Kathleen Stewart
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View article: Examining trip-level errors in passively collected mobile device data for data quality assurance
Examining trip-level errors in passively collected mobile device data for data quality assurance Open
Location-based service (LBS) data passively collected by mobile devices has been widely adopted in multiple fields for its advantages in revealing travel behaviors. Data quality assessments have always been important steps for analyses usi…
View article: Association Between Trust in Health Care Professionals and Health Care Access: Insights From an Online Survey Across 21 Countries
Association Between Trust in Health Care Professionals and Health Care Access: Insights From an Online Survey Across 21 Countries Open
Objectives This study evaluates the association between trust in health care professionals and health care delays across 21 countries. Methods We apply logistic regression models to survey data of over 621,000 individuals collected in Spri…
View article: Insights on Late-Stage COVID-19 Pandemic Recovery From a 21-Country Online Survey
Insights on Late-Stage COVID-19 Pandemic Recovery From a 21-Country Online Survey Open
Objectives The widespread impact of the COVID-19 pandemic on health systems, economies, and societies globally requires comprehensive data to guide effective recovery efforts. Online surveys have become crucial for rapid and extensive data…
View article: Understanding factors that impact vehicle travel times on urban road networks using machine learning approaches
Understanding factors that impact vehicle travel times on urban road networks using machine learning approaches Open
While travelers may have the same origin and destination for their trips, these trips may be associated with different travel times. Understanding what factors contribute to different travel times contributes to better transportation plann…
View article: The geographical distribution of the family-genetic risk score for drug use disorder in Sweden and its co-localization with areas of social deprivation
The geographical distribution of the family-genetic risk score for drug use disorder in Sweden and its co-localization with areas of social deprivation Open
Background Drug use Disorder (DUD), the risk for which is substantially influenced by both genetic and social factors, is geographically concentrated in high-risk regions. An important step toward understanding this pattern is to examine g…
View article: Mobility-GCN: a human mobility-based graph convolutional network for tracking and analyzing the spatial dynamics of the synthetic opioid crisis in the USA, 2013-2020
Mobility-GCN: a human mobility-based graph convolutional network for tracking and analyzing the spatial dynamics of the synthetic opioid crisis in the USA, 2013-2020 Open
Synthetic opioids are the most common drugs involved in drug-involved overdose mortalities in the U.S. The Center for Disease Control and Prevention reported that in 2018, about 70% of all drug overdose deaths involved opioids and 67% of a…
View article: Does Context Influence How People Higher and Lower in the Propensity to Worry React to Uncertainty?
Does Context Influence How People Higher and Lower in the Propensity to Worry React to Uncertainty? Open
It is well established that individuals high in chronic worry experience greater anxiety when faced with uncertainty than those lower in chronic worry (e.g., Dugas et al., 2004); however, there is a dearth of research on other potentially …
View article: Variation in spatial population structure in the<i>Anopheles gambiae</i>species complex
Variation in spatial population structure in the<i>Anopheles gambiae</i>species complex Open
Anopheles gambiae , Anopheles coluzzii , and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of th…
View article: Understanding work-related travel and its relation to malaria occurrence in Thailand using geospatial maximum entropy modelling
Understanding work-related travel and its relation to malaria occurrence in Thailand using geospatial maximum entropy modelling Open
Background Estimating malaria risk associated with work locations and travel across a region provides local health officials with information useful to mitigate possible transmission paths of malaria as well as understand the risk of expos…
View article: Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries Open
Background Drug Use Disorder (DUD) is a major contributor to world-wide morbidity and mortality. The extensive national registers in Sweden provide the basis for a study of spatial and temporal patterns of DUD onset and recurrence in Swede…
View article: Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model
Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model Open
Background More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers betwe…
View article: Making Space in Geographical Analysis
Making Space in Geographical Analysis Open
In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for all . We emphasize key aspect…
View article: Data Gap Filling Using Cloud-Based Distributed Markov Chain Cellular Automata Framework for Land Use and Land Cover Change Analysis: Inner Mongolia as a Case Study
Data Gap Filling Using Cloud-Based Distributed Markov Chain Cellular Automata Framework for Land Use and Land Cover Change Analysis: Inner Mongolia as a Case Study Open
With advances in remote sensing, massive amounts of remotely sensed data can be harnessed to support land use/land cover (LULC) change studies over larger scales and longer terms. However, a big challenge is missing data as a result of poo…
View article: Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base
Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base Open
Significance The University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS), launched April 2020, is the largest remote global health monitoring system. This study includes ∼30 million responses through December 2020 from all …
View article: Global Monitoring of the Impact of COVID-19 Pandemic through Online Surveys Sampled from the Facebook User Base
Global Monitoring of the Impact of COVID-19 Pandemic through Online Surveys Sampled from the Facebook User Base Open
Simultaneously tracking the global COVID-19 impact across multiple populations is challenging due to regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network…
View article: Understanding the Drivers of Mobility during the COVID-19 Pandemic in Florida, USA Using a Machine Learning Approach
Understanding the Drivers of Mobility during the COVID-19 Pandemic in Florida, USA Using a Machine Learning Approach Open
As of March 2021, the State of Florida, U.S.A. had accounted for approximately 6.67% of total COVID-19 (SARS-CoV-2 coronavirus disease) cases in the U.S. The main objective of this research is to analyze mobility patterns during a three mo…
View article: The impact of the attention training technique on attention control and worry
The impact of the attention training technique on attention control and worry Open
The present study examined whether the Attention Training Technique (ATT; Wells, 1990) is more efficacious at reducing worry and modifying GAD-related attention processes than a control intervention. Adults with Probable GAD (N = 29) monit…
View article: Attributing pedestrian networks with semantic information based on multi-source spatial data
Attributing pedestrian networks with semantic information based on multi-source spatial data Open
The lack of associating pedestrian networks, i.e. the paths and roads used for non-vehicular travel, with information about semantic attribution is a major weakness for many applications, especially those supporting accurate pedestrian rou…
View article: Making Space in Geographical Analysis
Making Space in Geographical Analysis Open
In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for women. We emphasize key aspec…
View article: Spatiotemporal analysis of medical resource deficiencies in the U.S. under COVID-19 pandemic
Spatiotemporal analysis of medical resource deficiencies in the U.S. under COVID-19 pandemic Open
Coronavirus disease 2019 (COVID-19) was first identified in December 2019 in Wuhan, China as an infectious disease, and has quickly resulted in an ongoing pandemic. A data-driven approach was developed to estimate medical resource deficien…
View article: Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke
Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke Open
Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public…
View article: Modeling spatial access to cervical cancer screening services in Ondo State, Nigeria
Modeling spatial access to cervical cancer screening services in Ondo State, Nigeria Open
Background Women in low- and middle-income countries (LMIC) remain at high risk of developing cervical cancer and have limited access to screening programs. The limits include geographical barriers related to road network characteristics a…
View article: Spatiotemporal Analysis of Medical Resource Deficiencies in the U.S. under COVID-19 Pandemic
Spatiotemporal Analysis of Medical Resource Deficiencies in the U.S. under COVID-19 Pandemic Open
A data-driven approach is developed to estimate medical resource deficiencies or medical burden at county level during the COVID-19 pandemic from February 15, 2020 to May 1, 2020 in the U.S. Multiple data sources were used to extract local…