and safety for walking and cycling, aesthetics, traffic safety, and safety from crime. Self-reported activity for leisure, walking for different purposes, and overall physical activity were assessed with the validated International Physical Activity Questionnaire (long version).

Results

The adapted NEWS subscales had moderate to high test-retest reliability (ICC range 0.59 –0.91). Construct validity was good, with residents of high-walkable neighborhoods reporting significantly higher residential density, more land use mix diversity, higher street connectivity, more traffic safety and more safety from crime, but lower infrastructure and safety for walking/cycling and aesthetics than residents of low-walkable neighborhoods. Concurrent validity correlations were low to moderate (r = 0.10 –0.31) with residential density, land use mix diversity, and traffic safety significantly associated with most physical activity outcomes.

Conclusions

The NEWS-Nigeria demonstrated acceptable measurement properties among Nigerian adults and may be useful for evaluation of the built environment in Nigeria. Further adaptation and evaluation in other African countries is needed to create a version that could be used throughout the African region.

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<![CDATA[Geographic variations in access and utilization of cancer screening services: examining disparities among American Indian and Alaska Native Elders]]> https://www.researchpad.co/product?articleinfo=5989dab5ab0ee8fa60bac714

Background

Despite recommendations for cancer screening for breast and colorectal cancer among the Medicare population, preventive screenings rates are often lower among vulnerable populations such as the small but rapidly growing older American Indian and Alaska Native (AIAN) population. This study seeks to identify potential disparities in the availability of screening services, distance to care, and the utilization of cancer screening services for Medicare beneficiaries residing in areas with a higher concentration of AIAN populations.

Methods

Using the county (n =3,225) as the level of analysis, we conducted a cross-sectional analysis of RTI International’s Spatial Impact Factor Data (2012) to determine the level of disparities for AIAN individuals. The outcomes of interest include: the presence of health care facilities in the county, the average distance in miles to the closest provider of mammography and colonoscopy (analyzed separately) and utilization of screening services (percent of adults aged 65 and older screened by county).

Results

Counties with higher concentrations of AIAN individuals had greater disparities in access and utilization of cancer screening services. Even after adjusting for income, education, state of residence, population 65 and older and rurality, areas with higher levels of AIAN individuals were more likely to see disparities with regard to health care services related to mammograms (p ≤ .05; longer distance, lower screening) and colonoscopies (p ≤ .05; longer distance, lower screening).

Conclusions

These findings provide evidence of a gap in service availability, utilization and access facing areas with higher levels of AIAN individuals throughout the US. Without adequate resources in place, these areas will continue to have less access to services and poorer health which will be accelerated as the population of older adults grows.

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<![CDATA[Assessing socioeconomic vulnerability to dengue fever in Cali, Colombia: statistical vs expert-based modeling]]> https://www.researchpad.co/product?articleinfo=5989db31ab0ee8fa60bd206a

Background

As a result of changes in climatic conditions and greater resistance to insecticides, many regions across the globe, including Colombia, have been facing a resurgence of vector-borne diseases, and dengue fever in particular. Timely information on both (1) the spatial distribution of the disease, and (2) prevailing vulnerabilities of the population are needed to adequately plan targeted preventive intervention. We propose a methodology for the spatial assessment of current socioeconomic vulnerabilities to dengue fever in Cali, a tropical urban environment of Colombia.

Methods

Based on a set of socioeconomic and demographic indicators derived from census data and ancillary geospatial datasets, we develop a spatial approach for both expert-based and purely statistical-based modeling of current vulnerability levels across 340 neighborhoods of the city using a Geographic Information System (GIS). The results of both approaches are comparatively evaluated by means of spatial statistics. A web-based approach is proposed to facilitate the visualization and the dissemination of the output vulnerability index to the community.

Results

The statistical and the expert-based modeling approach exhibit a high concordance, globally, and spatially. The expert-based approach indicates a slightly higher vulnerability mean (0.53) and vulnerability median (0.56) across all neighborhoods, compared to the purely statistical approach (mean = 0.48; median = 0.49). Both approaches reveal that high values of vulnerability tend to cluster in the eastern, north-eastern, and western part of the city. These are poor neighborhoods with high percentages of young (i.e., < 15 years) and illiterate residents, as well as a high proportion of individuals being either unemployed or doing housework.

Conclusions

Both modeling approaches reveal similar outputs, indicating that in the absence of local expertise, statistical approaches could be used, with caution. By decomposing identified vulnerability “hotspots” into their underlying factors, our approach provides valuable information on both (1) the location of neighborhoods, and (2) vulnerability factors that should be given priority in the context of targeted intervention strategies. The results support decision makers to allocate resources in a manner that may reduce existing susceptibilities and strengthen resilience, and thus help to reduce the burden of vector-borne diseases.

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<![CDATA[Social differences in avoidable mortality between small areas of 15 European cities: an ecological study]]> https://www.researchpad.co/product?articleinfo=5989da80ab0ee8fa60b9a680

Background

Health and inequalities in health among inhabitants of European cities are of major importance for European public health and there is great interest in how different health care systems in Europe perform in the reduction of health inequalities. However, evidence on the spatial distribution of cause-specific mortality across neighbourhoods of European cities is scarce. This study presents maps of avoidable mortality in European cities and analyses differences in avoidable mortality between neighbourhoods with different levels of deprivation.

Methods

We determined the level of mortality from 14 avoidable causes of death for each neighbourhood of 15 large cities in different European regions. To address the problems associated with Standardised Mortality Ratios for small areas we smooth them using the Bayesian model proposed by Besag, York and Mollié. Ecological regression analysis was used to assess the association between social deprivation and mortality.

Results

Mortality from avoidable causes of death is higher in deprived neighbourhoods and mortality rate ratios between areas with different levels of deprivation differ between gender and cities. In most cases rate ratios are lower among women. While Eastern and Southern European cities show higher levels of avoidable mortality, the association of mortality with social deprivation tends to be higher in Northern and lower in Southern Europe.

Conclusions

There are marked differences in the level of avoidable mortality between neighbourhoods of European cities and the level of avoidable mortality is associated with social deprivation. There is no systematic difference in the magnitude of this association between European cities or regions. Spatial patterns of avoidable mortality across small city areas can point to possible local problems and specific strategies to reduce health inequality which is important for the development of urban areas and the well-being of their inhabitants.

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<![CDATA[How many suffice? A computational framework for sizing sentinel surveillance networks]]> https://www.researchpad.co/product?articleinfo=5989da52ab0ee8fa60b8e12b

Background

Data from surveillance networks help epidemiologists and public health officials detect emerging diseases, conduct outbreak investigations, manage epidemics, and better understand the mechanics of a particular disease. Surveillance networks are used to determine outbreak intensity (i.e., disease burden) and outbreak timing (i.e., the start, peak, and end of the epidemic), as well as outbreak location. Networks can be tuned to preferentially perform these tasks. Given that resources are limited, careful site selection can save costs while minimizing performance loss.

Methods

We study three different site placement algorithms: two algorithms based on the maximal coverage model and one based on the K-median model. The maximal coverage model chooses sites that maximize the total number of people within a specified distance of a site. The K-median model minimizes the sum of the distances from each individual to the individual’s nearest site. Using a ground truth dataset consisting of two million de-identified Medicaid billing records representing eight complete influenza seasons and an evaluation function based on the Huff spatial interaction model, we empirically compare networks against the existing Iowa Department of Public Health influenza-like illness network by simulating the spread of influenza across the state of Iowa.

Results

We show that it is possible to design a network that achieves outbreak intensity performance identical to the status quo network using two fewer sites. We also show that if outbreak timing detection is of primary interest, it is actually possible to create a network that matches the existing network’s performance using 59% fewer sites.

Conclusions

By simulating the spread of influenza across the state of Iowa, we show that our methods are capable of designing networks that perform better than the status quo in terms of both outbreak intensity and timing. Additionally, our results suggest that network size may only play a minimal role in outbreak timing detection. Finally, we show that it may be possible to reduce the size of a surveillance system without affecting the quality of surveillance information produced.

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<![CDATA[High-resolution spatiotemporal weather models for climate studies]]> https://www.researchpad.co/product?articleinfo=5989d9ffab0ee8fa60b737d3

Background

Climate may exert a strong influence on health, in particular on vector-borne infectious diseases whose vectors are intrinsically dependent on their environment. Although critical, linking climate variability to health outcomes is a difficult task. For some diseases in some areas, spatially and temporally explicit surveillance data are available, but comparable climate data usually are not. We utilize spatial models and limited weather observations in Puerto Rico to predict weather throughout the island on a scale compatible with the local dengue surveillance system.

Results

We predicted monthly mean maximum temperature, mean minimum temperature, and cumulative precipitation at a resolution of 1,000 meters. Average root mean squared error in cross-validation was 1.24°C for maximum temperature, 1.69°C for minimum temperature, and 62.2 millimeters for precipitation.

Conclusion

We present a methodology for efficient extrapolation of minimal weather observation data to a more meaningful geographical scale. This analysis will feed downstream studies of climatic effects on dengue transmission in Puerto Rico. Additionally, we utilize conditional simulation so that model error may be robustly passed to future analyses.

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<![CDATA[A spatially filtered multilevel model to account for spatial dependency: application to self-rated health status in South Korea]]> https://www.researchpad.co/product?articleinfo=5989daddab0ee8fa60bba69e

Background

This study aims to suggest an approach that integrates multilevel models and eigenvector spatial filtering methods and apply it to a case study of self-rated health status in South Korea. In many previous health-related studies, multilevel models and single-level spatial regression are used separately. However, the two methods should be used in conjunction because the objectives of both approaches are important in health-related analyses. The multilevel model enables the simultaneous analysis of both individual and neighborhood factors influencing health outcomes. However, the results of conventional multilevel models are potentially misleading when spatial dependency across neighborhoods exists. Spatial dependency in health-related data indicates that health outcomes in nearby neighborhoods are more similar to each other than those in distant neighborhoods. Spatial regression models can address this problem by modeling spatial dependency. This study explores the possibility of integrating a multilevel model and eigenvector spatial filtering, an advanced spatial regression for addressing spatial dependency in datasets.

Methods

In this spatially filtered multilevel model, eigenvectors function as additional explanatory variables accounting for unexplained spatial dependency within the neighborhood-level error. The specification addresses the inability of conventional multilevel models to account for spatial dependency, and thereby, generates more robust outputs.

Results

The findings show that sex, employment status, monthly household income, and perceived levels of stress are significantly associated with self-rated health status. Residents living in neighborhoods with low deprivation and a high doctor-to-resident ratio tend to report higher health status. The spatially filtered multilevel model provides unbiased estimations and improves the explanatory power of the model compared to conventional multilevel models although there are no changes in the signs of parameters and the significance levels between the two models in this case study.

Conclusions

The integrated approach proposed in this paper is a useful tool for understanding the geographical distribution of self-rated health status within a multilevel framework. In future research, it would be useful to apply the spatially filtered multilevel model to other datasets in order to clarify the differences between the two models. It is anticipated that this integrated method will also out-perform conventional models when it is used in other contexts.

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<![CDATA[Creating &#8216;obesogenic realities&#8217;; do our methodological choices make a difference when measuring the food environment?]]> https://www.researchpad.co/product?articleinfo=5989daf9ab0ee8fa60bc3f9e

Background

The use of Geographical Information Systems (GIS) to objectively measure ‘obesogenic’ food environment (foodscape) exposure has become common-place. This increase in usage has coincided with the development of a methodologically heterogeneous evidence-base, with subsequent perceived difficulties for inter-study comparability. However, when used together in previous work, different types of food environment metric have often demonstrated some degree of covariance. Differences and similarities between density and proximity metrics, and within methodologically different conceptions of density and proximity metrics need to be better understood.

Methods

Frequently used measures of food access were calculated for North East England, UK. Using food outlet data from local councils, densities of food outlets per 1000 population and per km2 were calculated for small administrative areas. Densities (counts) were also calculated based on population-weighted centroids of administrative areas buffered at 400/800/1000m street network and Euclidean distances. Proximity (street network and Euclidean distances) from these centroids to the nearest food outlet were also calculated. Metrics were compared using Spearman’s rank correlations.

Results

Measures of foodscape density and proximity were highly correlated. Densities per km2 and per 1000 population were highly correlated (rs = 0.831). Euclidean and street network based measures of proximity (rs = 0.865) and density (rs = 0.667-0.764, depending on neighbourhood size) were also highly correlated. Density metrics based on administrative areas and buffered centroids of administrative areas were less strongly correlated (rs = 0.299-0.658).

Conclusions

Density and proximity metrics were largely comparable, with some exceptions. Whilst results suggested a substantial degree of comparability across existing studies, future comparability could be ensured by moving towards a more standardised set of environmental metrics, where appropriate, lessening the potential pitfalls of methodological variation between studies. The researchers’ role in creating their own obesogenic ‘reality’ should be better understood and acknowledged.

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<![CDATA[Global spatiotemporal and genetic footprint of the H5N1 avian influenza virus]]> https://www.researchpad.co/product?articleinfo=5989db04ab0ee8fa60bc7dec

Background

Since 2005, the Qinghai-like lineage of the highly pathogenic avian influenza A virus H5N1 has rapidly spread westward to Europe, the Middle East and Africa, reaching a dominant level at a global scale in 2006.

Methods

Based on a combination of genetic sequence data and H5N1 outbreak information from 2005 to 2011, we use an interdisciplinary approach to improve our understanding of the transmission pattern of this particular clade 2.2, and present cartography of global spatiotemporal transmission footprints with genetic characteristics.

Results

Four major viral transmission routes were derived with three sources— Russia, Mongolia, and the Middle East (Kuwait and Saudi Arabia)—in the three consecutive years 2005, 2006 and 2007. With spatiotemporal transmission along each route, genetic distances to isolate A/goose/Guangdong/1996 are becoming significantly larger, leading to a more challenging situation in certain regions like Korea, India, France, Germany, Nigeria and Sudan. Europe and India have had at least two incursions along multiple routes, causing a mixed virus situation. In addition, spatiotemporal distribution along the routes showed that 2007/2008 was a temporal separation point for the infection of different host species; specifically, wild birds were the main host in 2005–2007/2008 and poultry was responsible for the genetic mutation in 2009–2011. “Global-to-local” and “high-to-low latitude” transmission footprints have been observed.

Conclusions

Our results suggest that both wild birds and poultry play important roles in the transmission of the H5N1 virus clade, but with different spatial, temporal, and genetic dominance. These characteristics necessitate that special attention be paid to countries along the transmission routes.

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<![CDATA[Web GIS in practice VI: a demo playlist of geo-mashups for public health neogeographers]]> https://www.researchpad.co/product?articleinfo=5989db3fab0ee8fa60bd63b0

'Mashup' was originally used to describe the mixing together of musical tracks to create a new piece of music. The term now refers to Web sites or services that weave data from different sources into a new data source or service. Using a musical metaphor that builds on the origin of the word 'mashup', this paper presents a demonstration "playlist" of four geo-mashup vignettes that make use of a range of Web 2.0, Semantic Web, and 3-D Internet methods, with outputs/end-user interfaces spanning the flat Web (two-dimensional – 2-D maps), a three-dimensional – 3-D mirror world (Google Earth) and a 3-D virtual world (Second Life ®). The four geo-mashup "songs" in this "playlist" are: 'Web 2.0 and GIS (Geographic Information Systems) for infectious disease surveillance', 'Web 2.0 and GIS for molecular epidemiology', 'Semantic Web for GIS mashup', and 'From Yahoo! Pipes to 3-D, avatar-inhabited geo-mashups'. It is hoped that this showcase of examples and ideas, and the pointers we are providing to the many online tools that are freely available today for creating, sharing and reusing geo-mashups with minimal or no coding, will ultimately spark the imagination of many public health practitioners and stimulate them to start exploring the use of these methods and tools in their day-to-day practice. The paper also discusses how today's Web is rapidly evolving into a much more intensely immersive, mixed-reality and ubiquitous socio-experiential Metaverse that is heavily interconnected through various kinds of user-created mashups.

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<![CDATA[Geographic disparities in the risk of perforated appendicitis among children in Ohio: 2001&#8211;2003]]> https://www.researchpad.co/product?articleinfo=5989da17ab0ee8fa60b7bb85

Background

Rural-urban disparities in health and healthcare are often attributed to differences in geographic access to care and health seeking behavior. Less is known about the differences between rural locations in health care seeking and outcomes. This study examines how commuting patterns in different rural areas are associated with perforated appendicitis.

Results

Controlling for age, sex, insurance type, comorbid conditions, socioeconomic status, appendectomy rates, hospital type, and hospital location, we found that patient residence in a rural ZIP code with significant levels of commuting to metropolitan areas was associated with higher risk of perforation compared to residence in rural areas with commuting to smaller urban clusters. The former group was more likely to seek care in an urbanized area, and was more likely to receive care in a Children's Hospital.

Conclusion

To our knowledge, this is the first study to differentiate rural dwellers with respect to outcomes associated with appendicitis as opposed to simply comparing "rural" to "urban". Risk of perforated appendicitis associated with commuting patterns is larger than that posed by several individual indicators including some age-sex cohort effects. Future studies linking the activity spaces of rural dwellers to individual patterns of seeking care will further our understanding of perforated appendicitis and ambulatory care sensitive conditions in general.

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