Bivariate Maps Research Articles

Measuring crime: a new paradigm

PurposeThe purpose of this exploratory study is to expand on a previously developed crime harm index – the California Crime Harm Index (CA-CHI) – by discussing the development of the CA-CHI and presenting a comparison of the distribution of crime count and harm in a large Western city in the United States.Design/methodology/approachThis study used descriptive analyses, spatial univariate mapping and bivariate choropleth maps to analyze the distribution of Part I crime counts and harm.FindingsResults of the analysis show that while there was some variation in the distribution of crime count and harm city wide, spatial mapping and statistics reveal that the geographical distribution of crime count and harm across census tracts are largely consistent.Research limitations/implicationsMinor discrepancies between the distribution of crime count and harm indicate the potential for the CA-CHI to inform law enforcement practices. However, the distributions remain largely similar at the census tract level. There is room for further development of the CA-CHI to better distinguish between the distribution of crime harm and volume.Originality/valueNo other study has used spatial mapping techniques like bivariate choropleth mapping to examine the distribution of crime volume and crime harm based on the CA-CHI in any location in California.

Geospatiotemporal and Causal Inferential Study of European Epidemiological Patterns of Cannabis- and Substance-Related Congenital Orofacial Anomalies.

Since high rates of congenital anomalies (CAs), including facial CAs (FCAs), causally attributed to antenatal and community cannabis use have been reported in several recent series, it was of interest to examine this subject in detail in Europe. CA data were taken from the EUROCAT database. Drug exposure data were downloaded from the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). Income was taken from the World Bank's online sources. On the bivariate maps of both orofacial clefts and holoprosencephaly against resin, the Δ9-tetrahydrocannabinol concentration rates of both covariates increased together in France, Bulgaria, and the Netherlands. In the bivariate analysis, the anomalies could be ranked by the minimum E-value (mEV) as congenital glaucoma > congenital cataract > choanal atresia > cleft lip ± cleft palate > holoprosencephaly > orofacial clefts > ear, face, and neck anomalies. When nations with increasing daily use were compared to those without, the former had generally higher rates of FCAs (p = 0.0281). In the inverse probability weighted panel regression, the sequence of anomalies-orofacial clefts, anotia, congenital cataract, and holoprosencephaly-had positive and significant cannabis coefficients of p = 2.65 × 10-5, 1.04 × 10-8, 5.88 × 10-16, and 3.21 × 10-13, respectively. In the geospatial regression, the same series of FCAs had positive and significant regression terms for cannabis of p = 8.86 × 10-9, 0.0011, 3.36 × 10-8, and 0.0015, respectively. Some 25/28 (89.3%) E-value estimates and 14/28 (50%) mEVs were >9 (considered to be in the high range), and 100% of both were >1.25 (understood to be in the causal range). Rising cannabis use is associated with all the FCAs and fulfils the epidemiological criteria for causality. The data indicate particular concerns relating to brain development and exponential genotoxic dose-responses, urging caution with regard to community cannabinoid penetration.

Bivariate mapping of intimate partner violence prevalence and its correlates in Liberia by county: Results from the 2019-2020 Demographic and Health Survey.

Intimate partner violence (IPV) is a global public health concern and requires nuanced health policy response for effective addressal at the subnational level. Using the nationally and county level representative data from the 2019-20 Demographic and Health Survey of Liberia, the prevalence of IPV was computed for each of the sixteen Liberian counties in 15 - 49-year-old women. Additionally, prevalence of IPV acceptance and having parental IPV were also computed. Prevalence of each of the three metrics were mapped by county, in addition to bivariate mapping of the three attributes. Results demonstrate wide chasms in prevalence at the county level. Several countries with high prevalence of one metric were correlated with the high prevalence of the other two metrics, and vice versa. Albeit nuanced differences in associations at the county level were also observed. Findings auger for nuanced health policy measures to address IPV more effectively in Liberia.

The effect of various partial atomic charges on the bulk and liquid/vacuum interface properties of iodobenzene derivatives at their melting points

In this work, various atomic charge schemes including natural bond orbital (NBO), electrostatic potential based (CHELPG), and σ-hole model charges were applied in the OPLS-AA force field to investigate their effects on the thermophysical and structural properties of iodobenzene and its derivatives. Molecular dynamics simulations presented in this work show that the studied structural and thermophysical properties are in good agreement with experiments when the CHELPG charge was coupled with the OPLS-AA force field. Also, the arrangement of iodobenzene derivatives in the liquid phase was investigated via combined radial/angular distribution functions (CDFs) analyses and halogen-bonding theory. The most probable orientation of iodobenzene derivatives at the liquid/vacuum interface was assigned by atom density profile and bivariate orientational distribution maps. For all studied iodobenzene derivatives, benzene rings are oriented such that the iodine atoms tend toward the vacuum phase.

THE ASSOCIATION BETWEEN CHRONIC LUNG CONDITIONS AND COVID-19 MORTALITY AMONG 65+ IN CONNECTICUT AND RHODE ISLAND

Abstract Older adults aged 65 and older have accounted for 81% of all deaths from COVID-19 in the US. Individuals with chronic lung diseases have higher risk for severe COVID-19 and death. The aim of this research is to examine the association between town-level rates of asthma and COPD and deaths from COVID-19 in 208 towns in Connecticut and Rhode Island. This study utilized data from multiple publicly available datasets: the public health departments of Connecticut and Rhode Island, the 2021 Connecticut and 2020 Rhode Island Healthy Aging Data Reports (www.healthyagingdatareports.org), and the Census Bureau’s 2014-2018 American Community Survey (ACS). A multi-step analysis was conducted to examine the association between town-level chronic lung conditions and COVID-19 mortality. Bivariate correlations and mapping found strong, positive associations between town-level asthma prevalence and COVID-19 mortality (rs [206] = 0.15; P = .03) and COPD prevalence and COVID-19 mortality (rs [206] = 0.15; P = .03). After controlling for town-level factors associated with chronic lung conditions and COVID-19 mortality, linear regression models did not find support for an association between chronic lung conditions and COVID-19 mortality. However, town-level factors like percentage of the 65+ African American population (β: 0.19, SE: 249.18, p= .02) and 65+ with low educational attainment (β: 0.45, SE: 278.98, p= .001) were significant predictors of COVID-19 mortality. This research adds to the current knowledge base that high rates of racial minorities and low education among the 65+ population are significant predictors of town level COVID-19 mortality.

Modelling Species Richness and Functional Diversity in Tropical Dry Forests Using Multispectral Remotely Sensed and Topographic Data

Efforts to assess and understand changes in plant diversity and ecosystem functioning focus on the analysis of taxonomic diversity. However, the resilience of ecosystems depends not only on species richness but also on the functions (responses and effects) of species within communities and ecosystems. Therefore, a functional approach is required to estimate functional diversity through functional traits and to model its changes in space and time. This study aims to: (i) assess the accuracy of estimates of species richness and tree functional richness obtained from field data and Sentinel-2 imagery in tropical dry forests of the Yucatan Peninsula; (ii) map and analyze the relationships between these two variables. We calculated species richness and functional richness (from six functional traits) of trees from 87 plots of the National Forest Inventory in a semi-deciduous tropical forest and 107 in a semi-evergreen tropical forest. Species richness and functional richness were mapped using reflectance values, vegetation indices, and texture measurements from Sentinel-2 imagery as explanatory variables. Validation of the models to map these two variables yielded a coefficient of determination (R2) of 0.43 and 0.50, and a mean squared relative error of 25.4% and 48.8%, for tree species richness and functional richness, respectively. For both response variables, the most important explanatory variables were Sentinel-2 texture measurements and spectral bands. Tree species richness and functional richness were positively correlated in both forest types. Bivariate maps showed that 44.9% and 26.5% of the forests studied had high species richness and functional richness values. Our findings highlight the importance of integrating field data and remotely sensed variables for estimating tree species richness and functional richness. In addition, the combination of species richness and functional richness maps presented here is potentially valuable for planning, conservation, and restoration strategies by identifying areas that maximize ecosystem service provisioning, carbon storage, and biodiversity conservation.

Working from Home as a Catalyst for Urban Regeneration

Since the COVID-19 pandemic, working from home has become normalised and is likely to continue to gather pace. The adjustment in daytime population that this creates has implications for urban planning, as it can drive greater levels of localization and less car-dependent cities. In this paper, we describe how this shift changes urban daytime population density, a significant predictor of most measures of amenity, walkability, and liveability. First, we define a method for mapping access to amenity, applied to two cities: Melbourne and Sydney. Secondly, we analyse the two-way causal relationship between population density and amenity based on bivariate spatial mapping. Thirdly, we provide a method for estimating changes in daytime populations. Finally, the article provides a taxonomy of telework regeneration potential for different parts of the city based on the level of amenity and expected changes in daytime population (average changes in high job-density areas −14%, CBDs −30%, and +54% in residential areas). We argue that, if used as a catalyst within strategic planning, and for urban regeneration, increases could create higher levels of amenity in suburban areas, which can lead to improved sustainability outcomes, specifically greater levels of walkability, liveability, and reduced car dependence. We have calculated that opportunity areas account for 89% of the greater urban area and cover 49% of the population, which may well grow as the WFH trend continues. As such, and in conclusion, we outline a set of site-specific opportunities and challenges relevant to urban planners that aim for urban regeneration.

Geographic Examination of COVID-19 Test Percent Positivity and Proportional Change in Cancer Screening Volume, National Breast and Cervical Cancer Early Detection Program.

IntroductionIn 2020, the COVID-19 pandemic led to significant declines in cancer screening, including among women served by the National Breast and Cervical Cancer Early Detection Program (NBCCEDP). This study examined the spatial association between state-based COVID-19 test percent positivity and proportional change in NBCCEDP screening volume.MethodsUsing the COVID-19 Diagnostic Laboratory Testing dataset, we calculated state-based monthly COVID-19 test percent positivity from July through December 2020 and categorized rates into low, medium, and high groups. We used data from 48 NBCCEDP state awardees to calculate the state-based monthly proportional change in screening volume and compared data for July–December 2020 with the previous 5-year average for those months. We categorized changes in screening volume into large decrease, medium decrease, and minimal change and created maps of the associations between variable subgroups by using bivariate mapping in QGIS.ResultsBivariate relationships between COVID-19 test percent positivity and proportional change in cancer screening volume varied over time and geography. In 5 of 6 months, 4 states had high COVID-19 test percent positivity and minimal change in breast or cervical cancer screening volume; 2 states had high COVID-19 test percent positivity and minimal change in breast and cervical cancer screening volume.ConclusionSome states maintained pre–COVID-19 screening volumes despite high COVID-19 test percent positivity. Follow-up research will be conducted to determine how these states differ from those with consistent decreases in screening volume and identify factors that may have contributed to differences. This information could be useful for planning to maximize NBCCEDP awardees’ ability to maintain screening volume during future public health emergencies.

On exploring bivariate and trivariate maps as visualization tools for spatial associations in digital soil mapping: A focus on soil properties

On exploring bivariate and trivariate maps as visualization tools for spatial associations in digital soil mapping: A focus on soil properties

European Epidemiological Patterns of Cannabis- and Substance-Related Body Wall Congenital Anomalies: Geospatiotemporal and Causal Inferential Study.

As body wall congenital anomalies (BWCAs) have a long history of being associated with prenatal or community cannabis exposure (CCE), it was of interest to investigate these epidemiological relationships in Europe given the recent increases in cannabis use prevalence, daily intensity, and Δ9-tetrahydrocannabinol (THC) potency. Methods: This study makes use of BWCA data from Eurocat, drug exposure data from the European Monitoring Centre for Drugs and Drug Addiction, and income from the World Bank. Results: The mapping analysis showed that BWCARs increased in France, Spain, and the Netherlands. The bivariate mapping analysis showed that the BWCA rates (BWCAR) and the cannabis resin THC concentration rose simultaneously in France, the Netherlands, Bulgaria, Sweden, and Norway. The bivariate ranking of the BWCARs by median minimum E-value (mEV) was omphalocele > diaphragmatic hernia > abdominal wall defects > gastroschisis. With inverse probability weighted multivariable panel regression, the series of BWCAs, including gastroschisis, omphalocele, and diaphragmatic hernia, was positively related to various metrics of cannabis use from p = 2.45 × 10−14, 4.77 × 10−7 and <2.2 × 10−16. With geospatial regression, the same series of BWCAs was related to cannabis metrics from p = 0.0016, 5.28 × 10−6 and 4.88 × 10−9. Seventeen out of twenty-eight (60.7%) of the E-value estimates were >9 (high range), as were 14/28 (50.0%) of the mEVs. Conclusion: The data confirm the close relationship of the BWCARs with the metrics of CCE, fulfill the quantitative criteria of causal inference, and underscore the salience of the public health impacts of cannabinoid teratogenicity. Of major concern is the rising CCE impacting exponential cannabinoid genotoxic dose-response relationships. CCE should be carefully restricted to protect the food chain, the genome, and the epigenome of coming generations.

P153 Spatial Analysis of Perinatal Food Assistance Resources in Relation to Food Deserts in North Carolina

<h3>Background</h3> A number of risk factors can influence maternal and infant health including chronic conditions, health behaviors and prenatal care. Women with access to perinatal resources and healthy foods could limit the impact of these risk factors for the maternal and infant well-being. Geographic Information Systems (GIS) is a software used to capture, store, and analyze geographic data. The advantages of GIS allows understanding of maternal and perinatal food assistance gaps. <h3>Objectives</h3> To locate and map government food assistance perinatal resources such as WIC, SNAP Offices, WIC and SNAP approved vendors throughout North Carolina. Determine if there are spatial correlations between the density (ie number of physical locations at the census tract level) of food assistance clinics and approved retailers in comparison to areas classified as food deserts by the USDA (low access and low income designation). Assess the association between underlying population characteristics and WIC/SNAP locations. <h3>Study Design, Setting, Participants</h3> Undergraduate research assistants from Appalachian State University's Nutrition Department compiled a comprehensive list of WIC clinics, WIC-approved vendors, SNAP offices and SNAP retailers available in North Carolina from Google™. <h3>Measurable Outcome/Analysis</h3> These resources were geocoded to create a spatial distribution of the locations into ArcGIS Pro by ESRI by Appalachian State University's Geography/Planning Department. WIC and SNAP locations were spatially merged with USDA (food desert classification) and American Community Survey Data to create a relational GIS database. Bivariate map products and Kendall tau correlations were used to assess the association between underlying population characteristics and WIC/SNAP locations. <h3>Results</h3> Preliminary findings show limited WIC and SNAP office and retailer locations in rural, underserved locations with food deserts in NC. Spatially, variations in this association varies across the state with limited access in the far Eastern and Western regions of NC. <h3>Conclusions</h3> GIS and other simple spatial analysis allow for critical evaluation of WIC and SNAP offices/retailers and their relationship to food deserts, which could inform policies around support for more offices/retailers. <h3>Funding</h3> Internal Grant from University Research Council

Major Changes in Spatiotemporal Trends of US Rotavirus Laboratory Detections After Rotavirus Vaccine Introduction-2009-2021.

For the 15 years before rotavirus vaccine introduction in 2006, annual rotavirus activity in the United States showed a distinct spatiotemporal pattern, peaking first in the Southwest and last in the Northeast. We modeled spatiotemporal trends in rotavirus laboratory detections from 2009 to 2021. Laboratories reporting to the National Respiratory and Enteric Virus Surveillance System were eligible for inclusion in a given surveillance year (July to June) if ≥1 polymerase chain reaction or enzyme immunoassay rotavirus test per week was reported during ≥26 weeks and totaling ≥100 annual tests. For each laboratory, the season peak was the week with the highest 7-week moving average of the number of rotavirus positive tests during the national season, defined as the period with a 3-week moving average of >10% rotavirus positivity lasting ≥2 consecutive weeks. We input peak week as a continuous variable and the geospatial coordinates of each laboratory into a spherical variogram model for Kriging spatial interpolation. We also created a state-level bivariate choropleth map using tertiles of the 2010-2019 average birth rates and rotavirus vaccine coverage. Following the established biennial trend, the 2010-2011, 2012-2013, 2014-2015, 2016-2017, and 2018-2019 surveillance years had >10% rotavirus positivity for ≥2 weeks and were included in the geospatial analysis. During all 5 seasons included in the geospatial analysis, the earliest peak week occurred in Oklahoma, Arkansas, and the western Gulf coast, a pattern markedly different from prevaccine seasons. These states also had the average lowest rotavirus vaccine coverage and highest birth rate, suggesting that more rapid accumulation of susceptible children drives annual rotavirus season activity. Increasing vaccine coverage remains a key tool in reducing rotavirus burden.

Multivariate small area modelling of undernutrition prevalence among under-five children in Bangladesh.

District-representative data are rarely collected in the surveys for identifying localised disparities in Bangladesh, and so district-level estimates of undernutrition indicators - stunting, wasting and underweight - have remained largely unexplored. This study aims to estimate district-level prevalence of these indicators by employing a multivariate Fay-Herriot (MFH) model which accounts for the underlying correlation among the undernutrition indicators. Direct estimates (DIR) of the target indicators and their variance-covariance matrices calculated from the 2019 Bangladesh Multiple Indicator Cluster Survey microdata have been used as input for developing univariate Fay-Herriot (UFH), bivariate Fay-Herriot (BFH) and MFH models. The comparison of the various model-based estimates and their relative standard errors with the corresponding direct estimates reveals that the MFH estimator provides unbiased estimates with more accuracy than the DIR, UFH and BFH estimators. The MFH model-based district level estimates of stunting, wasting and underweight range between 16 and 43%, 15 and 36%, and 6 and 13% respectively. District level bivariate maps of undernutrition indicators show that districts in north-eastern and south-eastern parts are highly exposed to either form of undernutrition, than the districts in south-western and central parts of the country. In terms of the number of undernourished children, millions of children affected by either form of undernutrition are living in densely populated districts like the capital district Dhaka, though undernutrition indicators (as a proportion) are comparatively lower. These findings can be used to target districts with a concurrence of multiple forms of undernutrition, and in the design of urgent intervention programs to reduce the inequality in child undernutrition at the localised district level.

Spousal violence against women in Afghanistan: Bivariate mapping of correlates.

Spousal violence against women is endemic and owes its genesis to deeply entrenched socio-cultural norms. In this study 2015 Demographic and Health Survey data for Afghanistan was used to calculate the provincial prevalence and two correlates of spousal violence, and their bivariate mapping. Large differences were present in the provincial prevalence of spousal violence, having witnessed their father ever beat their mother, and acceptance of spousal violence by the currently or ever married women aged 15-49 years. In general, bivariate maps showed strong associations between spousal violence against women, its acceptance by women, and having witnessed their father beat their mother by ever married women. In an easily comprehensible manner, these maps underscore ensuring better quality of life in marital settings, higher and more equal social stature of women, and protecting their basic human rights would entail legal, social, and cultural paradigm shift.

Mapping basin-scale supply-demand dynamics of flood regulation service – A case study in the Baiyangdian Lake Basin, China

Recognizing changes in the supply–demand relationship of Flood Regulation Service (FRS) is significant for the rational planning of urban patterns and the prevention of flooding risks in river basins. Most existing studies have explored its spatial pattern but pay less attention to its spatiotemporal changes. This study explored the dynamic changes in the supply–demand relationship of FRS in rapidly urbanizing basins. We proposed the Supply-Demand Ratio (SDR) method, which used the Soil Conservation Service Curve Number (SCS-CN) model and the flood vulnerability index to quantify the supply and demand of FRS, and then, we calculated the SDR. Additionally, we calculated the rate of change in SDR from 1990 to 2018 in the basin and its subbasins. The case study in the Baiyangdian Lake Basin showed that the SDR method can effectively measure the changes in the relationship between the supply and demand of FRS in the river basin. The SDR was consistent with the supply–demand bivariate mapping method, with Kappa coefficients of 0.610 and 0.835 in 1990 and in 2018, respectively. Furthermore, we found that from 1990 to 2018, the imbalance of FRS in supply and demand intensified. The SDR for the whole basin decreased by 0.088 from 1990 to 2018, with a change rate of −27.8%. Rapid urbanization is an important reason for intensification of the FRS supply–demand imbalance. The proportion of urban area is the most relevant factor for the supply–demand relationship of FRS, with a Pearson correlation coefficient of −0.845 (p < 0.01). Therefore, we suggest that proactive policies be adopted to defend against flood disaster risks in the future construction of the Xiong'an New Area, which is located downstream from the Baiyangdian Lake Basin.

Impulsive components separation using minimum-determinant KL-divergence NMF of bi-variable map for bearing diagnosis

In vibration-based monitoring techniques, the periodic impulse response is a typical manifestation of the localized failure of rolling element bearings (REBs). Cyclic spectral help reveal the cyclostationarity of such signals by bridging the carrier frequency and the cyclic frequency, which are represented in bi-variable maps. By integrating the components within the optimal band over the carrier axis, the Enhanced Envelope Spectrum (EES) or Squared Envelope Spectrum (SES) can be obtained and provide attractive analysis tools for the bi-variable map. In this paper, as a complement of integration analysis of the bi-variable map, Non-negative Matrix Factorization is adopted to separate the cyclic components in bi-frequency map. In addition to using KL-divergence as the fidelity term, the minimum determinant regularization term is crafted to enforce the sparseness, uniqueness, and identifiability of the solution. With numerical simulation and bearing fault experiments, the result shows that the number of cyclic components is estimated correctly and that the periodic impulsive components are separated and enhanced from the bi-variable map, especially in the cases that cyclic interferences mask the fault feature.

Future global conflict risk hotspots between biodiversity conservation and food security: 10 countries and 7 Biodiversity Hotspots

Balancing biodiversity conservation and food security is the key to global sustainable development. However, we know little about the future global conflict risk hotspots between biodiversity and food security at both country and Biodiversity Hotspots (BHs) levels. First we calculated land use intensity index (LUII) based on future land use simulation, incorporated data on species richness(including birds, mammals and amphibians) and introduced the Global Food Security Index (GFSI). Then we used local indicators of spatial association (LISA) and bivariate choropleth map to identify the future global conflict risk hotspots between biodiversity conservation and food security. These include 10 countries (including Congo (Kinshasa), Sierra Leone, Malawi, Togo, Zambia, Angola, Guinea, Nigeria, Laos, Cambodia) and 7 BHs (Eastern Afromontane, Guinean Forests of West Africa, Horn of Africa, Indo-Burma, Mediterranean Basin, Maputaland-Pondoland-Albany and Tropical Andes). Special attention needs to be paid to these hotspots to balance biodiversity conservation and food security.

COVID-19 Vaccination Gap in Admitted Trauma Patients: A Critical Opportunity.

Coronavirus disease 2019 (COVID-19) vaccination is the core strategy for pandemic management. We hypothesized that a vaccination gap might exist between emergency department (ED) patients admitted for trauma and other ED patients. This was an observational quality improvement study using electronic health record data at an academic level-1 trauma center. Participants were all patients presenting to the adult ED with a Tennessee home address between January 1 and June 1, 2021. We measured the proportional difference in vaccination between admitted trauma patients and other ED patients over time (by week) and association via Spearman's rank correlation coefficient. Binary logistic regression facilitated covariate analysis to account for age, sex, race, home county, and ethnicity without and then with interaction between trauma admission and time. Geographic visual analysis compared county-level vaccination rates with odds of trauma admission by home county using a bivariate chloropleth map. The proportional difference in vaccination between trauma-admitted and other ED patients increased over time (Spearman's = 0.699). Adjusting for age, sex, race, home county, and ethnicity, there was a statistically significant vaccination difference between trauma-admitted and other ED patients (odds ratio = 0.53, 95% CI 0.43-0.65, p < 0.0001). Geographic analysis revealed increased trauma admission odds and lower vaccination rates in surrounding counties compared with Davidson County. We observed a widening COVID-19 vaccination gap between trauma-admitted and other ED patients. Vaccine outreach during trauma admission may provide a valuable point of contact for unvaccinated patients.

Visualising residents’ fear of crime with recorded crime data from four Czech cities

ABSTRACT The paper investigates if and where registered crime and the fear of crime intersect in the four locations. This information is important to reduce crime and increase the sense of security of the population. In the past, research was applied to small parts of a city or a whole city, but not in as much detail as this paper. Our research is detailed, and at the same time is applied to four entire locations - three Czech cities (Ostrava, Olomouc, and Kolín) and one Prague district (Prague 12). We placed registered crime and fear of crime on one map to show locations where people feel afraid, where crime happens, and where both events occur together. We drew these phenomena using Moran’s I in a bivariate map. The outputs will be applied by Municipal governments and police departments.

An uncustomary calculation of fractal dimension of graph of mixed (k, s)-Riemann-Liouville fractional integral of a bivariate continuous map

An uncustomary calculation of fractal dimension of graph of mixed (k, s)-Riemann-Liouville fractional integral of a bivariate continuous map