scholarly journals Visualizing demographic evolution using geographically inconsistent census data

2018 ◽  
Author(s):  
Fabio Dias ◽  
Daniel Silver
Keyword(s):  
Visual Analytics ◽  
Census Data ◽  
Demographic Data ◽  
Visual Exploration ◽  
Demographic Groups ◽  
Inconsistent Data ◽  
The Usa ◽  
Video Abstract ◽  
Demographic Evolution ◽  
Over Time

Video Abstract: https://youtu.be/bKeV08Os0uA Census measurements provide reliable demographic data going back centuries. However, their analysis is often hampered by the lack of geographical consistency across time. We propose a visual analytics system that enables the exploration of geographically inconsistent data. Our method also includes incremental developments in the representation, clustering, and visual exploration of census data, allowing an easier understanding of the demographic groups present in a city and their evolution over time. We present the feedback of experts in urban sciences and sociology, along with illustrative scenarios in the USA and Canada.

scholarly journals Visual Exploration of Energy Use in EU 28: Dynamics, Patterns, Policies

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7532
Author(s):  
George Halkos ◽  
Kyriaki Tsilika
Keyword(s):  
Energy Consumption ◽  
Visual Analytics ◽  
Energy Use ◽  
Visual Exploration ◽  
Dependence Structure ◽  
Low Carbon ◽  
Pollution Effects ◽  
Cross Sectional ◽  
Systematic Analysis ◽  
Over Time

The paper places emphasis on primary energy resources, their covariation, and their correlation with socioeconomic factors and aims to provide a systematic analysis of their development over time. The analysis uses evidence from European Union (EU) country-level data and is based on visual analytics techniques. Different results from the same territories show that energy consumption does not always reflect or is due to climatological or meteorological conditions. Extensive use of visualization is adopted as a means of contributing to the understanding of energy use, some involved problems and concepts, and energy consumption trends over time. We present an approach that addresses the informatics challenges based on the integration of visualization software, data integration, and cluster analysis. Our cross-sectional energy review advocates that EU energy leaders are moving towards a low-carbon economy. The correlations of energy variables with economic and pollution effects are stronger in greater levels of energy use, which means that energy use has an obvious impact on economic growth and the environment. Visual and automated methods employed for the analysis, reveal the direction, the strength, and the nature of the dependence structure, in clusters covering the range of energy use in EU 28 countries.

scholarly journals The Demographics of Total Ankle Replacement in the USA: A Study of 21,222 Cases Undergoing Pre- Operative CT Scan-Based Planning

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0038
Author(s):  
Murray J. Penner ◽  
Gregory C. Berlet ◽  
Ricardo Calvo ◽  
Eric Molina ◽  
David Reynolds ◽  
...  
Keyword(s):  
Ct Scan ◽  
Demographic Data ◽  
Total Ankle Replacement ◽  
Patient Specific ◽  
Clear Understanding ◽  
Ankle Arthritis ◽  
Ankle Replacement ◽  
The Usa ◽  
The Mean ◽  
Over Time

Category: Ankle; Ankle Arthritis Introduction/Purpose: To understand the role of total ankle replacement (TAR) in treating the spectrum of arthritis of the ankle, a clear understanding of the epidemiology of ankle arthritis is required. The largest pools of epidemiologic data available to date come from international registries. In the USA, the largest market for TAR, where an estimated 10,000 TARs are implanted per year, the largest pool of demographic data on patients undergoing TAR is comprised of just 805 cases collected over 6 years. With the advent of patient-specific instrumentation (PSI), detailed demographic and CT scan data can now be collected. These data on 21,222 cases undergoing CT scan-based PSI planning were reviewed to define the demographics of a very large cohort of TAR patients. Methods: The cohort contained 21,222 patients from the USA and Canada, with surgery dates from 2012 - 2019. Data analysed included deformity measures, presence of existing hardware and joint fusion status. To date, a subset sample of 4800 cases was available for analysis. Extraction is ongoing and data for the full cohort will soon be available. This subset described cases with surgery dates ranging from November 2015 through May 2019. Summary statistics to describe age, gender, ankle size, and tibio- talar deformity were calculated. Of the 4800 patients analyzed, 53% were male. Mean age 63.6 years (SD 10.4) (Age distribution in Figure 1a). The deformity distribution is shown in Figure 1b, with varus more common than valgus. The mean degree of deformity increased with every decade of patient age from 6.1° (age 30-39) to 9.2° (age 80-89), and over time from 9.3°(2016) to 11.8° (2019) [in stemmed- implant cases]. Results: Tibia size varied with gender. Females ranged between 34-38mm in 85% of cases; males from 41-48mm in 79%. Of 21,222 cases, 5964 (28%) had adjacent hardware (screws, etc) in situ and pre-existing ankle fusions were present in 517 (2.4%), increasing from 1.2% in 2013 to 2.9% in 2019.The mean age of TAR patients is similar to that reported in smaller series. Tibia size was significantly greater in males than females, a finding not previously reported in demographic literature. In contrast to knee arthritis, intra-articular deformity >5° is common, present in > 51% of cases (varus > valgus). This is the first series to show the degree of deformity increases with age. Over time, TAR is being used in cases with greater deformity. Conclusion: Hardware is seen to be commonly present in TAR, increasing complexity. Conversion of fusion to TAR, while rare, is more common than existing literature suggests, with the rate increasing each year, suggesting this may be an increasingly important role for TAR in the future. This study presents the largest set of demographic data on TAR patients in the literature. The demographics of USA patients undergoing TAR are similar to those seen in non-USA registries. Deformity is common, increasing with age. The severity of deformity treated with TAR and conversion of fusion to TAR are increasing over time.

scholarly journals Predictors of historical change in drug treatment coverage among people who inject drugs in 90 large metropolitan areas in the USA, 1993–2007

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Barbara Tempalski ◽  
Leslie D. Williams ◽  
Brooke S. West ◽  
Hannah L. F. Cooper ◽  
Stephanie Beane ◽  
...  
Keyword(s):  
Public Health ◽  
Drug Treatment ◽  
Resource Availability ◽  
People Who Inject Drugs ◽  
Census Data ◽  
Poverty Rate ◽  
Community Action ◽  
Historical Change ◽  
Treatment Coverage ◽  
Over Time

Abstract Background Adequate access to effective treatment and medication assisted therapies for opioid dependence has led to improved antiretroviral therapy adherence and decreases in morbidity among people who inject drugs (PWID), and can also address a broad range of social and public health problems. However, even with the success of syringe service programs and opioid substitution programs in European countries (and others) the US remains historically low in terms of coverage and access with regard to these programs. This manuscript investigates predictors of historical change in drug treatment coverage for PWID in 90 US metropolitan statistical areas (MSAs) during 1993–2007, a period in which, overall coverage did not change. Methods Drug treatment coverage was measured as the number of PWID in drug treatment, as calculated by treatment entry and census data, divided by numbers of PWID in each MSA. Variables suggested by the Theory of Community Action (i.e., need, resource availability, institutional opposition, organized support, and service symbiosis) were analyzed using mixed-effects multivariate models within dependent variables lagged in time to study predictors of later change in coverage. Results Mean coverage was low in 1993 (6.7%; SD 3.7), and did not increase by 2007 (6.4%; SD 4.5). Multivariate results indicate that increases in baseline unemployment rate (β = 0.312; pseudo-p < 0.0002) predict significantly higher treatment coverage; baseline poverty rate (β = − 0.486; pseudo-p < 0.0001), and baseline size of public health and social work workforce (β = 0.425; pseudo-p < 0.0001) were predictors of later mean coverage levels, and baseline HIV prevalence among PWID predicted variation in treatment coverage trajectories over time (baseline HIV * Time: β = 0.039; pseudo-p < 0.001). Finally, increases in black/white poverty disparity from baseline predicted significantly higher treatment coverage in MSAs (β = 1.269; pseudo-p < 0.0001). Conclusions While harm reduction programs have historically been contested and difficult to implement in many US communities, and despite efforts to increase treatment coverage for PWID, coverage has not increased. Contrary to our hypothesis, epidemiologic need, seems not to be associated with change in treatment coverage over time. Resource availability and institutional opposition are important predictors of change over time in coverage. These findings suggest that new ways have to be found to increase drug treatment coverage in spite of economic changes and belt-tightening policy changes that will make this difficult.

scholarly journals Monitoring streets through tweets: Using user-generated geographic information to predict gentrification and displacement

2021 ◽  
pp. 239980832110253
Author(s):  
Karen Chapple ◽  
Ate Poorthuis ◽  
Matthew Zook ◽  
Eva Phillips
Keyword(s):  
Big Data ◽  
San Francisco ◽  
Census Data ◽  
San Francisco Bay Area ◽  
Demographic Data ◽  
Activity Patterns ◽  
Neighborhood Change ◽  
Housing Affordability ◽  
Bay Area ◽  
Media Data

The new availability of big data sources provides an opportunity to revisit our ability to predict neighborhood change. This article explores how data on urban activity patterns, specifically, geotagged tweets, improve the understanding of one type of neighborhood change—gentrification—by identifying dynamic connections between neighborhoods and across scales. We first develop a typology of neighborhood change and risk of gentrification from 1990 to 2015 for the San Francisco Bay Area based on conventional demographic data from the Census. Then, we use multivariate regression to analyze geotagged tweets from 2012 to 2015, finding that outsiders are significantly more likely to visit neighborhoods currently undergoing gentrification. Using the factors that best predict gentrification, we identify a subset of neighborhoods that Twitter-based activity suggests are at risk for gentrification over the short term—but are not identified by analysis with traditional census data. The findings suggest that combining Census and social media data can provide new insights on gentrification such as augmenting our ability to identify that processes of change are underway. This blended approach, using Census and big data, can help policymakers implement and target policies that preserve housing affordability and protext tenants more effectively.

scholarly journals Topological and Morphological Controls on Morphodynamics of Salt Marsh Interiors

2021 ◽  
Vol 9 (3) ◽  
pp. 311
Author(s):  
Ben R. Evans ◽  
Iris Möller ◽  
Tom Spencer
Keyword(s):  
Salt Marsh ◽  
Salt Marshes ◽  
East Coast ◽  
Marsh Surface ◽  
Coastal Environments ◽  
Coastal System ◽  
Morphological Segmentation ◽  
The Usa ◽  
The Uk ◽  
Over Time

Salt marshes are important coastal environments and provide multiple benefits to society. They are considered to be declining in extent globally, including on the UK east coast. The dynamics and characteristics of interior parts of salt marsh systems are spatially variable and can fundamentally affect biotic distributions and the way in which the landscape delivers ecosystem services. It is therefore important to understand, and be able to predict, how these landscape configurations may evolve over time and where the greatest dynamism will occur. This study estimates morphodynamic changes in salt marsh areas for a regional domain over a multi-decadal timescale. We demonstrate at a landscape scale that relationships exist between the topology and morphology of a salt marsh and changes in its condition over time. We present an inherently scalable satellite-derived measure of change in marsh platform integrity that allows the monitoring of changes in marsh condition. We then demonstrate that easily derived geospatial and morphometric parameters can be used to determine the probability of marsh degradation. We draw comparisons with previous work conducted on the east coast of the USA, finding differences in marsh responses according to their position within the wider coastal system between the two regions, but relatively consistent in relation to the within-marsh situation. We describe the sub-pixel-scale marsh morphometry using a morphological segmentation algorithm applied to 25 cm-resolution maps of vegetated marsh surface. We also find strong relationships between morphometric indices and change in marsh platform integrity which allow for the inference of past dynamism but also suggest that current morphology may be predictive of future change. We thus provide insight into the factors governing marsh degradation that will assist the anticipation of adverse changes to the attributes and functions of these critical coastal environments and inform ongoing ecogeomorphic modelling developments.

scholarly journals How Does Administrative Data Compare with Census Data for the Measurement of Internal Migration? The Case of Northern Ireland, 2001–2011

2021 ◽  
Author(s):  
Brian Foley ◽  
Tony Champion ◽  
Ian Shuttleworth
Keyword(s):  
Administrative Data ◽  
Internal Migration ◽  
Census Data ◽  
Local Population ◽  
Population Data ◽  
Population Estimates ◽  
Demographic Groups ◽  
Small Areas ◽  
Intercensal Period ◽  
Statistical Agencies

AbstractThe paper compares and contrasts internal migration measured by healthcard-based administrative data with census figures. This is useful because the collection of population data, its processing, and its dissemination by statistical agencies is becoming more reliant on administrative data. Statistical agencies already use healthcard data to make migration estimates and are increasingly confident about local population estimates from administrative sources. This analysis goes further than this work as it assesses how far healthcard data can produce reliable data products of the kind to which academics are accustomed. It does this by examining migration events versus transitions over a full intercensal period; population flows into and out of small areas; and the extent to which it produces microdata on migration equivalent to that in the census. It is shown that for most demographic groups and places healthcard data is an adequate substitute for census-based migration counts, the exceptions being for student households and younger people. However, census-like information is still needed to provide covariates for analysis and this will still be required whatever the future of the traditional census.

scholarly journals Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ratanond Koonchanok ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Khairi Reda ◽  
Sarath Chandra Janga
Keyword(s):  
Single Molecule ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Direct Sequencing ◽  
Visual Exploration ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Rna Sequences ◽  
Sequencing Technologies ◽  
Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

scholarly journals Coadministration of tizanidine and ciprofloxacin: a retrospective analysis of the WHO pharmacovigilance database

2021 ◽  
Author(s):  
Annette Rudolph ◽  
Hendrike Dahmke ◽  
Hugo Kupferschmidt ◽  
Andrea Burden ◽  
Stefan Weiler
Keyword(s):  
Real World ◽  
Safety Issue ◽  
Demographic Data ◽  
Fatal Outcome ◽  
Individual Case ◽  
World Health ◽  
Global Database ◽  
The Usa ◽  
Pharmacovigilance Database ◽  
The Impact

Abstract Purpose Tizanidine, an alpha-adrenergic substance with antinociceptive and antihypertensive effects, is extensively metabolized via cytochrome P450 (CYP) 1A2. Therefore, coadministration with potent CYP1A2 inhibitors, such as ciprofloxacin, is contraindicated. However, both drugs are broadly utilized in various countries. Their concomitant use bears an inherent high risk for clinically significant symptoms, especially in multimorbid patients experiencing polypharmacy. This study aims to investigate the impact of coadministration of tizanidine and ciprofloxacin using real-world pharmacovigilance data and to raise awareness of this potentially underestimated safety issue. Methods We conducted a retrospective study including Individual Case Safety Reports (ICSR) registered until March 1, 2017, in the World Health Organization (WHO) global database. Demographic data, drug administration information, the course of the adverse drug reaction (ADR), its severity, and outcomes were analyzed for cases reporting ciprofloxacin comedication. Results In 91 (2.0%) of the identified 4192 worldwide ICSR on tizanidine, coadministration of ciprofloxacin was reported. Most of the patients were female (n = 59, 64.8%) with a median age of 54 years (range 13–85 years). The countries contributing most reports were the USA (n = 54, 59.3%) and Switzerland (n = 16, 17.6%). ADRs reported most often affected the nervous system and the cardiac function, especially with large tizanidine doses or drugs with CNS and cardiovascular depressant effects. In two cases, a fatal outcome was reported. Conclusion Despite the existing formal contraindication, the concomitant use of tizanidine and ciprofloxacin can be observed in real-world clinical practice. Reactions mainly affected the central nervous and the cardiovascular system resulting in potentially severe adverse effects. The concomitant use of tizanidine and ciprofloxacin should absolutely be avoided.

Diverging trends in US male-female condom use by STI risk factors: a nationally representative study

2020 ◽  
pp. sextrans-2020-054642
Author(s):  
Casey E Copen ◽  
Patricia J Dittus ◽  
Jami S Leichliter ◽  
Sagar Kumar ◽  
Sevgi O Aral
Keyword(s):  
Risk Factors ◽  
Condom Use ◽  
Illicit Drugs ◽  
Female Condom ◽  
Cross Sectional ◽  
The Past ◽  
Representative Study ◽  
The Usa ◽  
Over Time ◽  
Sex Partner

ObjectiveCondom use behaviours are proximal to recent STI increases in the USA, yet it remains unclear whether the use of condoms has changed over time among unmarried, non-cohabiting young men who have sex with women (MSW) and how this variability is influenced by STI risk factors.MethodsTo examine condom use over time among MSW aged 15–29, we used three cross-sectional surveys from the 2002, 2006–2010 and 2011–2017 National Survey of Family Growth. We estimated weighted percentages, adjusted prevalence ratios (APRs) and 95% confidence intervals (CI) to assess changes in condom use, stratified by whether MSW reported any STI risk factors in the past 12 months (ie, perceived partner non-monogamy, male-to-male sex, sex in exchange for money or drugs, sex partner who injects illicit drugs, or an HIV-positive sex partner).ResultsWe observed a divergence in trends in condom use at last sex between men aged 15 –29 with STI risk factors in the past 12 months and those without such history. We saw significant declines in condom use from 2002 to 2011–2017 among men with STI risk factors (APR=0.80, 95% CI 0.68 to 0.95), specifically among those aged 15–19 (APR=0.73, 95% CI 0.57 to 0.94) or non-Hispanic white (APR=0.71, 95% CI 0.54 to 0.93). In contrast, trends in condom use among men with no STI factors remained stable or increased. Across all time periods, the most prevalent STI risk factor reported was perception of a non-monogamous female partner (23.0%–26.9%). Post-hoc analyses examined whether condom use trends changed once this variable was removed from analyses, but no different patterns were observed.ConclusionsWhile STIs have been increasing, men aged 15–29 with STI risk factors reported a decline in condom use. Rising STI rates may be sensitive to behavioural shifts in condom use among young MSW with STI risk factors.

TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data

2019 ◽  
Vol 19 (1) ◽  
pp. 3-23
Author(s):  
Aurea Soriano-Vargas ◽  
Bernd Hamann ◽  
Maria Cristina F de Oliveira
Keyword(s):  
Visual Analytics ◽  
Visual Analysis ◽  
Multivariate Data ◽  
Visual Exploration ◽  
Data Sets ◽  
Time Varying ◽  
Domain Experts ◽  
Data Mining Algorithms ◽  
Temporal Relationships ◽  
Visualization Techniques

We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization and data mining algorithms providing the following capabilities: (1) visual exploration of multivariate data at different temporal scales, and (2) a hierarchical small multiples visualization combined with interactive clustering and multidimensional projection to detect temporal relationships in the data. We demonstrate the value of our framework for specific scenarios, by studying three use cases that were validated and discussed with domain experts.

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