GIS in Healthcare

The landscape of healthcare is dynamic, gradually becoming more complicated with factors beyond simple supply and demand. Similar to the diversity of social, political and economic contexts, the practical utilization of healthcare resources also varies around the world. However, the spatial components of these contexts, along with aspects of supply and demand, can reveal a common theme among these factors. This book presents advancements in GIS applications that reveal the complexity of and solutions for a dynamic healthcare landscape

Community Time-Activity Trajectory Modelling based on Markov Chain Simulation and Dirichlet Regression

Accurate modeling of human time-activity trajectory is essential to support community resilience and emergency response strategies such as daily energy planning and urban seismic vulnerability assessment. However, existing modeling of time-activity trajectory is only driven by socio-demographic information with identical activity trajectories shared among the same group of people and neglects the influence of the environment. To further improve human time-activity trajectory modeling, this paper constructs community time-activity trajectory and analyzes how social-demographic and built environment influence people s activity trajectory based on Markov Chains and Dirichlet Regression. We use the New York area as a case study and gather data from American Time Use Survey, Policy Map, and the New York City Energy & Water Performance Map to evaluate the proposed method. To validate the regression model, Box s M Test and T-test are performed with 80% data training the model and the left 20% as the test sample. The modeling results align well with the actual human behavior trajectories, demonstrating the effectiveness of the proposed method. It also shows that both social-demographic and built environment factors will significantly impact a community's time-activity trajectory. Specifically, 1) Diversity and median age both have a significant influence on the proportion of time people assign to education activity. 2) Transportation condition affects people s activity trajectory in the way that longer commute time decreases the proportion of biological activity (eg. sleeping and eating) and increases people s working time. 3) Residential density affects almost all activities with a significant p-value for all biological needs, household management, working, education, and personal preference.Comment: to be published in Computers, Environment and Urban Syste

Assessing Ozone-Related Health Impacts under a Changing Climate

Climate change may increase the frequency and intensity of ozone episodes in future summers in the United States. However, only recently have models become available that can assess the impact of climate change on O(3) concentrations and health effects at regional and local scales that are relevant to adaptive planning. We developed and applied an integrated modeling framework to assess potential O(3)-related health impacts in future decades under a changing climate. The National Aeronautics and Space Administration–Goddard Institute for Space Studies global climate model at 4° × 5° resolution was linked to the Penn State/National Center for Atmospheric Research Mesoscale Model 5 and the Community Multiscale Air Quality atmospheric chemistry model at 36 km horizontal grid resolution to simulate hourly regional meteorology and O(3) in five summers of the 2050s decade across the 31-county New York metropolitan region. We assessed changes in O(3)-related impacts on summer mortality resulting from climate change alone and with climate change superimposed on changes in O(3) precursor emissions and population growth. Considering climate change alone, there was a median 4.5% increase in O(3)-related acute mortality across the 31 counties. Incorporating O(3) precursor emission increases along with climate change yielded similar results. When population growth was factored into the projections, absolute impacts increased substantially. Counties with the highest percent increases in projected O(3) mortality spread beyond the urban core into less densely populated suburban counties. This modeling framework provides a potentially useful new tool for assessing the health risks of climate change

Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data

Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in order to effectively forecast regional economic variables. Several spatial econometric techniques are available in the literature, which deal with the spatial autocorrelation in geographically-referenced data. The experiments carried out in this paper are concerned with the analysis of the spatial autocorrelation observed for unemployment rates in 439 NUTS-3 German districts. We employ a semi-parametric approach – spatial filtering – in order to uncover spatial patterns that are consistently significant over time. We first provide a brief overview of the spatial filtering method and illustrate the data set. Subsequently, we describe the empirical application carried out: that is, the spatial filtering analysis of regional unemployment rates in Germany. Furthermore, we exploit the resulting spatial filter as an explanatory variable in a panel modelling framework. Additional explanatory variables, such as average daily wages, are used in concurrence with the spatial filter. Our experiments show that the computed spatial filters account for most of the residual spatial autocorrelation in the data.spatial filtering, eigenvectors, Germany, unemployment

Updating the PECAS Modeling Framework to Include Energy Use Data for Buildings

This study investigates the consumption of electricity and natural gas for building operations for several categories of residential and non-residential buildings. The study updates the Production Exchange Consumption Allocation System (PECAS) land use modeling framework to include energy components. An energy database was assembled to study energy consumption in buildings. The authors conducted statistical analysis of utility data and estimated linear regression models to predict energy consumption in buildings. Results are validated using data from independent sources, including the California Residential Appliance Saturation Study (RASS) and the Commercial End-Use Survey (CEUS). Results are used to update PECAS and form part of the baseline study to estimate energy and greenhouse gas balances in an urban metabolism framework for the analysis of the environmental impacts of complex urban regions. The results also allow the total energy consumption and greenhouse gas emissions for residential and commercial building operations to be estimated through the application to the total residential and commercial building inventory in the region. These results are then useful for the evaluation of possible energy savings in buildings

Why the poor in rural Malawi are where they are: An Analysis of the Spatial Determinants of the Local Prevalence of Poverty

"We examine the spatial determinants of the prevalence of poverty for small spatially defined populations in rural Malawi. Poverty prevalence was estimated using a small-area poverty estimation technique. A theoretical approach based on the risk chain conceptualization of household economic vulnerability guided our selection of a set of potential risk and coping strategies — the determinants of our model — that could be represented spatially. These were used in two analyses to develop global and local models, respectively. In our global model—a spatial error model — only eight of the more than two dozen determinants selected for analysis proved significant. In contrast, all of the determinants considered were significant in at least some of the local models of poverty prevalence. The local models were developed using geographically weighted regression. Moreover, these models provided strong evidence of the spatial nonstationarity of the relationship between poverty and its determinants. That is, in determining the level of poverty in rural communities, where one is located in Malawi matters. This result for poverty reduction efforts in rural Malawi implies that such efforts should be designed for and targeted at the district and subdistrict levels. A national, relatively inflexible approach to poverty reduction is unlikely to enjoy broad success." Authors' AbstractSpatial analysis (Statistics) ,Poverty mapping ,Spatial regression ,Poverty determinants ,

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

A Grounded Theory of Patient Flow Management within the Emergency Department

Background: Emergency department (ED) crowding is an urgent threat to patient safety and negatively impacts healthcare staff and institutions. Patient flow researchers have employed a range of methods to address this crisis, including an increase in the use of operations research and operations management strategies. However, identified patient flow solutions are inadequate. Research describing the complexities of patient flow processes and investigating the work and contributions of ED nurses is needed. Purposes: The purposes of this study were to explore how ED nurses perform patient flow management and to develop a constructivist grounded theory of patient flow management within the ED. Methods: A conceptual foundation for patient flow management was first established using evolutionary concept analysis and expanded concept analysis approaches. This study then employed constructivist grounded theory and situational analysis methodologies to examine the work of ED nurses. Data was collected through 29 focus groups and interviews with 27 participants and 64 hours of participant observations across four EDs. Data analysis relied on coding, constant comparative analysis, and memo-writing to identify emergent themes and develop a substantive theory. Findings: Concept analyses defined patient flow management as the application of ED experience, holistic perspectives, dynamic data, and complex considerations of multiple priorities by ED nurses to promote patient safety within their scope of responsibility. The study offers three main contributions: a theoretical model of the work of ED patient flow management, a theoretical framework to describe holistic considerations of factors that impact departmental capacity and nurse engagement in patient flow management, and a grounded theory of patient flow management capacity and engagement that describes how ED nurses adapt patient flow management strategies according to patient burden. Conclusion: This study offers a new conceptual and theoretical foundation to understand the work of patient flow management. This novel perspective centralizes the work of ED nurses as active agents in patient flow processes and describes their strategies and contributions to meet patient care needs. Several practical considerations are offered to engage and support nurses in their roles as patient flow managers, improve patient flow processes, and further investigate ED nurse patient flow management